CULTURED COLLECTION OF GUT MICROBIAL COMMUNITY

FIELD OF THE INVENTION

The present invention encompasses cultured collections of a gut microbial community, models comprising such cultures, and methods of use thereof.

BACKGROUND OF THE INVENTION

The largest microbial community in the human body resides in the gut and comprises somewhere between 300 and 1000 different microbial species. The human body, consisting of about 100 trillion cells, carries about ten times as many microorganisms in the intestines. The gut microbiome contains at least two orders of magnitude more genes than are found in the Homo sapiens genome. However, efforts to dissect the functional interactions between microbial communities and their environmental or animal habitats are complicated by the long-standing observation that, for many of these communities, the great majority of organisms have not been cultured in the laboratory, and some may not have been previously identified. Furthermore, experiments to determine the effect of a perturbation on a gut microbial community are hampered because teasing out the effects of a particular perturbation on each of the hundreds or thousands of different species in a gut microbial community using current techniques is difficult at best and may well be impossible. A need exists, therefore, for methods of culturing and dissecting the gut microbial community populations both in vitro and in vivo.

SUMMARY OF THE INVENTION

One aspect of the invention encompasses a composition. The composition comprises (i) an in vitro cultured collection of a gut microbial community or (ii) a clonally arrayed culture collection of a gut microbial community. In certain aspects, the gut microbial community is from a human or a germfree mouse colonized with a gut microbial community or an arrayed culture collection of a gut microbial community.

Another aspect of the invention encompasses a composition. The composition comprises (i) an in vitro cultured collection of a gut microbial community or (ii) a clonally arrayed culture collection of a gut microbial community. The cultured gut microbial community has (i) at least 60%, at least 70%, at least 80% or at least 90% of the order-level phylotopic composition of the original gut microbial community; or (ii) at least 60%, at least 70%, at least 80% or at least 90% of the metagenome, transcriptome, or proteome composition of the original gut microbial community; or (iii) at least 60%, at least 70%, at least 80% or at least 90% of the order-level phylotopic composition of the original gut microbial community and at least 60%, at least 70%, at least 80% or at least 90% of the metagenome, transcriptome, or proteome composition of the original gut microbial community. In certain aspects, the clonally arrayed culture collection was prepared (i) without colony picking and/or (ii) using a most probable number (MPN) technique.

Another aspect of the invention encompasses a method of determining the effect of a perturbation on a gut microbial community. The method comprises applying the perturbation to a cultured collection of a gut microbial community and determining the difference in the community before and after the application of the perturbation, wherein the difference in the cultured collection represents the effect of the perturbation on the original gut microbial community.

Another aspect of the invention encompasses a composition. The composition comprises (i) an in vitro cultured collection of a gut microbial community or (ii) a clonally arrayed culture collection of a gut microbial community. The cultured gut microbial community has (i) at least 98% of the order-level phylotopic composition of the original gut microbial community; or (ii) at least 98% of the metagenome, transcriptome, or proteome composition of the original gut microbial community; or (iii) at least 98% of the order-level phylotopic composition of the original gut microbial community and at least 98% of the metagenome, transcriptome, or proteome composition of the original gut microbial community. In certain aspects, the clonally arrayed culture collection was prepared (i) without colony picking and/or (ii) using a most probable number (MPN) technique.

Another aspect of the invention encompasses a method of specifically manipulating the abundance of a member of a gut microbiome of a host to a target level by changing the diet of the host. The method comprises (a) determining the linear coefficient for a particular gut microbiome member in relation to protein, fat, polysaccharide, and simple sugar; (b) determining the amount of protein, fat, polysaccharide and sugar in a diet necessary to achieve the target level of the gut microbiome member based on the linear coefficients from (a); and (c) feeding a diet to the host that contains the amount of protein, fat, polysaccharide and sugar determined in (b). In certain aspects, the abundance of a member of a gut microbiome may be calculated with the equation

y
_i=β₀+β_proteinX_protein+β_{Polysaccharide}X_{polysaccharide}+β_sucroseX_sucrose+β_fatX_fat,

where y_iis the abundance of the member of the gut microbiome, β₀is the calculated parameter for the intercept, X is the amount in g/(kg of total diet) of the diet ingredient, and β_protein, β_{polysaccharide}, β_sucrose, and β_fatare the linear coefficients for a particular gut microbiome member for each of the diet components.

Other aspects of the invention are described more thoroughly below.

REFERENCE TO COLOR FIGURES

The application file contains at least one photograph executed in color. Copies of this patent application publication with color photographs will be provided by the Office upon request and payment of the necessary fee.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 Comparison of the taxonomic representation of bacterial species and gene content in complete versus cultured human fecal microbial communities before and after their introduction into gnotobiotic mice. (A) 16S rRNA sequences from complete microbiota were compared with those identified from microbial communities cultured from the same human donors. At each taxonomic level, the proportion of reads in the complete community belonging to a taxonomic group observed in the cultured sample is shown in blue; the proportion of reads belonging to a taxonomic group not observed in the cultured sample (or lacking taxonomic assignment) is shown in black. (Data shown are the average of two unrelated human donors.) In vitro samples refer to comparisons between human fecal samples and plated material. In vivo samples refer to comparisons between gnotobiotic mice colonized with a complete human fecal microbiota and mice colonized with the readily cultured microbes from the same human fecal sample. (B) Annotated functions identified in the microbiomes of complete and cultured human gut communities. Each point represents a KO designation plotted by relative abundance (average across two donors, per 100,000 sequencing reads). Black points represent KO comparisons between the in vitro samples; orange points represent comparisons between in vivo samples. (C) The distribution of taxa and their relative abundance along the length of the intestine are similar in the two groups of animals. Relative abundances of class-level taxa at six locations are shown; data represent the average of mice colonized from two unrelated donors. SI, small intestine divided into 16 equal-size segments and sampled at SI-2 (proximal), SI-5 (middle), and SI-13 (distal). PCoA suggests that gut biogeography, rather than donor or culturing, explains the majority (58%) of variance between samples (FIG. 4 A-C).

FIG. 2 Abundance of readily cultured taxa in fecal samples from two unrelated human donors (Donor 1: A, C, E; Donor 2: B, D, F), as determined by SILVA-VOTE (A, B), Ribosomal Database Project (RDP)-based 16S rRNA annotation (C, D), and annotation-independent (OTU % ID cutoff) methods (E-F) Analyses were performed as described in FIG. 1. Unsupervised hierarchical clustering of 16S rRNA datasets generated from either complete uncultured (G) or readily cultured (H) human gut microbial communities separates all samples from Donor 1 (red) from Donor 2 (blue). Unweighted pair group method with arithmetic mean (UPGMA) clustering of unweighted UniFrac distances between samples (rarefied to 1,000 de-noised, chimera-checked sequences each) is shown; nonphylogenetic distance metrics (Jaccard, Hellinger, Bray-Curtis) produce similar results (data not shown). In both G and H, bootstrap support separating Donor 1 samples from Donor 2 samples is 100% [100 iterations; 500 sequences subsampled from each complete (nonrarefied) dataset].

FIG. 3 Relative abundance of functional annotations in the uncultured (complete) and readily cultured fecal communities of two unrelated donors. From each donor, complete and cultured fecal samples also were introduced into germfree mice. After a 4-wk acclimatization period on a standard LF/PP diet, fecal microbiomes were characterized by shotgun pyrosequencing. Reads were mapped to KO (A and B), EC (C and D), and level 2 KEGG pathways (E and F). In these graphs, each point represents a functional annotation, and the axes represent the relative abundance (per 100,000 shotgun pyrosequencer reads) of these predicted functions in comparisons of complete versus cultured microbiomes (black points) and in comparisons of complete versus cultured microbiomes after each had been introduced into germfree mice (orange points). In each comparison, the goodness of fit (R2) values increase in communities that share the same environment (mouse gut) regardless of the donor. (G) Annotation-independent comparison of functions encoded in the microbiomes of uncultured complete or cultured fecal communities: capture of antibiotic resistance genes. Shades represent number of E. coli clones (per GB of subcloned DNA from complete or readily cultured microbial communities from each of two human donors), resulting from each of 15 antibiotic selections. (H) Proof-of-principle study connecting captured genes with their associated bacterial sources. Fecal DNA fragments cloned into E. coli from Donor 1, but not from Donor 2, conferred resistance to the aminoglycoside amikacin. Replating these fecal samples directly on high levels of amikacin (4,100 μg/mL) reveals that this functional difference is mirrored in the source communities. Mean values±SEM of triplicate samples (separate frozen aliquots of the original fecal material) are plotted. *P<0.005 based on student's t test (unpaired, two-tailed, assuming equal variance; P<0.02 by heteroscedastic test).

FIG. 4 Biogeography of complete and readily cultured human gut microbial communities in gnotobiotic mice and the impact of colonization on host adiposity. (A-C) Principal coordinate analysis (PCoA) of weighted UniFrac distances between samples collected along the length of the gut indicates that mice colonized with readily cultured microbial communities have microbiota similar to those colonized from an uncultured source. (A) Principal coordinate 1 (PC1) separates samples by location. (B) Principal coordinate 2 (PC2) separates samples by donor. (C) No other coordinate explains ≧5% of the total variance between samples. (D) Epididymal fat pad:body weight ratios in germfree mice and those colonized with complete or readily cultured microbial communities from the two human donors. Ratios represent the average±SEM from n=5 mice per group (except the Donor 2 cultured community; n=3). Asterisks indicate statistically significant differences based on an unpaired, two-tailed student's t test. *P<0.005; **P<0.001; N/S, not significant.

FIG. 5 Human gut microbial communities composed only of cultured members exhibit in vivo dynamics similar to those in their complete counterparts. (A) PCoA of UniFrac distances between 16S rRNA datasets generated from fecal samples from gnotobiotic mice, colonized with complete or cultured human fecal microbial communities from two unrelated donors and sampled over time. From day 33-46, mice were switched from their standard LF/PP chow to a high-fat, high-sugar Western diet. Time series analysis of community structure as viewed along the first two principal coordinates from A shows that interpersonal (donor) differences separated communities on PC1 (B), and host diet separated communities on PC2 (C). Principal coordinate 3 (PC3) separated samples from mice colonized with complete communities from those colonized with cultured populations (FIG. 6A). Nonphylogenetic distance metrics produced similar results (FIG. 6 D-H). (D) Evidence that the community response to diet is driven by readily cultured bacteria and that members of the same taxonomic group manifest distinct responses to diet perturbations. Species-level taxa significantly influenced by diet (student's t test P≦0.01 after Bonferroni correction; n=97 taxa tested) in either the complete communities (blue names), the cultured communities (green names), or both (red names) are plotted over time (arrows). Each column represents the average relative abundance in fecal samples harvested from three to five individually caged mice that were sampled at various times: (i) during the initial LF/PP diet phase; (ii) during the subsequent shift to the Western diet; and (iii) upon return to LF/PP chow. Members of family-level groups with at least one diet-responsive species are shown (excluding rare species with average abundance <0.1% across each time point). The names of all taxa are shown in FIG. 7. (E) The functional gene repertoire in the fecal microbiomes of humanized gnotobiotic mice. Each point represents a KEGG level 2 pathway; the number of hits to each pathway per 100,000 shotgun pyrosequencing reads is plotted for mice consuming LF/PP (x axis) or Western (y axis) diets. Data represent the averages of mice colonized with microbial communities from two unrelated donors. The results show that the fecal microbiome associated with the Western diet is enriched for genes in pathways associated with PTS (red arrows) both in mice colonized with complete uncultured human gut communities (black points) and mice colonized with communities of readily cultured members (orange points). Donor-specific data and results from alternate annotation schemes are shown in FIG. 8.

FIG. 6 Diet shapes complete and readily cultured human gut microbial communities in a similar manner. (A) PCoA of unweighted UniFrac distances between fecal samples obtained from mice colonized with complete or cultured microbial communities from two unrelated human donors. On day 33 after gavage, mice were switched from an LF/PP chow to a high-fat, high-sugar Western diet (gray rectangle). On day 47 they were returned to the original LF/PP diet. Variance along principal coordinate 3 (PC3) is plotted against time. (B) Scree plot from PCoA analysis. Only PC1-PC3 (red) account for ≧5% of the variance between samples. (C) In gnotobiotic mice, communities composed of readily cultured human gut microbes and communities containing a complete human gut microbiota undergo similar diet-dependent changes in abundance of Bacteroidia and Erysipelotrichi upon changes in host diet. Each mouse in each treatment group was caged individually, and each group that received a given community was housed in a separate gnotobiotic isolator. Mean values±SEM and P values (*P<0.05; **P<0.01 based on a paired, two-tailed student's t test) are indicated when mice were consuming a LF/PP diet (black bars) and then switched to the Western diet (white bars). (D-H) Diet-dependent community-wide shifts in bacterial species representation as measured by PCoA analysis based on a nonphylogenetic (binary Jaccard) distance measurement. (D) PCoA plot of binary Jaccard distances between all samples. (E-G) Separate PCoA values plotted against time. (H) Scree plot of variance explained by PCoA axes.

FIG. 7 Relative abundances of species-level taxa in fecal samples obtained from gnotobiotic mice over time. (A-G) All identified taxa present at an abundance of ≧0.1% in at least a single time point are shown. Species significantly influenced by diet in either the complete community (blue names), the readily cultured community (green names), or both (red names) are plotted over time (arrows) during the initial LF/PP, subsequent Western, and final LF/PP phases of the diet oscillation experiment. Significance (P≦0.01 after Bonferroni correction) was determined by unpaired, two-tailed student's t test, assuming equal variances; n=97 taxa tested. The assumption of equal variances was tested by F test (P<0.02).

FIG. 8 KEGG level 2 pathway-based analysis of fecal microbiomes obtained from LF/PP- and Western diet-fed mice colonized with a complete or cultured human gut microbiota from two human donors. (A-D) Phosphotransferase system (PTS) pathways are marked in red and highlighted with arrows. (E and F) Multiple predicted PTS pathway components are enriched in the fecal microbiomes of mice colonized with complete (E) or cultured (F) human gut microbial communities and maintained on a high-fat, high-sugar Western diet. KO level-predicted functional annotations are colored by average fold-difference in their representation in microbiomes obtained from mice on the different diets (Western versus LF/PP). Data represent averages from mice colonized with the complete or cultured fecal communities from two unrelated human donors.

FIG. 9 The community composition of microbes cultured from humanized gnotobiotic mice can be reshaped by altering host diet. (A) Culture collections were generated from fecal samples obtained from gnotobiotic mice colonized with complete or cultured human gut microbial communities and maintained on LF/PP or Western diets. (B) PCoA of nonphylogenetic (binary Jaccard) distances between cultured samples indicates that manipulation of host diet can be used to shape the composition of communities recovered in culture from these animals. Analysis of phylogenetic (UniFrac) distances between samples produced similar clustering by donor and host diet (FIG. 10).

FIG. 10 Plated communities of human gut microbes can be reshaped through diet selection in gnotobiotic mice. (A) PCoA analysis of unweighted UniFrac distances between communities collected from mice before and after a diet switch and plated on GMM. Scree plots display variance explained by PCoA analysis of binary Jaccard (B) or unweighted UniFrac (C) distances between samples.

FIG. 11 Experimental parameters for en masse culturing, taxonomic assignment, inoculation of germfree mice, and arrayed strain collections. (A) Most readily cultured OTU in a human fecal sample are observed in six GMM plates. Rarefaction analysis describes the number of new OTU observed with each additional agar plate added to the dataset (10 plates were prepared independently). Points reflect the mean value after 100 iterations (plates sampled in random order without replacement); error bars represent one SD. The mean number of new OTU identified per plate drops below 20 with six or more plates (red). (B) Distributions of percent identities between pairwise comparisons of V2 16S rRNA gene sequences from representatives of bacterial taxa with varying degrees of shared phylogeny. We selected 4,041 16S rRNA sequences from the SILVA database (v102) that contain complete V2 regions and full (species-level) SILVAVOTE annotations. Sequences were aligned using PyNast. After removal of gap-only columns, the % ID between V2 regions was calculated for each pairwise comparison. The resulting % ID distributions are plotted for members of two different species within the same genus (interspecies), two different genera of the same family (intergenus), and so forth. (C) Comparison of three methods for assigning taxonomy to V2 16S rRNA sequences. (D and E) Sequences identified in gnotobiotic mice colonized with a readily cultured human gut microbiota do not reflect nongrowing or dormant cells. (D) Alpha-diversity analysis of fecal microbial communities of mice that had been inoculated with the control sample described in SI Materials and Methods. Diversity is similar at the 7-d and 14-d time points. (E) Time-course beta-diversity analysis of gnotobiotic mice inoculated with the control sample. UniFrac distances were calculated between all samples and represented spatially by PCoA. In this figure, variance along the major coordinate of variance (PC1) is plotted against time; colors represent individual mice. (F) Communities of cultured human gut microbes can be clonally archived in 384-well format by limiting dilution. At a dilution of a human fecal sample that produces 70% empty wells, a Poisson distribution predicts that 25% of wells will contain a clonal population of cells and that 5% of wells will be nonclonal (arrow). (G) Optimization of dilutions for arrayed strain collections. A 1.28×108-fold dilution of the stored fecal aliquot and subsequent inoculation into 384-well trays (0.17 mL per well) produces 70% empty wells. (H) Rarefaction analysis indicates that ten 384-well trays are sufficient to capture nearly all the genus-level diversity that can be retrieved from a single fecal sample using this arrayed culturing method.

FIG. 12 Personal culture collections archived in a clonally arrayed, taxonomically defined format. (A) After limiting dilution of the sample into 384-well trays to the point at which most turbid wells are clonal, a two-step, barcoded pyrosequencing scheme allows each culture well to be associated with its corresponding bacterial 16S rRNA sequence. In the first round of PCR, one of the V2-directed 16S rRNA primers incorporates 1 of 96 error correcting barcodes (BC1, highlighted in red) that designates the location (row and column) within a quadrant of the 384-well tray where the sample resides. The primer also contains a 12-bp linker (blue). All amplicons generated from all wells in a given quadrant from a single plate then are pooled and subjected to a second round of PCR in which one of primers, which targets the linker sequence, incorporates another error-correcting barcode (BC2; green) that designates the quadrant and plate from which the samples were derived, plus an oligonucleotide (gray) used for 454 pyrosequencing. Amplicons generated from the second round of PCR then are pooled from multiple trays and subjected to multiplex pyrosequencing. This approach allows unambiguous assignment of 16S rRNA reads to well and plate locations using a minimum number of barcodes and primers; e.g., 96 BC1 primers and 96 BC2 primers allow 96²(9,216) wells to be analyzed. (B) Representation of the original (complete) microbial community in the arrayed strain collection.

FIG. 13 Study design for refined diets. Two sets of gnotobiotic mice harboring a synthetic microbiota composed of ten sequenced human gut bacterial species were presented a total of 17 diets differing in their concentrations of casein (protein), corn oil (fat), sucrose (simple sugar), and cornstarch (polysaccharide). (A) The model community used for all experiments consisted of sequenced bacterial species from the four most abundant phyla in the adult human gut microbiota: Bacteroidetes (blue), Firmicutes (green), Actinobacteria (yellow), and Proteobacteria (red). (B,C) The first screen consisted of 11 refined diets: 9 of these diets (A-I in panel B) represent all possible combinations of high, medium, and low protein and fat; the two additional diets (J and K in panel C) contained high sucrose/low starch and high starch/low sucrose, respectively.

FIG. 14 Total community abundance (biomass) and the abundance of each community member can best be explained by changes in casein. (A) The total DNA yield per fecal pellet increased as the amount of casein in the host diet increased (shown are mean±S.E.M. for each tested concentration of casein). (B) Changes in species abundance as a function of changes in the concentration of casein in the host diet were also apparent for all 10 species; 7 species were positively correlated with casein concentration (e.g., B. caccae, right panel) while the remaining three species were negatively correlated with casein concentration (e.g. E. rectale, left panel). Data points from the first and second set of mice given the refined diets (see Table 9 for explanation) are shown in purple and green, respectively, while the mean and standard error for all diets at a given concentration of casein are shown in red and tan, respectively.

FIG. 15 Mean community member abundance for each diet. The height of each bar indicates the total DNA yield/biomass for a given diet. Casein concentrations (g/kg) for each diet are displayed in gray above each bar. See FIG. 13 and Table 6 for a description of diets A-Q.

FIG. 16 Total community DNA yield as a function of protein concentration. Nine different 15-week-old gnotobiotic male C57Bl/6J mice harboring the 10-member community were each given a randomly selected diet containing varying amounts of three different refined protein sources (soy, egg white solids, and lactalbumin), and two different refined fat sources (olive oil and lard) (see Table 9 for diet schema). Each mouse was sampled on days 5, 6, and 7 of the diet period. DNA was extracted from each fecal pellet and the three samples from each mouse were averaged to produce the final DNA yield per fecal pellet (see Table 17 for results of DNA measurements).

FIG. 17 Changes in species abundance as a function of changes in the concentration of casein in the host diet. Changes are apparent for all species in the model microbiota (note that the responses of E. rectale and B. caccae are shown in FIG. 14B of the main text). Data obtained from the first and second set of mice are shown in blue and green, respectively, while mean values±S.E.M are shown in red and tan, respectively.

FIG. 18 Simulation of competition for limiting resources. (A) Using equations 4 and 5 for species1 and species2, both species were initialized to a population size of 2 and a diet switch was initiated every ten days, increasing casein abundance at each switch (red numbers indicate % casein for each diet period). (B) The steady-state values of the simulation in panel A mirror the findings in our mouse datasets where the increase in a bacterial species (species1) that is casein limited leads to a decrease in species2 with increasing dietary casein.

FIG. 19 Example of community member responses to complex human foods. Changes in species abundance as a function of diet ingredients were apparent for all 10 species (Table 16). B. ovatus increased in absolute abundance with increased concentration of oats in the diet (A), while most of the ten bacterial species (including E. rectale and C. aerofaciens) responded to multiple ingredients (B and C). The mean and standard error for all diets are plotted (no error bars are shown when replicate points are not available). The colored z-axis mesh grid on the 3D plots is a triangle-based linear interpolation of the data with color changes corresponding to the values in the color bar on the right.

FIG. 20 Estimation of steady state. Nine adult male gnotobiotic mice harboring the ten-member model human gut community were fed a low-fat, low-protein diet (diet A in FIG. 13B) for 7-days and then switched to a high-fat, high-protein (diet I in FIG. 13B) at time-point zero for 13 days. The relative abundance of each of the taxa was subsequently defined using shotgun sequencing of fecal DNA to determine their Informative Genome Fraction (IGF). (A) The relative abundance of each bacterium changes rapidly within hours of a diet switch, reaching steady state levels by the third day (shown are the two species with the greatest increase and decrease respectively in relative abundance). Mean values±SEM are plotted at each time point. (B) Changes in total fecal DNA yield also increased rapidly in the first 24 h after the diet switch, reaching steady state levels on the fourth day.

FIG. 21 Reliable replication of human donor microbiota in gnotobiotic mice. (A) Assembly of bacterial communities in mice that had received microbiota transplants from the obese and lean co-twins in DZ pair 1. PCoA plot based on unweighted Unifrac distance matrix and 97% ID OTUs in sampled fecal communities. Spheres correspond to a single fecal sample obtained at a given time point from a given mouse and are colored according to the co-twin microbiota donor, and the experiment (n=3 independent experiments). Note that assembly is reproducible within members of a group of mice that have received a given microbiota, and between experiments. (B) Transplantation of fecal microbiota from human donors to recipient mice is not only reproducible within members of a recipient group but also captures interpersonal differences. Mean values±SEM for pairwise UniFrac distance measurements are plotted. ‘Self-Self’ comparison, same mouse sampled at different time points within a given experiment; ‘Mouse-Mouse (same donor)’, mice colonized with the same human donor's fecal microbiota sample (3-8 mice/donor; 1-4 independent experiments/donor sample); ‘Mouse-Human donor’, comparison of fecal bacterial communities in recipient group of mice versus their human donor's microbiota; ‘Mouse-Unrelated Humans’, comparison of fecal microbiota from recipients of given donor's microbiota compared to the fecal microbiota of all other unrelated individuals (across twin pair comparison). *, p-value<0.05, **, p-value<0.001; Monte Carlo simulation, 100 iterations.

FIG. 22 Unweighted UniFrac analysis of samples collected along the length of the gut. Mean values±SEM for pairwise UniFrac distance measurements are plotted. ‘Self-Self’, comparison of community structures from different regions of the gut (small intestinal segments 1, 2, 5, 9, 13, 15 each analyzed separately with pair wise comparisons of segments). ‘Mice colonized with the same donor’, mice colonized with the same human donor's fecal microbiota sample (3-8 mice/donor; 1-4 independent experiments/donor sample); ‘Mouse colonized with sibling donor’, where the sibling represents the discordant co-twin; ‘Unrelated human donors’, comparison of fecal microbiota from recipients of given donor's microbiota versus fecal microbiota of all other unrelated individuals (across twin pair comparison). *p-value<0.05, ** p-value<0.001; Monte Carlo simulation, 100 iterations.

FIG. 23 Correlation between the representation of genes with assigned KEGG EC annotations in human donor 1 (A), human donor 2 (B) human donor 3 (C) and human donor 4 (D) microbiome and their representation in the cecal microbiomes of the corresponding gnotobiotic mouse transplant recipients. Each sphere represents an EC. Mean values±SEM are plotted for each EC in a given group of mice (n=4 recipient mice/human donor). The Spearman correlation r-value is indicated and is significant in all cases (p<0.0001).

FIG. 24 Transmission of the increased adiposity phenotypes of obese co-twins in discordant pairs by transplantation of their fecal microbiota into gnotobiotic mice. (A) Body composition, defined by quantitative magnetic resonance, performed one day and two weeks post-colonization, of each mouse in each recipient group. Mean values±SEM are plotted of the increase in % body fat over 14 d in all recipient mice for each of the 4 obese co-twins' or lean co-twins' fecal microbiota (n=3-12 animals/donor microbiota; 41 mice/BMI bin; total of 82 mice). ***, p<0.001, as judged by a two-tail Mann-Whitney U-test. (B) More detailed and prolonged time course study for recipients of fecal microbiota from the co-twins in discordant pair 1 (mean values±SEM plotted; n=4 mice/donor microbiota). A linear mixed model revealed that the difference between the gain in adiposity between the two recipient groups of mice is statistically significant (p<0.001).

FIG. 25 Pathway maps representing ECs enriched in the fecal meta-transcriptome of mice colonized with an obese compared to lean co-twin's fecal microbiome.

FIG. 26 Metabolites with significant differences in their levels in the ceca of gnotobiotic recipients of obese compared to lean co-twin fecal microbiome transplants. (A) cellobiose and lactose levels as defined by non-targeted GC/MS. (B) Targeted GC/MS analysis of cecal SCFA. *, p<0.05; **, p<0.01 (two-tailed unpaired Student's t-test).

FIG. 27 Transplantation of a bacterial culture collection from an obese co-twin into germ-free mice produces an increased adiposity phenotype that is ameliorated by exposure to co-housed mice harboring a culture collection from her lean co-twin. (A) Design of follow-up co-housing experiment. 8 week-old, male germ-free C57Bl/6J mice received culture collections from the lean (Ln) co-twin or the obese (Ob) co-twin in DZ twin pair 1. Five days post gavage (5dpc) mice were dually co-housed in one of three configurations: control groups consisted of Ob-Ob, or Ln-Ln cagemates; the experimental group consisted of Obch-Lnch cagemates. The number of types of cages in each gnotobiotic isolator is shown. All mice were fed a low-fat, plant polysaccharide-rich diet. Adiposity phenotypes were measured by quantitative magnetic resonance. (B) Adiposity change from dpc1 measured by quantitative MR at dpc15 after 10 d of co-housing. (C-F). PCoA plot of UniFrac distances between transplanted bacterial communities showing the effects of co-housing over time. Also shown are the results obtained when two GF mice were co-housed (GFch) with a Lnch and a Obch mouse (n=3 cages). (G) Family-level taxa whose representation are significantly different between Ob mice and Ln, Obch, Lnch, or GFch mice (p<0.05 after Bonferroni correction) and discriminatory between the Ob and other groups (Random Forests, feature importance score >0.07). (H) GC/MS analysis of levels of short chain fatty acids in the ceca of the indicated groups of mice. Concentrations of acetate, propionate and butyrate were significantly higher in the ceca of control Ln, and Obch, Lnch, and GFch mice compared to Ob controls (*, p<0.05; two tailed Student's t-test). (I) Non-targeted GC/MS reveals that in contrast to Ob controls, cecal levels of cellobiose and lactose are undetectable in Ln mice and in all three groups of co-housed animals.

FIG. 28 Co-housing experiments designed to test the effects of a bacterial consortium assembled from the clonally arrayed culture collection from the lean co-twin in DZ pair 1. (A, B) Experimental design. Effects of co-housing Obch and Ln37ch mice on (C) adiposity (note that dashes connect animals that were co-housed, arrows highlight the Obch mice whose adiposity decreased during the period of co-housing, *, p<0.05, **, p<0.01 compared to Ob controls as defined by Mann-Whitney U test).

DETAILED DESCRIPTION OF THE INVENTION

The present invention discloses in vitro and in vivo cultures of a gut microbial community, models comprising such cultures, and methods of use thereof. Such a culture, while not a complete reproduction of a gut microbial community, maintains a phylotypic composition such that the culture reflects the original gut microbial community it was derived from. The original gut microbial community may be a complete gut microbial community, or a prior culture of a complete gut microbial community. As used herein, a “complete” gut microbial community refers to the natural in vivo composition of the gut microbial community of a given individual. Advantageously, a culture of the invention allows the analysis of the effect of perturbations on a complete gut microbial community by analyzing the effect of the perturbation on a culture derived from the gut microbial community.

The present invention comprises several different in vitro cultures, including a cultured collection of a gut microbial community and a clonally arrayed culture collection of a gut microbial community. Additionally, the invention comprises in vivo cultures, wherein an animal comprises a cultured collection of a gut microbial community or a clonally arrayed culture collection of a gut microbial community. Furthermore, the invention comprises methods of using a cultured collection of a gut microbial community, a clonally arrayed culture collection of a gut microbial community, or an animal comprising a culture of a gut microbial community.

(I) In Vitro Cultures of a Gut Microbial Community

The present invention encompasses in vitro cultures of a gut microbial community. For instance, the present invention encompasses a cultured collection of a gut microbial community and a clonally arrayed cultured collection of a gut microbial community as detailed below. Generally speaking, an in vitro culture will have a phylotypic composition similar to the original gut microbial community.

(a) Phylotypic Composition

The term “phylotypic composition,” as used herein, refers to the composition of a gut microbial community as defined by phylotypes. A phylotype is a biological type that classifies an organism by its phylogenetic, e.g. evolutionary, relationship to other organisms. The term phylotype is taxon-neutral, and therefore, may refer to the species composition, genus composition, class composition, etc. or, in alternative embodiments, may refer to organisms with a specified genetic similarity (e.g. 97% similar at a sequence level, or 97% similar at a gene function level).

In some embodiments, an in vitro culture of a gut microbial community may comprise between about 1 and 100% of the phylotypes present in the original gut microbial community. In certain embodiments, an in vitro culture of a gut microbial community may comprise at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10% of the phylotypes present in the original gut microbial community. In other embodiments, an in vitro culture of a gut microbial community may comprise at least about 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95 or 100% of the phylotypes present in the original gut microbial community. In still other embodiments, an in vitro culture of a gut microbial community may comprise at least about 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, or 90% of the phylotypes present in the original gut microbial community. In yet other embodiments, an in vitro culture of a gut microbial community may comprise at least about 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 or 100% of the phylotypes present in the original gut microbial community. In a preferred embodiment, an in vitro culture of a gut microbial community may comprise at least about 98.0, 98.1, 98.2, 98.3, 98.4, 98.5. 98.6, 98.7, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, or 99.9% of the phylotypes present in the original gut microbial community. In another preferred embodiment, an in vitro culture of a gut microbial community may comprise greater than 99.0% of the phylotypes present in the original gut microbial community.

In exemplary embodiments, an in vitro culture of a gut microbial community may comprise at least about 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, or 90% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community. In yet other embodiments, an in vitro culture of a gut microbial community may comprise at least about 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 or 100% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community. In a preferred embodiment, an in vitro culture of a gut microbial community may comprise at least about 98.0, 98.1, 98.2, 98.3, 98.4, 98.5. 98.6, 98.7, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, or 99.9% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community. In another preferred embodiment, an in vitro culture of a gut microbial community may comprise greater than 99.0% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community.

In certain exemplary embodiments, an in vitro culture of a gut microbial community may comprise at least about 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, or 90% of the metagenome, transcriptome, or proteome of the original gut microbial community. In yet other embodiments, an in vitro culture of a gut microbial community may comprise at least about 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 or 100% of the metagenome, transcriptome, or proteome of the original gut microbial community. In a preferred embodiment, an in vitro culture of a gut microbial community may comprise at least about 98.0, 98.1, 98.2, 98.3, 98.4, 98.5, 98.6, 98.7, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, or 99.9% of the metagenome, transcriptome, or proteome of the original gut microbial community. In another preferred embodiment, an in vitro culture of a gut microbial community may comprise greater than 99.0% of the metagenome, transcriptome, or proteome of the original gut microbial community.

The phylotypic composition of a cultured or complete gut microbial community may be evaluated using several different methods. Non-limiting examples of methods that may be used to evaluate the phylotypic composition of a complete or cultured gut microbial community may include the biological classification of individual isolated microbial colonies, the analysis of the biological functions represented in a sample, and the metagenomic analysis of genetic material isolated from the complete or cultured gut microbial community.

In some embodiments, the phylotypic composition of a gut microbial community may be evaluated by analyzing biological functions represented in a sample of the community. Suitable biological functions may include enzyme functions or drug resistance, such as antibiotic resistance. For instance, the capture and characterization of antibiotic resistance genes may be used to evaluate the biological functions represented in a sample. Non-limiting examples of antibiotics that may be used to capture and characterize antibiotic resistance genes may include amikacin, amoxicillin, carbenicillin, cefdinir, cloramphenicol, ciprofloxacin, cefepime, gentamicin, oxytetracyline, penicillin, piperacillin, piperacillin+Tazobactam, tetracycline, trimethoprim, and rimethoprim+sulfamethoxazole.

In other embodiments, the phylotypic composition of a gut microbial community may be evaluated using metagenomic analysis of genetic material isolated from the gut microbial community. For instance, a conserved region in the composite genomes of the gut microbial community may be sequenced, or the composite genome of a gut microbial community may be shotgun sequenced. In one embodiment, the phylotypic composition of a gut microbial community may be evaluated by sequencing a conserved 16S ribosomal RNA (rRNA) gene of the composite genomes of the gut microbial community. By way of non-limiting example, DNA from a complete or cultured collection of a gut microbial community may be extracted and the variable region 2 (V2) of bacterial 16S rRNA genes may be pyrosequenced.

In yet other embodiments, the phylotypic composition of a gut microbial community may be evaluated by shotgun sequencing of the composite genomes followed by analysis of predicted functions contained in the composite genomes of the gut microbial community. In one embodiment, the phylotypic composition of a gut microbial community may be evaluated by shotgun sequencing of the composite genomes followed by analysis of predicted functions contained in the composite genomes of the gut microbial community by querying against a known database, such as the KEGG Orthology (KO) database.

The phylotypic composition in a gut microbial community may be evaluated at various stages during sample collection, extraction, culture, and storage to produce a profile of diversity in a sample. In some embodiments, the phylotypic composition in the gut microbial community may be evaluated after extraction from the animal host but before culture. In other embodiments, the representation of the taxa in the gut microbial community may be evaluated after culture. In preferred embodiments, the taxa in the gut microbial community may be evaluated both after extraction from the animal host and after culture.

(b) Cultured Collection of a Gut Microbial Community

One aspect of the present disclosure provides a cultured collection of a gut microbial community. As used herein, a “cultured collection of a gut microbial community” refers to an in vitro collection of cultured microorganisms derived from an original gut microbial community. Cultivation of a cultured collection of a gut microbial community may alter the microbial community structure and representation of members of the original gut microbial community, resulting in a “cultured collection” with a phylotypic composition similar to the original gut microbial community. In an exemplary embodiment, the cultured collection is stable, meaning that over time the members comprising the collection do not substantially change. As used herein, “substantially change” means less than about 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1% difference between the members comprising the cultured collection when it is evaluated at two separate time points. In some embodiments, the cultured collection is stable for 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, or more than 90 days. In other embodiments, the cultured collection is stable for 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, or more than 12 months. In still other embodiments, the cultured collection is stable for 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or more than 10 years.

Culture conditions may be optimized to maximize the phylotypic composition of members of the original gut microbial community during culture. Non-limiting examples of methods that may be used to optimize culture conditions to maximize the phylotypic composition during culture may include using a low concentration of nutrients to limit growth of aggressive members of the gut microbial community, optimizing plating density to produce dense but distinct colonies, and optimizing the incubation period to balance the growth of aggressive and slow growing members of a gut microbial community.

In some embodiments, low concentrations of a nutrient may be used to limit growth of aggressive members of the gut microbial community to maximize the phylotypic composition of members of a gut microbial community during culture. Non-limiting examples of commonly used nutrients in microbial culture that may be used at low concentrations include glucose, tryptone and yeast extract.

In other embodiments, plating density is optimized to produce dense but distinct colonies to maximize the phylotypic composition of members of a gut microbial community during culture. In a preferred embodiment, a sample of a gut microbial community may be plated at a density of about 4000 to about 6000 colonies per 150 mm diameter culture plate. In another preferred embodiment, a sample of a gut microbial community may be plated at a density of about 2000 to about 7000 colonies per 150 mm diameter culture plate. In an exemplary embodiment, a sample of a gut microbial community may be plated at a density of about 5000 colonies per 150 mm diameter culture plate.

The number of colonies cultured from a sample of a gut microbial community can and will vary depending on the desired phylotypic composition in the resulting cultured collection of the gut microbial community. The number of colonies needed to culture a gut microbial community may be determined using any of the methods used to assess the phylotypic composition of a gut microbial community described above. In some embodiments, the number of colonies cultured from a sample of a gut microbial community is about 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, 10,000, 11,000, 12,000, 13,000, 14,000, 15,000, 16,000, 17,000, 18,000, 19,000, 20,000, or more than 20,000. In other embodiments, the number of colonies cultured from a sample of a gut microbial community is about 20,000 to 40,000. In yet other embodiments, the number of colonies cultured from a sample is greater than 40,000. In an exemplary embodiment, the number of colonies cultured from a sample of a gut microbial community is about 30,000 colonies.

The incubation period during the culture of a gut microbial community may be optimized to maximize the phylotypic composition. In some embodiments, plates comprising a gut microbial community may be incubated for about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14 days or more. In one embodiment, plates comprising a gut microbial community may be incubated for about 5 days.

In some embodiments, non-commercially available components that may help increase the phylotypic composition during culture may be used. Non-limiting examples of such components may include sterile rumen or human fecal extracts.

In one embodiment, a gut microbial community isolated from a subject is cultured on solid agar media.

In an exemplary embodiment, a cultured collection of a gut microbial community may comprise at least about 50, 60, 70, 80, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 or 100% of the phylotypes present in the original gut microbial community. In a preferred embodiment, a cultured collection of a gut microbial community may comprise at least about 98.0, 98.1, 98.2, 98.3, 98.4, 98.5. 98.6, 98.7, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, or 99.9% of the phylotypes present in the original gut microbial community. In another preferred embodiment, a cultured collection of a gut microbial community may comprise greater than 99.0% of the phylotypes present in the original gut microbial community.

In exemplary embodiments, a cultured collection of a gut microbial community may comprise at least about 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, or 90% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community. In yet other embodiments, a cultured collection of a gut microbial community may comprise at least about 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 or 100% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community. In a preferred embodiment, a cultured collection of a gut microbial community may comprise at least about 98.0, 98.1, 98.2, 98.3, 98.4, 98.5. 98.6, 98.7, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, or 99.9% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community. In another preferred embodiment, a cultured collection of a gut microbial community may comprise greater than 99.0% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community.

In certain exemplary embodiments, a cultured collection of a gut microbial community may comprise at least about 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, or 90% of the metagenome, transcriptome, or proteome of the original gut microbial community. In yet other embodiments, a cultured collection of a gut microbial community may comprise at least about 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 or 100% of the metagenome, transcriptome, or proteome of the original gut microbial community. In a preferred embodiment, a cultured collection of a gut microbial community may comprise at least about 98.0, 98.1, 98.2, 98.3, 98.4, 98.5, 98.6, 98.7, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, or 99.9% of the metagenome, transcriptome, or proteome of the original gut microbial community. In another preferred embodiment, a cultured collection of a gut microbial community may comprise greater than 99.0% of the metagenome, transcriptome, or proteome of the original gut microbial community.

Another aspect of the present disclosure provides a clonally arrayed culture collection of a gut microbial community. A “clonally arrayed culture collection” of a gut microbial community, as used herein, refers to a collection of cultured microbes each derived from a single microbial cell from a gut microbial community.

A clonally arrayed culture collection of a gut microbial community may be derived from a complete gut microbial community isolated from a subject, or from a previously cultured gut microbial community. A complete or previously cultured gut microbial community may be sampled as described in section I(d) below.

In some embodiments, a clonally arrayed culture collection of a gut microbial community may be generated by picking and isolating individual colonies from a gut microbial community cultured on plates. In certain embodiments, a clonally arrayed culture collection of a gut microbial community may be generated using a most probable number (MPN) technique, also known as the method of Poisson zeroes. In essence, the MPN technique allows for creating clonally arrayed species collections by inoculating culture wells with a diluted sample of a gut microbial community so that a certain percentage of the inoculated wells does not receive a microbe.

In some embodiments, a clonally arrayed culture collection of a gut microbial community is generated using a dilution point that yields about 30 to 90% empty wells. In other embodiments, a clonally arrayed culture collection of a gut microbial community is generated using a dilution point that yields about 50, 40, 60, 70, 80, or 90% empty wells. In a preferred embodiment, a clonally arrayed culture collection of a gut microbial community is generated using a dilution point that yields about 70% empty wells. At this dilution point, only about 5% of the wells will receive more than one cell in the inoculum, or non-clonal wells.

Handling, culture and storage conditions for generating a clonally arrayed culture collection of a gut microbial community are under strictly anaerobic conditions as described in section I(d) below. A clonally arrayed culture collection of a gut microbial community may be in multiwell culture plates. Non-limiting examples of multiwell culture plates that may be used for generating and storing a clonally arrayed culture collection of a gut microbial community include 6-well, 12-well, 24-well, 48-well, 96-well and 384-well plates. In an exemplary embodiment, a clonally arrayed culture collection of a gut microbial community may be in 384-well plates.

A clonally arrayed culture collection of a gut microbial community may be taxonomically defined. A two-step barcoded pyrosequencing scheme illustrated in FIG. 12 may be used to allow each culture well to be associated with its corresponding bacterial 16S rRNA sequence. In essence, the two-step barcoded pyrosequencing scheme uses two DNA amplification reactions using barcoded primers. This, combined with pyrosequencing, allows unambiguous assignment of 16S rRNA reads to well and plate locations using a minimum number of barcodes and primers.

In some embodiments, a clonally arrayed culture collection derived from an original gut microbial community contains about 100 to about 5000 taxonomically defined isolates. In other embodiments, a clonally arrayed culture collection may contain about 500, 600, 700, 800, 900, 1000, 2000, 3000, or 4000 to about 5000 taxonomically defined isolates. In still other embodiments, a clonally arrayed culture collection may contain about 800, 900, 1000, or 2000 to about 5000 taxonomically defined isolates. In an exemplary embodiment, the clonally arrayed culture collection may contain about 1,000 taxonomically defined isolates.

In an exemplary embodiment, a clonally arrayed culture collection of a gut microbial community may comprise at least about 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 or 100% of the phylotypes present in the original gut microbial community. In a preferred embodiment, a clonally arrayed culture collection of a gut microbial community may comprise at least about 98.0, 98.1, 98.2, 98.3, 98.4, 98.5. 98.6, 98.7, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, or 99.9% of the phylotypes present in the original gut microbial community. In another preferred embodiment, a clonally arrayed culture collection of a gut microbial community may comprise greater than 99.0% of the phylotypes present in the original gut microbial community.

In exemplary embodiments, a clonally arrayed culture collection of a gut microbial community may comprise at least about 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, or 90% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community. In yet other embodiments, a clonally arrayed culture collection of a gut microbial community may comprise at least about 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 or 100% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community. In a preferred embodiment, a clonally arrayed culture collection of a gut microbial community may comprise at least about 98.0, 98.1, 98.2, 98.3, 98.4, 98.5. 98.6, 98.7, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, or 99.9% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community. In another preferred embodiment, a clonally arrayed culture collection of a gut microbial community may comprise greater than 99.0% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community.

In certain exemplary embodiments, a clonally arrayed culture collection of a gut microbial community may comprise at least about 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, or 90% of the metagenome, transcriptome, or proteome of the original gut microbial community. In yet other embodiments, a clonally arrayed culture collection of a gut microbial community may comprise at least about 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 or 100% of the metagenome, transcriptome, or proteome of the original gut microbial community. In a preferred embodiment, a clonally arrayed culture collection of a gut microbial community may comprise at least about 98.0, 98.1, 98.2, 98.3, 98.4, 98.5, 98.6, 98.7, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, or 99.9% of the metagenome, transcriptome, or proteome of the original gut microbial community. In another preferred embodiment, a clonally arrayed culture collection of a gut microbial community may comprise greater than 99.0% of the metagenome, transcriptome, or proteome of the original gut microbial community.

(d) Gut Microbial Community and Collection

An in vitro culture of a gut microbial community may be derived from a subject that is a rodent, a human, a livestock animal, a companion animal, or a zoological animal. In one embodiment, a culture of a gut microbial community may be derived from a rodent, e.g. a mouse, a rat, a guinea pig, etc. In another embodiment, an in vitro culture of a gut microbial community may be derived from a livestock animal. Non-limiting examples of suitable livestock animals may include pigs, cows, horses, goats, sheep, llamas and alpacas. In still another embodiment, an in vitro culture of a gut microbial community may be derived from a companion animal. Non-limiting examples of companion animals may include pets such as dogs, cats, rabbits, and birds. In still yet another embodiment, an in vitro culture of a gut microbial community may be derived from a zoological animal. As used herein, a “zoological animal” refers to an animal that may be found in a zoo. Such animals may include non-human primates, large cats, wolves, and bears. In an exemplary embodiment, an in vitro culture of a gut microbial community may be derived from a human.

An in vitro culture of a gut microbial community may be derived from the same subject over a predetermined time period. For instance, in some embodiments, the microbial community may be sampled at an interval of 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, or 200 days.

In some embodiments, an in vitro culture of a gut microbial community may be derived from a subject with an endemic gut microbial community. In other embodiments, an in vitro culture of a gut microbial community may be derived from a sterile subject inoculated with a gut microbial community from another subject. In yet other embodiments, an in vitro culture of a gut microbial community may be derived from a sterile animal inoculated with a previously cultured gut microbial community (e.g. a cultured collection or a clonally arrayed cultured collection as described herein). In other embodiments, an in vitro culture of a gut microbial community may be derived from a sterile animal inoculated with a defined mixture of gut microbes. In yet other embodiments, an in vitro culture of a gut microbial community may be derived from a sterile animal inoculated with a mixture of gut microbes from a clonally arrayed culture collection of a gut microbial community.

The gut environment in a suitable subject is anaerobic. Any prolonged exposure to aerobic conditions may lead to a significant alteration in the gut microbial community structure. Therefore, to reflect the gut microbial community structure in a subject, sample collection, extraction, culture and storage conditions should be maintained under strictly anaerobic conditions upon harvesting the sample from the animal host. Methods for providing anaerobic conditions for sample collection, extraction, culture and storage are known in the art and include performing all operations in anaerobic chambers and incubators.

Anaerobic conditions must also be maintained in sample extraction buffers and growth media. Anaerobic conditions may be maintained in the sample extraction buffers and growth media by using reducing agents. Non-limiting examples of reducing agents may include cysteine.

Methods of collecting a gut microbial community are known in the art. In certain embodiments, a gut microbial community may be extracted from luminal material collected from the gastrointestinal system, such as from the proximal, central, or distal portions of the small intestine, cecum, or colon. In other embodiments, a gut microbial community may be extracted from a freshly excreted fecal sample. Generally speaking, a freshly excreted fecal sample should be transferred to an anaerobic chamber within 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 minutes of its collection. In one embodiment, a freshly excreted fecal sample is transferred to an anaerobic chamber within 5 minutes of its collection.

Generally speaking, a newly collected sample of a gut microbial community may be suspended in buffer. In a preferred embodiment, the sample is allowed to separate in the buffer, allowing large insoluble particles to settle, thus improving downstream handling steps. In an exemplary embodiment, a gut microbial community may be suspended in pre-reduced PBS buffer.

(II) In Vivo Culture of a Gut Microbial Community

Yet another aspect of the present disclosure provides an animal comprising a gut microbial community consisting of cultured microbial members. In essence, to generate an animal comprising a gut microbial community consisting of cultured microbial members, a sterile animal may be colonized with a cultured gut microbial community. Such an animal may be referred to as gnotobiotic. Methods of colonizing sterile animals with a gut microbial community are known in the art and consist of introducing an extract comprising a gut microbial community directly into the animal by oral gavage. Oral gavage is the administration of fluids directly into the lower esophagus or stomach using a feeding needle or tube introduced into the mouth and threaded down the esophagus.

In some embodiments, the animal is a laboratory animal. Non-limiting examples of a laboratory animal may include rodents, canines, felines, and non-human primates. In certain embodiments, the animal is a rodent. Non-limiting examples of rodents may include mice, rats, guinea pigs, etc. The genotype of the sterile animal can and may vary depending on the intended use of the animal. In embodiments where the animal is a mouse, the mouse may be a C57BL/6 mouse, a Balb/c mouse, a 129sv, or any other laboratory strain. In an exemplary embodiment, the mouse is a C57BL/6J mouse. In other embodiments, the animal is a livestock animal, such as swine.

Sterile animal husbandry methods are known in the art. Sterile animals are typically born under aseptic conditions, which may include removal from the mother by Caesarean section. Sterile animals are generally housed in a sterile or microbially-controlled laboratory environment in which they remain free of all microbes such as bacteria, exogenous viruses, fungi, and parasites.

In some embodiments, a sterile animal may be colonized with an in vitro culture of a gut microbial community. An in vitro culture of a gut microbial community may be derived from an animal as described in section I above. In certain embodiments, a sterile animal may be colonized with a cultured collection of a gut microbial community. In other embodiments, a sterile animal may be colonized with a clonally arrayed culture collection of a gut microbial community.

In yet other embodiments, a sterile animal may be colonized with a subset of a clonally arrayed culture collection of a gut microbial community. For instance, a sterile animal may be colonized with one or more clonal members of a clonally arrayed culture collection of a gut microbial community. In one embodiment, a sterile animal may be colonized with 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or more than 10 clonal members of a clonally arrayed culture collection of a gut microbial community. In another embodiment, a sterile animal may be colonized with about 10, 20, 30, 40, 50, 60, 70, 80, 90, 100 or more than 100 clonal members of a clonally arrayed culture collection of a gut microbial community. In yet another embodiment, a sterile animal may be colonized with about 100, 200, 300, 400, 500, 600, 700, 800, 900 1000 or more than 1000 clonal members of a clonally arrayed culture collection of a gut microbial community. In still another embodiment, a sterile animal may be colonized with about 1000, 2000, 3000 or more clonal members of a clonally arrayed culture collection of a gut microbial community.

In an exemplary embodiment, an in vivo culture of a cultured gut microbial community may comprise at least about 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 or 100% of the phylotypes present in the original gut microbial community. In a preferred embodiment, an in vivo culture of a cultured gut microbial community may comprise at least about 98.0, 98.1, 98.2, 98.3, 98.4, 98.5. 98.6, 98.7, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, or 99.5% of the phylotypes present in the original gut microbial community. In another preferred embodiment, an in vivo culture of a cultured gut microbial community may comprise greater than 99.0% of the phylotypes present in the original gut microbial community.

In exemplary embodiments, an in vivo culture of a cultured gut microbial community may comprise at least about 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, or 90% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community. In yet other embodiments, an in vivo culture of a cultured gut microbial community may comprise at least about 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 or 100% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community. In a preferred embodiment, an in vivo culture of a cultured gut microbial community may comprise at least about 98.0, 98.1, 98.2, 98.3, 98.4, 98.5. 98.6, 98.7, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, or 99.9% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community. In another preferred embodiment, an in vivo culture of a cultured gut microbial community may comprise greater than 99.0% of the phylum, class, order, family, genus or species phylotypes present in the original gut microbial community.

In certain exemplary embodiments, an in vivo culture of a cultured gut microbial community may comprise at least about 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, or 90% of the metagenome, transcriptome, or proteome of the original gut microbial community. In yet other embodiments, an in vivo culture of a cultured gut microbial community may comprise at least about 90, 91, 92, 93, 94, 95, 96, 97, 98, 99 or 100% of the metagenome, transcriptome, or proteome of the original gut microbial community. In a preferred embodiment, an in vivo culture of a cultured gut microbial community may comprise at least about 98.0, 98.1, 98.2, 98.3, 98.4, 98.5, 98.6, 98.7, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8, or 99.9% of the metagenome, transcriptome, or proteome of the original gut microbial community. In another preferred embodiment, an in vivo culture of a cultured gut microbial community may comprise greater than 99.0% of the metagenome, transcriptome, or proteome of the original gut microbial community.

(III) Models and Methods of the Invention

Yet another aspect of the present disclosure provides methods of using an in vitro or in vivo culture of the invention. Importantly, an in vitro or in vivo culture of the invention may be used as a model of a complete gut microbial community. For instance, as described in more detail below, an in vitro or in vivo culture may be used to determine the effect of a perturbation on a gut microbial community or host thereof. As used herein, “perturbation” refers to any compound or condition administered or applied to a gut microbial community. Advantageously, the effect of the perturbation on an in vitro or in vivo culture of the invention or a host thereof may be representative of the effect of the perturbation on the complete gut microbial community that the culture was derived from.

(a) Perturbations and Effects

As described above, a “perturbation,” as used herein, refers to any compound or condition administered or applied to a gut microbial community. For instance, in one embodiment, a perturbation may be diet related. Non-limiting examples of diet related perturbations may include foods, specific food ingredients, specific nutrients (e.g. vitamin, mineral, protein, carbohydrate, etc.), or combinations thereof.

In another embodiment, a perturbation may be environmentally related. Non-limiting examples of environmentally related perturbations may include temperature, humidity, or other climate related variables, exposure to other gut microbial communities, exposure to other environmental microbial communities, exposure to different living conditions (e.g. different physical conditions, different psychological conditions, different sleeping conditions, different work conditions, etc.), or exposure to pathogens.

In yet another embodiment, a perturbation may be pharmaceutical. Non-limiting examples of a pharmaceutical may be a drug, a prebiotic, a probiotic, or a neutraceutical. In some embodiments where the perturbation is a drug, the drug is an approved drug. In other embodiments where the perturbation is a drug, the drug is undergoing clinical studies or regulatory testing. In certain embodiments, a drug may be a small molecule, a protein, an antibody, a nucleic acid (e.g. antisense, aptamer, miRNA, RNAi, etc.), or other pharmaceutical.

In an alternative embodiment, a perturbation may be genetic.

In an exemplary embodiment, the perturbation is a food or food ingredient. In another exemplary embodiment, the perturbation is a drug, prebiotic, or probiotic.

Non-limiting examples of the types of effects that can be determined using a model and method of the invention include effects of the perturbation on the composition of the gut microbial community, effects of the perturbation on the metabolism of the gut microbial community, and effects of the perturbation on host biology due to changes in the gut microbial community. In one embodiment, a model and method of the invention may be used to determine the effect of a perturbation on the composition of the gut microbial community. In this regard, “composition of the gut microbial community,” may include the phylotypic composition, the metagenomic composition, the transcriptome composition, or the proteome composition of the gut microbial community. In another embodiment, a model and method of the invention may be used to determine the effect of a perturbation on the metabolism of the gut microbial community. In yet another embodiment, a model and method of the invention may be used to determine the effects of the perturbation on host biology. By way of non-limiting examples, the effects may be changes in host metabolism, changes in host transcription, changes in host protein expression, changes in host immune response, and changes in host gut cellular biology.

In an exemplary embodiment, a method of the invention comprises applying the perturbation to the gut microbial community and determining the impact of the perturbation on the spatial and/or functional organization of the gut microbial community and the niches (professions) of its component members, the impact of the perturbation on the capacity of the community to respond to changes in diet, the impact of the perturbation on the ability of component members to forage adaptively on host-derived mucosal substrates, the impact of the perturbation on the physical and functional interactions that occur between the changing microbial communities and the intestinal epithelial barrier, or the impact of the perturbation on the interaction of the gut microbial community and the immune system of the host.

(b) Diet Related Perturbations

One method of the invention encompasses a method of determining the effect of a diet related perturbation on a gut microbial community or host thereof. Such a method comprises applying the perturbation to the gut microbial community and determining the effect of the perturbation on the gut microbial community or host thereof. As detailed above, the gut microbial community may be an in vitro or in vivo cultured gut microbial community. In exemplary embodiments, differences in the cultured gut community before and after the application of the perturbation advantageously represent the effect of the perturbation on the original gut microbial community or host thereof.

In some embodiments, a method of the invention encompasses a method of determining the effect of a food or food ingredient on a cultured gut microbial community. Such a method comprises evaluating the cultured gut microbial community before and after the perturbation, wherein the difference in the cultured collection represents the effect of the perturbation on the original gut microbial community.

In another embodiment, the invention encompasses a method of evaluating how the nutritional value of a food ingredient varies with the composition of a subject's gut microbial community. The method generally comprises administering a food ingredient (or food) to one or more subjects with varying gut microbial communities and evaluating the differences in nutritional value of the food ingredient between the subjects in conjunction with evaluating the differences in the gut microbial community of the subjects. Nutritional value of a food or food ingredient may be measured using any method known in the art. In certain embodiments, nutritional value may be determined in terms of growth of the host, metabolic activity of the microbiome, metabolic activity of the host, or microbiome biomass. Such methods may provide information on which foods (or food ingredients) provide better nutrition to a particular group of subjects. For instance, it may be determined for a particular population that the nutritional value of one food ingredient is better than a second food ingredient. Hence, such a method may be used to increase the feed efficiency of a particular diet for either agricultural animals, performance animals, or humans.

In an exemplary embodiment of the above method, the gut microbial community is a cultured gut microbial community.

In a further embodiment, for a malnourished population, such a method may be used to determine the best food or food ingredient for ameliorating the malnourishment. As used herein, “malnourishment” refers to the inadequate or excessive consumption of dietary ingredients leading to the development of disease.

In other embodiments, a method of the invention encompasses a method of predicting the variations in the abundance of a member of a gut microbiome of a host in response to a proposed diet. Generally speaking, the method comprises (a) determining the abundance of a member of a gut microbime in a host, (b) determining the amount of the diet ingredients protein, fat, polysaccharide and simple sugar in a proposed diet, (c) determining the linear coefficient for a particular gut microbiome member in relation to protein, fat, polysaccharide, and simple sugar, (d) predicting the absolute abundance of the member of the gut microbiome if the host were to be fed the proposed diet in (b) based on the linear coefficient from (c) for a particular diet ingredient and the amount of the diet ingredient, and determining the difference between (a) and (d), wherein the difference is the predicted variation in the abundance of a gut microbiome member in response to the proposed diet.

In yet other embodiments, a method of the invention encompasses a method of predicting the abundance of a member of a gut microbiome of a host in response to a proposed diet. The method comprises (a) determining the amount of the diet ingredients protein, fat, polysaccharide and simple sugar in a proposed diet, (b) determining the linear coefficient for a particular gut microbiome member in relation to protein, fat, polysaccharide, and simple sugar, and (c) predicting the absolute abundance of the member of the gut microbiome if the host were to be fed the proposed diet in (a) based on the linear coefficient from (b) for a particular diet ingredient and the amount of the diet ingredient.

In still other embodiments, a method of the invention encompasses a method of specifically manipulating the abundance of a member of a gut microbiome of a host to a target level by changing the diet of the host. The method comprises (a) determining the linear coefficient for a particular gut microbiome member in relation to protein, fat, polysaccharide, and simple sugar, (b) determining the amount of protein, fat, polysaccharide and sugar in a diet necessary to achieve the target level of the gut microbiome member based on the linear coefficients from (a), and (c) feeding a diet to the host that contains the amount of protein, fat, polysaccharide and sugar determined in (b).

For each of the above embodiments, methods of determining the abundance of a member of a gut microbiome are known in the art. Similarly, methods of determining the amount of the diet ingredients protein, fat, polysaccharide and simple sugar in a proposed diet are known in the art. The linear coefficient for a particular gut microbiome member for a particular food ingredient may be determined using a model of a human gut microbiome community. The abundance of a member of a gut microbiome may be calculated with the equation yi=β0+βproteinXprotein+βpolysaccharideXpolysaccharide+βsucroseXsucrose+βfatXfat, where yi is the abundance of the member of the gut microbiome, β0 is the calculated parameter for the intercept, X is the amount in g/(kg of total diet) of the diet ingredient, and βprotein, βpolysaccharide, βsucrose, and βfat are the linear coefficients for a particular gut microbiome member for each of the diet components. In some embodiments, β₀for a particular gut microbiome member for a particular food ingredient may be determined using a gnotobiotic mouse model of a human gut microbiome community.

One method of the invention encompasses a method of determining the effect of an environmental perturbation on a gut microbial community or host thereof. Such a method comprises applying the perturbation to the gut microbial community and determining the effect of the perturbation on the gut microbial community or host thereof. As detailed above, the gut microbial community may be an in vitro or in vivo cultured gut microbial community. In exemplary embodiments, differences in the cultured gut community before and after the application of the perturbation advantageously represent the effect of the perturbation on the original gut microbial community or host thereof.

(d) Pharmaceutical Perturbations

Yet another aspect of the present disclosure provides a method of evaluating the impact of a pharmaceutical on a gut microbial community. The method typically comprises evaluating a culture of a gut microbial community in the presence and absence of the pharmaceutical, and identifying the differences, if any, between the culture exposed to the pharmaceutical, and the culture not exposed to the pharmaceutical. For instance, in one embodiment, an in vivo model (as detailed in section II above) of a particular subject's gut microbial community may be used to determine how a particular pharmaceutical would impact that subject's gut microbial community. Such a method may be used to determine the reaction of the subject's gut microbial community to the pharmaceutical without having to administer the drug or pharmaceutical to the subject itself. Such reactions may include any changes in the composition of the gut microbial community, changes in the metabolism of the gut microbial community, or changes in host biology stemming from a change in the gut microbial community.

(e) Methods of Identifying Agents that Impact a Gut Microbial Community

In some instances the invention encompasses methods of identifying agents that impact a gut microbial community. In one embodiment, such a method may comprise applying a perturbation to a gut microbial community and determining the changes the perturbation evokes in the community. Specifically, in certain embodiments, changes in one or more taxa are identified. These taxa may then be applied to a cultured gut microbial community, either individually or in combinations, to determine their impact on the cultured gut microbial community. In this manner, agents that impact a gut microbial community may be identified.

In one embodiment, the invention encompasses a method of discovering a probiotic. The method generally comprises identifying a microbe that thrives after administration of a particular food or food ingredient to a subject. For instance, an in vitro culture may be created before and after administration of a food or food ingredient to a subject. Differences in the before and after gut microbial cultures may be evaluated to determine a microbe that thrives upon the administration of the particular food or food ingredient. Similarly, a particular food or food ingredient may be administered to a sterile animal comprising a known culture of a gut microbial community. Changes in the gut microbial community may be evaluated to identify a microbe that thrives upon the administration of the particular food or food ingredient. Methods of evaluating a gut microbial community, and method of identifying a microbe that is thriving in a gut microbial community are known in the art, and may include those detailed herein.

(f) Disease Models

Another aspect of the present disclosure provides a method of creating a disease model. The method generally comprises 1) identifying a gut microbial community that is related to, the cause of, or the result of a particular disease or disorder, and 2) reproducing that gut microbial community in an in vitro or in vivo model as described above.

Yet another aspect of the present disclosure provides a method of treating a disease. The method typically comprises identifying a difference between a normal gut microbial community and a gut microbial community of a subject afflicted with the disease or disorder, and altering the gut microbial community of the subject afflicted with the disease or disorder to more closely resemble a normal gut microbial community.

(g) Administration of a Specific Cultured Gut Microbiome

Yet another aspect of the present disclosure provides a method of altering the gut microbiome of a subject, the method comprising administering a cultured gut microbiome to the subject. For instance, it may be determined, using a method of the invention, that a particular gut microbiome culture may be advantageous to a subject. Such a microbiome may be administered via oral gavage, as described herein, or in any other manner suitable for administering the cultured collection. By way of non-limiting example, a gut microbiome may be administered to a subject early in its life to form a gut microbiome that is best suited for the growth of the subject in a particular environment. Suitable subjects may include animals (e.g. performance animals, food animals, companion animals, etc.) and humans.

DEFINITIONS

The term “metagenomics” refers to the application of modern genomic techniques to the study of the composition and operations of communities of microbial organisms sampled directly in their natural environments, by passing the need for isolation and lab cultivation of individual species.

The term “sterile animal” refers to an animal that has no microorganisms living in or on it. In one embodiment, the sterile animal is a sterile mouse.

The term “gnotobiotic animal” refers to an animal in which only certain known strains of bacteria and other microorganisms are present.

EXAMPLES

The following examples illustrate various embodiments of the invention. It should be appreciated by those of skill in the art that the techniques disclosed in the examples that follow represent techniques discovered by the inventors to function well in the practice of the invention. Those of skill in the art should, however, in light of the present disclosure, appreciate that many changes can be made in the specific embodiments that are disclosed and still obtain a like or similar result without departing from the spirit and scope of the invention, therefore all matter set forth or shown in the accompanying drawings is to be interpreted as illustrative and not in a limiting sense.

Introduction to Examples 1-9

Efforts to dissect the functional interactions between microbial communities and their environmental or animal habitats are complicated by the long-standing observation that, for many of these communities, the great majority of organisms have not been cultured in the laboratory. Methodological differences between culture-independent and culture-based approaches have contributed to the challenge of deriving a realistic appreciation of exactly how much discrepancy exists between the culturable components of a microbial ecosystem and total community diversity. (Table 1 gives examples of these methodological differences.)

The largest microbial community in the human body resides in the gut: Its microbiome contains at least two orders of magnitude more genes than are found in our Homo sapiens genome. Culture-independent metagenomic studies of the human gut microbiota are identifying microbial taxa and genes correlated with host phenotypes, but mechanistic and experimentally demonstrated links between key community members and specific aspects of host biology are difficult to establish with these methods alone. The goals of the examples presented below are (i) to evaluate the representation of readily cultured phylotypes in the human gut microbiota; (ii) to profile the dynamics of these cultured communities in a mammalian gut ecosystem; and (iii) to determine whether a clonally arrayed, personalized strain collection could be constructed to serve as a foundation for reassembling varying elements of a human's gut microbiota in vitro or in vivo.

Example 1
Estimating the Abundance of Readily Cultured Bacterial Phylotypes in the Distal Human Gut

To estimate the abundance of readily cultured bacterial phylotypes in the distal human gut, primers were used to amplify variable region 2 (V2) of bacterial 16S ribosomal RNA (rRNA) genes present in eight freshly discarded fecal samples obtained from two healthy, unrelated anonymous donors living in the United States (n=1 complete sample per donor at t=1, 2, 3, and 148 d). Amplicons were subjected to multiplex pyrosequencing, and the results were compared with those generated from DNA prepared from ˜30,000 colonies cultured from each sample, under strict anaerobic conditions and harvested after 7 d at 37° C. on a rich gut microbiota medium (GMM) composed of commercially available ingredients (“cultured” samples; details of the culturing technique are given in Materials and Methods, and a description of GMM is given in Table 2). The resulting 16S rRNA datasets were de-noised to remove sequencing errors, reads were grouped into operational taxonomic units (OTU) of ≧97% nucleotide sequence identity (ID), and chimeric sequences were eliminated (Materials and Methods).

In total, 632 distinct 97% ID OTU were observed in the complete samples, and 316 were identified in the cultured samples. The average abundance of cultured OTU in the complete samples was 0.4%, but the average abundance of uncultured OTU (i.e., those observed in the complete but not the cultured samples) was significantly lower (0.06%; P<10⁻⁶by an unpaired, two-tailed student's t test, not assuming equal variances).

Example 2
Evaluating the Representation of Readily Cultured Taxa in the Human Gut Microbiota

To evaluate the representation of readily cultured taxa in the human gut microbiota at varying phylogenetic levels, taxonomic designations were assigned to each 97% ID OTU (Materials and Methods). Each 16S rRNA read from the complete fecal sample was scored as “cultured” if it had a taxonomic assignment that also was identified in the corresponding cultured population. If a 97% ID OTU in the complete sample could not be placed in any known taxonomic group, it was scored as “cultured” only if the same 97% ID OTU was observed in the cultured sample. This analysis indicated that 99% of the 16S rRNA reads derived from the complete fecal samples from either donor belong to phylum-, class- and order-level taxa that also are present in the corresponding cultured sample; 89±4% of the reads are derived from readily cultured family-level taxa, and 70±5% and 56±4% belong to readily cultured genus- and species-level taxa, respectively (FIG. 1A Upper). Two alternate taxonomic binning methods, the Ribosomal Database Project (RDP) Bayesian classifier v2.0 and an arbitrary % ID cutoff, produced similar results (FIG. 2 A-F). Control experiments described in Materials and Methods indicate that at least 98% of the reads generated from 30,000 pooled colonies are not derived from nongrowing or lysed bacteria (the percentage of reads from the original fecal samples that is derived from dead cells is unknown).

Unsupervised hierarchical clustering of the complete and cultured microbial communities, across the two donors and four time points, revealed that cultured samples cluster separately from those that had not been cultured. Both phylogenetic and nonphylogenetic metrics segregate cultured samples by donor, suggesting that the distinctiveness of each donor's microbiota is preserved in their collections of readily cultured representatives (FIGS. 2 G and H).

Shotgun DNA pyrosequencing was performed to determine the degree to which predicted functions contained in the composite genomes of the complete human fecal microbial communities were represented in the corresponding collection of cultured microbes [n=4 samples (one complete and one cultured from each of two donors); 119,842±43,086 high-quality shotgun reads per microbiome; average read length, 366 nt]. On average, 90% of the 2,302 distinct KEGG Orthology (KO) annotations identified in the two uncultured samples also were observed in the cultured communities (FIG. 1B, FIGS. 3 A and B). This high percentage of functional representation also was observed when the microbiomes were subjected to alternate annotation schemes: On average, 94% of 929 enzyme commission (EC) assignments and 95% of 216 level 2 KEGG pathways associated with the complete fecal samples also were detected in the cultured communities (FIG. 3 C—F).

Example 3
Comparing Functions Represented in the Complete and Cultured Microbiota

To compare further the functions represented in the complete and cultured microbiota independent of annotation, antibiotic-resistance genes were captured from their microbiomes in expression vectors in Escherichia coli. Each E. coli library contained ˜1 GB of 1.5- to 4-kB fragments of microbiome DNA subcloned into an expression vector and was screened against a panel of 15 antibiotics and clinically relevant antibiotic combinations (Table 3). Genes encoding resistance to the same 14 antibiotics were captured in libraries prepared from complete and cultured fecal samples (FIG. 3G and Table 4). In one example, a screen for DNA fragments that confer resistance to the aminoglycoside amikacin produced candidate genes from the microbiomes of both complete and cultured microbial communities from Donor 1 but not from Donor 2. Two genes conferring amikacin resistance (either the 16S rRNA methylase rmtD or the aminoglycoside phosphotransferase aphA-3) were identified in 70% of the DNA fragments captured in selections for this phenotype. Direct culturing of the original fecal communities in the presence of amikacin confirmed that this resistance function is significantly enriched in the readily cultured microbiota of Donor 1 compared with Donor 2 (P<0.005 based on triplicate samples; unpaired, two-tailed student's t test assuming equal variances) (FIG. 3H); and PCR analysis showed that many of the amikacin resistant fecal strains harbor rmtD or aphA-3. Sequencing the 16S rRNA genes of a subset of these isolates indicated that rmtD is present in strains of Bacteroides uniformis, B. caccae, and B. thetaiotaomicron in this donor (although, notably, not in the sequenced type strains of these species) and that aphA-3 is contained in the genome of a member of the genus Desulfotomaculum (order Clostridiales).

Example 4
Determining Whether an Individual's Readily Cultured Community Exhibits Behavior In Vivo Mirroring that of the Individual's Complete Microbial Community

To determine whether a community composed of an individual's readily cultured bacteria exhibits behavior in vivo mirroring that of the individual's complete microbial community, 9-wk-old C57B16/J germfree mice were colonized with a complete or cultured microbiota from each of the two human donors (n=5 recipient mice per sample type). A fecal sample from each donor was divided after collection, and one aliquot was gavaged directly into one group of recipient mice; the other aliquot was cultured on GMM plates for 7 d, as above, harvested, and introduced into a second group of recipient animals. Mice were maintained on a standard autoclaved low-fat, plant polysaccharide-rich (LF/PP) chow diet before and 4 wk after gavage. 16S rRNA analysis of fecal samples collected from these mice at the end of the 4-wk period indicated that the complete and the cultured communities were influenced similarly by host selection: 91±3% of the 16S rRNA reads identified from mice colonized with a human donor's complete fecal microbiota were derived from genus-level taxa that also were identified in the mice colonized with the cultured microbial community from the same donor (FIG. 1A Lower). Importantly, control experiments demonstrated that the harvested, actively growing colonies gavaged into each germfree mouse are able to exclude nongrowing species that might be present on GMM plates from establishing themselves in recipient animals (details are given in Materials and Methods).

Luminal material was collected from the proximal, central, and distal portions of the small intestine, cecum, and colon of mice colonized with either the complete or cultured communities from each of the two human donors. V2-directed bacterial 16S rRNA sequencing revealed similar geographic variations in community structures (FIG. 1C and FIG. 4 A-C).

Example 5
Determining Whether the Similarities in Community Composition In Vivo Extend to Similarities in Community Gene Content

To determine whether the similarities in community composition in vivo extend to similarities in community gene content, the same fecal DNA samples that had been prepared from these mice after 4 wk on the LF/PP diet for 16S rRNA analyses were subjected to shotgun pyrosequencing (n=4 samples; 87,357±30,710 reads per sample). As with the 16S rRNA analysis, comparisons of the representation of KOs in the various microbiome samples revealed an even greater correlation between complete and cultured communities after they had been subjected to in vivo selection than before their introduction into mice (FIG. 1B, FIG. 3 A-F).

Example 6
Assessing Whether a Complex Community of Cultured Microbes could Restore Epididymal Fat Pad Weights to the Levels Associated with Complete Microbial Communities

Previous comparisons of adult germfree mice with those that harbor gut microbial communities (either conventionally raised animals or formerly germfree animals colonized from mouse or human donors) have shown that the presence of a complete gut microbiota is associated with increased adiposity. In comparison, colonization of germfree mice with a single, readily cultured, prominent human gut symbiont (Bacteroides thetaiotaomicron) or with a defined community of 12 bacterial species prominently represented in the distal human gut is insufficient to restore epididymal fat pad stores to levels observed in conventionally raised animals (data not shown). To assess whether a complex community of cultured microbes could restore epididymal fat pad weights to the levels associated with complete microbial communities, we evaluated mice colonized with the complete or the cultured fecal communities from the two human donors. All animals displayed significantly greater fat pad to body weight ratios than germfree controls, and no significant difference was observed in adiposity between mice colonized with the donors' complete or cultured microbiota (FIG. 4D).

Example 7
Testing Whether a Microbial Community Consisting Only of Cultured Members Recapitulates Known Diet-Induced Changes in Microbial Community Structure In Vivo

Mice colonized with a complete human microbiota undergo drastic changes in microbial community structure (even after a single day) when shifted from LF/PP chow to a high-fat, high-sugar Western diet. To test whether a microbial community consisting only of cultured members recapitulates this behavior in vivo, the four groups of gnotobiotic mice colonized with the complete or cultured microbes from two unrelated human donors were monitored by fecal sampling before, during, and after a 2-wk period when they were placed on the Western diet (samples were collected at days 4, 7, and 14 of the first LF/PP phase, then 1 d before and 3, 7, and 14 d after initiation of the Western diet phase, and finally 1, 3, 8, and 15 d after the return to the LF/PP diet). 16S rRNA-based comparisons of fecal communities were performed using both phylogenetic and nonphylogenetic distance metrics. With either metric, principal coordinates analysis (PCoA) revealed that mice colonized with the complete or cultured samples maintain communities that cluster first by donor (principal coordinate 1; PC1) and that the complete and cultured communities from both donors respond to the diet shift in a similar manner [principal coordinate 2 (PC2); FIG. 5A-C and FIGS. 6A and B]. Like the transplanted complete microbiota examined here and in previous reports, the cultured microbiota responded to this Western diet by increasing the relative proportion of representatives of one class of Firmicutes (the Erysipilotrichi) and decreasing the relative proportion of the Bacteroidia class (FIG. 6C). Notably, of the 18 species-level phylotypes significantly affected by diet shift in the mice containing the complete microbiota of both human donors, 14 were detected and demonstrated the same statistically significant response in mice colonized with readily cultured taxa (FIG. 5D and FIG. 7).

The fecal microbiomes of LF/PP-fed mice harboring complete or cultured communities from each of the two unrelated donors were compared with microbiomes sampled after these mice consumed the Western diet for 14 d (101,222±24,271 reads per sample). The representation of level 2 KEGG pathway functions was highly concordant on both diets, with one exception: Genes encoding phosphotransferase system (PTS) pathways for carbohydrate transport were significantly overrepresented in Western diet-fed mice harboring complete or cultured communities from either donor (FIG. 5E and FIG. 8A-D). Higher-resolution KO level annotations confirmed that the diet-based PTS pathway enrichment reflected increased representation of multiple carbohydrate transporters (FIGS. 8E and F). These results emphasize that the similar taxonomic restructuring of complete and cultured communities in response to diet is accompanied by similar changes in community gene content.

Example 8
Using Gnotobiotic Mice as Biological Filters to Recover Collections of Readily Cultured Microbes

Because human gut communities composed of readily cultured members exhibit responses to host diet that mirror those characteristic of a complete microbiota, the possibility that gnotobiotic mice can be used as biological filters to recover collections of readily cultured microbes, obtained from selected human hosts, that are enriched for certain properties [e.g., the ability to prosper (bloom) when exposed to specific foods or food ingredients] was explored. To this end, fecal samples from mice colonized with the complete or corresponding cultured human gut microbial communities from the two unrelated donors and fed the LF/PP or Western diets were collected directly into anaerobic medium and then plated on prereduced GMM plates (FIG. 9A). After 7-d incubation, V2-directed 16S rRNA profiling of these plated microbial collections confirmed that these populations of cultured microbes can be reshaped deliberately in vivo and then recovered in vitro (FIG. 9B and FIG. 10). On either diet, cultured populations showed significantly greater resemblance to the in vivo communities from mice consuming the same diet than to the in vivo communities from the same mice consuming the alternate diet (P<10-11, unpaired two-tailed student's t test of within donor distances shown in FIG. 9B, assuming equal variances).

Example 9
Creating Arrayed Species Collections Representing the Bacterial Diversity of the Gut Microbiota

The strict anaerobic techniques used here, compounded with highly diverse colony morphologies across taxa, complicate efforts to pick and isolate individual colonies at a scale sufficient to capture the bacterial diversity represented on the culture plates. Therefore, a most probable number (MPN) technique was used for creating arrayed species collections in a multiwall format without colony picking. First, the dilution point for a fecal sample that yields 70% empty wells (no detectable growth) after inoculation into 384-well trays and 7-d anaerobic incubation was empirically determined. Assuming that the distribution of cells into the wells follows a Poisson distribution, a dilution that leaves 70% of wells empty should yield nonclonal wells (that is, wells that received more than one cell in the inoculum) only 5% of the time; the remainder should be clonal (FIGS. 11F and G). At this dilution, ten 384-well trays should yield ˜1,000 clonal wells. The two-step barcoded pyrosequencing scheme outlined in FIG. 12A was developed to assign a 16S rRNA sequence to the isolate(s) present in each turbid well.

This approach was used to create an archived, personalized culture collection of ten 384-well trays from one of the human donors. 16S rRNA sequences could be assigned to more than 99% of growth-positive wells. One advantage of clonally arrayed collections is that the effects of 16S rRNA primer bias encountered using DNA templates prepared from complex microbial populations are minimized when wells contain a single taxon. This point is illustrated by the known bias of most commonly used primers against Bifidobacteria spp.: Members of this genus were better represented among the set of 16S rRNA genes produced from individual wells than among those observed in complex communities harvested from GMM plates.

After the archived trays had been frozen under anaerobic conditions and stored at −80° C. for 7 mo, recovery of organisms from wells exceeded 60%. Full-length 16S rRNA sequences generated from these recovered strains matched the assignments from the barcoded pyrosequencing data in every case, suggesting that the dilutions did follow a Poisson distribution as predicted. Like 16S rRNA-based community profiling, such collections may miss rare, but important, members of the microbiota; seeding additional 384-well trays with the diluted sample will capture additional phylotypes (FIG. 11H). In total, this individual's culture collection contained 1,172 taxonomically defined isolates from four different phyla, seven classes, eight orders, 15 families, 23 genera, and 48 named bacterial species. Novel isolates were encountered at the family-, genus-, and species-levels, and 69% of the complete community had a genus-level representative in the arrayed collection (FIG. 12B). As a frame of reference, we identified a total of 159 human fecal or gut bacterial species from humans worldwide (including pathogens) in the German Resource Centre for Biological Material (DSMZ) culture collection (Materials and Methods). As such, personalized microbiota collections can complement those of international repositories by capturing strains that coexist in a shared habitat where community structure and host parameters can be measured.

The ability to capture this level of diversity after MPN dilution in these arrayed collections indicates that it is unlikely that interspecies syntrophic relationships by themselves are sufficient to explain the diversity observed on the GMM agar plates. On the other hand, these personalized arrayed culture collections should help identify obligate syntrophic relationships (e.g., by analyzing the patterns of co-occurrence of taxa in wells harboring more than one phylotype or by comparing arrayed collections in which one set of trays contains a candidate syntroph deliberately added to all wells).

Discussion for Examples 1-9.

The Examples presented above show that it is possible to capture a remarkable proportion of a person's fecal microbiota using straightforward anaerobic culturing conditions and easily obtained reagents. Variations in culturing conditions, including components that are not commercially available (e.g., sterile rumen or human fecal extracts) and other approaches for more closely approximating a native gut habitat, undoubtedly will allow additional members of the human gut microbiota to be cultured in vitro. These personal culture collections can be generated from humans representing diverse cultural traditions and various physiologic or pathophysiologic states. A key opportunity is provided when anaerobic culture initiatives are combined with gnotobiotic mouse models, thereby allowing culture collections to be characterized and manipulated in mice with defined (including engineered) genotypes who are fed diets comparable to those of the human donor, or diets with systematically manipulated ingredients. Temporal and spatial studies of these communities can be used to identify readily cultured microbes that thrive in certain physiological and nutritional contexts, creating a discovery pipeline for new probiotics and for preclinical evaluation of the nutritional value of food ingredients. Based on their in vivo responses, clonally archived cultured representatives of a person's microbiota can be selected for complete genome sequencing (including multiple strains of a given species-level phylotype) to identify potential functional variations that exist or evolve within a species occupying a given host's body habitat. Coinciding with the introduction of yet another generation of massively parallel DNA sequencers, this approach also should allow vast scaling of current sequencing efforts directed at characterizing human (gut) microbial genome diversity, evolution, and function. Recovered organisms also could be used as source material for functional metagenomic screens (bio-prospecting). Guided by the results of metagenomic studies of human microbiota donors, components of a personalized collection that have coevolved in a single host can be reunited in varying combinations in gnotobiotic mice, potentially after genome-wide transposon mutagenesis of selected taxa of interest, for further mechanistic studies of their interactions and impact on host phenotypes.

Materials and Methods for Examples 1-9.

Culturing of Fecal Microbiota.

Freshly discarded fecal samples from two anonymous unrelated human donors were transferred into an anaerobic chamber (Coy Laboratory Products) within 5 min of their collection. Samples were placed in prereduced PBS with 0.1% cysteine (PBSC) 15 mL⁻¹g⁻¹feces. The fecal material was suspended by vortexing for 5 min, and the suspension was allowed to stand at room temperature for 5 min to permit large insoluble particles to settle to the bottom of the tube. 16S ribosomal RNA (rRNA) sequencing of the starting material and of the supernatant obtained after the settling step showed no significant differences in community composition. This settling step dramatically increased the reproducibility of subsequent dilutions. Diluted (10⁻⁴) samples were plated on plates 150 mm in diameter containing prereduced, nonselective Out Microbiota Medium (GMM) (Table 2) so that colonies were dense but distinct (˜5,000 colonies per plate) after a 7-d incubation at 37° C. under an atmosphere of 75% N₂, 20% CO₂, and 5% H₂. GMM is modified from tryptone-yeast-glucose agar with 6% NaCl (TYGS) medium and contains only commercially available components; to discourage colony overgrowth, the concentration of glucose, tryptone, and yeast extract is reduced fivefold compared with TYGS. Colonies were harvested en masse from each of six plates by scraping with a cell scraper (BD Falcon) into 10 mL of prereduced PBSC. Stocks were generated by adding prereduced glycerol containing 0.1% cysteine to the fecal or cultured samples (final concentration of glycerol, 20%). Stocks were stored in anaerobic glass vials in a standard −80° C. freezer.

To determine the optimal number of plates to be surveyed for each fecal sample, a freshly discarded sample from one of the anonymous human donors was processed as above, and the 10⁻⁴dilution was plated on 10 prereduced GMM plates. De-noised, chimera-checked variable region 2 (V2)-directed 16S rRNA reads generated from the pooled colonies obtained from each plate separately after a 7-d incubation were assigned to operational taxonomic units (OTU) at 97% nucleotide sequence identity (ID) using QIIME v1.1. Each additional plate contributed new OTU, although, as shown by the rarefaction curves plotted in FIG. 11A, the contribution of each added plate fell to <20 new OTU after approximately six plates. For this reason, each subsequent cultured sample reflects pooled scraped material from six plates.

Gnotobiotic Mouse Husbandry.

Germfree adult male C57BL/6J mice were maintained in plastic gnotobiotic isolators. Mice were housed under a strict 12-h light/dark cycle and fed a standard, autoclaved low-fat/plant polysaccharide-rich (LF/PP) chow diet (B&K Universal.) ad libitum. Mice were colonized by gavage (0.2 mL of the resuspended fecal material or pooled cultured organisms recovered from GMM after 7-d incubation as above, per germfree recipient). Animals receiving different microbial inoculations were placed in separate gnotobiotic isolators before gavage; once gavaged, they were caged individually.

After 4 wk of acclimatization on the LF/PP diet, mice were transitioned to Western diet (Harlan-Teklad TD96132) ad libitum for 2 wk and then were returned to the LF/PP diet for 2 wk. 16S rRNA analysis of fecal samples collected 1, 4, 7, and 14 d after gavage indicated that both complete and cultured communities reached a steady state well before the diet transition. During the initial LF/PP diet phase, fecal samples were collected at postgavage days 4, 7, 14, and either on day 32 when the input community was a complete microbiota or on day 25 in the case of an input cultured community. Mice were sampled on days 1, 3, 7, and 14 after the shift to the Western diet and on days 1, 3, 8, and 15 upon return to LF/PP chow. The animals then were fasted for 24 h and returned to the LF/PP diet for 1 wk before they were killed.

Fecal samples for subsequent culture were collected from each mouse directly into BBL thioglycollate medium (BD), transported to an anaerobic chamber within 30 min, then diluted and plated on GMM as above. Fecal samples from fasted mice were not cultured because 16S rRNA analysis did not show significant changes in community composition at either the 12-h or 24-h fasting time points. After mice were killed, the intestine was subdivided into 16 segments of equivalent length numbered from 1 (proximal) to 16 (distal). Contents from small intestine segments 2, 5, and 13, plus cecum and colon contents, were snap frozen in liquid nitrogen and stored at −80° C.

DNA Extraction and Purification.

Fecal samples (0.1 g) were resuspended into 710 μL of 200 mM NaCl, 200 mM Tris, 20 mM EDTA (Buffer A) plus 6% SDS). After the addition of 0.5 mL of 0.1-mm zirconia/silica beads (BioSpec Products) and 0.5 mL of phenol/chloroform/isoamyl alcohol, pH 7.9 (Ambion), cells were lysed by mechanical disruption with a bead-beater (BioSpec Products) for 3 min. Samples were centrifuged for 3 min at 6,800×g, and the aqueous phase was collected and subjected to a second phenol-chloroform-isoamyl alcohol extraction using Phase Lock Gel tubes (5 Prime). DNA in the aqueous phase was precipitated by the addition of an equal volume of isopropanol and 0.1 volumes of 3 M sodium acetate, pH 5.5 (Ambion). After overnight incubation at −20° C., samples were centrifuged for 20 min at 4° C. at 18,000×g, and the supernatant was removed. Pelleted DNA was washed once with 0.5 mL of 100% ethanol, and dried using a vacuum evaporator. DNA pellets then were resuspended in 0.2 mL of Tris-EDTA containing 4 μg RNAseA (Qiagen). Crude DNA extracts were column-purified using the Rapid PCR Purification Kit (Marligen Biosciences). DNA concentrations were adjusted to 50 ng/μL for subsequent 16S rRNA or shotgun pyrosequencing.

16S rRNA Sequencing.

The V2 region of bacterial 16S rRNA genes was subjected to PCR amplification. PCR reactions were carried out in triplicate using 2.5× Master Mix (5 Prime), forward primer FLX-8F; 5′-GCCTTGCCAGCCCGCTCAGTCAGAGTTTGATCCTGGCTCAG-3′ (SEQ ID NO 1); (the 54 FLX Amplicon primer B sequence is underlined, and the 16S rRNA primer sequence 8F is italicized), barcoded reverse primer FLX-BC-338R; 5′-GCCTCCCTCGCGCCATCAGNNNNNNNNNNNNCA TGCTGCCTCCCGTAGGAGT-3′; (SEQ ID NO 2) (the 454 FLX Amplicon primer A sequence is underlined, “Ns” indicate the barcode sequence, and the 16S rRNA primer sequence 338R is shown in italics), and 50 ng input DNA purified as described above. Reactions were incubated for 2 min at 95° C., followed by 30 cycles of 20 s at 95° C., 20 s at 52° C., and 1 min at 65° C. Triplicate reactions were pooled, inspected by gel electrophoresis, and purified on AMPure beads (Agencourt Biosciences). For each barcoded primer, negative control reactions lacking input DNA were conducted in parallel. Purified samples were combined at equimolar concentrations and sequenced with FLX chemistry on a 454 pyrosequencer (Roche).

16S rRNA Sequence Analysis.

Metadata for all 500 samples, including barcodes, are provided in Table 26. For 16S rRNA sequence analysis, sequences were preprocessed to remove reads with low-quality scores (sliding window set to 50 bp), ambiguous characters, and incorrect lengths (<200 or >300 bp). Reads passing these criteria were assigned to specific samples based on their error-corrected barcode sequence, de-noised using default parameters, grouped into OTU at 97% ID, and a representative sequence was selected from each OTU using default parameters in QIIME v.1.1. These representative sequences then were filtered for possible chimeric sequences using ChimeraSlayer (microbiomeutil.sourceforge.net) with default parameters (sequences designated “unknown” were not discarded). Filtered datasets were subsampled to 1,000 sequences per sample (the only exceptions were the datasets from the human-derived complete and cultured samples collected at the day 148 time point shown in FIG. 1A, which were subsampled to 5,000 sequences). Beta-diversity calculations were conducted using Jaccard (nonphylogenetic) and UniFrac (phylogenetic) metrics in QIIME v1.1.

Weighted Taxonomic Analysis.

To quantify the representation of cultured and uncultured lineages in microbial communities, the presence or absence of each phylum-, class-, order-, family-, genus-, or species-level phylotype assigned to sequences in the complete sample(s) was determined in the cultured sample(s). Analysis of full-length and V2-region delimited sequences from the 16S rRNA genes of taxonomically defined bacteria indicated that discrete % ID cutoffs do not correspond closely to established taxonomic levels: Histograms of the distributions of % ID values of 16S rRNA sequences between representatives of two species in the same genus, two genera in the same family, and so forth, overlap to a large extent. (FIG. 11B shows comparisons of 16S V2 regions, which are used commonly in multiplex pyrosequencing studies, between 4,041 bacterial species selected from the SILVA database v102.) For this reason, a taxonomic assignment method was primarily used to compare uncultured and cultured communities across taxonomic levels rather than approximating taxonomic groups by selecting arbitrary % ID cutoffs to represent each taxonomic level. (For example, FIG. 11B illustrates that there is no clear % ID cutoff that distinguishes species-level from genus-level groups or family-level from order-level groups.) As an alternate, taxonomy-independent approach, de-noised 16S rRNA sequences were grouped into OTU at a range of % ID cutoffs (80%, 90%, 95%, 97%) using uclust in QIIME v1.1. At each % ID cutoff, OUT were filtered for chimeras as above. The proportion of reads in the uncultured sample that belonged to OTU also identified in the corresponding cultured sample were determined as in FIG. 1A (see FIG. 2A-F for a comparison of results obtained from different assignment methods).

SILVA-VOTE: A Computational Pipeline for Improved Accuracy in Taxonomic Assignments of V2 16S rRNA Sequences.

Commonly used tools for taxonomy assignment often failed to assign correctly V2 16S rRNA sequences derived from known human gut microbes. To generate a nonredundant, curated 16S rRNA database for taxonomy assignment, the v102 SILVA database was downloaded prefiltered for redundancy at a 99% ID (SSURef_—102_SILVA_NR_—99.fasta;://www.arb-silva.de). This database is composed of 262,092 full-length sequences from the small subunit rRNAs of Eukaryotes, Bacteria, and Archaea. A total of 297 sequences whose accession numbers had been removed from or modified by GenBank or were not associated with a complete National Center for Biotechnology Information (NCBI) taxonomy (i.e., phylum, class, order, family, genus, and species designations) were excluded. The remaining sequences were aligned using PyNast as implemented in QIIME v1.1: 224,899 sequences were aligned successfully and contained more than 90% of the V2 region. These V2 sequences were filtered for redundancy by clustering and selection of a representative sequence from each cluster, using uclust at a 99% identity. To assign consensus taxonomies to the representative sequences, we applied a 75% majority voting scheme: For each taxonomic level, the representative sequence was assigned a taxonomic designation if more than 75% of the sequences within the cluster shared the same assignment; otherwise, the cluster was labeled “unknown” at that taxonomic level. Taxonomic designations of sequences within a cluster that included the nonunique identifiers “unknown,” “uncultured,” “candidatus,” or “bacterium” were not considered in the 75% majority vote for taxonomy assignment of the representative sequence. Species-level annotations with numbers or decimal points (which in almost all cases refer to strains rather than species) also were excluded. After removal of sequence clusters with little or no consensus taxonomy (i.e., with 50% or more of the taxonomic levels labeled “unknown” after the voting analysis), 34,181 nonredundant, annotated, bacterial 16S rRNA V2 sequences remained and were designated as our reference database.

To assign taxonomy to the 16S rRNA V2-amplicon pyrosequencing reads, significant matches to the 34,181-sequence reference database were identified by BLAST (the top 100 hits with an e-value cutoff of 0-30 were retained). All the BLAST hits with a score within 10% of the score of the best BLAST hit were considered for the taxonomy assignment. Taxonomy was assigned for each phylogenetic level independently by using a majority voting scheme: A read was assigned a taxonomic designation if 50% or more of the selected reference sequences (whose BLAST scores were within 10% of the top score for that query sequence) shared the same taxonomic assignment. As above, sequences designated “unknown” were not taken into account for the voting. When no assignment was conserved in >50% of the selected BLAST hits, the query sequence was labeled as “nonidentified” at that taxonomic level. Data were normalized by the abundance of each taxonomic group in the original (uncultured) sample. For analysis of microbial communities from mice, taxonomic groups observed in fewer than two replicate animals were omitted.

To test this method, 16S rRNA V2 sequences were extracted from the genomes of 66 human gut microbes. Taxonomy was assigned to these test sequences in QIIMEv.1.1 using three methods: (i) the Ribosomal Database Project Bayesian classifier (v.2.0); (ii) a BLAST top hit-based query of the Greengenes core sequence set [composed of 4,938 sequences; downloaded Sep. 15, 2009; (greengenes.lbl.gov/Download/Sequence_Data/Fasta_data_files/core_set_aligned_fast a. imputed) (7)]; and (iii) with SILVA-VOTE. Comparison of these results suggests that SILVA-VOTE yields a significantly increased number of correct taxonomic assignments, particularly at the genus and species levels (FIG. 11C).

Control Experiments to Address the Influence of Lysed or Nongrowing Cells on 16S rRNA Datasets from Colonies Collected from Agar Plates.

Although each average-sized colony among the ˜30,000 colonies obtained from each cultured sample likely contributed ˜10⁹cells to the pooled population, in theory genetic material from lysed or nongrowing cells also could contribute to the sequences obtained from the plated samples. To test this possibility directly, fecal samples were diluted to the same level as above and plated onto GMM and also onto plates containing ingredients that should not support growth of bacteria and thus represent the background expected if 100% of the plated material was nongrowing or lysed [control PARC plates contained Phosphate buffer, noble Agar, Resazurin (oxygen indicator), and Cysteine (reducing agent) Table 5]. After a 7-d anaerobic incubation, no colonies were detected on the PARC plates. Twenty randomly selected single colonies from the GMM plates were picked, an aliquot was reserved for 16S rRNA gene sequencing, and the remainder was pooled with the scraped surfaces of the PARC plates. Sequencing this pool revealed that >98% of the 16S rRNA reads could be attributed to the 20 colonies from the GMM plates; among the remainder, none belonged to OTU represented by more than two reads per 1,000. Together, these findings suggest that at least 98% of the reads generated from 30,000 pooled colonies are not derived from nongrowing or lysed bacteria.

Testing the Possible Contribution of Lysed or Nongrowing Cells to Microbial Communities in Gnotobiotic Mice Gavaged with a Readily Cultured Human Gut Microbiota.

As noted in the main text, the initial cultured inoculum was prepared by scraping GMM plates en masse. In theory, this input could include cells that did not actually grow in these conditions but instead remained dormant, below the limit of detection by 16S rRNA sequencing, over the 7-d in vitro incubation period. To determine whether such non-growing taxa contributed to the distal gut communities of mice that received a readily cultured microbiota, a control sample containing material harvested from PARC plates and pooled with 20 visible colonies picked directly from GMM plates was introduced into five age-matched, individually caged, germfree mice fed a LF/PP diet. Fecal samples were collected at 3, 7, and 14 d postgavage and were subjected to V2-targeted 16S rRNA pyrosequencing. Community composition, as determined both by alpha-diversity and beta-diversity metrics, was stable after the 7-d time point (average UniFrac distance within 7-d or 14-d samples=0.319; average distance between 7-d and 14-d samples=0.321; P>0.89 based on unpaired, two-tailed student's t test; FIG. 11D-E). When 16S rRNA sequences obtained from the 14-d fecal samples were compared with sequences obtained from the 20 picked colonies, it was discovered that the mice harbored only two OTU, both mapping to Akkermansia muciniphila, that could not be attributed to the 20 colonies and that were not observed on GMM plates in any other experiments. Akkermansia muciniphila type strain ATCC BAA-835 contains three 16S rRNA genes and grows readily on GMM. This species was a minor component in the fecal microbiota of the two donors (no or one read per 1,000 reads from eight samples collected over time); in fecal communities sampled from mice that received the readily cultured component of either donor's microbiota, abundance averaged 1.8% across all time points. These findings indicate that just 20 actively growing colonies are able to exclude virtually all nongrowing species that may be present on GMM plates from colonizing germfree mice.

Shotgun Pyrosequencing.

Five hundred-nanogram aliquots of DNA prepared from selected complete and cultured microbiota were sheared and ligated to the default 454 Titanium multiplex identifiers (MIDs; Roche Rapid Library Preparation Method Manual, GS FLX Titanium Series, October 2009). 16S rRNA sequencing of samples from individually caged mice colonized with the same community indicated a high degree of similarity between individual animals; for this reason, fecal DNAs from replicate mice were pooled (n=3-5 mice per pool), and the 12 pooled samples, each labeled with a unique MID, were sequenced in a single 454 Titanium run.

Shotgun pyrosequencing reads were parsed by MID and filtered to remove short sequences (<60 bp), low-quality sequences (three or more N bases in the sequence or two continuous N bases), and replicate sequences (>97% ID over the length of the read, with identical sequences over the first 20 bases). Reads reflecting host DNA contamination were identified by BLAST (against the mouse genome for samples isolated from mice and against the human genome for all other samples) and were removed in silico (≧75% identify, E-value≦10⁻⁵, bitscore≧50). Remaining sequences were queried against the KEGG Orthology (KO) database (v52) with a Blastx e-value cutoff of 10⁻⁵. KO assignments were mapped further to Enzyme Classification (EC) and KEGG pathway annotations.

Bio-Prospecting for Antibiotic-Resistance Genes in Uncultured and Readily Cultured Microbiota.

DNA fragments from complete and cultured communities were cloned into an expression vector, electroporated into Escherichia coli, and screened for their ability to confer resistance to 15 different antibiotics. To this end, 10 μg of DNA purified from the two human donors' fecal microbiota, from the derived cultured communities, plus pooled contents of the arrayed strain collection were sheared to 1.5- to 4-kB fragments (Bioruptor XL), followed by size selection (1% agarose gel electrophoresis). Sheared DNA then was endrepaired (Epicentre Endlt Kit), column-purified (Qiagen Qia-Quick PCR Purification Kit), and concentrated in a vacuum evaporator (SpeedVac). The expression vector pZE21-MCS1 was prepared by PCR amplification using primers flanking the HincII site [pZE21_—126_—146FOR, 5′-GACGGTATCGATAAGCTTGAT-3′ (SEQ ID NO 3); pZE21_—111_—123rcREV, 5′-GACCTCGAGGGGGGG-3′ (SEQ ID NO 4)] to linearize the vector, gel-purification of the linear product, dephosphorylation (calf intestinal phosphatase), and column purification. Approximately 500 ng of the DNA fragments were ligated to 100 ng of the linearized vector in an overnight ligation reaction (Epicentre FastLink Ligation Kit). The ligation reaction was desalted by dialysis in double-distilled H₂O and electroporated into E. coli MegaX DH10B T1R cells (Invitrogen). After 1 h of recovery, a small (1 μL) aliquot of the library was titered with serial dilutions onto LB agar plates containing 50 μg/mL kanamycin (to select for pZE21 transformants) and incubated at 37° C. for 16 h. The insert size distribution for each library was characterized by gel electrophoresis of amplicons obtained using primers flanking the HincII site in the multiple cloning site of pZE21 MCS1. The total size of each library was estimated by multiplying average insert size by the number of cfu in a given library. The remainder of the recovered cells was inoculated into 10 mL LB containing 50 μg/mL kanamycin and grown overnight, with shaking, at 27° C. for ˜16 h. The culture subsequently was diluted with an equal volume of LB medium containing 30% glycerol and stored at −80° C. before screening.

For functional selections, 100 μL of each library freezer stock (corresponding to 0.5-1×10⁸cfu) was plated on an LB agar plate containing kanamycin (50 μg/mL) plus one of 15 different antibiotics (Table 3). The total number of cells plated on each antibiotic represented ˜10 copies of each original unique transformant. Antibiotic-resistant colonies were scored after plates had been incubated at 37° C. for 16 h. Inserts contained in colonies with amikacin-, piperacillin- and piperacillin/tazobactam-resistant phenotypes were subjected to bidirectional Sanger sequencing (Beckman Coulter Genomics) using primers pZE21_—81_—104_—57C (5′-GAATTCATTAAAGAGGAGAAA GGT-3′; SEQ ID NO 5) and pZE21_—151_—174rc_—58C (5′-TTTCGTTTTATTTGATGCCTCTAG-3′; SEQ ID NO 6). Resulting reads were trimmed to remove low-quality and vector sequences and subjected to within-library contig assembly (≧200 bp of 97% ID sequence required). Contigs and unassembled reads were mapped by BLAST to the National Center for Biotechnology Information (NCBI) nonredundant database and to a custom database of 122human gutmicrobial genomes. All sequence datasets have been deposited in the NCBI Sequence Read Archive (SRA) under accession no. SRA026271.

Amikacin-resistant strains were quantified from each donor, in triplicate, by plating diluted fecal samples on GMM with and without amikacin (4,100 μg/mL; lower concentrations produced high background). Amikacin-resistant colonies were quantified after 5-d incubation under anaerobic conditions, and colony counts were normalized to the total number of colonies obtained in the absence of the antibiotic. A total of 48 fecal isolates (12 from the GMM+amikacin selection and 12 from the nonselective plates, from each of two donors) were chosen for a PCR-based survey for the amikacin-resistance genes captured in the E. coli libraries described above and for 16S rRNA sequencing.

Preparation of an Arrayed Species Collection.

A single vial of the −80° C. anaerobic glycerol stock containing an aliquot of a fecal sample from Donor 2 was diluted into prereduced TYGs medium lacking resazurin in an anaerobic chamber and was dispensed into prereduced 384-well flat-bottomed trays (0.17 mL per well). To determine the dilution at which a high percentage of wells received a single viable cell in the initial inoculation (FIG. 11F), two- and fourfold serial dilutions were performed (from 10-6 to 10-10) in a trial inoculation (48 wells per dilution; 0.17 mL per well). Trays were sealed with sterile foil lids and incubated anaerobically at 37° C. for 5 d; the dilution at which ˜30% of wells were turbid (OD₆₃₀>0.2) was chosen for the subsequent large-scale culturing (FIG. 11G). To this end, a second vial of the frozen anaerobic glycerol stock from the same donor was added to 500 mL of prereduced TYGS medium lacking resazurin at the calculated dilution and dispensed into ten 384-well culture trays (170 μL per well). Trays were sealed and incubated as above. Cells then were resuspended in each well of each tray by pipetting, and 25 μL aliquots were transferred to each of two archive trays containing 25 μL prereduced TYGS (resazurin included) plus 40% glycerol per well. The arrayed archive trays were sealed with aluminum foil, frozen on dry ice inside the anaerobic chamber, and transported on dry ice to a conventional −80° C. freezer for storage. Cultures stored in this fashion remain anaerobic, as judged colorimetrically using resazurin in the medium and by recovery of strict anaerobes (as long as they are transported frozen, on dry ice, into an anaerobic chamber for strain recovery). Another 50-μL aliquot from the culture trays (not from the archive trays) was measured by OD₆₃₀and stored at −80° C. for PCR amplification.

Taxonomies were assigned to each strain in the 3,840-well collection by two-step barcoded 454 FLX pyrosequencing. The V2 16S rRNA region of the DNA present in each well was amplified with an invariant V2-directed forward primer and 1 of 96 barcoded V2-directed reverse primers. A 1-μL aliquot from each well was transferred to a new tray, and cells were lysed in 10 μL of lysis buffer (25 mM NaOH, 0.2 mM EDTA; incubation for 30 min at 95° C.) followed by the addition of 10 μL of neutralization buffer (40 mM Tris-HCl). To reduce the amplification of background DNA present from dead or lysed cells, the neutralized lysate was diluted 1:10 into EB buffer (Qiagen). To barcode each bacterial strain uniquely before amplicon sequencing, the V2 region of their 16S rRNA gene was targeted for PCR using 2× Master Mix (Phusion HF), 2 μL input DNA, primers 454_—16S_—8F and 1 of 96 barcoded (Roche Multiplex Identifiers) reverse primers (454_—16S_—338R_barcode1) that include a 12-bp tail sequence in a 10-μL reaction (384-well format). Duplicate reactions were incubated for 30 s at 98° C., followed by 30 cycles of 10 s at 98° C., 30 s at 61° C., and 30 s at 72° C.

Reactions were combined so that each pool contained one representative associated with each barcode (four pools per 384-well tray), passed over a PCR cleanup column (Qiagen), and diluted to 0.5 ng/μL. Pools then were subjected to a second round of PCR amplification with 0.5 ng of pool DNA in a 25-μL reaction. Reactions were incubated for 30 s min at 98° C., followed by five cycles of 10 s at 98° C., 30 s at 54° C., and 30 s at 72° C., followed by an additional 25 cycles of 10 s at 98° C. and 30 s at 70° C. In this second PCR, the reverse primers were replaced with a second barcoded linker primer (454_linker_barcode2) specific to the 12-bp tail sequence added in the first PCR. In this way, the 16S rRNA V2 regions of the bacterial genomes in each initial well were associated with a unique twobarcode pointer sequence (FIG. 12A and legend). After the second-round PCR, reactions were pooled and run over a PCR cleanup column (Qiagen), and DNA in the expected size range (200-300 bp) was gel purified (Qiagen). The final product was quantified and subjected to multiplex 454 FLX pyrosequencing at a depth expected to yield 250 sequences per well (25% of one sequencing run).

The resulting reads were assigned to wells in the archive trays based on their associated barcodes. Of the 3,840 wells, 1,181 (30.8%) were turbid as defined by OD₆₃₀≧0.2; of the turbid wells, 1,172 (99.2%) had at least a single sequence with the correct barcode combination. Barcode combinations mapping to wells with culture OD₆₃₀<0.2 also were identified in the sequencing dataset. However, the total number of reads that mapped to these wells was much lower than to turbid wells (51,925 turbid versus 14,427 nonturbid), and the percentage of mapped wells was much lower for the nonturbid subset (62.2% vs. 99.2%).

The taxonomy of the most abundant sequence associated with each barcode combination was assigned using SILVA-VOTE. These most abundant sequences also were clustered into 97% ID OTU using uclust in QIIME 1.1. To evaluate the diversity captured at varying taxonomic levels, representative 97% ID OUT sequences were assigned taxonomy using SILVA-VOTE. Reads designated “nonidentified” by SILVA-VOTE were not considered to represent an additional taxonomic group unless they were associated with a distinct higher-order taxonomic classification (e.g., sequences annotated as “Family Clostridiaceae; Genus nonidentified” were scored as representing a different genus-level group than sequences annotated as “Family Ruminococcaceae; Genus nonidentified”). Rarefaction analysis of the number of additional taxa added with each additional 384-well culture tray is shown in FIG. 11H. Mapping was verified by recovery of strains from the archive trays, colony purification, and full-length Sanger sequencing of their 16S rRNA gene.

Identification of Human Gut Isolates in the German Resource Centre for Biological Material Culture Collection.

The German Resource Centre for Biological Material (DSMZ) bacterial culture collection (www.dsmz.de/microorganisms/bacteria_catalogue. php; Oct. 14, 2010) was searched under the terms “gut,” “faeces,” “feces,” “fecal,” and “stool.” Search results were filtered to exclude strains from nonhuman sources. Strains that matched the search terms without host species information were included, as were noncommensals (i.e., pathogens).

Tables for Examples 1 to 9

TABLE 1

Common methodological differences between culture-independent and

culture-based surveys of human gut microbial diversity.

Culture-Independent

Metagenomic Methods
Culture-Based Methods

Survey depth
Thousands to millions of 16S
Tens to hundreds of isolates cultured

rRNA gene sequences
per sample

generated per microbial

community sample

Accuracy of
454 FLX (FLX standard)
Taxonomy typically defined from full

(bacterial) 16S
pyrosequencing platform: 10x-100x
length 16S rRNA genes using the

rRNA gene
over-estimate of species-
more accurate Sanger method of

assigments
level diversity due to artifacts
dideoxy-chain termination

(sequencing errors, chimeras)
sequencing, or from high-coverage

Illumina sequencing platform:
assemblies of isolate genomes

≧100x over-estimate of species-

level diversity due to artifacts

Documentation
“Culturability” determined by
Many readily cultured taxa not

matching 16S rRNA reads to
documented in public databases (in

public databases
one study, 64%)

TABLE 2

Gut microbiota medium (GMM)

Component
Amount/L
Concentration
Comments

Tryptone
2
g
0.2%

Peptone

Yeast Extract
1
g
0.1%

D-glucose
0.4
g
2.2 mM

L-cysteine
0.5
g
3.2 mM

Cellobiose
1
g
2.9 mM

Maltose
1
g
2.8 mM

Fructose
1
g
2.2 mM

Meat Extract
5
g
0.5%

KH₂PO4
100
mL
100 mM
1M stock solution pH 7.2

MgSO₄—7H₂0
0.002
g
0.008 mM

NaHCO₃
0.4
g
4.8 mM

NaCl₂
0.08
g
1.37 mM

CaCl2
1
mL
0.80%
0.8 g/100 mL stock

Vitamin K
1
mL
5.8 mM
1 mg/mL stock solution

(menadione)

FeSO₄
1
mL
1.44 mM
0.4 mg FeSO₄/mL stock

solution

Histidine
1
mL
0.1%
1.2 mg hematin/mL in

Hematin

0.2M histidine

Solution

Tween 80
2
mL
0.05%
25% stock solution

ATCC Vitamin
10
mL
1%

Mix

ATCC Trace
10
mL
1%

Mineral Mix

Acetic acid
1.7
mL
30 mM

Isovaleric acid
0.1
mL
1 mM

Propionic acid
2
mL
8 mM

Butyric acid
2
mL
4 mM

Resazurin
4
mL
4 mM
0.25 mg/mL stock solution

Noble Agar
12
g
1.2%

TABLE 3

Antibiotics used in functional metagenomic selections

Name
Class
Abbreviation
MIC (mg/mL)

Amikacin
Aminoglycoside
AM
64

Amoxicillin
βlactam
AX
16

Carbenicillin
βlactam
CA
64

Cefdinir
Cephalosporin
CF
2

Cloramphenicol
Amphenicol
CH
8

Ciprofloxacin
Flouroquinolone
CI
4

Cefepime
Cephalosporin
CP
8

Gentamicin
Aminoglycoside
GE
16

Oxytetracyline
Tetracyline
OX
8

Penicillin
βlactam
PE
128

Piperacillin
βlactam
PI
16

Piperacillin +
βlactam +
PI + TZ
16(PI), 4(TZ)

Tazobactam
βlactamase

inhibitor

Tetracyline
Tetracycline
TE
8

Trimethoprim
Pyrimidine derivative
TR
8

Trimethoprim +
Pyrimidine
TR + SX
2(TR), 38(SX)

Sulfamethoxazole
derivative +

Sulfonamide

TABLE 4

BLAST analysis of metagenomic sequences identified by selection in E. coli

E. coli libraries containing microbiome fragments were selected on each of 15 antibiotics and antibiotic

combinations. Microbiome DNA fragments identified from three of these selections (amikacin, piperacillin,

piperacillin plus tazobactam) were subjecte

Antibiotic
Gene identified
Donor
Complete/Cultured

Amikacin
rmtD; 16S rRNA methylase rmtD
1
Complete*

Amikacin
aphA-3; aminoglycoside phosphotransferase type III
1
Complete, Cultured

Amikacin
bcrA; bacitracin transport ATP-binding protein
1
Cultured

Amikacin
marR locus; multiple antibiotic resistance repressor
1
Cultured

Pipericillin
beta-lactamase; non-experimental evidence, no additional details
1, 2
Complete, Cultured

recorded

Pipericillin

Megamonas hypermegale beta-lactamase class D
1
Cultured

Pipericillin

Bacteroides uniformis beta-lactamase cblA
1, 2
Cultured

Pipericillin
beta-lactamase/D-alanine carboxypeptidase ampC
2
Cultured

Pipericillin
Beta-lactamase precursor ampC
2
Cultured

Pipericillin

Clostridium nexile beta-lactamase class A
2
Cultured

Pipericillin
ABC-type multidrug transport system
2
Cultured

Pipericillin +
beta-lactamase; non-experimental evidence, no additional details
1
Complete, Cultured

Tazobactam
recorded

Pipericillin +

Clostridium bolteae beta-lactamase class A
1
Cultured

Tazobactam

Pipericillin +

Megamonas hypermegale beta-lactamase class D
1
Cultured

Tazobactam

Pipericillin +

Bacteroides uniformis Multi Antimicrobial Exclusion family
1
Cultured

Tazobactam

Pipericillin +

Bactreroides caccae beta-lactamase class A
1
Cultured

Tazobactam

Pipericillin +

Bacteroides uniformis beta-lactamase cblA
1
Cultured

Tazobactam

Pipericillin +
beta-lactamase/D-alanine carboxypeptidase ampC
2
Cultured

Tazobactam

*rmtD sequences were found in readily cultured amikacin-resistant fecal strains from Donor 1

TABLE 5

Control PARC medium

Component
Amount/L
Concentration
Comments

P
KH2PO4
100 mL
100 mM
1M stock solution pH 7.2

A
Noble Agar
12 g
1.2%

R
Resazurin
4 mL
4 mM
0.25 mg/mL stock

solution

C
L-cysteine
0.5 g
3.2 mM

Example 10
Modeling the Response of a Microbiota to Changes in Host Diets

Owing to its many roles in human health, there is great interest in deciphering the principles that govern the operations of an individual's gut microbiota. Current estimates indicate that each of us harbors several hundred bacterial species in our intestine and different diets lead to large and rapid changes in the composition of the microbiota. Given the dynamic interrelationship between diet, the configuration of the microbiota, and the partitioning of nutrients in food to the host, inferring the rules that govern the microbiota's responses to dietary ingredients represents a challenge.

Gnotobiotic mice colonized with simple, defined collections of sequenced representatives of the various phylotypes present in the human gut microbiota provide a simplified in vivo model system where metabolic niches, host-microbe, and microbemicrobe interactions can be examined using a variety of techniques. These studies have focused on small communities exposed to a few perturbations. In this example, gnotobiotic mice harboring a 10-member community of sequenced human gut bacteria were used to model the response of a microbiota to changes in host diet. The aim was to predict the absolute abundance of each species in this microbiota based on knowledge of the composition of the host diet. Another aim was to gain insights into the niche preferences of members of the microbiota, and to discover how much of the response of the community was a reflection of their phenotypic plasticity.

The ten bacterial species were introduced into germ-free mice to create a model community with representatives of the four most prominent bacterial phyla in the healthy human gut microbiota (FIG. 13A). Their genomes encode major metabolic functions that have been identified in anaerobic food webs, including the ability to break down complex dietary polysaccharides not accessible to the host (Bacteroides thetaiotaomicron, Bacteroides ovatus and Bacteroides caccae), consume oligosaccharides and simple sugars (Eubacterium rectale, Marvinbryantia formatexigens, Collinsella aerofaciens, Escherichia coli), and ferment amino acids (Clostridium symbiosum, E. coli). Two species capable of removing the end products of fermentation were also included: a H₂-consuming, sulfate-reducing bacterium (Desulfovibrio piger) and a H₂-consuming acetogen (Blautia hydrogenotrophica).

To perturb this community, a series of refined diets were used where each ingredient represented the sole source of a given macronutrient (casein=protein, corn oil=fat, cornstarch=polysaccharide, and sucrose=simple sugar) and where the concentrations of these four ingredients were systematically varied (FIG. 13B, C and Table 6). Each individually caged male C57Bl/6J mouse was fed a randomly selected diet with diet switches occurring every two-weeks (n=13 animals; Table 7 shows the variation of diet presentation between animals). 13 gnotobiotic mice harboring the 10-member community were each fed a randomly selected diet every two weeks for eight weeks (i.e., four total diets per mouse). Shotgun sequencing of total fecal DNA allowed the determination of the absolute abundance of each community member, based on assignment of reads to the various species' genomes, in samples obtained from each mouse on days 1, 2, 4, 7, and 14 of a given diet period. Analyses of the shotgun sequencing data revealed that steady state levels of community members were achieved within 24 h of a diet change. Therefore, the values from all five time points sampled within a diet period were averaged to obtain the mean absolute abundance of each community member for each of the refined diet periods.

TABLE 7

Variation of diet presentation between animals.

mouse:
m1
m2
m3
m4
m5
m6
m7
m8
m9
m10
m11
m12
m13

1^stdiet period
E
E
E
E
E
E
E
E
E
E
E
E
E

2^nddiet period
B
G
E
K
F
J
H
D
J
A
C
I
E

3^rddiet period
B
G
C
J
F
I
K
A
K
H
E
D
E

4^thdiet period
I
F
D
H
E
J
C
G
J
A
K
B
E

To predict the abundance of each species in the model human gut microbiome given only knowledge of the concentration of each of the four perturbed diet ingredients, a linear model was used,

y
_i=β₀+β_caseinX_casein+β_starchX_starch+β_sucroseX_sucrose+β_oilX_oil

where y_i; is the absolute abundance of species i, X_casein, X_starch, X_sucrose, and X_oilare the amounts (in g/kg of mouse diet) of casein, corn starch, sucrose, and corn oil respectively in a given host diet, β₀is the estimated parameter for the intercept, and β_casein, β_starch, β_sucrose, and β_oilare the estimated parameters for each of the perturbed diet components. Since each mouse underwent a sequence of three diet permutations presented in different order, and each of the diet periods covered all of the 11 possible diets (Table 7), it was possible to use two of these three diet intervals to fit the model for the equation (13 mice×2 diets per mouse=26 samples per bacterial species) and then the ability to predict the abundance of each bacterial species for the 13 samples was measured in the remaining (third) diet. Averaging this cross-validation from all three subsets, the model explained over 61% of the variance in the abundance of the community members (abundance weighted mean R²=0.61; see Table 8 for species-specific R²).

Example 11
Predicting Response of Microbiota to a Diet

Although the cross-validation provided evidence that the response of this microbiota was predictable from knowledge of these diet ingredients, a more conclusive validation of the model would be its ability to make predictions for new diets. Therefore, six additional diets were designed with new combinations of the four refined ingredients. Using a design similar to the first experiment, eight different 10-week-old gnotobiotic male C57Bl/6J mice harboring the 10-member community were each given a randomized sequence of diets selected from the six new diets (shaded diets L-Q in FIG. 13B), or one of the previous diets (Table 9). Fitting the model parameters with the data from the first experiment, we were able to explain 61% of the variance in the abundance of the community members on the new diets, showing virtually equivalent results to the cross validation procedure (see Table 8).

TABLE 9

Variation of diet presentation between animals.

mouse:
m1
m2
m3
m4
m5
m6
m7
m8

1^stdiet period
Q
M
P
N
L
E
E
O

2^nddiet period
N
D
O
M
E
Q
P
L

3^rddiet period
P
N
M
O
F
E
L
Q

These results indicate that the linear model explains the majority of the variation in abundance of each organism using only a knowledge of the species in the community and the concentrations of casein, cornstarch, sucrose, and corn oil in the diet, without having to explicitly consider the effects of microbe-microbe or microbe-host interactions, or diet order. As described in Materials and Methods below, several other models were also tested including adding interactions between the variables, quadratic terms, and interactions with quadratic terms. After correcting for the number of parameters in the model using Akaike information criterion, the linear model was still the best performing.

Example 12
Inferring the Association of Ingredients with the Abundance of Each Community Member

To further dissect the community response to these diet perturbations, we need to infer which set of diet ingredients is associated with the abundance of each community member. Feature selection algorithms assume that the response variable (in this case, the abundance of each organism) is potentially affected by only a fraction of the variables in the model, and use statistical methods to choose the subset of variables that most informatively predict the abundance of each species. Using stepwise regression as a feature selection procedure with the equation above, all species in the 10-member community had the diet variable X_caseinsignificantly associated with their abundance (Table 10).

E. coli and C. symbiosum were the only bacteria with more than one variable significantly associated with their abundance (casein and sucrose for E. coli and casein and starch for C. symbiosum). Further exploring this finding, we found casein highly correlated with the yield of total DNA per fecal pellet across all diets (FIG. 14A and FIG. 15). A component of casein, presumably amino acids and/or nitrogen, limits the biomass of the community: this resource limitation was observed even for combinations of three additional refined protein and two additional fat sources (soy, lactalbumin, egg-white solids, olive oil and lard; n=9 different diets given to another group of 9 C57Bl/6J male mice; FIG. 16; Table 11). However, the observed changes in species abundance are not a simple consequence of a constant relative abundance of each community member that is scaled upwards as casein is increased: three community members, E. rectale, D. piger, and M. formatexigens, decreased in absolute abundance by 1.4-2.4-fold from the low casein to high casein diets even though total community biomass tripled (FIG. 14B, 17; Table 12). Similar changes in species abundance and total community DNA levels were observed when casein concentrations were altered in gnotobiotic mice harboring a 9-member or an 8-member subset of the original community (minus B. hydrogenotrophica or minus D. piger and B. hydrogenotrophica) (Table 13).

Example 13
Correlation of Diet Ingredients with mRNA Expression

Microbial RNA-Seq was used on fecal RNA samples, prepared from mice on each diet (mean=2.1±0.7 replicates per diet; Table 14), to determine if perturbations in diet ingredients correlated with underlying changes in mRNA expression by community members. Each of the 36 RNA-Seq datasets was composed of 36 nt-long reads (3.20±1.35×10⁶mRNA reads/sample). Transcript abundances were normalized for each of the 10 species to reads per million per kilobase (RPKM). After correcting for multiple-hypotheses, no statistically significant changes in gene expression were found within a given bacterial species as a function of any of the diet perturbations. While community members do not appear to significantly alter their gene expression, they do respond by increasing or decreasing their absolute abundances (FIG. 15), thereby adjusting the total available transcript pool in the microbiota for processing dietary components. For example, as casein levels are increased across the diets, B. caccae increases its contribution to the gene pool/community transcriptome; so the number of transcripts per unit of casein remains roughly constant.

Since RNA-Seq provides accurate estimates of absolute transcript levels, transcript abundance information was used as a proxy to predict the major metabolic niche occupied by each community member. For species positively correlated with casein, it was found that high expression of mRNAs predicted to be involved in pathways using amino acids as substrates for nitrogen, as energy and/or as carbon sources. By contrast, the three species that negatively correlated with dietary casein concentration showed no clear evidence of high levels of expression of genes involved in catabolism of amino acids. The changes in abundance of the negatively correlated species (e.g., E. rectale) can be explained by competition with another member of the community that increases with casein (see FIG. 18).

Example 14
Use of the Modeling Framework with Typically Consumed Human Diets

The power of the refined diets used lies in the capacity to precisely control individual diet variables and to aid data interpretation from more complex diets. To test if the modeling framework used here generalizes to diets containing food more typically consumed in human diets, 48 meals were created consisting of random combinations and concentrations of four ingredients selected from a set of eight pureed human baby foods (apples, peaches, peas, sweet potatoes, beef, chicken, oats, and rice; Table 15). The meals were administered for periods of 7 d to the same eight gnotobiotic mice used for the follow-up refined diet experiments described above and in FIG. 13E. Each mouse received a sequence of 6 baby food diets. The order of presentation of the baby food diets was varied between animals (see Table 15). The absolute abundance of each bacterial community member was measured on days 1, 5, 6, and 7 for each diet. Using the linear modeling approach described above, over half of the variation in species abundance could be explained using only knowledge of the concentrations of the pureed foods present in each meal (R²=0.62). Stepwise regression was used to identify the type of pureed food(s) present in a given mixed meal that was most significantly associated with changes in each bacterial species (Table 16; FIG. 19).

Defining the interrelationship between diet and the structure and operations of the human gut microbiome is key to advancing understanding of the nutritional value of food, for creating new guidelines for feeding humans at various stages of their lifespan, for improving global human health, and for developing new ways to manipulate the properties of the microbiota to prevent or treat various diseases. The experiments and model described above highlight the extent to which host diet can explain the configuration of the microbiota, both for refined diets where all of the perturbed diet components are digestible by the host, and for human diets whose ingredients are only partially known. These models can now be tested using larger defined gut microbial communities representing those of humans living in different cultural settings, and with more complex diets, including various combinations of food ingredients that they consume.

Materials and Methods for Examples 10 to 14.
Assembling a Model Human Microbiota in Gnotobiotic Mice

B. caccae ATCC 43185 (GenBank genome accession number NZ_AAVM00000000), B. ovatus ATCC 8483 (NZ_AAXF00000000), B. thetaiotaomicron VPI-5482 (NC_—004663), B. hydrogenotrophica DSM 10507 (NZ_ACBZ00000000), M. formatexigens DSM 14469 (NZ_ACCL00000000), C. symbiosum ATCC 14940, C. aerofaciens ATCC 25986 (NZ_AAVN00000000), E. coli str. K-12 substr. MG1655 (NC_—000913), and E. rectale ATCC 33656 (NC_—012781) were obtained from public strain repositories (ATCC or DSMZ). A draft genome assembly for C. symbiosum ATCC 25986 is available at the Washington University Genome Center public web site (genome.wustl.edu/pub/organism/Microbes/Human_Gut_Microbiome/Clostridium_symbi osum/assembly/Clostridium_symbiosum-1.0/output/). D. piger GOR1 was isolated from a healthy human by plating serial dilutions of freshly voided feces under strictly anaerobic conditions (80% H₂/20% CO₂at 15 psi) onto plates containing medium with the following components (quantities expressed per liter): K₂HPO₄(0.3 g); KHPO₄(0.3 g); (NH₄)SO₄(0.3 g); NaCl (0.6 g); MgSO₄.7H₂O (0.13 g); CaCl₂.2H₂O (0.008 g), yeast extract (0.5 g); NH₄Cl (1.0 g); NaHCO₃(5.0 g); dithiothreitol (0.5 g); sodium formate (3.0 g); Noble agar (10 g); 5 ml of a 0.2% (w/v) solution of Fe(NH₄)₂(SO₄)₂.6H₂O, 1 ml of a 0.2% (w/v) solution of resazurin; cysteine (1 g), 10 ml of trace mineral solution (ATCC), and 10 ml of a vitamin solution (ATCC). The genome sequence of D. piger was determined by 454 FLX and FLX Titanium pyrosequencing. For both C. symbiosum and D. piger, genes were identified using Glimmer3.0, tRNAScan 1.23, and RNAmmer 1.2. All 10 genomes were annotated using PFAM v23; and String COG version 7.1. Annotations for all 40,669 predicted protein-coding genes in the 10 genomes can be found at gordonlab.wustl.edu/modeling_microbiota/.

Each community member was grown anaerobically in 5 ml of TYGS medium in Balch tubes. Inoculation times were staggered so that all organisms reached stationary phase within a 24 h window. Just prior to gavage, equal volumes (1 ml) of each culture were pooled and mixed regardless of the final stationary phase density reached by each mono-culture (OD₆₀₀values ranged from 0.4 to >2.0). Each germ-free mouse was subsequently gavaged with 300 μl of the pooled cultures.

Refined Diet Composition, Experimental Design, and Data Processing

A set of eleven diets was initially designed (FIG. 13B,C and Table 6), each differing in their concentrations of casein (protein), corn oil (fat), cornstarch (polysaccharide), and sucrose (simple sugar). Nine of the diets consisted of all possible combinations of high, medium, and low casein and corn oil, with a fixed amount of cornstarch and the remainder as sucrose (FIG. 13B; diets A-I). Using sucrose as the ‘remainder’ for these initial nine diets generated a negative correlation between sucrose concentration and casein/fat concentration. Therefore, two diets, one with high starch and low sucrose and the other with low starch and high sucrose, were designed to lessen this negative correlation (see diets J and K in FIG. 13C).

Initially, all mice were co-housed and given the diet labeled ‘E’ in Table 7 (5% fat, 20% protein, 62% carbohydrate). Mice were then individually caged in the gnotobiotic isolator, and every two weeks each animal received another randomly selected diet (second, third and fourth diet periods in Table 7). Mouse 13 received only control diet E to determine if there was any ‘drift’ in steady state over the 8-week period.

The steady state mean absolute abundance of each community member was estimated for each of the 36 mouse/diet combinations for the second, third, and fourth diet periods shown in Table 7. To do so, DNA was isolated from fecal samples taken from each mouse on days 1, 2, 4, 7, and 14 of a diet and analyzed by COmmunity PROfiling by sequencing (COPRO-Seq). This generally applicable method relies on the massive number of short reads generated by the Illumina GA-II instrument during shotgun sequencing of total community DNA. Briefly, “informative” tags are identified that map uniquely to a single location in one species' genome. These tags are then summed to generate raw “counts” of each species' abundance. To account for non-unique matches, species-specific counts are normalized by the “Informative Genome Fraction” of each genome (defined as the fraction of all possible k-mers a genome can produce that are unique). Up to 16 barcoded fecal DNA samples were pooled in each sequencing lane: a minimum of 50,000 reads per sample were generated so that all organisms comprising ≧0.02% of the community could be detected (for a mouse colonized at 10¹²cfu/ml cecal contents or feces, this represents ˜10⁸cfu/ml; at this sequencing depth, all species were detected in all samples). Total DNA yield per fecal pellet was used as a proxy for community biomass and multiplied the relative abundance of each species by the mean total DNA yield per fecal pellet for a particular diet to estimate the absolute abundance of each species in units of nanograms per fecal pellet. The absolute abundance N_impdof each species i in mouse m on diet period p on day d was calculated N_impd=F_impdT_jwhere F_impdis the Informative Genome Fraction adjusted fraction of species i in mouse m on diet period p on day d as measured by COPRO-Seq and T_jis the mean total DNA yield per fecal pellet for all samples taken from mice on diet j. Fecal pellets were used because they reflect overall microbiota composition in the gut and they provide the only means to sample each mouse over time. Mice were weighed during each diet period (Table 17). Although there was a trend towards increased weight gain as levels of casein and corn oil were increased (Table 18), there were no significant correlations between any of the diet perturbations and weight gain.

Model Description and Performance Evaluation

Population growth can be modeled as exponential growth with a carrying capacity:

$\begin{matrix} \frac{\partial N}{\partial t} = rN (1 - \frac{N}{K}) & Equation 1 \end{matrix}$

where r is the growth rate, N is the population size, and K is the carrying capacity. Extending the above equation to include multiple species (i) and multiple diets (j), the model becomes:

$\begin{matrix} \frac{\partial N_{i}}{\partial t} = r_{ij} N_{i} (1 - \frac{N_{i}}{K_{ij}}) & Equation 2 \end{matrix}$

where K_ijis the carrying capacity of species ion diet j (i.e. the steady-state level). We were interested in predicting the steady-state abundance of each species in the synthetic community as a function of the ingredients in the host diet. Thus, we can ignore the time-specific abundance of each community member N_i(t) on each diet and the growth rate r, assuming it is sufficiently large to allow each community member to reach their carrying capacity for each diet within the period that a given mouse was consuming the diet.

To predict the steady-state levels (K_ij) for each community member i given each diet j, we measured the abundance of each community member for each mouse and diet combination (FIG. S1D,E). The absolute abundance K_impdfor each community member (i) in a specific mouse (m) for a specific diet period (p) for a given day (d) was calculated as described above. These abundances were averaged across all available time points for each mouse after the microbiota had reached steady-state (d_s) for a specific diet period (i.e., the cells in the diet/mouse matrices in Tables 7 and 9; see below for estimation of steady-state). On average, 2.7 samples were available per mouse per diet period to give the steady-state abundance of each species (i) in the fecal microbiota for a given mouse (m) and diet period (p) combination in Tables 7 and 9.

y
_imp=mean(K_impd) where d>=d_s Equation 3

These y_impvalues served as the data for the linear model described in the Examples above.

Scoring Model Performance

All of the models used in this study were linear. Therefore, model could be scored by using R², which for linear models represent the proportion of variance in the system that is explained by the model. The R²was used for each species in the community separately to calculate a weighted mean R², where the weights represent the fraction of total fecal DNA content represented by each species (i.e., the R²for abundant taxa are given more weight than those of less abundant taxa). By using this weighted scoring schema, the final R²metric represents the amount of the total variation in species DNA content that can be explained by the model. An alternative method is to weight each species' R²equally, which produces similar albeit slightly worse results (Table 8).

Estimating Steady-State

Since the model assumes the microbiota is at steady-state, values of species abundance were only included from time points after the microbiota reaches steady-state for a given diet period (i.e. d_sin Equation 3 needs to be define). To determine the time required by the microbiota to reach steady-state after a diet switch, nine 22-week-old C57Bl/6J mice were fed a low protein/low fat diet for 7 d, followed by a switch to the high protein/high fat diet for 13 d (FIG. 13B diets A and I respectively). All mice were sampled approximately once every 24 h with twice-daily sampling around the time of the diet switch. To estimate whether the community had stabilized at a given time point, (i) the total microbial community biomass using DNA yield (ng/fecal pellet) as a marker, and (ii) the relative abundance of each species using the Informative Genome Fraction estimated from Illumina DNA sequencing were measured. It was found that the biomass of the gut microbiota was stable at the end of the first diet, highly variable during the initial time points after the diet transition, and then stable again by the fourth day after the diet switch (although even by 24 h after the switch, the mean yield largely reflects final steady-state abundance on the new diet). Similar results were found for the relative abundance data, although the relative abundance of each species appeared to stabilize faster than biomass (FIG. 20A compared with FIG. 20B). Given the results for both the biomass and relative abundance metrics, the number of days required by the microbiota to reach steady-state was set to four (i.e. d_s=4).

Comparing More Complex Models

Although the linear model performed well (see examples above and Table 8), more complex linear and nonlinear models could perhaps yield even better predictive ability. Therefore the cross validation procedure was repeated for the casein, corn oil, sucrose, starch diet combinations (see Examples above) using models that allowed for interactions between variables, quadratic terms, and interactions with quadratic terms:

y
_i=β₀+β_AX_A+β_BX_B, Linear

y
_i=β₀+β_AX_A+β_BX_B+β_ABX_AX_B, Interaction

y
_i=β₀+β_AX_A+β_BX_B+β_AAX_AX_A+β_BBX_BXB, Quadratic

y
_i=β₀+β_AX_A+β_BX_B+β_AAX_AX_A+β_BBX_BX_B+β_ABX_AX_B, Pure Quadratic

Akaike information criterion (AIC) was used as the scoring metric to allow for comparisons between these models with varying numbers of parameters and found the linear model performed best overall (Table 8). Given the slightly asymptotic behavior of the microbiota at extremely low and high casein concentrations (FIG. 14), it was also attempted to fit a nonlinear logistic function to the data to account for these saturation points. However, it was found that the lack of data at and beyond the asymptote made the nonlinear regression difficult to reliably fit. While it is interesting to question whether the microbiota will reach and maintain an asymptotic behavior with sampling at extreme concentrations of these ingredients, moving beyond the current maximum and minimum casein values would be unrealistic in terms of modern human eating habits and would be unhealthy for the animals.

Transcriptional Responses of the Microbiota to Host Diet Perturbations

To deplete total microbial community RNA of 16S, 23S, 5S rRNA and tRNA species prior to synthesis of cDNA with random hexanucleotide primers, each fecal RNA preparation was subjected to column-based size-selection and hybridization to custom biotinylated oligonucleotides directed at conserved regions of bacterial rRNA genes present in human gut communities, followed by streptavidin-bead based capture of the hybridized RNA sequences. RNA-Seq data were normalized as described previously. After normalization, the list was filtered to remove all transcripts whose total number of counts (log₂) summed across all 36 RNA-Seq expression profiles was <64 (2⁶). This threshold was chosen to be as inclusive as possible while still requiring a sufficient number of reads so that a dynamic range of roughly 5-fold could be detected across the 17 sampled diets. For example, if a transcript linearly increases 5-fold in response to diets with a 20-fold range in their casein concentration, with the lowest concentration yielding a number of reads that was just below level of detection for both replicates and the highest casein concentration yielding 5 reads for that transcript per replicate, 55 reads would be require. After normalization and filtering, a list of 26,643 genes across the 10 species remained (64±20% of the annotated genes in each species were detected as ‘expressed’). For each of these genes, the correlation and the p-value of the correlation were calculated between (i) each of the four perturbed refined diet ingredients and (ii) the log₂(gene expression) in reads per million per kilobase (RPKM). Multiple hypotheses correction was performed using the Storey procedure.

Highly Expressed Transcripts for Each Species

the highest 10% expressed genes in each community member were examined (gordonlab.wustl.edu/modeling_microbiota/), as major metabolic activities of gut microbes have consistently been identified among the abundant genes. Among the most highly expressed genes in B. thetaiotaomicron, were those encoding components of glycolysis/gluconeogenesis pathways (e.g. BT1658-1660, BT1672, 1691), the pentose phosphate pathway (e.g. BT3946-3950), plus members of polysaccharide utilization loci (PULs), including one PUL predicted to act on O-glycan containing mucins (BT0317-0319; S12), and another PUL involved in the degradation of fructans (BT1757-1763 and BT1765; 26). In addition to several peptidases (BT2522, BT2706, BT3926, BT4583), genes predicted to be involved in the metabolism of glutamate (glutamate dehydrogenase (BT1973); glutamate decarboxylase (BT2570)), glutamine (glutaminase (BT2571)), serine (L-serine dehydrate (BT4678)), aspartate (aspartate ammonia lyase (BT2755)), asparagine (L-asparaginase (BT2757)), and branched-chain amino acids (branched-chain alpha-keto acid dehydrogenase (BT0311-12)) were highly expressed. Similar results were observed in B. caccae and B. ovatus. Although the ability of colonic Bacteroides to access protein has not been extensively explored, there is evidence that members of this genus have extracellular proteolytic activity, and can incorporate amino acids into cellular components other than proteins. This feature, combined with their ability to use complex polysaccharides not accessible to other members in the community (including host glycans), may explain why they benefit from increased levels of dietary protein (casein).

Among the most highly expressed genes in C. symbiosum were components of the hydroxyglutarate pathway for degradation of glutamate (Csym2026-2031), the most abundant amino acid in casein (25.3% w/w), and a sodium/glutamate transporter (Csym3971). This pathway yields crotonyl-CoA, which is metabolized to butyrate, acetate, H2 and ATP. Genes encoding components of the pathway for butyrate production (Csym1328-1334) were also among the highest expressed.

Another Firmicute that grows on amino acids is the acetogenic bacterium B. hydrogenotrophica. Genes predicted to encode key enzymes of the acetyl-CoA pathway involved in the reductive assimilation of CO₂were among the most highly expressed in this species (e.g., carbon monoxide dehydrogenase (Rumhyd0314-0320)), as were genes involved in fermentation of aliphatic (Rumhyd0546-0555) and aromatic amino acids (Rumhyd1109-1113), and the metabolism of ribose (Rumhyd2245-2256).

E. coli also benefited from higher levels of protein; among its most highly expressed genes were components of a cytochrome d terminal oxidase involved in the consumption of oxygen (b0733-0734), genes involved in the utilization of simple sugars (e.g., b2092-2097 (galactitol), b2416-2417 (glucose), b2801-2803 (fucose)) and several genes involved in the metabolism of tryptophan (b3708-b3709), aspartate (b1439) asparagine (b2957), and threonine (b3114-3117).

C. aerofaciens expressed high levels of transcripts encoding proteins predicted to be involved in the catabolism of arginine (COLAER0352-356, COLAER1230), plus components of several phosphotransferase systems (a predicted sucrose-specific PTS (COLAER0919-0921), a predicted mannose/fructose/N-acetylgalactosamine-specific PTS (COLAER1259-1260) and a predicted mannitol/fructose PTS (COLAER0058-0061)).

Levels of E. rectale and M. formatexigens decreased as protein increased. Inspection of their most highly expressed genes suggested that they focus on catabolism of carbohydrates. For example, among the most highly expressed genes in M. formatexigens were components of several ABC transporters with predicted specificities for monosaccharides/oligosaccharides (e.g., BRYFOR5076-BRYFOR5080, BRYFOR06841-06843), and genes encoding key enzymes of the acetyl-CoA pathway (e.g., BRYFOR06355-06360). There was no clear evidence of genes involved in catabolism of amino acids being highly expressed.

D. piger also decreased as casein levels increased. D. piger is fairly restricted in its metabolism: it can use a few substrates (e.g., lactate, H₂, succinate) to reduce different forms of sulfur to H₂S and generate energy, and it can oxidize lactate and pyruvate incompletely to acetate. Among its most highly expressed genes were components of the sulfate reducing pathway (DpigGOR12316-18, DpigGOR110789-10794), a C4-dicarboxylate transport system (DpigGOR12113-2115), subunits of a Ni—Fe hydrogenase, and several genes predicted to be involved in lactate metabolism (DpigGOR11071-1075). Three predicted transporters of amino acids were highly expressed, but there was no evidence of further metabolism of these amino acids, which likely indicates that they are used for protein biosynthesis.

Simulation of Negatively Correlated Species with Constant Behavioral Responses

Using Equation 2 above, a simulated 2-member community was created where one member (species1=N₁) is casein limited (C) and the second member (species2=N₂) is negatively influenced in proportion to the abundance of species1 (α₁₂) (e.g., species1 could consume a limiting resource of species2, produce an inhibitory compound, or act through apparent competition). It was assumed that both species have the same growth constant (r₁=r₂) on all diets and that species1 is able to convert a proportion (s) of the casein into increases in population size (K₁=sC; note that 1.3, 2/3, 0, 2/3, and 15 were used for constants r, s, α₂₁, α₁₂, and K₂respectively, but this choice of values is arbitrary and similar results can be obtained over a wide-range of stable values):

$\begin{matrix} \frac{\partial N_{1}}{\partial t} = r_{1} N_{1} (1 - \frac{N_{1} + α_{21} N_{2}}{K_{1}}) & Equation 4 \\ \frac{\partial N_{2}}{\partial t} = r_{2} N_{2} (1 - \frac{N_{2} + α_{12} N_{1}}{K_{2}}) & Equation 5 \end{matrix}$

Simulating the above equations, where every ten days we change the amount of casein (C_j) from 2, 5, 10, 20, and 40% respectively, yields the result shown in FIG. 18 where species1 increases with increased casein while species2 decreases, during which time both maintain the same behaviors.

This type of behavior at the transcriptional level of a microbial community resembles similar phenomena observed in macro-ecology. For example, if two species of naturally co-occurring grasshoppers, one that eats almost exclusively grasses (Ageneotettix deorum) and the other that eats both grasses and forbs (Melanoplus sanguinipes), are co-housed to compete in environments with different dietary contexts, the final population size of each grasshopper species is dependent not only on the ability of A. deorum to compete for grass (i.e. its essential resource), but also M. sanguinipes' ability to utilize both grass and forbs. Thus, if the amount of grass available to the grasshoppers is held constant while the amount of forbs is increased, the population of A. deorum decreases even though it maintains the constant behavioral response of exclusively eating grass.

Design, Administration, and Modeling of Complex Diets

The following commercially available eight pureed human baby foods were used as the source ingredients to construct a set of 48 meals: peaches (Gerber 3^rdfoods®; Gerber Products Company); apple sauce (Gerber 3^rdfoods); peas (Gerber 2^ndfoods®), sweet potatoes (Gerber 3^rdfoods); chicken (Gerber 2^ndfoods); beef (Gerber 2^ndfoods), oats (Gerber Single Grain with VitaBlocks®); and rice (Gerber Single Grain with VitaBlocks). Oats and rice were purchased dry and mixed with dH₂O in a 1:5 ratio prior to use (e.g., a meal with 6 g of oats contained 1 g dried oats and 5 g dH₂O). Each meal consisted of four ingredients randomly selected from the set of eight total pureed human foods, with different concentrations of the four ingredients used in different diet periods. Meals were autoclaved and each mouse was fed a sequence of 5 different diets, with each diet provided for 1 week. The order of presentation of the 48 diets to the 8 gnotobiotic mice is described in Table 15. The table shows how a 1 week period of consumption of one of the 17 diets composed of refined ingredients was interposed, between each 1 week period of administration of a given pureed baby food meal, to ensure mice obtained adequate amounts of vitamins and minerals.

Absolute abundance of each bacterial community member was measured on days 1, 5, 6, and 7 of each human baby food diet. As before, the abundance values (y_imp) were calculated from the mean of all samples within a given diet period. However, day 1 was excluded in case the microbiota had not yet reached steady state by 24 h. To cover more of the potential “meal” space, the schema for the complex diets used less replication than was used for the refined diets, so there were fewer fecal pellets available to estimate the DNA yield data used to calculate absolute abundance of each species. Therefore, to estimate DNA yields for each diet, a nearest neighbor smoothing procedure was used where the DNA yield for each sample was calculated as a weighted average of the ten nearest samples with weights corresponding to the Euclidean distance from the true sample to the Nth-nearest sample (e.g., the nearest samples would be exact replicates and have a weight of 1.0).

The modeling performance was estimated with a species abundance weighted R²as described above using the following equation:

y
_i=β₀+β_appleX_apple+β_peachX_peach+β_peaX_pea+β_sweetpotatoX_sweetpotato+β_chickenX_chicken+β_beefX_beef+β_oatsX_oats+β_riceX_rice,

where the variables correspond to the concentration of each pureed ingredient in each meal. The final performance metric was the mean of ten replicates of 10-fold crossvalidation on the 48 samples. The performance when training on the larger set (n˜43) and testing on the smaller set (n˜5) was similar to training and testing using the larger set only (weighted R²=0.62 and R²=0.66 respectively).

Tables for Examples 10 to 14

TABLE 6A

Composition of refined diets: seventeen perturbations to casein, sucrose, corn starch, and corn oil concentrations.

First set of diets

Diet ID:

A
B
C
D
E
F
G
H
I
J
K

Harlan Teklad Diet Number:

TD.09049
TD. 09050
TD.09051
TD.09052
TD.09053
TD.09054
TD.09055
TD.09056
TD.09057
TD.09058
TD.09059

g/kg
g/kg
g/kg
g/kg
g/kg
g/kg
g/kg
g/kg
g/kg
g/kg
g/kg

Casein
69
230
460
69
230
460
69
230
460
230
230

L-Cystine
0.9
3
6
0.9
3
6
0.9
3
6
3
3

Sucrose
675.88
514.13
283.08
633.46
471.66
240.66
473.98
312.38
81.38
171.66
571.66

Corn Starch
100
100
100
100
100
100
100
100
100
400
0

Maltodextrin,
50
50
50
50
50
50
50
50
50
50
50

Lo-Dex 10

Cellulose (Fiber)
50
50
50
50
50
50
50
50
50
50
50

Corn Olil
10
10
10
50
50
50
200
200
200
50
50

79055 Mineral
12.73
12.73
12.73
13.4
13.4
13.4
16.08
16.08
16.08
13.4
13.4

Mix, Ca-p

Deficient

Calcium
2.6
6.25
11.3
2.6
6.4
11.3
3
6.5
11.6
6.4
6.4

Carbonate

Calcium
12.5
7.5
0.5
13.4
8.3
1.4
16.4
11.4
4.3
8.3
8.3

Phosphate

40077
14.25
14.25
14.25
15
15
15
18
18
18
15
15

Vitamin mix

Choline
2.1
2.1
2.1
2.2
2.2
2.2
2.6
2.6
2.6
2.2
2.2

Bitratrate

Ethoxyquin
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04

(Liquid)

Protein
6.1
20.3
40.6
6.1
20.3
40.6
6.1
20.3
40.6
20.3
20.3

(% by weight)

Protein
6.7
22.7
46.5
6.3
21.5
44.1
5.3
18.0
36.8
22.2
21.3

(% of kcal)

Carbohydrate
82.7
66.6
43.5
78.6
62.4
39.3
62.9
46.8
23.7
59.4
63.4

(% by weight)

Carbohydrate
90.7
74.3
49.7
81.8
66.0
42.6
55.1
41.5
21.4
64.9
66.4

(% by kcal)

Fat
1.1
1.2
1.5
5.1
5.2
5.5
20.1
20.2
20.5
5.2
5.2

(% by weight)

Fat (% by kcal)
2.6
3.1
3.8
11.9
12.5
13.3
39.6
40.4
41.7
12.9
12.3

kcal/g diet
3.6
3.6
3.5
3.8
3.8
3.7
4.6
4.5
4.4
3.7
3.8

TABLE 6B

Composition of refined diets: seventeen perturbations to casein, sucrose,

corn starch, and corn oil concentrations.

Second set of diets

L
M
N
O
P
Q

TD.09620
TD.09621
TD.09622
TD.09623
TD.09624
TD.09625

g/kg
g/kg
g/kg
g/kg
g/kg
g/kg

138
345
138
345
35
690

1.8
4.5
1.8
4.5
45
9

585.425
377.525
484.52
276.42
667.61
108.11

100
100
100
100
100
0

50
50
50
50
50
50

50
50
50
50
50
50

30
30
125
125
50
50

13.06
13.06
14.74
14.74
13.4
13.4

4.2
8.8
4.5
9
1.9
12.25

10.7
4.3
12.5
6.4
14.4
0

14.525
14.525
16.5
16.5
15
15

2.15
2.15
2.4
2.4
2.2
2.2

0.04
0.04
0.04
0.04
0.04
0.04

12.2
30.5
12.2
30.5
3.1
60.9

13.1
33.5
11.7
29.7
3.2
67.1

73.7
52.9
63.8
43
82
17

79.4
58.1
61.1
41.9
85.1
18.7

3.1
3.4
12.6
12.9
5
5.7

7.5
8.4
27.2
28.3
11.7
14.1

3.7
3.6
4.2
4.1
3.9
3.6

Calcium carbonate and calcium phosphate were used to maintain calcium and phosphorus levels at 0.5% and 0.35%, respectively, across all diets with the exception of the diet with the highest level of protein (TD.09621) where the phosphorus present in casein brings its level to 0.48%. Vitamin and mineral mixes were adjusted based on the caloric density of each diet.

Custom diets designed for this study are now commercial available from Harlan Teklad using the Harlan Teklad Diet Number above.

TABLE 8

Model performance measurements for individual species in experiments involving variations

in dietary casein, corn oil, corn starch and sucrose concentrations.

A. R²performance measurements for linear model

cross validation
prediction on new diets

Eubacterium rectale ATCC 33656
0.25
0.68

Collinsella aerofaciens ATCC 25986
0.08
0.42

Blautia hydrogenotrophica DSM 10507
0.70
0.63

Desulfovibrio piger GOR1
0.08
0.13

Clostridium symbiosum ATCC 14940
0.70
0.70

Escherichia coli str. K-12 substr. MG1655
0.22
0.61

Marvinbryantia formatexigens DSM 14469
0.08
0.43

Bacteroides ovatus ATCC 8483
0.69
0.54

Bacteroides thetaiotaomicron VPI-5482
0.69
0.50

Bacteroides caccae ATCC 43185
0.78
0.80

mean
0.43
0.54

weighted mean (weighted by species abundance)
0.61
0.61

B. Cross validation comparison of AIC scores across different models

linear
interaction
quadratic
pure quadratic

Eubacterium rectate ATCC 33656
121.3
132.9
140.9
129.5

Collinsella aerofaciens ATCC 25986
161.5
174.9
182.9
170.7

Blautia hydrogenotrophica DSM 10507
137.0
150.8
158.8
146.3

Desulfovibrio piger GOR1
193.3
205.9
213.9
201.8

Clostridium symbiosum ATCC 14940
169.7
181.2
189.7
177.2

Escherichia coli str. K-12 substr. MG1655
200.0
213.3
221.3
209.4

Marvinbryantia formatexigens DSM 14469
199.4
210.6
218.6
206.7

Bacteroides ovatus ATCC 8483
204.9
216.5
224.5
212.4

Bacteroides thetaiotaomicron VPI-5482
211.6
222.0
229.7
218.2

Bacteroides caccae ATCC 43185
206.8
220.8
228.8
216.3

TABLE 10

Stepwise regression selection of diet ingredients significantly associated with

changes in species abundance.

Casein
Sucrose
Corn Starch
Corn Oil

Eubacterium rectale ATCC 33656

1.10E−07

0.43
0.35
1.00

Collinsella aerofaciens ATCC 25986

3.13E−03

0.21
0.49
0.26

Blautia hydrogenotrophica DSM 10507

1.51E−08

0.24
0.65
0.18

Desulfovibrio piger GOR1

1.13E−02

0.31
0.90
0.12

Clostridium symbiosum ATCC 14940

2.63E−15

0.64

2.44E−03

0.65

Escherichia coli str. K-12 substr. MG1655

1.57E−07

9.38E−03

0.55
0.56

Marvinbryantia formatexigens DSM 14469

1.31E−03

0.65
0.97
0.48

Bacteroides ovatus ATCC 8483

1.36E−07

0.32
0.06
0.36

Bacteroides thetaiotaomicron VPI-5482

3.29E−12

0.43
0.74
0.38

Bacteroides caccae ATCC 43185

4.48E−19

0.47
0.52
0.76

Significant p-values from regression are shown in boldface

TABLE 11

Composition of nine diets with combinations of three refined protein sources and two refined fat sources.

Mouse

m1
m2
m3
m4
m5
m6
m7
m8
m9

Harlan Teklad Diet Number:

TD.10321
TD.10309
TD.10314
TD.10316
TD.10311
TD.10319
TD.10310
TD.10307
TD.10308

Ingredients
g/kg
g/kg
g/kg
g/kg
g/kg
g/kg
g/kg
g/kg
g/kg

Isolated Soy Protein
172
17.2
17.2
172
17.2
172
17.2
17.2
17.2

Egg White Solids, spray-dried
187.5
187.5
18.8
187.5
18.8
18.8
18.8
18.8
187.5

Lactalbumin
172
17.2
17.2
17.2
172
172
172
17.2
17.2

Sucrose
15.5
322.3
682.4
264.5
336.2
278.4
528.1
585.3
514.2

Maltodextrin
100
100
100
100
100
100
100
100
100

Corn Starch
50
50
50
50
50
50
50
50
50

Cellulose (Fiber)
50
50
50
50
50
50
50
50
50

79055 Mineral mix, Ca—P Deficient
16.1
16.1
12.7
14.7
16.1
14.7
12.7
14.7
12.7

Calcium Carbonate
6.3
2.3
1.7
5.5
2.6
5.5
2.3
1.8
1.9

Calcium Phosphate Dibasic
10.0
16.8
13.7
9.6
16.5
9.6
12.6
16.1
13.0

40077 Vitamin mix
18.0
18.0
14.3
16.5
18.0
16.5
14.3
16.5
14.3

Choline Bitartrate
2.6
2.6
2.1
2.4
2.6
2.4
2.1
2.4
2.1

Biotin
0.004
0.004
0.004
0.004
0.004
0.004
0.004
0.004
0.004

Olive Oil
100
100
10
100
100
10
10
10
10

Lard
100
100
10
10
100
100
10
100
10

TBHQ (antioxidant)
0.04
0.04
0.01
0.02
0.04
0.02
0.01
0.02
0.01

Protein, g/kg
451
181
45
316
181
315
181
45
181

CHO, g/kg
177
480
837
423
496
438
684
742
668

Fat, g/kg
215
201
21
118
208
125
28
111
21

Fiber, g/kg
50
50
50
50
50
50
50
50
50

TABLE 12

Correlation of species abundance with mouse diet casein concentration.

correlation with

casein
p-value

Eubacterium rectale ATCC 33656
−0.61
1.1E−07

Collinsella aerofaciens ATCC 25986
0.37
3.1E−03

Blautia hydrogenotrophica DSM 10507
0.64
1.5E−08

Desulfovibrio piger GOR1
−0.32
1.1E−02

Clostridium symbiosum ATCC 14940
0.77
1.3E−13

Escherichia coli str. K-12 substr. MG1655
0.61
8.5E−08

Marvinbryantia formatexigens DSM 14469
−0.40
1.3E−03

Bacteroides ovatus ATCC 8483
0.61
1.4E−07

Bacteroides thetaiotaomicron VPI-5482
0.74
3.3E−12

Bacteroides caccae ATCC 43185
0.86
4.5E−19

TABLE 13

Responses of 8-member and 9-member subset communities to low and

high casein.

A. Increase in total community DNA from low casein to high casein

mean totat DNA yield (ng/fecal pellet)
percent

Community
diet 6 (tow casein)
diet I (high casein)
increase

8-member
8568
13800
61%

9-member
12448
16875
36%

10-member
7692
11718
52%

8-member and 9-member community samples were from 13 to 14-week

old NMRI mice

10-member community samples were from 10 to 16-week old

C57BI/6J mice

B. Species-level responses ro changes in casein concentration

Species
8-member
9-member
10-member

Bacteroides caccae ATCC 43185
p
p
p

Clostridium symbiosum

p
p
p

ATCC 14940

Bacteroides thetaiotaomicron

p
p
p

VPI-5482

Blautia hydrogenotrophica

—
—
p

DSM 10507

Escherichia coli str. K-12
p
p
p

substr. MG1655

Eubacterium rectale ATCC 33656
n
n
n

Bacteroides ovatus ATCC 8483
p
p
p

Marvinbryantia formatexigens

n
n
n

DSM 14469

Collinsella aerofaciens

n
p
p

ATCC 25986

Desulfovibrio piger GOR1
—
n
n

species are sorted by the p-value of the correlation between casein and

species abundance for the 10-member community.

n = negatively correlated with casein concentration.

p = positively correlated with casein concentration.

— = not present in community.

TABLE 14

Number of expressed genes/species with ≧64 sequencing reads.

Total
%

Genes
Genes in
Observed

Species
Observed
Genome
Genes

Eubacterium rectale ATCC 33656
453
3621
13%

Collinsella aerofaciens ATCC 25986
1779
2367
75%

Blautia hydrogenotrophica

2612
3869
68%

DSM 10507

Desulfovibrio piger GOR1
1660
2487
67%

Clostridium symbiosum ATCC 14940
3141
5128
61%

Escherichia coli str. K-12 substr.
2969
4132
72%

MG1655

Marvinbryantia formatexigens

3173
4896
65%

DSM 14469

Bacteroides ovatus ATCC 8483
3785
5536
68%

Bacteroides thetaiotaomicron

3696
4778
77%

VPI-5482

Bacteroides caccae ATCC 43185
3375
3855
88%

TABLE 15

Composition of and experimental design for complex diets composed of pureed baby foods.

mouse 1
mouse 2
mouse 3
mouse 4
mouse 5
mouse 6
mouse 7
mouse 8
g/kg

week 1
apple sauce
peas
sweet
peaches
oatmeal
sweet
rice
beef
666.7
BABY FOOD

potatoes

potatoes

MEAL 1

peaches
peaches
chicken
peas
rice
apple sauce
apple sauce
peaches
222.2

chicken
chicken
beef
oatmeal
beef
beef
sweet
sweet
55.6

potatoes
potatoes

sweet
oatmeal
peas
rice
sweet
peaches
beef
rice
55.6

potatoes

potatoes

week 2
TD.09052
TD.09623
TD.09621
TD.09622
TD.09620
TD.09624
TD.09625
TD.09054

Refined Diet

week 3
apple sauce
peas
sweet
peaches
oatmeal
sweet
rice
beef
666.7
BABY FOOD

potatoes

potatoes

MEAL 2

peaches
peaches
chicken
peas
rice
apple sauce
apple sauce
peaches
222.2

chicken
chicken
beef
oatmeal
beef
beef
sweet
sweet
55.6

potatoes
potatoes

sweet
oatmeal
peas
rice
sweet
peaches
beef
rice
55.6

potatoes

potatoes

week 4
TD.09620
TD.09623
TD.09621
TD.09622
TD.09625
TD.09624
TD.09052
TD.09054

Refined Diet

week 5
sweet
chicken
beef
apple sauce
apple sauce
apple sauce
peas
peaches
666.7
BABY FOOD

potatoes

MEAL 3

oatmeal
peaches
rice
oatmeal
peaches
beef
apple sauce
oatmeal
222.2

peaches
beef
peas
chicken
chicken
chicken
sweet
sweet
55.6

potatoes
potatoes

peas
rice
chicken
beef
rice
peaches
peaches
chicken
55.6

week 6
TD.09049
TD.09053
TD.09050
TD.09056
TD.09058
TD.09053
TD.09051
TD.09059

Refined Diet

week 7
peas
chicken
peaches
peaches
peas
chicken
sweet
peas
666.7
BABY FOOD

potatoes

MEAL 4

rice
sweet
peas
peas
chicken
peaches
rice
rice
222.2

potatoes

apple sauce
rice
rice
apple sauce
oatmeal
rice
peaches
sweet
55.6

potatoes

beef
oatmeal
beef
chicken
sweet
oatmeal
beef
peaches
55.6

potatoes

week 8
TD.09053
TD.09051
TD.09059
TD.09053
TD.09050
TD.09049
TD.09058
TD.09056

Refined Diet

week 9
oatmeal
oatmeal
sweet
peaches
sweet
peas
peaches
chicken
421.1
BABY FOOD

potatoes

potatoes

MEAL 5

rice
apple sauce
rice
oatmeal
oatmeal
chicken
beef
beef
421.1

chicken
beef
chicken
sweet
chicken
rice
oatmeal
peas
105.3

potatoes

apple sauce
rice
peas
beef
rice
peaches
rice
apple sauce
52.6

week 10
TD.09053
TD.09053
TD.09053
TD.09055
TD.09057
TD.09055
TD.09057
TD.09053

Refined Diet

week 11
peas
apple sauce
peaches
sweet
sweet
beef
apple sauce
apple sauce
250
BABY FOOD

potatoes
potatoes

MEAL 6

oatmeal
rice
oatmeal
beef
apple sauce
peas
oatmeal
rice
250

beef
oatmeal
rice
peaches
peaches
chicken
rice
peaches
250

chicken
beef
sweet
rice
beef
oatmeal
beef
chicken
250

potatoes

Custom Harlan Teklad Diet Numbers are provided for the weeks mice were on refined diets.

TABLE 16

Stepwise regression selection of complex diet ingredients significantly associated with changes in species abundance.

Apple
Beef
Chicken
Oat
Pea
Peach
Rice
Sweet Potato

Desulfovibrio
piger GOR1
0.37
0.18
1.26E−04
6.08E−03
0.81
0.10
2.27E−06
0.17

Collinsella
aerofaciens ATCC 25986
0.06
4.49E−05
5.55E−07
0.26
0.10
0.91
0.08
0.19

Blautia
hydrogenotrophica DSM 10507
0.14
1.73E−03
5.62E−06
0.99
0.14
0.21
0.50
0.57

Clostridium
symbiosum

1.14E−03
7.29E−04
2.30E−04
0.25
0.16
4.96E−04
0.35
0.84

Escheria
coli str. K-12 substr. MG1655
4.30E−04
1.42E−03
8.63E−05
0.85
0.28
0.38
7.74E−05
0.70

Bryantella
formatexigens DSM 14469
0.48
0.07
0.87
0.38
0.98
0.10
0.96
0.18

Eubacterium
rectale ATCC 33656
3.77E−05
0.27
0.07
6.27E−06
0.13
2.76E−03
0.68
0.58

Bacteroides
caccae ATCC 43185
0.28
7.56E−06
2.00E−05
0.37
0.57
0.76
2.46E−03
3.72E−02

Bacteroides
thetaiotaomicron VPI-5482
2.31E−05
0.78
0.12
3.51E−03
1.94E−02
6.52E−04
0.31
0.43

Bacteroides
ovatus ATCC 8483
0.20
0.46
1.00
1.43E−08
0.92
0.11
0.16
0.34

TABLE 17

Mean Weight Gain (g/diet period).

mouse
m1
m2
m3
m4
m5
m6
m7
m8
m9
m10
m11
m12
m13

2^nddiet period
0.891
1.400
1.909
2.291
1.527
−1.909
−1.655
−1.145
2.927
0.636
0.255
2.291
0.636

3^rddiet period
0.800
0.000
0.600
1.200
0.300
0.600
0.100
1.400
−0.100
1.900
1.200
−0.700
1.000

4^thdiet period
1.400
2.800
0.700
2.300
1.100
2.400
1.300
2.700
3.300
0.300
1.100
1.900
2.700

TABLE 18

Weight gain as a function casein and corn oil concentration.

Mean Weight Gain (g/diet period)
SEM

A. Weight gain per diet period as a function of Casein concentration

% Casein

7%
0.589
0.386

23%
1.233
0.295

46%
1.233
0.294

B. Weight gain per diet period as a function of Corn oil concentration

% Corn Oil

1%
0.900
0.180

5%
1.110
0.301

20%
1.211
0.463

TABLE 19

Fecal DNA yields from diverse protein diets.

mouse
diet
nanograms (mean ± SEM)

m1
TD.10321
19716 ± 5689

m2
TD.10309
15488 ± 7023

m3
TD.10314
3781 ± 2906

m4
TD.10316
27989 ± 5462

m5
TD.10311
10378 ± 1515

m6
TD.10319
14283 ± 3203

m7
TD.10310
18604 ± 1007

m8
TD.10307
259 ± 75

m9
TD.10308
19684 ± 9045

Example 15
Intact and Cultured Gut Microbial Communities from Twins Discordant for Obesity Transplanted into Gnotobiotic Mice

Substantial interpersonal differences in microbial community configurations normally exist between unrelated individuals, creating a challenge in designing surveys of sufficient power to determine whether observed differences between healthy versus disease-associated microbiomes are significantly different from normal interpersonal variation. Microbiome configurations are influenced by early environmental exposures and are generally more similar among family members. In the case of same-sex twins discordant for a disease phenotype, the genetically related, healthy co-twin provides a valuable reference control for characterizing the disease-associated co-twin's microbiome. However, while each discordant pair can provide a vignette about the potential role of the microbiome in disease pathogenesis, the comparison is fundamentally descriptive and does not establish causality. Transplanting a fecal sample obtained from each co-twin in a discordant pair into multiple recipient mice provides an opportunity to conduct a virtual clinical trial designed to identify structural and functional differences between their communities, to generate and test hypotheses about the impact of these differences on host biology, and to directly test the effects of manipulating the representation of microbial taxa in the community.

A number of studies of obese and lean humans have revealed compositional differences in their gut microbiomes. Mono- or dizygotic twins discordant for obesity provide an attractive study paradigm for studies of the contributions of the gut microbiome to differences in body mass index (BMI). Two Finnish twin cohort studies have provided much of the published data about BMI discordance for obesity among monozygotic (MZ) twin pairs. In one cohort, with participants aged 35-60 years at the time of data collection, 1.3% of MZ twin pairs were defined as discordant for obesity [body mass index (BMI) difference ≧3 kg/m2 with one twin >27 kg/m²and the other <25 kg/m²]. In the other study, with participants aged 22-27 years at data collection, 2.16% of MZ twin pairs had a BMI difference ≧4 kg/m². Data collected at the 5th wave of assessment from 1539, 21-32 year-old female twin pairs enrolled in the Missouri Adolescent Female Twin Study (MOAFTS) was surveyed. Four discordant twin pairs with a BMI difference ≧6 kg/m²were recruited for the present study (n=1 MZ; 3 DZ pairs; Table 20).

TABLE 20

Features of the 4 discordant twin pairs.

Twin Pair

1
2
3
4

BMI (kg/m²)
23
32
25.5
31
19.5
30.7
24
33

Zygosity
DZ
DZ
DZ
MZ

Comparisons of the input human fecal microbiota, and ‘output’ mouse fecal communities surveyed two weeks after transplantation revealed that 77.8±7.4% (SD) of genus-level bacterial taxa in the human donor microbiota were represented in the microbiota of gnotobiotic mouse recipients (n=3-12 animals analyzed/microbiota; Table 21). The UniFrac metric measures the overall degree of phylogenetic similarity of any two bacterial communities by comparing the degree of branch length they share on a Bacterial tree of life. V2-16S rRNA reads sharing 97% nucleotide sequence identity were considered to represent a given species-level operational taxonomic unit (OTU). Principal Components Analysis (PCoA) of unweighted UniFrac distance matrices based on the 97% ID OTU datasets revealed that transplanted microbial communities achieved a stable configuration in recipients within 3 d. This configuration was sustained for at least 38 d. Importantly, the overall phylogenetic architecture of the transplanted community evolved in a reproducible way between singly housed recipient mice within given experiment for a given co-twin microbiota, and between replicate experiments (FIG. 21B). Pairwise UniFrac-based comparisons of fecal samples and of communities sampled along the length of the gut of transplant recipients also demonstrated a significantly higher similarity among recipients colonized with the same human donor, and a greater similarity to their human donor compared to mice colonized with unrelated human donor microbiota (FIG. 21C; FIG. 22).

TABLE 21

Fecal samples obtained from American female twin pairs discordant for obesity and used as donor samples for gnotobiotic mice.

Percent recapitulation at each taxonomical level based on pyrosequencing data from the V2 region of the 16S rRNA gene.

Twin Pair ID

1
2
3
4
All

BMI of the
Lean
Obese
Overweight
Obese
Lean
Obese
Lean
Obese

donor (kg/m²)
(23)
(32)
(25.5)
(31)
(19.5)
(30.7)
(24)
(33)

Twin ID
TSDC17
TSDC16
TSDC19
TSDC20
TSDC22
TSDC23
TSDC7
TSDC8

Phyla (%)
100
75
100
80
100
100
100
100
94.4 ± 10.5

Class (%)
80
80
100
83.3
85.7
85.7
60
85.7
82.6 ± 11.1

Order (%)
57.1
66.7
80
57.1
87.5
66.6
70
66.6
69.0 ± 10.4

Family (%)
62.5
63.6
83.3
66.7
77.8
83.3
82.3
68.7
73.5 ± 9.1

Genus (%)
69
66.7
88
76
80
84.2
82.9
75.9
77.8 ± 7.4

OTU level (%)
30.80 ± 7.81
44.39 ± 3.81
27.74 ± 2.59
17.13 ± 4.10
16.91 ± 2.09
21.43 ± 1.32
19.41 ± 9.56
28.54 ± 7.92
25.89 ± 10.33

Transplant recipients not only efficiently captured the organismal features of their human donor's microbiota but also the functions encoded by the donor's microbiome, as judged by shotgun pyrosequencing of cecal DNA samples isolated from mice colonized with each of the 8 human fecal microbiota [n=3-8 mice sampled 15 d after transplantation/microbiota; n=45 cecal samples; 90,164±37,526 (mean±SD) reads per sample; 337±62 (SD) nt/read; 9.43±4.12 Mb/sample]. Shotgun reads were functionally annotated with KEGG orthology groups (KO) and Enzyme Commission (E.C.) numbers (KEGG version 58; see Methods). The results disclosed that 99.69±0.2% of donor ECs were captured in recipients. Remarkably, there was a significant correlation between the proportional representation of reads with given assignable EC and KO in donor and recipient microbiomes (Spearman's correlation, p-value<0.0001, Spearman's R≧0.88) (FIG. 23), highlighting the remarkable ability of a human microbiome to reassemble itself in a mouse gut ecosystem.

Body composition was analyzed using quantitative magnetic resonance imaging 1 d, 15 d, and in the case of longer experiments 38 d after transplantation. The increased adiposity phenotype of each obese co-twin in a discordant twin pair was transmissible: the differences in adiposity between mice that received an obese co-twins fecal microbiome was statistically greater than the adiposity of mice receiving her lean co-twins microbiome within an experiment, and was reproducible between experiments (One-tail Mann-Whitney U test, p-value<0.001; n=92 recipients phenotyped) (FIG. 24A, B). Epididymal fat pad weights were also significantly higher in mice colonized with gut communities from obese co-twins (p<0.05, one-tail Mann-Whitney U test). These differences in adiposity were not associated with statistically significant differences in daily chow consumption among recipients of obese versus lean co-twin microbiomes.

Supervised machine learning was performed using Random Forests to identify family-level bacterial phylotypes that differentiate gnotobiotic mice harboring a gut community transplanted from all lean versus all obese co-twins. The estimated generalization error of the trained model was 12.6%, indicating that it could be predicted if a sample came from a mouse colonized with a lean or obese human donor microbiota with 87.4% accuracy using family-level taxonomic classifications. Only three family-level taxa were identified as producing a mean decrease in classification accuracy of ≧5% when they were ignored; all three families were members of the order Clostridiales: Lachnospiraceae, Ruminococcaceae and Veillonellaceae; two of the three (Ruminococcacae and Veillonellaceae) were significantly increased in fecal samples obtained from mice colonized with a lean donor's microbiota (Table 22).

TABLE 22

Discriminatory family level taxa between gnotobiotic mice colonized with the microbiota of human

co-twins discordan for obesity. Feature importance score was calculated using supervised machine learning

(Random Forest algorithm) and represents t

Feature importance scores =

Mean decrease in
Relative Abundance (%)

accuracy when the feature
Lean donors
Obese donors
p-adjust

Feature ID
is ignored
(mean ± SEM)
(mean ± SEM)
(ANOVA, FDR)

Firmicutes; Clostridia; Clostridiales;
10.06%
1.19 ± 0.47
0.00 ± 0.00
1.58E−15

Veillonellaceae

Firmicutes; Clostridia; Clostridiales;
9.45%
16.02 ± 1.68
8.34 ± 3.19
7.64E−09

Ruminococcaceae

Firmicutes; Clostridia; Clostridiales;
7.84%
21.29 ± 2.29
30.82 ± 1.35
2.81E−12

Lachnospiraceae

Firmicutes; Clostridia; Clostridiales;
3.40%
0.04 ± 0.03
0.19 ± 0.10
3.28E−04

Eubacteriaceae

Bacteroidetes; Bacteroidia;
1.62%
0.57 ± 0.20
0.84 ± 0.38
7.26E−02

Bacteroidales; Rikenellaceae

Firmicutes; Clostridia; Clostridiales;
0.70%
0.74 ± 0.18
1.17 ± 0.26
8.05E−03

Others

Firmicutes; Clostridia; Clostridiales;
0.46%
0.04 ± 0.01
0.00 ± 0.00
8.61E−03

Clostridiales FamilyXIII. Incertae

Sedis

Tenericutes; Erysipelotrichi;
0.42%
1.91 ± 0.68
2.61 ± 0.45
5.55E−02

Erysipelotrichales;

Erysipelotrichaceae

Firmicutes; Clostridia; Clostridiales;
0.40%
0.17 ± 0.11
0.34 ± 0.22
5.69E−02

Clostridiaceae

Proteobacteria; Deltaproteobacteria;
0.27%
0.09 ± 0.05
0.16 ± 0.07
5.10E−02

Desulfovibrionales;

Desulfovibrionaceae

Actinobacteria; Actinobacteria;
0.13%
0.11 ± 0.04
0.11 ± 0.05
9.63E−01

Coriobacteriales; Coriobacteriaceae

Actinobacteria; Actinobacteria;
0.12%
0.00 ± 0.00
0.02 ± 0.01
1

Coriobacteriales; Others

Verrucomicrobia; Verrucomicrobiae;
0.12%
1.05 ± 0.40
0.93 ± 0.29
7.80E−01

Verrucomicrobiales;

Verrucomicrobiaceae

Firmicutes; Clostridia; Clostridiales;
0.07%
0.01 ± 0.00
0.05 ± 0.07
8.02E−02

Peptococcaceae

Firmicutes; Bacilli; Turicibacterales;
0.01%
0.15 ± 0.15
0.15 ± 0.07
9.41E−01

Turicibacteraceae

Estimated generalization error = 0.126050

Error estimation method = Out-of-bag prediction of training data

Number of features used = 15

Parameters

# values of all non-default parameters

# method was “random_forest”

seed:616869664

cross.validation.k:10

ShotgunFunctionalizerR, a software tool designed for metagenomic analysis and based on a Poisson model, was used to identify genes encoding KEGG KOs and ECs whose proportional representation in cecal microbiomes differed significantly between recipients of transplanted obese versus lean co-twin microbiomes (p-value<0.0001). Random Forests is an ensemble classifier, that uses multiple decision trees to identify which features are discriminatory among different class labels, rather than features that are over- or underrepresented. This complementary approach to Shotgun FunctionalizerR identified KOs and ECs that best discriminate transplanted obese and lean microbiomes (relevant discriminatory features defined as those with a feature importance score ≧0.0001). These predictive KOs and ECs were among the most significantly different KOs and ECs as judged by ShotgunFunctionalizeR.

This type of DNA-level analysis provides information about functional capacity, but not about expressed functions. Therefore, the same cecal samples were used to prepare RNA for microbial RNA-Seq characterization of the transplanted microbial communities' meta-transcriptomes. Transcripts were mapped to 127 sequenced human gut genomes and assigned to KEGG KOs and ECs (see Methods). Significant differences in gene expression between transplanted obese and lean co-microbiomes were defined using ShotgunFunctionalizerR and Random Forests.

All transplanted lean co-twin microbiomes exhibited increased relative abundance of transcripts encoding components of the KEGG ‘Starch and Sucrose’ metabolic pathway (cellobiose and pyruvate metabolism) as well as the KEGG ‘Mannose and Fructose’ metabolic pathway (propanoate and butanoate metabolism). ECs involved in the KEGG pathway for ‘Pyrimidine and Purine’ metabolism were also enriched in the transcriptomes expressed by lean co-twin microbiomes, consistent with the significantly greater fecal microbial biomass (defined by fecal DNA content) observed in mice colonized with the gut microbial communities of lean versus obese co-twin donors (p<0.00X, ANOVA). Obese microbiomes had a significant increased in the representation of ECs involved in more futile energy metabolic cycles [e.g. KEGG ‘Pentose phosphate’ pathway) (FIG. 25).

Non-targeted gas chromatography-mass spectrometry (GC/MS) analyses of cecal contents was used to confirm these findings, and to identify other differences in expressed microbiome-associated metabolic activities. A metabolite profile was obtained for each sample using the spectral abundances of all identifiable metabolites (cecal samples from 3-5 mice/microbiome donor). A total of 26 metabolites satisfied a reverse match score cutoff of 65% (for definition, see Methods) and were present in at least 50% of samples representing a given transplanted microbiome (Table 23); 10 were robust discriminatory biomarkers of lean versus obese microbiome donor transplants in all four pairs (two tail Student's t-test, p-value<0.01; Random Forests, importance score >0.0007). Five of these 10 metabolites were mono- and disaccharides [cellobiose, mannose, glucose, lactose, and talose (C2-epimer of galactose)]; each was present at significantly lower levels in the cecal metabolomes of mice colonized with the gut communities of lean co-twins and each can be fermented by members of gut microbiota to short chain fatty acids (SCFA). Targeted GC/MS of cecal SCFA revealed significant increases in propionate and butyrate levels in mice harboring transplanted lean co-twin microbiomes (p<0.05, Student's t-test), consistent with increased carbohydrate fermentation (FIG. 26A, B). Bomb calorimetry revealed a trend towards increased energy content in the feces of mice containing transplanted lean compared to obese microbiomes (2.4±0.2 (SEM) and 1.9±0.3 kcal/mg dry fecal weight, respectively; p=0.07; two tailed Student's t-test; 2 discordant twin pairs surveyed; 7-12 mice/co-twin microbiome). This trend, coupled with the significantly greater biomass and lower SCFA levels associated with transplanted lean co-twin microbiomes, raise the question of whether the transplanted gut communities from lean co-twin donors may be more ‘selfish’, consuming energy for their own use, and less altruistic in distributing energy to their gnotobiotic hosts.

TABLE 23

Metabolites whose levels are significantly different in 29

cecal samples obtained from gnotobiotic recipients of intact fecal

samples from obese versus lean co-twins from four discordant pairs.

Metabolites were identified using non-targeted GC/M

Metabolite
ttest
p-adjust

tagatose 1
0.165003758
0.4158388

D-lyxosylamine
0.377652896
0.61797747

D-altrose
0.022259913
0.08903965

lactose 2
0.000758951
0.02714539

3-(3-hydroxyphenyl)propionic acid
0.908546205
0.93858256

cellobiose 1
0.001508077
0.02714539

D-allose
0.022259913
0.08903965

gluconic acid lactone 1
0.010717259
0.0654987

talose 1
0.016037437
0.08247825

Phenylalanine
0.529530864
0.65734866

coniferyl alcohol
0.347509677
0.61797747

maleic acid
0.055489479
0.18160193

fumaric acid
0.931223792
0.93858256

beta-alanine 1
0.473120794
0.63082773

acetoacetate 2
0.173266167
0.4158388

cholesterol
0.450002889
0.62308092

oxalic acid
0.444235043
0.62308092

5-Hydroxylysine
0.502472019
0.64603545

succinic acid
0.89644695
0.93858256

L-alanine 1
0.351162848
0.61797747

2-hydroxybutyric acid
0.338703755
0.61797747

glycine
0.006317688
0.0654987

D-malic acid
0.757829475
0.85255816

L-glutamic acid 2
0.145769214
0.40366859

5-aminovaleric acid 1
0.00890099
0.0654987

ribose
0.660979975
0.76758965

D-lyxose
0.429692899
0.62308092

2-amino-1-phenylethanol custom-character

, Ä†
0.325820188
0.61797747

putrescine
0.127190686
0.38157206

Myristic Acid
0.267126773
0.60103524

L-sorbose 1
0.620036783
0.74404414

fructose 1
0.938582558
0.93858256

D-mannose 1
0.033391959
0.12021105

D-glucose 1
0.01091645
0.0654987

Myoinositol
0.364584224
0.61797747

inosine
0.41516831
0.62308092

GPCRs comprise the largest superfamily of transmembrane signaling proteins encoded in the human genome, and participate in an array of signaling pathways that regulate myriad aspects of host physiology. GPCRs expressed by gut epithelial cell lineages (e.g. enteroendocrine cells) would be in a strategic position to transduce metabolic signals emanating from the microbiota to the host. To determine whether obese versus lean microbiota have differential effects on GPCR signaling, TaqMan assays were used to survey the expression of 350 GPCRs, belonging to 50 subfamilies, in the distal small intestine (ileums) of microbiota transplant recipients (initially 2 discordant pairs; 4 mice/donor microbiota). Three GPCRs satisfied criteria for a consistent >2-fold difference in expression in the distal small intestines of recipients of lean versus obese co-twin microbiota (p-value<0.05; Student's t-test). qRT-PCR was used to confirm the differential patterns of expression of these three GPCRs, Gpr15, Gpr3 and Gabbr2, in gnotobiotic recipients of microbiota from members of all four discordant twin pairs (n=4 mice/microbiota). Gpr15/Bob is abundant at the basal surface of the small intestinal epithelium 0. In the human enterocyte-like cell line HT-29-D4 cells, activation of Gpr15 leads to a 70% decrease in sodium-dependent glucose and lipid transport. Gpr15 down-regulation in mice harboring an obese microbiome would be expected to result in increased glucose and lipid absorption.

Procrustes analysis utilizing a Bray-Curtis distance matrix from the different groups of gnotobiotic recipients revealed significant correlations (p-value<10⁻⁷) between taxonomic structure (V2-16S rRNA family-level bacterial phylotype), functional capacity (EC representation in cecal microbiomes), transcriptional profiles (EC representation in cecal mRNA populations), and metabolic profile (non-targeted GC/MS profiles) (Mantel test with 10,000,000 iterations, p-value<0.001), with separation of groups based on donor microbiota and adiposity phenotype.

These observations were followed up, generated from studies of transplanted intact (uncultured) donor communities, with a set of experiments involving culture collections produced from the fecal microbiota of one of the discordant twin pairs. The goal was to determine whether cultured bacterial members of the co-twins'microbiota could transmit the discordant adiposity phenotypes and metabolic profiles of the corresponding uncultured microbiomes to gnotobiotic recipients.

Collections of cultured anaerobic bacteria were generated from each co-twin in DZ pair 1 (see Methods). The bacterial taxa present in the culturable component of each co-twin's microbiota were defined by sequencing V2-16S rRNA amplicons generated DNA isolated from the entire collection harvested directly from plates. Subsequently, each transplanted collection was harvested from plates directly into separate groups of 8-week old germ-free male C57Bl/6J mice (n=3 independent experiments; 4-6 recipient mice/culture collection/experiment). Capture of the cultured taxa was reproducible with 61±2% and 56±7% of the genus-level phylotypes present in the obese and lean co-twin's intact cultured microbiota retained in gnotobiotic recipients of their culture collection as shown (Table 24) by unweighted UniFrac analysis of V2-16S rRNA datasets (97% ID OTUs generated from cecal community DNA 15 d after gavage of an intact uncultured fecal microbiota or the corresponding non-arrayed culture collection generated from that fecal sample (n=5 mice/treatment group; 4 treatment groups). The culture collections reached a steady state configuration within 3 d after transplantation. Shotgun sequencing of the cecal microbiomes of transplant recipients confirmed that the functional features of the intact (non-cultured) donor microbiomes were efficiently captured and their proportional representation was recapitulated. Remarkably, statistically significantly greater increases in adiposity was documented 15 d after gavage in recipients of the obese co-twin's compared to the lean co-twin's culture collection (p<0.02; Mann Whitney U-test).

TABLE 24

Efficiency of capture of taxa, present in culture

collections prepared from obese and lean co-twins belonging to

twin pair 1, in gnotobiotic mouse recipients.

Shared with mice

Twin Pair 1
colonized with an
Shared with intact

BMI of co-
intact community
Human donor sample

twin donor
Obese
Lean
Obese
Lean

Phyla
89.7 ± 8.1
100 ± 8.7
84.0 ± 8.9
96.0 ± 8.9

Class
88.9 ± 8.0
88.8 ± 11.6
80.0 ± 13.9
74.3 ± 12.0

Order
86.6 ± 7.0
87.2 ± 11.9
68.6 ± 12.0
54.0 ± 8.9

Family
83.2 ± 3.4
86.4 ± 8.2
63.1 ± 3.4
50.9 ± 7.5

Genus
73.9 ± 6.6
82.0 ± 7.3
61 ± 2.2
55.6 ± 6.5

OUT-97% ID
73.8 ± 6.6
69.5 ± 7.4
41.9 ± 9.3
18.1 ± 3.2

Given that mice are coprophagic, co-housing was used to determine whether exposure of a mouse harboring a culture collection from the lean co-twin could modify or rescue development of an increased adiposity phenotype in a cagemate colonized with the culture collection generated from her obese co-twin, or vice versa. Five days after gavage, a mouse with the lean co-twin's culture collection was co-housed with a mouse with the obese co-twin's culture collection, with or without two age-matched germ-free animals. Control groups consisted of cages of dually-housed recipients of the lean co-twin culture collection, or dually-housed recipients of the obese co-twin's culture collection (n=3-5 cages/experiment; n=2 independent experiments; each cage in each experiment placed a separate gnotobiotic isolator) (FIG. 27A). All mice were fed a low-fat, plant polysaccharide-rich diet. Adiposity phenotypes were measured by quantitative magnetic resonance imaging 1 and 5 days after transplantation, and after 10 days of co-housing. Fecal samples were collected from all mice on days 1, 2, 3, 5, 6, 7, 8, 10 and 15.

The results revealed that the microbiota of the co-housed mouse harboring the obese co-twin's culture collection (abbreviated Obch) was re-configured so that its phylogenetic composition came to resemble that of the animal with the lean co-twin's culture collection (abbreviated Ln^ch). In contrast, the microbiota of the Ln^chmouse remained stable (FIG. 27C-F). Moreover, Ob^chmice exhibited a significantly lower change in adiposity compared to Ob controls that had never been exposed to mice harboring the lean co-twin's culture collection, while Ln^chmice had adiposity phenotypes that were indistinguishable from Ln controls (FIG. 27B). Co-housing experiments that included germ-free members revealed that these animals had adiposity phenotypes that were indistinguishable from Ln^chcagemates (FIG. 27B).

Similar to what was observed with complete community transplants, the ceca of mice colonized with the lean co-twin's culture collection exhibited significantly greater levels of short chain fatty acids, particularly acetate, propionate and butyrate than recipients of the obese co-twin's culture collection (FIG. 27H). The differences with regards to lactose and cellobiose were even more dramatic than with the complete (uncultured) transplants: These metabolites were undetectable in mice with culture collection from the lean co-twin (FIG. 27I). Co-housing not only affected host adiposity phenotypes but also transformed the Ob^chmouse's cecal metabolic profile such that it was indistinguishable from Ln controls (FIG. 27I).

To delineate the contribution of specific members of the lean co-twin's microbiota to these phenotypic changes, limiting dilution was used to produce a clonal arrayed collection of the lean twin's culture collection in replicate 384 well plates (Methods). 16S rRNA sequencing was initially used to identify the bacterial taxa present in wells that exhibited growth (see Methods) and to confirm that the well contained a clonal population of bacterial cells. The collection contained 54 strains representing 23 phylotypes (Table 25). DNA prepared from wells containing a single strain was then sequenced at ≧50× coverage and their genomes annotated. Then, a pool containing 37 was assembled comprising strains whose genomes were sequenced. This pool contained six strains of the known cellobiose fermentor Collinsella aerofaciens (family Coriobacteriaceae) plus 22 members of the family Bacteroidaceae and 11 members of Ruminococcaceae. These latter 33 members were chosen because Random Forests indicated that they discriminated between the transplanted lean and obese co-twin culture collections (feature importance score ≧0.1) and because their abundance increased significantly in the Ob^chgut microbiota during the co-housing experiment described above (ANOVA; p-value<0.05 after Bonferroni correction) (Table 25).

TABLE 25

Components of the arrayed anaerobic bacterial culture collection produced

from the lean co-twin in DZ pair 1.

Lactose
Cellobiose

Strain designation
37 Selected taxa
degrading
degrading

Ruminococcus_bromii_TSDC17.2_V2.2.5
+

Ruminococcus_bromii_TSDC17.2_V2.2.2
+

Ruminococcus_bromii_TSDC17.2_V2.1.7
+

Ruminococcus_albus_TSDC17.2_V2.2.8
+

+

Ruminococcus_albus_TSDC17.2_V2.1.7
+

+

Ruminococcus_albus_TSDC17.2_V2.1.6
+

+

Ruminococcus_albus_TSDC17.2_V2.1.16
+

+

Ruminococcaceae_TSDC17.2_V2.2.3
+

Ruminococcaceae_TSDC17.2_V2.2.1
+

Ruminococcaceae_TSDC17.2_V2.2.1
+

Ruminococcaceae_TSDC17.2_V2.1.1
+

Peptoniphilus_TSDC17.2_V2.1.1

Parabacteroides_distasonis_TSDC17.2_V2.1.2

Odoribacter_splanchnicus_TSDC17.2_V2.1.2

Odoribacter_splanchnicus_TSDC17.2_V2.1.1

final_name

Escherichia_coli_TSDC17.2_V2.1.2

Escherichia_coli_TSDC17.2_V2.1.1

Dorea_TSDC17.2_V2.1.1

Coprococcus_comes_TSDC17.2_V2.1.2

Coprococcus_comes_TSDC17.2_V2.1.1

Collinsella_aerofaciens_TSDC17.2_V2.4.22
+
+

Collinsella_aerofaciens_TSDC17.2_V2.3.23
+
+

Collinsella_aerofaciens_TSDC17.2_V2.3.20
+
+

Collinsella_aerofaciens_TSDC17.2_V2.2.24
+
+

Collinsella_aerofaciens_TSDC17.2_V2.1.9
+
+

Collinsella_aerofaciens_TSDC17.2_V2.1.10
+
+

TABLE 25

Components of the arrayed anaerobic bacterial culture collection produced from the lean co-twin in

DZ pair 1.

Lactose
Cellobiose

Strain designation
37 Selected taxa
degrading
degrading

Clostridiaceae_TSDC17.2_V2.3.1

Clostridiaceae_TSDC17.2_V2.2.4

Bifidobacterium_pseudocatenulatum_TSDC17.2_V2.1.5
+

Bacteroides_vulgatus_TSDC17.2_V2.2.12
+

−

Bacteroides_vulgatus_TSDC17.2_V2.1.5
+

−

Bacteroides_vulgatus_TSDC17.2_V2.1.11
+

−

Bacteroides_thetaiotaomicron_TSDC17.2_V2.3.1
+

−

Bacteroides_thetaiotaomicron_TSDC17.2_V2.2.5
+

−

Bacteroides_thetaiotaomicron_TSDC17.2_V2.2.4
+

−

Bacteroides_thetaiotaomicron_TSDC17.2_V2.1.3
+

−

Bacteroides_ovatus_TSDC17.2_V2.3.1
+

−

Bacteroides_ovatus_TSDC17.2_V2.2.2
+

−

Bacteroides_massiliensis_TSDC17.2_V2.1.3
+

−

Bacteroides_massiliensis_TSDC17.2_V2.1.2
+

−

Bacteroides_intestinalis_TSDC17.2_V2.1.9
+

−

Bacteroides_intestinalis_TSDC17.2_V2.1.7
+

−

Bacteroides_intestinalis_TSDC17.2_V2.1.5
+

−

Bacteroides_finegoldii_TSDC17.2_V2.1.4
+

−

Bacteroides_finegoldii_TSDC17.2_V2.1.2
+

−

Bacteroides_caccae_TSDC17.2_V2.1.7
+

−

Bacteroides_caccae_TSDC17.2_V2.1.6
+

−

Bacteroides_caccae_TSDC17.2_V2.1.3
+

−

Bacteroides_caccae_TSDC17.2_V2.1.1
+

−

Bacteroides_acidifaciens_TSDC17.2_V2.1.8
+

−

Bacteroides_acidifaciens_TSDC17.2_V2.1.3
+

−

Anaerococcus_TSDC17.2_V2.1.1

The experimental design is shown in FIG. 28A, B. Groups of mice were colonized with one of three culture collections: the non-arrayed collection from the obese co-twin; the non-arrayed collection or the assembled 37-member consortium from lean co-twin. In the case of the 37-member consortium, the abundance of members in the non-arrayed collection was not preserved; rather, equivalent numbers of cells/strain were inoculated into recipient mice. Five days after inoculation, mice harboring the non-arrayed culture collection from the obese co-twin were co-housed with one another (negative control), or with mice containing the non-arrayed culture collection from the lean co-twin (positive control), or were co-housed with mice containing the ‘manufactured’ 37 member collection (5 mice/treatment group; total of 26 mice). FIG. 28A emphasizes how mice with 37-member consortium can be viewed as a prevention arm of the experiment: i.e., does the presence of these microbes prevent their host from gaining the level of adiposity achieved in mice harboring the obese co-twin microbiota?). These mice can also be viewed as a treatment arm: i.e., can the 37-member consortia ameliorate the increased adiposity phenotype that develops in mice colonized with the obese co-twin's culture collection? Quantitative MR was performed on days 1, 5, 15 and 19 of the 20 d long experiment revealed that the non-arrayed lean co-twin's culture collection produced a consistent reduction in adiposity in co-housed mice with the obese co-twin's culture collection. In 4 of 5 cages, co-housed mice with 37-member consortia (Ln37^ch) did not develop increased adiposity; in two of these 4 cages, the cage-mate with the obese co-twin's culture collection (Ob^ch) exhibited a very marked reduction in adiposity compared to the control group (dually housed mice, each with the obese co-twin's culture collection) (see arrows in FIG. 28C).

A similar experiment may be performed to further identify individual microbes from the 37-member consortium that, when inoculated into gnotobiotic mice and cohoused with mice containing the obese co-twin's culture collection, may induce reduced adiposity in the mice containing the obese co-twin's culture collection, and prevent increased adiposity in the mice containing the individual member of the 37-member consortium. In short, wherein individual members of the 37-member consortium may be used to colonize gnotobiotic mice. The mice may then be cohoused with mice containing the obese co-twin's culture collection, and the change in adiposity of all mice may be measured over time as described above. Such an experiment may identify individual members of the 37-member consortium that may induce reduce adiposity in obese mice, or prevent increased adiposity in mice harboring the individual member of the 37-member consortium.

Example 16
Discordance for Obesity Among Adult Female Twin Pairs in the MOAFTS Study Cohort

There were 3,427 participants in the MOAFTS wave 5 assessment; height and weight data were available for 3,416 (99.7%). The majority of participants (55.8%) were classified as lean (BMI 18.50-24.99 kg/m2), while 21.9% were classified as overweight (25-29.99 kg/m2), 18.3% as obese (≧30 kg/m2), and 3.98% as underweight (<18.5 kg/m2). African-Americans, who comprised 14.4% of the wave 5 sample, had significantly higher rates of overweight and obesity compared to European-Americans (EA) (32.5% and 36.6% vs. 20.1% and 15.2%, respectively p<0.001).

Height and weight data were available for 1,539 complete twin pairs participating in wave 5. 54.3% of the twin pairs were MZ. The mean difference in BMI between co-twins was 3.53 kg/m2 (SD 3.78 kg/m²). The mean difference in BMI was greater in DZ compared to MZ twin pairs (4.65±4.58 kg/m²versus 2.60±2.57 kg/m²; p<0.001). Using the criteria that one co-twin was obese and the other lean, 5.72% of twin pairs were defined as BMI discordant (mean difference=11.42±4.09 kg/m²). The rate of discordance was substantially lower for MZ pairs compared to DZ pairs (2.3% versus 9.9%; p<0.001) and AA twin pairs were more likely to be discordant than EA pairs (p=0.008). Alternatively, when BMI discordance was defined as a BMI difference ≧8 kg/m2, 18.3% of DZ pairs and 5.2% of MZ pairs were classified as discordant (p<0.001); AA pairs were again more likely to be discordant (21.6% vs. 9.4%; p<0.001).

Methods for Examples 15 and 16.

Animal Husbandry.

All experiments involving mice were performed using protocols approved by the Washington University Animal Studies Committee. Germ-free adult male C57BL/6J mice were maintained in plastic flexible film gnotobiotic isolators under a strict 12 hr light cycle and fed an autoclaved low-fat, polysaccharide-rich chow diet (B&K diet 7378000) ad libitum.

Collection of Fecal Samples from Twin Pairs Discordant for Obesity and Transplantation of their Uncultured Fecal Microbiota into Germ-Free Mice.

Adult female twin pairs with a BMI discordance ranging from 6-10 kg/m²were recruited for this study. Procedures for obtaining their consent to provide fecal samples were approved by the Washington University Human Studies Committee. A single fecal sample was collected at t=0 and another 2 months later from each subject. Each sample was frozen immediately at −20° C., shipped in a frozen state to a biospecimen repository overseen by one of the authors, and then de-indentified. All samples were subsequently stored at −80° C. until the time of processing.

A given human fecal sample was homogenized with a mortar and pestle packed in dry ice. A 500 mg aliquot of the pulverized material was diluted in 5 mL of reduced PBS (PBS supplemented with 0.1% Resazurin (w/v), 0.05% L-cysteine-HCl), in an anaerobic Coy chamber (atmosphere, 70% N₂, 25% CO₂, 5% H₂), and then vortexed at room temperature for 5 min. The suspension was allowed to settle by gravity for 5 min, after which time the clarified supernatant was transferred to an anaerobic crimped tube that was then transported to the gnotobiotic mouse facility. The surface of the tube was sterilized by exposure for 20 min to chlorine dioxide in the transfer sleeve attached to the gnotobiotic isolator, transferred into the isolator. A 1 mL syringe was used to obtain a 200 μL aliquot of the suspension and was introduced by gavage into each adult C57BL6/J germ-free recipient. Transplant recipients were maintained in separate cages within an isolator dedicated to mice colonized with the same donor microbiota, except in the case of the co-housing experiments described below.

Analysis of Body Composition by Quantitative Magnetic Resonance Imaging (MRI).

Body composition was defined using MRI analysis (EchoMRI-3in1 instrument; EchoMRI, Houston, Tex.). Mice were transported from the gnotobiotic isolator to the MR instrument using in a HEPA filter capped glass vessel. Fat, lean and tissue-free body water were measured 1 d after gavage, and weekly for up to 5 weeks.

Sample Collection from Gnotobiotic Mice.

Fecal samples were collected at defined times after gavage from the mouse. At the time of sacrifice, luminal contents were collected as described in the Examples above at defined positions along the length of the gut (stomach, small intestinal segments 1, 2, 5, 9, 13 and 15 after its division into 16 equal-sized segments, cecum, and proximal and distal halves of the colon). Blood was harvested by retro-orbital phlebotomy into capillary blood collection tubes (BD), which were then centrifuged at 5,000×g at 4° C. for 5 min. The supernatant (serum) was frozen in liquid nitrogen for subsequent GC/MS analyses. Urine, also obtained at the time of sacrifice, was flash frozen in liquid nitrogen for metabolomic analysis. Both epididymal fat pads were recovered from each animal, by dissection, and weighed.

Multiplex Pyrosequencing of Amplicons Generated from Bacterial 16S rRNA Genes.

Genomic DNA was extracted from feces and gut samples using a bead-beating protocol. Briefly, a ˜500 mg aliquot of each pulverized frozen human fecal sample, or mouse fecal pellets (˜50 mg), or stomach, small intestinal, cecal or colonic contents (˜20 mg each); were re-suspended in a solution containing 500 μL of extraction buffer [200 mM Tris (pH 8.0), 200 mM NaCl, 20 mM EDTA], 210 μL of 20% SDS, 500 μL of phenol:chloroform:isoamyl alcohol (pH 7.9, 25:24:1, Ambion) and 500 μL of a slurry of 0.1-mm diameter zirconia/silica beads. Cells were then mechanically disrupted using a bead beater (Biospec, maximum setting; 3 min at room temperature), followed by extraction with phenol:chloroform:isoamyl alcohol and precipitation with isopropanol.

Amplicons of ˜330 bp, spanning variable region 2 (V2) of the 16S rRNA gene, were generated by using modified primers 8F and 338R incorporating sample specific barcodes as described in the Examples above and subjected to multiplex pyrosequencing (454 FLX Standard or Titanium chemistry). V2-16S rRNA sequences from Titanium chemistry were trimmed to FLX standard length and, together with the sequenced generated using FLX chemistry, filtered for low quality reads and assigned to a particular pyrosequencing bin according to their sample-specific barcodes. Sequencing errors were corrected using OTUpipe (QIIME v1.3) and classified into 97% ID OTUs using UCLUST. A representative OTU set was created using the most-abundant OTU from each bin. Reads were aligned using PyNAST. Taxonomy was assigned using RDP classifier.

Samples were rarefied at a depth of 815 OTUs/sample for time series studies of the fecal microbiota of gnotobiotic recipients of human microbiota and for the donor fecal microbiota) and 800 OTUs/sample in the case of the gut biogeography datasets. Data analysis (beta-diversity calculations, PCoA clustering) was performed using QIIME v1.3 and Vegan R package v 1.17-4 for pairwise distance analysis.

Shotgun Pyrosequencing of Total Community DNA.

For multiplex pyrosequencing (454 FLX Titanium chemistry), each of the 45 cecal DNA samples was randomly fragmented by nebulization to 500-800 bp and subsequently labeled with one of 12 MIDs (Multiplex Identifier; Roche) using the MID manufacturer's protocol (Rapid Library preparation for FLX Titanium). Equivalent amounts of up to 12 MID-labeled samples were pooled prior to each sequencer run. Shotgun reads were filtered to remove all reads <60 nt long, LR70 reads with at least one degenerate base (N), or reads with two continuous and/or three total degenerate bases, plus all duplicates (defined as sequences whose initial 20 nt were identical and shared an overall identity of >97% throughout the length of the shortest read). In the case of human fecal DNAs, all sequences with significant similarity to human reference genomes (BLASTN with e-value<10-5, bitscore>50, percent identity>75%) were removed. Comparable filtering against the mouse genome was performed for reads produced from samples obtained from recipient gnotobiotic animals.

All resulting filtered sequences were queried against the KEGG database (v58) using BLASTX. Sequences were annotated as the best hit in the database if (i) they had an E-value<10⁻⁵; (ii) the bit score was >50; and (iii) the query and subject were at least 50% identical after being aligned. If two entries were assigned as the best BLAST hit, the read was annotated with both entries. KO, E.C., and KEGG Pathway assignments were made using the “ko” file provided by KEGG. A matrix containing the counts for each KEGG annotation for each sample was generated for analysis with ShotgunFunctionalizeR (R package version 1.2-8).

Microbial RNA-Seq.

Each fecal pellet (˜50 mg) collected 15 or 17 days after colonization, was suspended while frozen in 1 ml of RNAprotect bacteria reagent (Qiagen), vortexed for 5 min at room temperature and centrifuged (10 min; 5,000×g; 4° C.). After decanting the supernatant, pelleted cells were suspended in 500 μL of extraction buffer [200 mM NaCl, 20 mM EDTA], 210 μl of 20% SDS, 500 μL of phenol:choloroform:isoamyl alcohol (pH 4.5, 125:24:1, Ambion), and 250 μL of acid-washed glass beads (Sigma-Aldrich, 212-300 μm diameter). Microbial cells were lysed by mechanical disruption using a bead beater (Biospec, maximum setting; 5 min at room temperature), followed by phenol:chloroform:isoamyl alcohol extraction and precipitation with isopropanol. RNA was treated with RNAse-free TURBO-DNAse (Ambion) and 5S rRNA and tRNAs were removed using MEGAClear columns (Ambion). A second DNAse treatment was performed (Baseline-ZERO DNAse; Epicenter). rRNA was initially depleted using MICROBexpress kit (Ambion) followed by a second MEGAClear purification. In addition, custom biotinylated oligonucleotides, directed against conserved regions of sequenced human gut bacterial rRNA genes were employed for streptavidin bead-based pulldowns. cDNA was synthesized using SuperScript II (Invitrogen), followed by second strand synthesis with RNAseH, E. coli DNA polymerase (NEB) and E. coli DNA ligase (NEB). Samples were sheared using a BioRuptor XL sonicator (Diagenode) and 150-200 bp fragments gel selected and prepared for sequencing.

Multiplexed microbial cDNA sequencing was performed using Illumina Hi-Seq2000 instruments to generate 23.7±6.5 million unidirectional 101 nt reads/sample. Reads were split according to 4-bp barcodes used to label each of four samples pooled together. After dividing sequences by barcode, reads were mapped to genes in a custom database of 127 sequenced human gut microbial genomes using the ssaha2 algorithm. A minimum score threshold of 42 was selected for ssaha, based on the distribution of scores for 101 nt barcoded reads. If a read mapped to more than one location in a genome or multiple genomes, the counts for each gene were added to the gene according to the gene's fraction of unique-match counts. Pseudo counts were added (i.e. added 1 count) to each gene prior to normalization to account for different sampling depths (i.e. normalized to reads/kb/million mapped reads).

Culturing Fecal Microbiota.

Each human fecal sample was pulverized while frozen and resuspended in pre-reduced PBS (0.1% Resazurin, 0.05% Cysteine/HCl; 15 mL/g feces). Samples were subsequently vortexed for 5 min and allowed to settle by gravity for 5 min to permit large, insoluble particles to settle. The supernatant was diluted 1000-fold in pre-reduced PBS and plated on 150 mm diameter plates containing pre-reduced, non-selective Gut Microbiota Medium (GMM, Goodman et al., 2011). Plates were incubated in a Coy chamber under anaerobic conditions for 7 d at 37° C. Colonies were subsequently harvested en masse from six plates by scraping (10 mL of pre-reduced PBS/plate). Glycerol (30%)/PBS stocks were stored in anaerobic glass vials at −80° C. 200 μL of the non-arrayed culture collection was used to gavage each germ-free recipient.

Creating a Clonally Arrayed Taxonomically Defined Sequenced Culture Collection.

Methods for creating clonally arrayed culture collections from frozen fecal samples were as described in the Examples above. A set of interfaces was also created for a Precision XS robot (BioTek) so that picking, arraying, and archiving of fecal bacterial culture collections can be done with speed and economy within a Coy anaerobic chamber. Taxonomies were assigned to each strain in an arrayed collection by 454 Titanium V2-16S rRNA pyrosequencing.

For a given culture collection, most strains (unique V2-16S rRNA sequence) are found in more than one well across the arrayed library. Therefore, several replicate wells of each strain were picked robotically from the 384-well plate, and streaked onto 8-well TYGS-agar plates. Plates were incubated under anaerobic conditions for 3 d at 37° C. in a Coy chamber. A single colony from each agar well was picked, grown in TYGS and archived as a TYGs/15% glycerol stock at −80° C. A small aliquot of each stock was taken for DNA extraction and subjected to multiplex genome sequencing with an Illumina HiSeq 2000 instrument [fold coverage 119±66 (mean±SD) coverage; range, 35-289].

TABLE 26

Metadata for 16S sequencing

Primer
Split

Sample
Barcode

454 run
Plate
Lib

ID
Sequence
Linker Primer Sequence
454 run IDs
Dates
Well
Reads
Donor

2
CTGTTCGTAGAG,
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_A1
1231
2

GTCACGACTATT

3
GACAGGAGATAG,
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_B1
2833
2

GTCTGACAGTTG

5
GACTCACTCAAT,
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_C1
1252
1

GTGTGCTATCAG

6
GAGCATTCTCTA,
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_D1
2753
1

TACAGATGGCTC

7
ACAGAGTCGGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_B3
1634
2

8
ACCGCAGAGTCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_C3
1518
2

9
ACGGTGAGTGTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_D3
1493
2

10
ACTCGATTCGAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_E3
1834
2

11
AGACTGCGTACT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_F3
1932
2

12
AGCAGTCGCGAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_G3
1491
1

14
AAGAGATGTCGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_A4
1857
1

15
ACAGCAGTGGTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_B4
1904
1

16
ACCTCGATCAGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_C4
1885
1

17
ACGTACTCAGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_D4
1854
2

18
ACTCGCACAGGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_E4
1734
2

19
AGAGAGCAAGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_F4
1444
2

20
AGCATATGAGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_G4
1938
1

21
AGGCTACACGAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_H4
1396
1

22
AAGCTGCAGTCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_A5
2936
1

23
ACAGCTAGCTTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_B5
2561
1

24
ACCTGTCTCTCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_C5
2830
1

25
AGTGTTCGATCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_A5
4245
2

26
ATATCGCTACTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_B5
2842
2

27
ATCTCTGGCATA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_C5
3899
2

28
ATGGATACGCTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_D5
3353
2

29
CAACTCATCGTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_E5
3213
2

30
CACTACTGTTGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_F5
2970
1

31
CAGCGGTGACAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_G5
2532
1

32
CATATACTCGCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_H5
3384
1

33
AGTTAGTGCGTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_A6
4685
1

34
ATATGCCAGTGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_B6
3926
1

35
ATCTGAGCTGGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_C6
3573
2

36
ATGGCAGCTCTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_D6
3211
2

37
CAAGATCGACTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_E6
3509
2

38
CACTCAACAGAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_F6
2617
1

39
CAGCTAGAACGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_G6
3000
1

40
CATATCGCAGTT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_H6
2264
1

41
AGTTCAGACGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_A7
3821
1

42
ATCACGTAGCGG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_B7
3316
1

43
ATCTGGTGCTAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_C7
3703
2

44
ATGGCGTGCACA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_D7
2682
2

45
CAAGTGAGAGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_E7
3429
2

46
CACTCTGATTAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_F7
3117
2

47
CAGGTGCTACTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_G7
2917
2

48
CATCAGCGTGTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_H7
3119
1

49
AGTTCTACGTCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_A8
4706
1

50
ATCACTAGTCAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_B8
3644
1

51
ATCTTAGACTGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_C8
2541
1

52
ATGGTCTACTAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_D8
3143
1

53
CACACGTGAGCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_E8
3225
2

54
CACTGGTATATC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_F8
3485
2

55
CAGTACGATCTT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_G8
2971
2

56
CATCATGAGGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_H8
3508
1

57
ATAATCTCGTCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_A9
5065
1

58
ATCAGGCGTGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_B9
3503
1

59
ATGACCATCGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_C9
4798
1

60
ATGTACGGCGAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_D9
3642
1

61
GATCAGAAGATG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_E1
2146
2

62
GCAATAGCTGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_F1
2757
2

63
GCATATAGTCTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_G1
2347
2

64
CTTAGCACATCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_A2
3189
2

65
GACAGTTACTGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_B2
2423
2

66
GACTCGAATCGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_C2
2105
1

67
GAGCTGGCTGAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_D2
1986
1

68
GATCCGACACTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_E2
2738
1

69
GCACATCGAGCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_F2
2227
1

70
GCATCGTCAACA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_G2
3092
1

71
GCGTTACACACA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_H2
2686
2

72
CTTGATGCGTAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_A3
2552
2

73
GACATCGGCTAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_B3
2489
2

74
GACTGATCATCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_C3
3026
1

75
GAGGCTCATCAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_D3
2671
1

76
GATCGCAGGTGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_E3
2940
1

77
GCACGACAACAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_F3
2811
1

78
GCATGTGCATGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_G3
3283
1

79
TATTCGTGTCAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_A9
3865
2

80
TCAGGACTGTGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_B9
2719
2

81
TCCTGAGATACG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_C9
3072
2

82
TCGTACGTCATA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_D9
3757
2

83
TCTCTAGAGCAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_E9
3255
2

84
GCTAAGAGAGTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_H3
3353
2

85
TGAGACGTGCTT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_F9
2567
2

86
TGCATTACGCAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_G9
2460
2

87
TGGATATGCGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_H9
3075
2

88
TCAACAGCATCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_A10
3998
2

89
TCAGTACGAGGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_B10
4152
2

90
CTTGTGTCGATA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_A4
3128
2

91
TCGAATCACAGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_C10
2934
2

92
TCGTCGATAATC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_D10
3590
2

93
TCTCTCCGTCGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_E10
2537
2

94
TGAGAGAGCATA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_F10
2656
2

95
TGCGCGAATACT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_G10
3900
2

96
GACCACTACGAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_B4
3207
2

97
TGGCTCTACAGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_H10
6179
2

98
TCAATCTAGCGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_A11
2758
2

102
GACTGCATCTTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_C4
3461
2

108
GAGTAGCTCGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_D4
2931
2

110
TCGAGACGCTTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_C12
2488
1

111
TCGTGTCTATAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_D12
3204
1

112
TCTGCGTACTAA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_E12
3109
1

113
TGAGCGATTCTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_F12
2739
1

114
GATCGTCCAGAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_E4
1893
1

115
TGCGTCAGTTAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_G12
3190
1

116
TGTACACGGCGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_H12
3369
1

120
GCACTCGTTAGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_F4
3832
1

126
GCATTGCGTGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_G4
1654
1

132
GCTAGATGCCAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_H4
4293
1

144
CATCGTATCAAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_H9
2199
2

150
GACTGTCATGCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_C5
3645
2

156
GAGTATGCAGCC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_D5
3804
2

162
GATCTATCCGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_E5
2547
1

168
GCACTGAGACGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_F5
2587
1

174
GCCACTGATAGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_G5
5182
1

180
GCTAGTCTGAAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_H5
4795
1

186
GAACTGTATCTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_A6
4916
1

187
ACGTCTGTAGCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_D5
2958
2

188
ACTCTTCTAGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_E5
2558
2

189
AGAGCAAGAGCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_F5
2598
2

190
AGCCATACTGAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_G5
2597
2

191
AGGTGTGATCGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_H5
2756
2

192
AATCAGTCTCGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_A6
2861
1

193
ACAGTGCTTCAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_B6
2886
1

194
ACGACGTCTTAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_C6
2451
1

195
ACGTGAGAGAAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_D6
2718
1

196
ACTGACAGCCAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_E6
2845
1

197
AGAGTAGCTAAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_F6
3027
2

198
AGCGACTGTGCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_G6
2666
2

199
AGTACGCTCGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_H6
2054
2

200
AATCGTGACTCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_A7
2368
1

201
ACAGTTGCGCGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_B7
2191
1

202
ACGAGTGCTATC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_C7
3087
1

203
ACGTGCCGTAGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_D7
1995
1

204
ACTGATCCTAGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_E7
2715
1

205
CACAGCTCGAAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_E9
3780
2

207
CAGTCACTAACG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_G9
4148
2

208
CATCGTATCAAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_H9
4183
2

209
ATACACGTGGCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_A10
4825
2

210
ATCCGATCACAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_B10
3543
1

211
ATGACTCATTCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_C10
2816
1

212
ATGTCACCGTGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_D10
3590
1

213
CACAGTGGACGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_E10
3382
1

214
CAGACATTGCGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_F10
3892
1

215
CAGTCGAAGCTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_G10
2712
2

216
CATCTGTAGCGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_H10
4157
2

217
ATACAGAGCTCC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_A11
4694
2

218
ATCCTCAGTAGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_B11
3396
1

219
ATGAGACTCCAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_C11
3888
1

220
ATGTGCACGACT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_D11
3586
1

221
CACATCTAACAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_E11
3484
1

222
CAGACTCGCAGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_F11
3945
1

223
CAGTGATCCTAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_G11
3838
2

224
CATGAGTGCTAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_H11
3414
2

225
ATACGTCTTCGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_A12
5041
2

226
ATCGATCTGTGG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_B12
4240
2

227
ATGATCGAGAGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_C12
4558
2

228
ATGTGTCGACTT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_D12
3653
1

229
CACATTGTGAGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_E12
3431
1

230
CAGAGGAGCTCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_F12
4546
1

231
CAGTGCATATGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_G12
3572
1

232
CATGCAGACTGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
2_H12
3448
1

233
TAGTTGCGAGTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
6_A1
1448
2

234
TCACGATTAGCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010;
6_B1
2084
2

GK_run_5.1
Jul. 6, 2010

235
TCATCGCGATAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
6_C1
1143
2

236
TCGAGCGAATCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
6_D1
1160
1

238
TCACTATGGTCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
6_B2
1650
1

240
TCGAGGACTGCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010;
6_D2
2005
1

GK_run_5.1
Jul. 6, 2010

261
GACGAGTCAGTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_B6
2652
2

262
GACTTCAGTGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_C6
3091
2

263
GAGTCTGAGTCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_D6
2839
2

265
GCAGCACGTTGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010;
4_F6
1367
1

GK_run_5.1
Jul. 6, 2010

266
GCCAGAGTCGTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_G6
2358
1

267
GCTATCACGAGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_H6
3173
1

268
GAAGAGTGATCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_A7
2451
1

269
GACGATATCGCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_B7
3617
2

270
GAGAATACGTGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_C7
2850
2

271
GAGTGAGTACAA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_D7
4874
2

272
GATCTTCAGTAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_E7
3025
1

273
GCAGCCGAGTAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_F7
2346
1

274
GCCTATACTACA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_G7
3861
1

275
GCTATTCGACAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_H7
2016
1

276
GAAGCTACTGTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_A8
4143
1

277
GACGCAGTAGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_B8
3776
2

278
GAGACAGCTTGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_C8
3315
2

279
GAGTGGTAGAGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_D8
4263
2

280
GATGATCGCCGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_E8
4051
2

281
GCAGGATAGATA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_F8
1899
2

282
GCGACTTGTGTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_G8
2026
1

284
GAAGTCTCGCAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_A9
2928
1

285
GACGCTAGTTCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_B9
1767
1

287
ATGTCACCGTGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_D10
2764
2

288
GATGCATGACGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_E9
3009
2

289
GCAGGCAGTACT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_F9
3693
2

290
GCGAGATCCAGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_G9
3696
1

291
GCTCGCTACTTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_H9
2907
1

292
GAATGATGAGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_A10
3714
1

293
GACGTTGCACAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_B10
3562
1

294
GAGAGCTCTACG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_C10
2135
1

295
AGAGTCCTGAGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_F7
3232
2

296
AGCGAGCTATCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_G7
2868
2

297
AGTACTGCAGGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_H7
2498
2

298
ACACACTATGGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_A8
2242
2

299
ACATCACTTAGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_B8
2942
2

300
ACGATGCGACCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_C8
2635
1

301
ACGTTAGCACAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_D8
2630
1

302
ACTGTACGCGTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_E8
2806
1

303
AGATACACGCGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_F8
2814
1

304
AGCGCTGATGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_G8
2181
1

305
AGTAGTATCCTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_H8
1951
2

306
CAGTCGAAGCTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_G10
1452
2

307
CATCTGTAGCGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_H10
1764
2

308
ACGCAACTGCTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_C9
5485
1

309
ACTACAGCCTAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_D9
6799
1

310
ACTGTCGAAGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_E9
5436
1

311
AGATCGGCTCGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_F9
7218
1

312
AGCGTAGGTCGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_G9
5252
1

313
TGATGCTAACTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_G6
3297
2

314
TGCTCGTAGGAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_H6
2848
2

315
TATGCGAGGTCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_A7
2502
2

316
TCAGCCATGACA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_B7
2074
2

317
TCCTAGCAGTGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_C7
15122
2

318
TCGCTAGTGAGG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_D7
223
1

319
TCTCCGCATGTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_E7
2269
1

321
TGATGTGTGACC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_G7
2047
1

323
TATGGCACACAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_A8
2898
2

324
TCAGCTCAACTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_B8
2070
2

325
TCCTCTGTCGAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_C8
1996
2

326
TCGGCTACAGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_D8
2003
1

328
TGACGGACATCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_F8
2864
1

329
TGCAGAGCTCAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_G8
1111
1

330
TGCTGTGAGCTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_H8
15062
1

332
TCTGTTGCTCTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010;
6_F2
2453
2

GK_run_5.1
Jul. 6, 2010

333
TGAGTCACTGGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010;
6_G2
3264
2

GK_run_5.1
Jul. 6, 2010

334
TGCTACCATGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010;
6_H2
2765
2

GK_run_5.1
Jul. 6, 2010

335
TATCAGGTGTGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010;
6_A3
2150
2

GK_run_5.1
Jul. 6, 2010

338
TCACTGGCAGTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
6_B3
3399
1

339
TCATGGTACACT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010;
6_C3
2604
1

GK_run_5.1
Jul. 6, 2010

340
TCGATACTTGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010;
6_D3
3308
1

GK_run_5.1
Jul. 6, 2010

341
TCTACTCGTAAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
6_E3
1747
2

342
TCTTAGACGACG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010;
6_F3
3081
2

GK_run_5.1
Jul. 6, 2010

343
TGAGTTCGCTAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
6_G3
1233
2

344
TGCTAGTCATAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010;
6_H3
2169
1

GK_run_5.1
Jul. 6, 2010

345
TATCGCGCGATA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
6_A4
1368
1

347
TCCACGTCGTCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010;
6_C4
2467
1

GK_run_5.1
Jul. 6, 2010

348
TCGATGAACTCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.3
Mar. 30, 2010
6_D4
1063
1

349
TCTAGCGTAGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_E4
3880
2

350
TGAACGCTAGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_F4
3359
2

351
TGATAGTGAGGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_G4
4397
2

352
TGCTATATCTGG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_H4
2412
2

353
TATCTCGAACTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_A5
1464
2

354
TCAGACAGACCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_B5
2501
1

355
TCCAGTGCGAGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_C5
3236
1

356
TCGCATGAAGTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_D5
2745
1

357
TCTAGTTAGTCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_E5
2956
1

358
TGACATCAGCGG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_F5
2763
1

359
TGATCAGAAGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_G5
2997
2

360
TGCTCAGTATGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_H5
2927
2

361
TATGCACCAGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_A6
2951
2

362
TCAGATCCGATG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010;
6_B6
4486
1

GK_run_5.1
Jul. 6, 2010

363
TCCGTCGTCTGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010;
6_C6
4602
1

GK_run_5.1
Jul. 6, 2010

364
TCGCGTATTAGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010;
6_D6
4390
1

GK_run_5.1
Jul. 6, 2010

365
TCTCACTAGGTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_E6
3685
1

366
TGACCATATCGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.4
Apr. 7, 2010
6_F6
3512
1

367
GATAGCTGTCTT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_D10
2567
2

369
GCAGTATCACTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_F10
1714
2

370
GCGATATATCGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_G10
2385
2

371
GCTGATGAGCTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_H10
2805
2

372
GACACTCGAATC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_A11
2511
1

373
GACTAACGTCAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_B11
2274
1

374
GAGATGCCGACT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_C11
1609
1

375
GATAGTGCCACT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_D11
2282
1

376
GATGTGAGCGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_E11
2557
1

377
GCAGTTCATATC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_F11
2944
2

378
GCGGATGTGACT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_G11
2793
2

379
GCTGCTGCAATA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_H11
2359
2

380
GACAGCGTTGAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_A12
2942
1

381
GACTAGACCAGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_B12
2840
1

382
GAGCAGATGCCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_C12
2397
1

383
GATATGCGGCTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_D12
1625
1

384
GATTAGCACTCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_E12
2688
1

385
GCATAGTAGCCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_F12
2655
2

386
GCGTACAACTGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_G12
1886
2

387
GCTGGTATCTGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
4_H12
2759
2

388
AACGCACGCTAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010;
1_A1
2596
2

GK_run_5.1
Jul. 6, 2010

389
ACACTGTTCATG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
1_B1
1176
2

390
ACCAGACGATGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
1_C1
1290
1

391
ACGCTCATGGAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
1_D1
1180
1

392
ACTCACGGTATG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010;
1_E1
3017
1

GK_run_5.1
Jul. 6, 2010

393
AGACCGTCAGAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010;
1_F1
2347
1

GK_run_5.1
Jul. 6, 2010

394
AACTCGTCGATG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010;
1_A2
2185
1

GK_run_5.1
Jul. 6, 2010

395
ACAGACCACTCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
1_B2
1159
2

396
ACCAGCGACTAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010;
1_C2
3200
2

GK_run_5.1
Jul. 6, 2010

397
ACGGATCGTCAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010;
1_D2
2392
2

GK_run_5.1
Jul. 6, 2010

398
ACTCAGATACTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010
1_E2
1181
1

399
AGACGTGCACTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010;
1_F2
2872
1

GK_run_5.1
Jul. 6, 2010

400
AGCAGCACTTGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010;
1_G2
1894
1

GK_run_5.1
Jul. 6, 2010

401
AGCTTGACAGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010;
1_H2
2327
1

GK_run_5.1
Jul. 6, 2010

402
AACTGTGCGTAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.1
Mar. 19, 2010;
1_A3
4056
1

GK_run_5.1
Jul. 6, 2010

403
CAGATCGGATCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_G2
4392
2

GK_run_5.1
Jul. 6, 2010

404
CATACCAGTAGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_H2
3733
2

GK_run_5.1
Jul. 6, 2010

405
AGTGGATGCTCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_A3
4140
2

GK_run_5.1
Jul. 6, 2010

406
ATAGCTCCATAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_B3
5023
2

GK_run_5.1
Jul. 6, 2010

407
ATCGTACAACTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_C3
2418
2

GK_run_5.1
Jul. 6, 2010

408
ATGCCTGAGCAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_D3
2404
1

GK_run_5.1
Jul. 6, 2010

409
CAACACGCACGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_E3
2338
1

GK_run_5.1
Jul. 6, 2010

410
CACGTCGATGGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_F3
2766
1

GK_run_5.1
Jul. 6, 2010

411
CAGCACTAAGCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_G3
3609
1

GK_run_5.1
Jul. 6, 2010

412
CATAGACGTTCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_H3
3321
1

GK_run_5.1
Jul. 6, 2010

413
AGTGTCACGGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_A4
4793
2

GK_run_5.1
Jul. 6, 2010

414
ATAGGCGATCTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_B4
4093
2

GK_run_5.1
Jul. 6, 2010

416
ATGCGTAGTGCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_D4
2956
1

GK_run_5.1
Jul. 6, 2010

417
CAACTATCAGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_E4
3557
1

GK_run_5.1
Jul. 6, 2010

418
CACGTGACATGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_F4
6453
1

GK_run_5.1
Jul. 6, 2010

419
CAGCATGTGTTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
2_G4
49
1

420
CATAGCGAGTTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_H4
5822
1

GK_run_5.1
Jul. 6, 2010

421
AGTCACATCACT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_H9
5301
2

422
ACACGAGCCACA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_A10
5245
2

423
ACATGTCACGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_B10
4861
2

424
ACGCGATACTGG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_C10
4704
2

425
ACTACGTGTGGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_D10
3767
2

426
ACTGTGACTTCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_E10
4999
1

427
AGATCTCTGCAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_F10
5880
1

428
AGCTATCCACGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_G10
5964
1

429
AGTCCATAGCTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_H10
4127
1

430
ACACGGTGTCTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_A11
3610
1

431
ACATTCAGCGCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_B11
4799
2

432
ACGCGCAGATAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_C11
3223
2

433
ACTAGCTCCATA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_D11
4541
2

434
ACTTGTAGCAGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_E11
4676
1

435
AGATGTTCTGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_F11
5414
1

436
AGCTCCATACAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_G11
4879
1

437
AGTCTACTCTGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_H11
2988
1

438
ACACTAGATCCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_A12
4897
1

439
ACCACATACATC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_B12
4214
2

440
ACGCTATCTGGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_C12
3336
2

441
ACTATTGTCACG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_D12
2357
2

442
AGAACACGTCTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_E12
2645
2

443
AGCACACCTACA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_F12
2079
2

444
AGCTCTCAGAGG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_G12
1493
1

445
AGTCTCGCATAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010
1_H12
1350
1

446
AGTGAGAGAAGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_A1
3610
1

GK_run_5.1
Jul. 6, 2010

447
ATACTATTGCGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_B1
4784
1

GK_run_5.1
Jul. 6, 2010

448
ATCGCGGACGAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_C1
4650
1

GK_run_5.1
Jul. 6, 2010

449
ATGCACTGGCGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_D1
3538
2

GK_run_5.1
Jul. 6, 2010

450
ATTATCGTGCAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_E1
3876
2

GK_run_5.1
Jul. 6, 2010

451
AGTGCGATGCGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_A2
3747
2

GK_run_5.1
Jul. 6, 2010

452
ATACTCACTCAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_B2
3353
1

GK_run_5.1
Jul. 6, 2010

453
ATCGCTCGAGGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_C2
3304
1

GK_run_5.1
Jul. 6, 2010

454
ATGCAGCTCAGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_D2
4065
1

GK_run_5.1
Jul. 6, 2010

455
ATTCTGTGAGCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_E2
4245
1

GK_run_5.1
Jul. 6, 2010

456
CACGGACTATAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.2
Mar. 25, 2010;
2_F2
4068
1

GK_run_5.1
Jul. 6, 2010

457
AACGCACGCTAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_A1
6941
2

458
ACACTGTTCATG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_B1
7024
2

459
ACCAGACGATGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_C1
7007
2

460
ACGCTCATGGAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_D1
5334
2

461
ACTCACGGTATG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_E1
4648
2

462
AGACCGTCAGAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_F1
6188
1

463
AGCACGAGCCTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_G1
8077
1

465
AACTCGTCGATG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_A2
5968
1

466
ACAGACCACTCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_B2
6100
1

467
ACCAGCGACTAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_C2
5769
2

468
ACGGATCGTCAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_D2
4274
2

469
ACTCAGATACTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_E2
9537
2

470
AGACGTGCACTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_F2
5685
1

471
AGCAGCACTTGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_G2
6851
1

472
AGCTTGACAGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_H2
6656
1

473
AACTGTGCGTAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_A3
10052
1

474
ACAGAGTCGGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_B3
5010
1

493
ACTCTTCTAGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_E5
4958
2

494
AGAGCAAGAGCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_F5
2101
2

495
AGCCATACTGAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_G5
5489
2

496
AGGTGTGATCGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_H5
4575
2

498
ACAGTGCTTCAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_B6
3493
1

499
ACGACGTCTTAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_C6
6218
1

500
ACGTGAGAGAAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_D6
4192
1

501
ACTGACAGCCAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_E6
3052
1

502
AGAGTAGCTAAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_F6
3287
1

503
AGCGACTGTGCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_G6
5799
2

505
AATCGTGACTCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_A7
3504
2

506
ACAGTTGCGCGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_B7
4162
1

507
ACGAGTGCTATC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_C7
3582
1

509
ACTGATCCTAGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_E7
3784
1

510
AGAGTCCTGAGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_F7
4672
1

511
AGCGAGCTATCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_G7
5618
2

512
AGTACTGCAGGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_H7
4820
2

513
ACACACTATGGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_A8
4098
2

514
ACATCACTTAGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_B8
4915
2

515
ACGATGCGACCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_C8
3875
2

517
ACTGTACGCGTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_E8
4062
1

518
AGATACACGCGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_F8
4990
1

519
AGCGCTGATGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_G8
5519
1

520
AGTAGTATCCTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_H8
4261
1

521
ACACATGTCTAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_A9
6732
2

522
ACATGATCGTTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_B9
4845
2

523
ACGCAACTGCTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_C9
5789
2

524
ACTACAGCCTAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_D9
4604
1

525
ACTGTCGAAGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_E9
4773
1

526
AGATCGGCTCGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_F9
3210
1

527
AGCGTAGGTCGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_G9
3990
1

547
ACGCTATCTGGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_C12
4539
2

548
ACTATTGTCACG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_D12
4432
2

549
AGAACACGTCTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_E12
4431
2

550
AGCACACCTACA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_F12
5001
2

551
AGCTCTCAGAGG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_G12
5141
2

552
AGTCTCGCATAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
1_H12
6246
1

553
AGTGAGAGAAGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_A1
1985
1

554
ATACTATTGCGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_B1
1930
1

555
ATCGCGGACGAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_C1
1727
1

557
ATTATCGTGCAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_E1
2954
2

558
CACGACAGGCTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_F1
2126
2

559
CAGATACACTTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_G1
2754
2

560
CAGTGTCAGGAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_H1
1691
1

561
AGTGCGATGCGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_A2
2213
1

562
ATACTCACTCAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_B2
2106
1

563
ATCGCTCGAGGA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_C2
1525
1

583
CAGCATGTGTTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_G4
288
2

584
CATAGCGAGTTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_H4
1839
2

587
ATCTCTGGCATA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_C5
1881
2

588
ATGGATACGCTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_D5
3537
1

589
CAACTCATCGTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_E5
1777
1

591
CAGCGGTGACAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_G5
1509
1

592
CATATACTCGCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_H5
1686
1

593
AGTTAGTGCGTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010;
2_A6
2178
2

GK_run_5.1
Jul. 6, 2010

594
ATATGCCAGTGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_B6
1751
2

595
ATCTGAGCTGGT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_C6
2451
2

596
ATGGCAGCTCTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_D6
1984
1

597
CAAGATCGACTC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_E6
1965
1

598
CACTCAACAGAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_F6
1667
1

599
CAGCTAGAACGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_G6
2507
1

600
CATATCGCAGTT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010;
2_H6
1927
1

GK_run_5.1
Jul. 6, 2010

601
AGTTCAGACGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_A7
1996
2

602
ATCACGTAGCGG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_B7
2261
2

603
ATCTGGTGCTAT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_C7
2300
2

604
ATGGCGTGCACA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_D7
3097
2

605
CAAGTGAGAGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_E7
3208
2

606
CACTCTGATTAG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_F7
2974
1

607
CAGGTGCTACTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_G7
3147
1

608
CATCAGCGTGTA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_H7
3555
1

609
AGTTCTACGTCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_A8
2425
1

610
ATCACTAGTCAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_B8
2533
1

611
ATCTTAGACTGC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_C8
1678
2

612
ATGGTCTACTAC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_D8
2063
2

613
CACACGTGAGCA
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_E8
2638
2

614
CACTGGTATATC
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_F8
3166
1

615
CAGTACGATCTT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_G8
1642
1

616
CATCATGAGGCT
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_H8
1550
1

617
ATAATCTCGTCG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_A9
1278
1

618
ATCAGGCGTGTG
CATGCTGCCTCCCGTAGGAGT
GK_run_4.5
Apr. 21, 2010
2_B9
1185
1

1001
GAGAATACGTGA
CATGCTGCCTCCCGTAGGAGT
GK_run_1.1
Jul. 16, 2009;
4_C7
5862
2

GK_run_3.1
Oct. 30, 2009

1002
GACGATATCGCG
CATGCTGCCTCCCGTAGGAGT
GK_run_1.1
Jul. 16, 2009;
4_B7
4352
2

GK_run_3.1
Oct. 30, 2009

1003
GAAGAGTGATCA
CATGCTGCCTCCCGTAGGAGT
GK_run_1.1
Jul. 16, 2009;
4_A7
7940
2

GK_run_3.1
Oct. 30, 2009

2000
TCAACAGCATCG
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009
6_A10
3417
2

2001
TCAGTACGAGGC
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009;
6_B10
2740
2

GK_run_3.1
Oct. 30, 2009

2002
TCGAATCACAGC
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009;
6_C10
3010
2

GK_run_3.1
Oct. 30, 2009

2003
TCGTCGATAATC
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009;
6_D10
2387
2

GK_run_3.1
Oct. 30, 2009

2004
TCTCTCCGTCGA
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009;
6_E10
2351
2

GK_run_3.1
Oct. 30, 2009

2005
TGAGAGAGCATA
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009;
6_F10
2724
2

GK_run_3.1
Oct. 30, 2009

2006
TGCGCGAATACT
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009;
6_G10
2557
2

GK_run_3.1
Oct. 30, 2009

2007
TGGCTCTACAGA
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009;
6_H10
2284
2

GK_run_3.1
Oct. 30, 2009

2008
TCAATCTAGCGT
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009;
6_A11
2534
2

GK_run_3.1
Oct. 30, 2009

2009
TCAGTCGACGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009;
6_B11
2719
2

GK_run_3.1
Oct. 30, 2009

2010
TCGACTCCTCGT
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009
6_C11
2410
1

2011
TCGTGATGTGAC
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009
6_D11
3470
1

2012
TCTGAGTCTGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009
6_E11
2229
1

2013
TGAGCACACACG
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009
6_F11
2769
1

2014
TGCGTATAGTGC
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009
6_G11
2382
1

2015
TGGTCATCACTA
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009
6_H11
2396
1

2016
TCACAGATCCGA
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009
6_A12
2361
1

2017
TCAGTGACGTAC
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009
6_B12
2255
1

2018
TCGAGACGCTTA
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009
6_C12
2400
1

2019
TCGTGTCTATAG
CATGCTGCCTCCCGTAGGAGT
GK_run_2.1
Aug. 17, 2009
6_D12
2675
1

3001
CCGATGTCAGAT
CATGCTGCCTCCCGTAGGAGT
GK_run_3.1
Oct. 30, 2009
3_A10
3103
2

3002
CGAGTTGTAGCG
CATGCTGCCTCCCGTAGGAGT
GK_run_3.1
Oct. 30, 2009
3_B10
3266
2

3003
CGCGTAACTGTA
CATGCTGCCTCCCGTAGGAGT
GK_run_3.1
Oct. 30, 2009
3_C10
4179
2

3004
CGTCACGACTAA
CATGCTGCCTCCCGTAGGAGT
GK_run_3.1
Oct. 30, 2009
3_D10
3499
2

3005
CTACACAAGCAC
CATGCTGCCTCCCGTAGGAGT
GK_run_3.1
Oct. 30, 2009
3_E10
2039
2

3006
CTATCTAGCGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_3.1
Oct. 30, 2009
3_F10
3584
2

3007
CTCTGAAGTCTA
CATGCTGCCTCCCGTAGGAGT
GK_run_3.1
Oct. 30, 2009
3_G10
2929
2

3008
CTGTCTCTCCTA
CATGCTGCCTCCCGTAGGAGT
GK_run_3.1
Oct. 30, 2009
3_H10
3741
2

3009
CCTAGTACTGAT
CATGCTGCCTCCCGTAGGAGT
GK_run_3.1
Oct. 30, 2009
3_A11
3439
2

3010
CGATAGATCTTC
CATGCTGCCTCCCGTAGGAGT
GK_run_3.1
Oct. 30, 2009
3_B11
3261
2

3011
CGCTAGAACGCA
CATGCTGCCTCCCGTAGGAGT
GK_run_3.1
Oct. 30, 2009
3_C11
0
2

3012
CGTCAGACGGAT
CATGCTGCCTCCCGTAGGAGT
GK_run_3.1
Oct. 30, 2009
3_D11
3504
2

4000
GCTGTAGTATGC
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_A1
1614
1

4001
GGTCACTGACAG
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_B1
1478
1

4002
GTAGTGTCTAGC
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_C1
1803
1

4003
GTCGCTGTCTTC
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_D1
1732
1

4004
GTGAGGTCGCTA
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_E1
1449
1

4005
GTTGACGACAGC
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_F1
1656
1

4006
TACGCGCTGAGA
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_G1
1564
1

4007
TAGATCCTCGAT
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_H1
2002
1

4008
GCTGTGTAGGAC
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_A2
1951
1

4009
GGTCGTAGCGTA
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_B2
2229
1

4010
GTATATCCGCAG
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_C2
1933
1

4011
GTCGTAGCCAGA
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_D2
1391
1

4012
GTGATAGTGCCG
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_E2
1780
1

4013
GTTGTATACTCG
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_F2
1555
1

4014
TACGGTATGTCT
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_G2
1234
1

4015
TAGCACACCTAT
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_H2
2106
1

4016
GCTTACATCGAG
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_A3
1172
1

4017
GGTGCGTGTATG
CATGCTGCCTCCCGTAGGAGT
GK_run_5.1
Jul. 6, 2010
5_B3
1324
1

Donor

Date human

Date human

Sample
Mouse
Source
Sample
sample
Date human
sample plate

ID
Sample
Material
Type
collection
sample plating
collection
Mouse ID

2
Donor
direct
fc
Dec. 10, 2009
N/A
N/A
N/A

3
Donor
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
N/A

5
Donor
direct
fc
Dec. 10, 2009
N/A
N/A
N/A

6
Donor
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
N/A

7
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

8
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

9
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

10
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

11
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

12
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

14
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

15
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

16
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

17
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

18
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

19
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

20
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

21
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

22
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

23
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

24
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

25
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

26
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

27
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

28
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

29
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

30
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

31
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

32
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

33
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

34
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

35
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

36
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

37
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

38
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

39
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

40
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

41
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

42
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

43
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

44
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

45
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

46
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

47
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

48
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

49
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

50
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

51
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

52
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

53
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

54
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

55
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

56
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

57
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

58
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

59
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

60
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

61
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

62
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

63
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

64
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

65
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

66
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

67
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

68
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

69
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

70
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

71
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

72
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

73
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

74
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

75
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

76
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

77
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

78
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

79
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

80
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

81
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

82
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

83
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

84
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

85
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

86
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

87
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

88
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

89
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

90
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

91
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

92
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

93
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

94
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

95
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

96
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

97
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

98
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

102
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

108
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

110
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

111
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

112
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

113
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

114
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

115
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

116
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

120
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

126
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

132
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

144
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

150
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

156
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

162
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

168
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

174
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

180
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

186
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

187
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

188
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

189
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

190
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

191
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

192
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

193
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

194
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

195
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

196
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

197
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

198
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

199
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

200
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

201
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

202
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

203
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

204
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

205
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

207
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

208
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

209
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

210
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

211
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

212
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

213
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

214
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

215
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

216
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

217
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

218
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

219
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

220
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

221
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

222
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

223
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

224
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

225
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

226
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

227
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

228
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

229
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

230
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

231
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

232
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

233
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

234
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

235
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

236
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

238
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

240
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

261
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

262
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

263
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

265
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

266
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

267
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

268
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

269
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

270
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

271
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

272
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

273
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

274
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

275
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

276
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

277
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

278
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

279
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

280
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

281
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

282
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

284
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

285
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

287
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

288
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

289
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

290
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

291
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

292
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

293
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

294
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

295
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

296
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

297
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

298
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

299
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

300
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

301
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

302
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

303
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

304
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

305
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

306
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

307
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

308
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

309
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

310
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

311
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

312
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

313
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

314
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

315
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

316
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

317
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

318
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

319
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

321
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

323
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

324
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

325
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

326
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

328
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

329
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

330
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

332
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

333
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

334
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

335
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

338
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

339
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

340
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

341
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

342
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

343
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

344
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

345
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

347
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

348
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

349
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

350
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

351
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

352
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

353
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

354
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

355
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

356
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

357
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

358
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

359
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

360
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

361
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

362
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

363
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

364
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

365
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

366
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

367
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

369
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

370
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

371
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

372
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

373
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

374
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

375
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

376
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

377
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

378
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

379
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

380
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

381
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

382
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

383
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

384
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

385
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

386
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

387
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

388
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

389
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

390
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

391
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

392
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

393
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

394
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

395
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

396
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

397
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

398
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

399
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

400
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

401
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

402
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

403
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

404
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

405
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

406
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

407
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

408
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

409
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

410
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

411
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

412
Mouse
direct
pt
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

413
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

414
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

416
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

417
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

418
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

419
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

420
Mouse
cultured
pt
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

421
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

422
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

423
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

424
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

425
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

426
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

427
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

428
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

429
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

430
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

431
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

432
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

433
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

434
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

435
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

436
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

437
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

438
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

439
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

440
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

441
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

442
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

443
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

444
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

445
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

446
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

447
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

448
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

449
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

450
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

451
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

452
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

453
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

454
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

455
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

456
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

457
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

458
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

459
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

460
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

461
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

462
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

463
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

465
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

466
Mouse
direct
fc
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

467
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

468
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

469
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

470
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

471
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

472
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

473
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

474
Mouse
cultured
fc
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

493
Mouse
direct
Si2
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

494
Mouse
direct
Si2
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

495
Mouse
direct
Si2
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

496
Mouse
direct
Si2
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

498
Mouse
direct
Si2
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

499
Mouse
direct
Si2
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

500
Mouse
direct
Si2
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

501
Mouse
direct
Si2
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

502
Mouse
direct
Si2
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

503
Mouse
cultured
Si2
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

505
Mouse
cultured
Si2
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

506
Mouse
cultured
Si2
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

507
Mouse
cultured
Si2
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

509
Mouse
cultured
Si2
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

510
Mouse
cultured
Si2
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

511
Mouse
direct
Si5
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

512
Mouse
direct
Si5
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

513
Mouse
direct
Si5
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

514
Mouse
direct
Si5
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

515
Mouse
direct
Si5
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

517
Mouse
direct
Si5
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

518
Mouse
direct
Si5
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

519
Mouse
direct
Si5
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

520
Mouse
direct
Si5
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

521
Mouse
cultured
Si5
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

522
Mouse
cultured
Si5
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

523
Mouse
cultured
Si5
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

524
Mouse
cultured
Si5
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

525
Mouse
cultured
Si5
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

526
Mouse
cultured
Si5
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

527
Mouse
cultured
Si5
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

547
Mouse
direct
Si13
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

548
Mouse
direct
Si13
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

549
Mouse
direct
Si13
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

550
Mouse
direct
Si13
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

551
Mouse
direct
Si13
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

552
Mouse
direct
Si13
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

553
Mouse
direct
Si13
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

554
Mouse
direct
Si13
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

555
Mouse
direct
Si13
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

557
Mouse
cultured
Si13
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

558
Mouse
cultured
Si13
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

559
Mouse
cultured
Si13
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

560
Mouse
cultured
Si13
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

561
Mouse
cultured
Si13
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

562
Mouse
cultured
Si13
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

563
Mouse
cultured
Si13
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

583
Mouse
direct
cec
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

584
Mouse
direct
cec
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

587
Mouse
direct
cec
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

588
Mouse
direct
cec
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

589
Mouse
direct
cec
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

591
Mouse
direct
cec
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

592
Mouse
direct
cec
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

593
Mouse
cultured
cec
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

594
Mouse
cultured
cec
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

595
Mouse
cultured
cec
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

596
Mouse
cultured
cec
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

597
Mouse
cultured
cec
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

598
Mouse
cultured
cec
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

599
Mouse
cultured
cec
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

600
Mouse
cultured
cec
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

601
Mouse
direct
col
Dec. 10, 2009
N/A
N/A
GK_mouse_4.1

602
Mouse
direct
col
Dec. 10, 2009
N/A
N/A
GK_mouse_4.2

603
Mouse
direct
col
Dec. 10, 2009
N/A
N/A
GK_mouse_4.3

604
Mouse
direct
col
Dec. 10, 2009
N/A
N/A
GK_mouse_4.4

605
Mouse
direct
col
Dec. 10, 2009
N/A
N/A
GK_mouse_4.5

606
Mouse
direct
col
Dec. 10, 2009
N/A
N/A
GK_mouse_4.6

607
Mouse
direct
col
Dec. 10, 2009
N/A
N/A
GK_mouse_4.7

608
Mouse
direct
col
Dec. 10, 2009
N/A
N/A
GK_mouse_4.8

609
Mouse
direct
col
Dec. 10, 2009
N/A
N/A
GK_mouse_4.9

610
Mouse
direct
col
Dec. 10, 2009
N/A
N/A
GK_mouse_4.10

611
Mouse
cultured
col
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.11

612
Mouse
cultured
col
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.13

613
Mouse
cultured
col
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.15

614
Mouse
cultured
col
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.16

615
Mouse
cultured
col
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.17

616
Mouse
cultured
col
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.18

617
Mouse
cultured
col
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.19

618
Mouse
cultured
col
Dec. 10, 2009
Dec. 10, 2009
Dec. 17, 2009
GK_mouse_4.20

1001
Donor
direct
fc
Jun. 24, 2009
N/A
N/A
N/A

1002
Donor
direct
fc
Jun. 24, 2009
N/A
N/A
N/A

1003
Donor
cultured
pt
Jun. 24, 2009
Jun. 24, 2009
Jun. 30, 2009
N/A

2000
Donor
cultured
pt
Jul. 15, 2009
Jul. 15, 2009
Jul. 22, 2009
N/A

2001
Donor
direct
fc
Jul. 15, 2009
N/A
N/A
N/A

2002
Donor
direct
fc
Jul. 15, 2009
N/A
N/A
N/A

2003
Donor
cultured
pt
Jul. 16, 2009
Jul. 16, 2009
Jul. 23, 2009
N/A

2004
Donor
direct
fc
Jul. 16, 2009
N/A
N/A
N/A

2005
Donor
direct
fc
Jul. 16, 2009
N/A
N/A
N/A

2006
Donor
cultured
pt
Jul. 17, 2009
Jul. 17, 2009
Jul. 24, 2009
N/A

2007
Donor
direct
fc
Jul. 17, 2009
N/A
N/A
N/A

2008
Donor
direct
fc
Jul. 17, 2009
N/A
N/A
N/A

2009
Donor
cultured
pt
Jun. 24, 2009
Jun. 24, 2009
Jun. 30, 2009
N/A

2010
Donor
cultured
pt
Jul. 15, 2009
Jul. 15, 2009
Jul. 22, 2009
N/A

2011
Donor
direct
fc
Jul. 15, 2009
N/A
N/A
N/A

2012
Donor
direct
fc
Jul. 15, 2009
N/A
N/A
N/A

2013
Donor
cultured
pt
Jul. 16, 2009
Jul. 16, 2009
Jul. 23, 2009
N/A

2014
Donor
direct
fc
Jul. 16, 2009
N/A
N/A
N/A

2015
Donor
direct
fc
Jul. 16, 2009
N/A
N/A
N/A

2016
Donor
cultured
pt
Jul. 17, 2009
Jul. 17, 2009
Jul. 24, 2009
N/A

2017
Donor
direct
fc
Jul. 17, 2009
N/A
N/A
N/A

2018
Donor
direct
fc
Jul. 17, 2009
N/A
N/A
N/A

2019
Donor
cultured
pt
Jun. 24, 2009
Jun. 24, 2009
Jun. 30, 2009
N/A

3001
Donor
cultured
pt
Aug. 21, 2009
Aug. 21, 2009
Aug. 27, 2009
N/A

3002
Donor
cultured
pt
Aug. 21, 2009
Aug. 21, 2009
Aug. 27, 2009
N/A

3003
Donor
cultured
pt
Aug. 21, 2009
Aug. 21, 2009
Aug. 27, 2009
N/A

3004
Donor
cultured
pt
Aug. 21, 2009
Aug. 21, 2009
Aug. 27, 2009
N/A

3005
Donor
cultured
pt
Aug. 21, 2009
Aug. 21, 2009
Aug. 27, 2009
N/A

3006
Donor
cultured
pt
Aug. 21, 2009
Aug. 21, 2009
Aug. 27, 2009
N/A

3007
Donor
cultured
pt
Aug. 21, 2009
Aug. 21, 2009
Aug. 27, 2009
N/A

3008
Donor
cultured
pt
Aug. 21, 2009
Aug. 21, 2009
Aug. 27, 2009
N/A

3009
Donor
cultured
pt
Aug. 21, 2009
Aug. 21, 2009
Aug. 27, 2009
N/A

3010
Donor
cultured
pt
Aug. 21, 2009
Aug. 21, 2009
Aug. 27, 2009
N/A

3011
Donor
direct
fc
Aug. 21, 2009
N/A
N/A
N/A

3012
Donor
direct
fc
Aug. 21, 2009
N/A
N/A
N/A

4000
Donor
cultured
pt
May 25, 2010
May 25, 2010
Jun. 1, 2010
N/A

4001
Donor
cultured
pt
May 25, 2010
May 25, 2010
Jun. 1, 2010
N/A

4002
Donor
cultured
pt
May 25, 2010
May 25, 2010
Jun. 1, 2010
N/A

4003
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.1

4004
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.2

4005
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.3

4006
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.4

4007
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.5

4008
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.1

4009
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.2

4010
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.3

4011
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.4

4012
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.5

4013
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.1

4014
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.2

4015
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.3

4016
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.4

4017
Mouse
cultured
fc
May 25, 2010
May 25, 2010
Jun. 1, 2010
GK_mouse_5.5

Date

Date mouse
Date
replating

Sample

sample
replating
from mouse

ID
Mouse DOB
Date gavage
Timepoint
Mouse Diet
collection
from mouse
collection

2
N/A
N/A
initial
N/A
N/A
N/A
N/A

3
N/A
N/A
initial
N/A
N/A
N/A
N/A

5
N/A
N/A
initial
N/A
N/A
N/A
N/A

6
N/A
N/A
initial
N/A
N/A
N/A
N/A

7
Oct. 5, 2009
Dec. 10, 2009
4pg
LF/PP
Dec. 14, 2009
N/A
N/A

8
Oct. 5, 2009
Dec. 10, 2009
4pg
LF/PP
Dec. 14, 2009
N/A
N/A

9
Oct. 5, 2009
Dec. 10, 2009
4pg
LF/PP
Dec. 14, 2009
N/A
N/A

10
Oct. 5, 2009
Dec. 10, 2009
4pg
LF/PP
Dec. 14, 2009
N/A
N/A

11
Oct. 5, 2009
Dec. 10, 2009
4pg
LF/PP
Dec. 14, 2009
N/A
N/A

12
Oct. 5, 2009
Dec. 10, 2009
4pg
LF/PP
Dec. 14, 2009
N/A
N/A

14
Oct. 5, 2009
Dec. 10, 2009
4pg
LF/PP
Dec. 14, 2009
N/A
N/A

15
Oct. 5, 2009
Dec. 10, 2009
4pg
LF/PP
Dec. 14, 2009
N/A
N/A

16
Oct. 5, 2009
Dec. 10, 2009
4pg
LF/PP
Dec. 14, 2009
N/A
N/A

17
Oct. 5, 2009
Dec. 17, 2009
4pg
LF/PP
Dec. 21, 2009
N/A
N/A

18
Oct. 5, 2009
Dec. 17, 2009
4pg
LF/PP
Dec. 21, 2009
N/A
N/A

19
Oct. 5, 2009
Dec. 17, 2009
4pg
LF/PP
Dec. 21, 2009
N/A
N/A

20
Oct. 5, 2009
Dec. 17, 2009
4pg
LF/PP
Dec. 21, 2009
N/A
N/A

21
Oct. 5, 2009
Dec. 17, 2009
4pg
LF/PP
Dec. 21, 2009
N/A
N/A

22
Oct. 5, 2009
Dec. 17, 2009
4pg
LF/PP
Dec. 21, 2009
N/A
N/A

23
Oct. 5, 2009
Dec. 17, 2009
4pg
LF/PP
Dec. 21, 2009
N/A
N/A

24
Oct. 5, 2009
Dec. 17, 2009
4pg
LF/PP
Dec. 21, 2009
N/A
N/A

25
Oct. 5, 2009
Dec. 10, 2009
7pg
LF/PP
Dec. 17, 2009
N/A
N/A

26
Oct. 5, 2009
Dec. 10, 2009
7pg
LF/PP
Dec. 17, 2009
N/A
N/A

27
Oct. 5, 2009
Dec. 10, 2009
7pg
LF/PP
Dec. 17, 2009
N/A
N/A

28
Oct. 5, 2009
Dec. 10, 2009
7pg
LF/PP
Dec. 17, 2009
N/A
N/A

29
Oct. 5, 2009
Dec. 10, 2009
7pg
LF/PP
Dec. 17, 2009
N/A
N/A

30
Oct. 5, 2009
Dec. 10, 2009
7pg
LF/PP
Dec. 17, 2009
N/A
N/A

31
Oct. 5, 2009
Dec. 10, 2009
7pg
LF/PP
Dec. 17, 2009
N/A
N/A

32
Oct. 5, 2009
Dec. 10, 2009
7pg
LF/PP
Dec. 17, 2009
N/A
N/A

33
Oct. 5, 2009
Dec. 10, 2009
7pg
LF/PP
Dec. 17, 2009
N/A
N/A

34
Oct. 5, 2009
Dec. 10, 2009
7pg
LF/PP
Dec. 17, 2009
N/A
N/A

35
Oct. 5, 2009
Dec. 17, 2009
7pg
LF/PP
Dec. 24, 2009
N/A
N/A

36
Oct. 5, 2009
Dec. 17, 2009
7pg
LF/PP
Dec. 24, 2009
N/A
N/A

37
Oct. 5, 2009
Dec. 17, 2009
7pg
LF/PP
Dec. 24, 2009
N/A
N/A

38
Oct. 5, 2009
Dec. 17, 2009
7pg
LF/PP
Dec. 24, 2009
N/A
N/A

39
Oct. 5, 2009
Dec. 17, 2009
7pg
LF/PP
Dec. 24, 2009
N/A
N/A

40
Oct. 5, 2009
Dec. 17, 2009
7pg
LF/PP
Dec. 24, 2009
N/A
N/A

41
Oct. 5, 2009
Dec. 17, 2009
7pg
LF/PP
Dec. 24, 2009
N/A
N/A

42
Oct. 5, 2009
Dec. 17, 2009
7pg
LF/PP
Dec. 24, 2009
N/A
N/A

43
Oct. 5, 2009
Dec. 10, 2009
14pg
LF/PP
Dec. 24, 2009
N/A
N/A

44
Oct. 5, 2009
Dec. 10, 2009
14pg
LF/PP
Dec. 24, 2009
N/A
N/A

45
Oct. 5, 2009
Dec. 10, 2009
14pg
LF/PP
Dec. 24, 2009
N/A
N/A

46
Oct. 5, 2009
Dec. 10, 2009
14pg
LF/PP
Dec. 24, 2009
N/A
N/A

47
Oct. 5, 2009
Dec. 10, 2009
14pg
LF/PP
Dec. 24, 2009
N/A
N/A

48
Oct. 5, 2009
Dec. 10, 2009
14pg
LF/PP
Dec. 24, 2009
N/A
N/A

49
Oct. 5, 2009
Dec. 10, 2009
14pg
LF/PP
Dec. 24, 2009
N/A
N/A

50
Oct. 5, 2009
Dec. 10, 2009
14pg
LF/PP
Dec. 24, 2009
N/A
N/A

51
Oct. 5, 2009
Dec. 10, 2009
14pg
LF/PP
Dec. 24, 2009
N/A
N/A

52
Oct. 5, 2009
Dec. 10, 2009
14pg
LF/PP
Dec. 24, 2009
N/A
N/A

53
Oct. 5, 2009
Dec. 17, 2009
14pg
LF/PP
Dec. 31, 2009
N/A
N/A

54
Oct. 5, 2009
Dec. 17, 2009
14pg
LF/PP
Dec. 31, 2009
N/A
N/A

55
Oct. 5, 2009
Dec. 17, 2009
14pg
LF/PP
Dec. 31, 2009
N/A
N/A

56
Oct. 5, 2009
Dec. 17, 2009
14pg
LF/PP
Dec. 31, 2009
N/A
N/A

57
Oct. 5, 2009
Dec. 17, 2009
14pg
LF/PP
Dec. 31, 2009
N/A
N/A

58
Oct. 5, 2009
Dec. 17, 2009
14pg
LF/PP
Dec. 31, 2009
N/A
N/A

59
Oct. 5, 2009
Dec. 17, 2009
14pg
LF/PP
Dec. 31, 2009
N/A
N/A

60
Oct. 5, 2009
Dec. 17, 2009
14pg
LF/PP
Dec. 31, 2009
N/A
N/A

61
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
N/A
N/A

62
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
N/A
N/A

63
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
N/A
N/A

64
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
N/A
N/A

65
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
N/A
N/A

66
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
N/A
N/A

67
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
N/A
N/A

68
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
N/A
N/A

69
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
N/A
N/A

70
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
N/A
N/A

71
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
N/A
N/A

72
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
N/A
N/A

73
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
N/A
N/A

74
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
N/A
N/A

75
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
N/A
N/A

76
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
N/A
N/A

77
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
N/A
N/A

78
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
N/A
N/A

79
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

80
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

81
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

82
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

83
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

84
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

85
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

86
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

87
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

88
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

89
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

90
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

91
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

92
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

93
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

94
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

95
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

96
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

97
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

98
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

102
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

108
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

110
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

111
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

112
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

113
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

114
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

115
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

116
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

120
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

126
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

132
Oct. 5, 2009
Dec. 10, 2009
32pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

144
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

150
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

156
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

162
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

168
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

174
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

180
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

186
Oct. 5, 2009
Dec. 17, 2009
25pg
LF/PP
Jan. 11, 2010
Jan. 11, 2010
Jan. 18, 2010

187
Oct. 5, 2009
Dec. 10, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

188
Oct. 5, 2009
Dec. 10, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

189
Oct. 5, 2009
Dec. 10, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

190
Oct. 5, 2009
Dec. 10, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

191
Oct. 5, 2009
Dec. 10, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

192
Oct. 5, 2009
Dec. 10, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

193
Oct. 5, 2009
Dec. 10, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

194
Oct. 5, 2009
Dec. 10, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

195
Oct. 5, 2009
Dec. 10, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

196
Oct. 5, 2009
Dec. 10, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

197
Oct. 5, 2009
Dec. 17, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

198
Oct. 5, 2009
Dec. 17, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

199
Oct. 5, 2009
Dec. 17, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

200
Oct. 5, 2009
Dec. 17, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

201
Oct. 5, 2009
Dec. 17, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

202
Oct. 5, 2009
Dec. 17, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

203
Oct. 5, 2009
Dec. 17, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

204
Oct. 5, 2009
Dec. 17, 2009
1pw
Western
Jan. 13, 2010
N/A
N/A

205
Oct. 5, 2009
Dec. 10, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

207
Oct. 5, 2009
Dec. 10, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

208
Oct. 5, 2009
Dec. 10, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

209
Oct. 5, 2009
Dec. 10, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

210
Oct. 5, 2009
Dec. 10, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

211
Oct. 5, 2009
Dec. 10, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

212
Oct. 5, 2009
Dec. 10, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

213
Oct. 5, 2009
Dec. 10, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

214
Oct. 5, 2009
Dec. 10, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

215
Oct. 5, 2009
Dec. 17, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

216
Oct. 5, 2009
Dec. 17, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

217
Oct. 5, 2009
Dec. 17, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

218
Oct. 5, 2009
Dec. 17, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

219
Oct. 5, 2009
Dec. 17, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

220
Oct. 5, 2009
Dec. 17, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

221
Oct. 5, 2009
Dec. 17, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

222
Oct. 5, 2009
Dec. 17, 2009
3pw
Western
Jan. 15, 2010
N/A
N/A

223
Oct. 5, 2009
Dec. 10, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

224
Oct. 5, 2009
Dec. 10, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

225
Oct. 5, 2009
Dec. 10, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

226
Oct. 5, 2009
Dec. 10, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

227
Oct. 5, 2009
Dec. 10, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

228
Oct. 5, 2009
Dec. 10, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

229
Oct. 5, 2009
Dec. 10, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

230
Oct. 5, 2009
Dec. 10, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

231
Oct. 5, 2009
Dec. 10, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

232
Oct. 5, 2009
Dec. 10, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

233
Oct. 5, 2009
Dec. 17, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

234
Oct. 5, 2009
Dec. 17, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

235
Oct. 5, 2009
Dec. 17, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

236
Oct. 5, 2009
Dec. 17, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

238
Oct. 5, 2009
Dec. 17, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

240
Oct. 5, 2009
Dec. 17, 2009
7pw
Western
Jan. 19, 2010
N/A
N/A

261
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

262
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

263
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

265
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

266
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

267
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

268
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

269
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

270
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

271
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

272
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

273
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

274
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

275
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

276
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
N/A
N/A

277
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

278
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

279
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

280
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

281
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

282
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

284
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

285
Oct. 5, 2009
Dec. 10, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

287
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

288
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

289
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

290
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

291
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

292
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

293
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

294
Oct. 5, 2009
Dec. 17, 2009
14pw
Western
Jan. 26, 2010
Jan. 26, 2010
Feb. 2, 2010

295
Oct. 5, 2009
Dec. 10, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

296
Oct. 5, 2009
Dec. 10, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

297
Oct. 5, 2009
Dec. 10, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

298
Oct. 5, 2009
Dec. 10, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

299
Oct. 5, 2009
Dec. 10, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

300
Oct. 5, 2009
Dec. 10, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

301
Oct. 5, 2009
Dec. 10, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

302
Oct. 5, 2009
Dec. 10, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

303
Oct. 5, 2009
Dec. 10, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

304
Oct. 5, 2009
Dec. 10, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

305
Oct. 5, 2009
Dec. 17, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

306
Oct. 5, 2009
Dec. 17, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

307
Oct. 5, 2009
Dec. 17, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

308
Oct. 5, 2009
Dec. 17, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

309
Oct. 5, 2009
Dec. 17, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

310
Oct. 5, 2009
Dec. 17, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

311
Oct. 5, 2009
Dec. 17, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

312
Oct. 5, 2009
Dec. 17, 2009
1pb
LF/PP
Jan. 27, 2010
N/A
N/A

313
Oct. 5, 2009
Dec. 10, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

314
Oct. 5, 2009
Dec. 10, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

315
Oct. 5, 2009
Dec. 10, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

316
Oct. 5, 2009
Dec. 10, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

317
Oct. 5, 2009
Dec. 10, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

318
Oct. 5, 2009
Dec. 10, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

319
Oct. 5, 2009
Dec. 10, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

321
Oct. 5, 2009
Dec. 10, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

323
Oct. 5, 2009
Dec. 17, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

324
Oct. 5, 2009
Dec. 17, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

325
Oct. 5, 2009
Dec. 17, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

326
Oct. 5, 2009
Dec. 17, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

328
Oct. 5, 2009
Dec. 17, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

329
Oct. 5, 2009
Dec. 17, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

330
Oct. 5, 2009
Dec. 17, 2009
3pb
LF/PP
Jan. 29, 2010
N/A
N/A

332
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
N/A
N/A

333
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
N/A
N/A

334
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
N/A
N/A

335
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
N/A
N/A

338
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
N/A
N/A

339
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
N/A
N/A

340
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
N/A
N/A

341
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
N/A
N/A

342
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
N/A
N/A

343
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
N/A
N/A

344
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
N/A
N/A

345
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
N/A
N/A

347
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
N/A
N/A

348
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
N/A
N/A

349
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

350
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

351
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

352
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

353
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

354
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

355
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

356
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

357
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

358
Oct. 5, 2009
Dec. 10, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

359
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

360
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

361
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

362
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

363
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

364
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

365
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

366
Oct. 5, 2009
Dec. 17, 2009
8pb
LF/PP
Feb. 3, 2010
Feb. 3, 2010
Feb. 10, 2010

367
Oct. 5, 2009
Dec. 10, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

369
Oct. 5, 2009
Dec. 10, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

370
Oct. 5, 2009
Dec. 10, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

371
Oct. 5, 2009
Dec. 10, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

372
Oct. 5, 2009
Dec. 10, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

373
Oct. 5, 2009
Dec. 10, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

374
Oct. 5, 2009
Dec. 10, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

375
Oct. 5, 2009
Dec. 10, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

376
Oct. 5, 2009
Dec. 10, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

377
Oct. 5, 2009
Dec. 17, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

378
Oct. 5, 2009
Dec. 17, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

379
Oct. 5, 2009
Dec. 17, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

380
Oct. 5, 2009
Dec. 17, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

381
Oct. 5, 2009
Dec. 17, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

382
Oct. 5, 2009
Dec. 17, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

383
Oct. 5, 2009
Dec. 17, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

384
Oct. 5, 2009
Dec. 17, 2009
15pb
LF/PP
Feb. 10, 2010
N/A
N/A

385
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

386
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

387
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

388
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

389
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

390
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

391
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

392
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

393
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

394
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

395
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

396
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

397
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

398
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

399
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

400
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

401
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

402
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
N/A
N/A

403
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

404
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

405
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

406
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

407
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

408
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

409
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

410
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

411
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

412
Oct. 5, 2009
Dec. 10, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

413
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

414
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

416
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

417
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

418
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

419
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

420
Oct. 5, 2009
Dec. 17, 2009
1pf
Fasting
Feb. 11, 2010
Feb. 11, 2010
Feb. 18, 2010

421
Oct. 5, 2009
Dec. 10, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

422
Oct. 5, 2009
Dec. 10, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

423
Oct. 5, 2009
Dec. 10, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

424
Oct. 5, 2009
Dec. 10, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

425
Oct. 5, 2009
Dec. 10, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

426
Oct. 5, 2009
Dec. 10, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

427
Oct. 5, 2009
Dec. 10, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

428
Oct. 5, 2009
Dec. 10, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

429
Oct. 5, 2009
Dec. 10, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

430
Oct. 5, 2009
Dec. 10, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

431
Oct. 5, 2009
Dec. 17, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

432
Oct. 5, 2009
Dec. 17, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

433
Oct. 5, 2009
Dec. 17, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

434
Oct. 5, 2009
Dec. 17, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

435
Oct. 5, 2009
Dec. 17, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

436
Oct. 5, 2009
Dec. 17, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

437
Oct. 5, 2009
Dec. 17, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

438
Oct. 5, 2009
Dec. 17, 2009
2pf
LF/PP
Feb. 12, 2010
N/A
N/A

439
Oct. 5, 2009
Dec. 10, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

440
Oct. 5, 2009
Dec. 10, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

441
Oct. 5, 2009
Dec. 10, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

442
Oct. 5, 2009
Dec. 10, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

443
Oct. 5, 2009
Dec. 10, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

444
Oct. 5, 2009
Dec. 10, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

445
Oct. 5, 2009
Dec. 10, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

446
Oct. 5, 2009
Dec. 10, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

447
Oct. 5, 2009
Dec. 10, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

448
Oct. 5, 2009
Dec. 10, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

449
Oct. 5, 2009
Dec. 17, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

450
Oct. 5, 2009
Dec. 17, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

451
Oct. 5, 2009
Dec. 17, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

452
Oct. 5, 2009
Dec. 17, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

453
Oct. 5, 2009
Dec. 17, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

454
Oct. 5, 2009
Dec. 17, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

455
Oct. 5, 2009
Dec. 17, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

456
Oct. 5, 2009
Dec. 17, 2009
5pf
LF/PP
Feb. 15, 2010
N/A
N/A

457
Oct. 5, 2009
Dec. 10, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

458
Oct. 5, 2009
Dec. 10, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

459
Oct. 5, 2009
Dec. 10, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

460
Oct. 5, 2009
Dec. 10, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

461
Oct. 5, 2009
Dec. 10, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

462
Oct. 5, 2009
Dec. 10, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

463
Oct. 5, 2009
Dec. 10, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

465
Oct. 5, 2009
Dec. 10, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

466
Oct. 5, 2009
Dec. 10, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

467
Oct. 5, 2009
Dec. 17, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

468
Oct. 5, 2009
Dec. 17, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

469
Oct. 5, 2009
Dec. 17, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

470
Oct. 5, 2009
Dec. 17, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

471
Oct. 5, 2009
Dec. 17, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

472
Oct. 5, 2009
Dec. 17, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

473
Oct. 5, 2009
Dec. 17, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

474
Oct. 5, 2009
Dec. 17, 2009
9pf
LF/PP
Feb. 19, 2010
N/A
N/A

493
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

494
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

495
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

496
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

498
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

499
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

500
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

501
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

502
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

503
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

505
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

506
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

507
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

509
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

510
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

511
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

512
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

513
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

514
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

515
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

517
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

518
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

519
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

520
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

521
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

522
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

523
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

524
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

525
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

526
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

527
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

547
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

548
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

549
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

550
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

551
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

552
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

553
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

554
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

555
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

557
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

558
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

559
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

560
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

561
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

562
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

563
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

583
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

584
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

587
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

588
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

589
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

591
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

592
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

593
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

594
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

595
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

596
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

597
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

598
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

599
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

600
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

601
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

602
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

603
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

604
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

605
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

606
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

607
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

608
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

609
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

610
Oct. 5, 2009
Dec. 10, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

611
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

612
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

613
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

614
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

615
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

616
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

617
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

618
Oct. 5, 2009
Dec. 17, 2009
sac
LF/PP
Feb. 19, 2010
N/A
N/A

1001
N/A
N/A
N/A
N/A
N/A
N/A
N/A

1002
N/A
N/A
N/A
N/A
N/A
N/A
N/A

1003
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2000
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2001
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2002
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2003
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2004
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2005
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2006
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2007
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2008
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2009
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2010
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2011
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2012
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2013
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2014
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2015
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2016
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2017
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2018
N/A
N/A
N/A
N/A
N/A
N/A
N/A

2019
N/A
N/A
N/A
N/A
N/A
N/A
N/A

3001
N/A
N/A
N/A
N/A
N/A
N/A
N/A

3002
N/A
N/A
N/A
N/A
N/A
N/A
N/A

3003
N/A
N/A
N/A
N/A
N/A
N/A
N/A

3004
N/A
N/A
N/A
N/A
N/A
N/A
N/A

3005
N/A
N/A
N/A
N/A
N/A
N/A
N/A

3006
N/A
N/A
N/A
N/A
N/A
N/A
N/A

3007
N/A
N/A
N/A
N/A
N/A
N/A
N/A

3008
N/A
N/A
N/A
N/A
N/A
N/A
N/A

3009
N/A
N/A
N/A
N/A
N/A
N/A
N/A

3010
N/A
N/A
N/A
N/A
N/A
N/A
N/A

3011
N/A
N/A
N/A
N/A
N/A
N/A
N/A

3012
N/A
N/A
N/A
N/A
N/A
N/A
N/A

4000
N/A
N/A
N/A
N/A
N/A
N/A
N/A

4001
N/A
N/A
N/A
N/A
N/A
N/A
N/A

4002
N/A
N/A
N/A
N/A
N/A
N/A
N/A

4003
Jan. 10, 2010
Jun. 1, 2010
3pg
LF/PP
Jun. 4, 2010
N/A
N/A

4004
Jan. 10, 2010
Jun. 1, 2010
3pg
LF/PP
Jun. 4, 2010
N/A
N/A

4005
Jan. 10, 2010
Jun. 1, 2010
3pg
LF/PP
Jun. 4, 2010
N/A
N/A

4006
Jan. 10, 2010
Jun. 1, 2010
3pg
LF/PP
Jun. 4, 2010
N/A
N/A

4007
Jan. 10, 2010
Jun. 1, 2010
3pg
LF/PP
Jun. 4, 2010
N/A
N/A

4008
Jan. 10, 2010
Jun. 1, 2010
7pg
LF/PP
Jun. 8, 2010
N/A
N/A

4009
Jan. 10, 2010
Jun. 1, 2010
7pg
LF/PP
Jun. 8, 2010
N/A
N/A

4010
Jan. 10, 2010
Jun. 1, 2010
7pg
LF/PP
Jun. 8, 2010
N/A
N/A

4011
Jan. 10, 2010
Jun. 1, 2010
7pg
LF/PP
Jun. 8, 2010
N/A
N/A

4012
Jan. 10, 2010
Jun. 1, 2010
7pg
LF/PP
Jun. 8, 2010
N/A
N/A

4013
Jan. 10, 2010
Jun. 1, 2010
14pg
LF/PP
Jun. 15, 2010
N/A
N/A

4014
Jan. 10, 2010
Jun. 1, 2010
14pg
LF/PP
Jun. 15, 2010
N/A
N/A

4015
Jan. 10, 2010
Jun. 1, 2010
14pg
LF/PP
Jun. 15, 2010
N/A
N/A

4016
Jan. 10, 2010
Jun. 1, 2010
14pg
LF/PP
Jun. 15, 2010
N/A
N/A

4017
Jan. 10, 2010
Jun. 1, 2010
14pg
LF/PP
Jun. 15, 2010
N/A
N/A

Number	Date	Country
61450741	Mar 2011	US
61485887	May 2011	US
61497663	Jun 2011	US

	Number	Date	Country
Parent	PCT/US2012/028600	Mar 2012	US
Child	14022000		US

CULTURED COLLECTION OF GUT MICROBIAL COMMUNITY

Information

Publication Number

Date Filed

Date Published

Inventors

CPC

US Classifications

International Classifications

Abstract

Description

Claims

CROSS REFERENCE TO RELATED APPLICATIONS

GOVERNMENTAL RIGHTS

Provisional Applications (3)

Continuation in Parts (1)