Reagents and methods for using human embryonic stem cells to evaluate toxicity of pharmaceutical compounds and other chemicals

Information

  • Patent Grant
  • 8703483
  • Patent Number
    8,703,483
  • Date Filed
    Tuesday, April 10, 2007
    17 years ago
  • Date Issued
    Tuesday, April 22, 2014
    10 years ago
Abstract
The invention provides biomarker profiles of cellular metabolites and methods for screening chemical compounds including pharmaceutical agents, lead and candidate drug compounds and other chemicals using human embryonic stem cells (hESC) or lineage-specific cells produced therefrom. The inventive methods are useful for testing toxicity, particularly developmental toxicity and detecting teratogenic effects of such chemical compounds.
Description
BACKGROUND OF THE INVENTION

1. Field of the Invention


This invention provides methods for toxicological screening of pharmaceuticals and other chemical compounds. The invention specifically provides reagents that are human embryonic stem cells (hESC) or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells, as well as methods for using these cells to detect developmental toxicity or teratogenic effects of pharmaceutical compounds and other chemicals. More particularly, the invention provides an in vitro means for analyzing toxicity of compounds predictive of their toxicity during human development. Candidate predictive biomarkers for toxic or teratogenic effects are also identified and provided herein.


2. Background of Invention


Birth defects are a major cause of infant morbidity in the United States, affecting 1 in every 33 infants born (Brent & Beckman, 1990, Bull NY Acad Med 66: 123-63; Rosano et al., 2000, J Epidemiology Community Health 54:660-66), or approximately 125,000 newborns per year. It is understood that developmental toxicity can cause birth defects, and can generate embryonic lethality, intrauterine growth restriction (IUGR), dysmorphogenesis (such as skeletal malformations), and functional toxicity, which can lead to cognitive disorders such as autism. There is an increasing concern about the role that chemical exposure can play in the onset of these disorders. Indeed, it is estimated that 5% to 10% of all birth defects are caused by in utero exposure to known teratogenic agents (Beckman & Brent, 1984, Annu Rev Pharmacol 24: 483-500).


Concern exists that chemical exposure may be playing a significant and preventable role in producing birth defects (Claudio et al., 2001, Environm Health Perspect 109: A254-A261). This concern has been difficult to evaluate, however, since the art has lacked a robust and efficient model for testing developmental toxicity for the more than 80,000 chemicals in the market, plus the new 2,000 compounds introduced annually (General Accounting Office (GAO), 1994, Toxic Substances Control Act: Preliminary Observations on Legislative Changes to Make TSCA More Effective, Testimony, Jul. 13, 1994, GAO/T-RCED-94-263). Fewer than 5% of these compounds have been tested for reproductive outcomes and even fewer for developmental toxicity (Environmental Protective Agency (EPA), 1998, Chemical Hazard Data Availability Study, Office of Pollution Prevention and Toxins). Although some attempts have been made to use animal model systems to assess toxicity (Piersma, 2004, Toxicology Letters 149:147-53), inherent differences in the sensitivity of humans in utero have limited the predictive usefulness of such models. Development of a human-based cell model system would have an enormous impact in drug development and risk assessment of chemicals.


Toxicity, particularly developmental toxicity, is also a major obstacle in the progression of compounds through the drug development process. Currently, toxicity testing is conducted on animal models as a means to predict adverse effects of compound exposure, particularly on development and organogenesis in human embryos and fetuses. The most prevalent models that contribute to FDA approval of investigational new drugs are whole animal studies in rabbits and rats (Piersma, 2004, Toxicology Letters 149: 147-53). In vivo studies rely on administration of compounds to pregnant animals at different stages of pregnancy and embryonic/fetal development (first week of gestation, organogenesis stage and full gestation length). However, these in vivo animal models are limited by a lack of robustness between animal and human responses to chemical compounds during development. Species differences are often manifested in trends such as dose sensitivity and pharmacokinetic processing of compounds. At present, animal models are only 50% efficient in predicting human developmental response to compounds (Greaves et al., 2004, Nat Rev Drug Discov 3:226-36). Thus, human-directed predictive in vitro models present an opportunity to reduce the costs of new drug development and enable safer drugs.


In vitro models have been employed in the drug industry for over 20 years (Huuskonen, 2005, Toxicology & Applied Pharm 207:S495-S500). Many of the current in vitro assays involve differentiation models using primary cell cultures or immortalized cells lines (Huuskonen, 2005, Toxicology & Applied Pharm 207:S495-S500). Unfortunately, these models differ significantly from their in vivo counterparts in their ability to accurately assess development toxicity. In particular, the ECVAM initiative (European Center for Validation of Alternative Methods) has used mouse embryonic stem cells as a screening system for predictive developmental toxicology. The embryonic stem cell test (EST) has shown very promising results, with a 78% statistically significant correlation to in vivo studies, and the test was able to differentiate strong teratogens from moderate/weak or non-embryotoxic compounds (Spielmann et al., 1997, In Vitro Toxicology 10:119-27). This model is limited in part because toxicological endpoints are defined only for compounds that impair cardiac differentiation. This model also fails to account for interspecies developmental differences between mice and humans, and so does not fully address the need in the art for human-specific model systems.


Thus there remains a need in this art for a human-specific in vitro method for reliably determining developmental toxicity in pharmaceutical agents and other chemical compounds. There also is a need in the art to better understand human development and its perturbation by toxins and other developmental disrupting agents, to assist clinical management of acquired congenital disorders and the many diseases that share these biochemical pathways, such as cancer.


The present invention provides for the assessment of a plurality of small molecules, preferably secreted or excreted by hES cells or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells, and is determined and correlated with health and disease or insult state. Similar analyses have been applied to other biological systems in the art (Want et al., 2005 Chem Bio Chem 6: 1941-51), providing biomarkers of disease or toxic responses that can be detected in biological fluids (Sabatine et al., 2005 Circulation 112:3868-875).


SUMMARY OF THE INVENTION

The present invention provides reagents and methods for in vitro screening of toxicity and teratogenicity of pharmaceutical and non-pharmaceutical chemicals using undifferentiated human embryonic stem cells (hESC) or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells. The invention provides human-specific in vitro methods for reliably determining toxicity, particularly developmental toxicity and teratogenicity, of pharmaceuticals and other chemical compounds using human embryonic stem cells (hESCs) or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells. As provided herein, hESCs or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells, are useful for assessing toxic effects of chemical compounds, particularly said toxic and teratogenic effects on human development, thus overcoming the limitations associated with interspecies animal models. In particular, the invention demonstrates that metabolite profiles of hES cells or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells are altered in response to known disruptors of human development.


The invention shows that the hESC metabolome is a source of human biomarkers for disease and toxic response. In particular embodiments, exposure of hESC to valproate induced significant changes in different metabolic pathways, consistent with its known activity as a human teratogen. In other embodiments, hESC exposure to varying levels of ethanol induced significant alterations in metabolic pathways consistent with alcohol's known effects on fetal development.


In one aspect, the invention provides methods for using undifferentiated pluripotent human embryonic stem cells (hESC) or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells, for in vitro evaluation. In the inventive methods, undifferentiated hESCs or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells are exposed to test compounds, preferably at concentrations reflective of in vivo levels or at levels found in maternal circulation. Further embodiments of this aspect of the invention provide for determination of the capacity of the test compound to induce differentiation of pluripotent hESC into particular cell types. In other embodiments, the inventive methods are provided using pluripotent, non-lineage restricted cells. The benefit of utilizing pluripotent stem cells is they permit analysis of global toxic response(s) and are isolated from the physiological target of developmental toxicity, i.e. the human embryo. In addition, because these cells have not differentiated into a specific lineage, the potential for false negatives is reduced. In yet further embodiments are provided methods using hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells, for assessing toxicity and particularly developmental toxicity and teratogenicity.


In another aspect the invention provides methods for identifying predictive biomarkers of toxic responses to chemical compounds, particularly pharmaceutical and non-pharmaceutical chemicals, and particularly to known teratogens. In embodiments of this aspect, a dynamic set representative of a plurality of cellular metabolites, preferably secreted or excreted by hES cells or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells, is determined and correlated with health and disease or toxic insult state. Cellular metabolites according to this aspect of the invention generally range from about 10 to about 1500 Daltons, more particularly from about 100 to about 1000 Daltons, and include but are not limited to compounds such as sugars, organic acids, amino acids, fatty acids and signaling low-molecular weight compounds. Said biomarker profiles are diagnostic for toxicity of chemical compounds, particularly pharmaceutical and non-pharmaceutical chemicals, that participate in and reveal functional mechanisms of cellular response to pathological or toxic chemical insult, thus serving as biomarkers of disease or toxic response that can be detected in biological fluids. In particularly preferred embodiments of this aspect of the invention, these biomarkers are useful for identifying active (or activated) metabolic pathways following molecular changes predicted, inter alia, by other methods (such as transcriptomics and proteomics).


The invention thus also provides biomarker and pluralities of biomarkers, in some instances associated with metabolites from particular metabolic pathways, that are indicative of toxic or teratogenic insult. Said markers as provided by the invention are used to identify toxic and teratogenic insult, and in particular embodiments are used to characterize the amount or extent of said insult by being correlated with the amount or extent of the particular biomarker or plurality of biomarkers detected in cell culture media. In particular embodiments, said plurality of biomarkers provide a diagnostic pattern of toxic or teratogenic insult, more particularly identifying one or a multiplicity of specific metabolic pathways comprising metabolites detected after toxic or teratogenic insult.


The present invention is advantageous compared with inter alia the ECVAM mouse model because toxicity testing and biomarker identification are performed with human cells, specifically human embryonic stem cells (hESC). Human embryonic stem cells are able to recapitulate mammalian organogenesis in vitro (Reubinoff et al., 2000, Nature Biotechnology 18:399-404; He et al., 2003, Circ Res 93:32-9; Zeng et al., 2004, Stem Cells 22:925-40; Lee et al., 2000, Mol Genet Metab 86:257-68; Yan et al., 2005, Stem Cells 22:781-90) because they are pluripotent and self-renewing cells. Thus, hESCs can reveal mechanisms of toxicity, particularly developmental toxicity, and identify developmental pathways that are particularly sensitive to chemicals during early human development. The “human for human” embryonic model provided by the inventive methods disclosed herein permits a better understanding of the pathways associated with developmental toxicity, as this is a system developed directly from the target organism, as well as being a more accurate and sensitive assay for toxic or teratogenic insult in human development.


The methods of the invention provide further advantages in identifying important biomarkers for toxicity and teratogenicity by functional screening of hESCs or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells. These biomarkers advantageously identify metabolic and cellular pathways and mechanisms of toxicity, particularly developmental toxicity. Importantly, these biomarkers may also assist in the evaluation of toxic effects of chemicals on the developing human embryo.


In yet another aspect of the invention, differentially-detected secreted or excreted cellular products identified by methods of the invention include those associated with neurodevelopmental disorders and alterations in associated metabolic pathways, and include but are not limited to kynurenine, glutamate, pyroglutamic acid, 8-methoxykynurenate, N′-formylkynurenine 5-hydroxytryptophan, N-acetyl-D-tryptophan and other metabolites in the tryptophan and glutamate metabolic pathways.


Functional toxicity in post-natal life can be predicted using hESC since differentiated cells with critical in vivo properties can be generated in vitro. hESCs can be used to produce lineage-specific cells, including lineage-specific stem cells, precursor cells and terminally-differentiated cells, providing therein enriched populations of cells typically present in vivo in mixtures of different cell types comprising tissues. The invention thus provides methods for using hESCs to produce said enriched and developmental stage-specific populations of cells for toxicity screening of chemical compounds, particularly drugs, drug lead compounds and candidate compounds in drug development, to identify human-specific toxicities of said chemical compounds. These aspects of the methods of the invention are advantageous over art-recognized in vitro and in vivo animal model systems.


Specific preferred embodiments of the present invention will become evident from the following more detailed description of certain preferred embodiments and the claims.





BRIEF DESCRIPTION OF THE DRAWINGS

These and other objects and features of this invention will be better understood from the following detailed description taken in conjunction with the drawing wherein:



FIGS. 1A through 1C are profiles of secreted cellular metabolite biomarkers produced after contacting hESCs with 1 mM valproate. These profiles were produced using liquid chromatography/electrospray ionization-time of flight (TOF) mass spectrometry (LC/ESI-TOF-MS) after treating the cells with valproate for 24 hours (FIG. 1A), four days (FIG. 1B) and eight days (FIG. 1C). Secreted small molecules from treated (blue) and untreated (red) human embryonic stem cells were measured.



FIGS. 2A through 2D are profiles of secreted/excreted cellular metabolite biomarkers produced after contacting hESCs with 1 mM valproate. These profiles were produced using liquid chromatography/electrospray ionization time of flight mass spectrometry (LC/ESI-TOF-MS) after treating cells with valproate for 24 hours (FIG. 2A), four days (FIG. 2B), eight days (FIG. 2C), and comparative metabolic profiling of hES cells (blue) and conditioned media (yellow) (FIG. 2D).



FIGS. 3A through 3D are photomicrographs of cellular morphology showing the pluripotent embryonic stem cells following extended culture. The marker Oct-4 was retained in a similar manner as untreated controls (FIG. 3A=5 days valproate, FIG. 3B=5 days control, FIG. 3C-8 days valproate, FIG. 3D-8 days control).



FIG. 4 shows the results of comparative mass spectrometry in the presence of chemical standards confirming the chemical identity of folic acid (exact mass 441.14), pyroglutamic acid (exact mass 129.04), glutamate (exact neutral mass 147.05) and kynurenine (exact mass 208.08).



FIG. 5 represents the kynurenine metabolism pathway of tryptophan in humans (Wang et al., 2006, J Biol Chem 281: 22021-22028, published electronically on Jun. 5, 2006).



FIG. 6 illustrates a hierarchical clustering of fold-change differences from 22,573 unique masses and is representative of multiple independent experiments in which hESCs and neural precursors produced from hESCs were treated with 1 mM valproate. Non-embryonic cells (human fibroblasts) were used as controls (data not shown). Positive fold changes are red, negative fold changes are green, and missing data is grey.



FIG. 7 shows the relative expression of enzymes in the kynurenine and serotonin synthesis pathways in hES cells. INDO, indoleamine 2,3 dioxygenase, TDO or TDO2, tryptophan 2,3-dioxygenase. (TDO2 was upregulated in valproate-treated hES cells in comparison to controls.) AFMID, arylformamidase, TPH1, tryptophan hydroxylase, AADAT, aminoadipate aminotransferase, KYNU, kynunreninase, GAPDH, glyceraldehyde 3-phosphate dehydrogenase, housekeeping control gene. KMO, kynurenine 3-monooxygenase, was not expressed in valproate-treated cells or controls.





DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The invention provides reagents, including human embryonic stem cells (hESC) or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells produced therefrom, for assessing developmental toxicity using the human embryonic stem cell metabolome. Human embryonic stem cells are pluripotent, self-renewing cells isolated directly from preimplantation human embryos that recapitulate organogenesis in vitro. Lineage-specific precursor cells are derived from hES cells and have entered a specific cellular lineage, but yet remain multipotent with regard to cell type within that specific lineage. For example, neural precursors have committed to neural differentiation but yet remain unrestricted as to its neural cell type. Also within the scope of the inventive methods are terminally-differentiated cell types, such as neurons. Biochemical pathways of human development and disease are active in hESCs and or hESC-derived lineage-specific cells, because they recapitulate differentiation into functional somatic cells. Disruption of these pathways during development contributes to disorders such as neural tube defects (NTDs) and cognitive impairment. Environmental agents, namely chemicals or drugs, participate in the ontogenesis of certain acquired congenital disorders. The question of which pathways during early human development are particularly susceptible to the effects of the environment remains unsolved.


The metabolome, defined as the total dynamic set of cellular metabolites present in cells, is a product of health or disease/insult states. Metabolomics is particularly sensitive to environmental effects in comparison to other “omic” areas of study, such as genomics and proteomics. Cellular metabolites include but are not limited to sugars, organic acids, amino acids and fatty acids, particularly those species secreted or excreted from cells, that participate in functional mechanisms of cellular response to pathological or chemical insult. These cellular metabolites serve as biomarkers of disease or toxic response and can be detected in biological fluids (Soga et al., 2006, J Biol Chem 281:16768-78; Zhao et al., 2006, Birth Defects Res A Clin Mol Teratol 76:230-6), including hESC culture media. Importantly, metabolomic profiling may confirm functional changes that are often predicted by transcriptomics and proteomics.


However, because it was known that hESCs are highly sensitive to the culture microenvironment (Levenstein et al., 2005, Stem Cells 24: 568-574; Li et al., 2005, Biotechnol Bioeng 91:688-698.), their application as a source of predictive biomarkers in response to chemical compounds, including toxins, teratogens and particularly pharmaceutical agents, drug lead compounds and candidate compounds in drug development, and their usefulness in establishing in vitro models of disease and development was uncertain, inter alia because those of skill in the art could anticipate that exposure to an exogenous chemicals could be highly detrimental to survival of hES cells and preclude obtaining useful information from them. This concern has turned out not to be justified.


As used herein, the term “human embryonic stem cells (hESCs)” is intended to include undifferentiated stem cells originally derived from the inner cell mass of developing blastocysts, and specifically pluripotent, undifferentiated human stem cells and partially-differentiated cell types thereof (e.g., downstream progenitors of differentiating hESC). As provided herein, in vitro cultures of hESC are pluripotent and not immortalized, and can be induced to produce lineage-specific cells and differentiated cell types using methods well-established in the art. In preferred embodiments, hESCs useful in the practice of the methods of this invention are derived from preimplantation blastocysts as described by Thomson et al., in co-owned U.S. Pat. No. 6,200,806. Multiple hESC cell lines are currently available in US and UK stem cell banks.


The terms “stem cell progenitor,” “lineage-specific cell,” “hESC derived cell” and “differentiated cell” as used herein are intended to encompass lineage-specific cells that are differentiated from hES cells such that the cells have committed to a specific lineage of diminished potency. In some embodiments, these lineage-specific precursor cells remain undifferentiated with regard to final cell type. For example, neuronal stem cells are derived from hESCs and have differentiated enough to commit to neuronal lineage. However, the neuronal precursor retains ‘stemness’ in that it retains the potential to develop into any type of neuronal cell. Additional cell types include terminally-differentiated cells derived from hESCs or lineage-specific precursor cells, for example neural cells.


The term “cellular metabolite” as used herein refers to any small molecule secreted and/or excreted by a hESC or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells, produced therefrom. In preferred embodiments, cellular metabolites include but are not limited to sugars, organic acids, amino acids, fatty acids, hormones, vitamins, oligopeptides (less than about 100 amino acids in length), as well as ionic fragments thereof. Cells may also be lysed in order to measure cellular products present within the cell. In particular, said cellular metabolites are from about 10 to about 3600 Daltons in molecular weight, more particularly about 10 to about 1500 Daltons, and yet more particularly from about 100 to about 1000 Daltons.


hESCs are cultured according to the methods of the invention using standard methods of cell culture well-known in the art, including, for example those methods disclosed in Ludwig et al. (2006, Feeder-independent culture of human embryonic stem cells, Nat Methods 3: 637-46.). In preferred embodiments, hESCs are cultured in the absence of a feeder cell layer during the practice of the inventive methods; however, hESCs may be cultured on feeder cell layer prior to the practice of the methods of this invention.


The term “administering” as used herein refers to contacting in vitro cultures of hESCs or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells produced therefrom with a toxic, teratogenic, or test chemical compound. In a preferred embodiment the dosage of the compound is administered in an amount equivalent to levels achieved or achievable in vivo, for example, in maternal circulation.


The phrases “identifying cellular metabolites that are differentially produced” or “detecting alterations in the cells or alternations in cell activity” as used herein include but are not limited to comparisons of treated hES cells or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells, to untreated (control) cells (i.e., cells cultured in the presence (treated) or absence (untreated) of a toxic, teratogenic, or test chemical compound). Detection or measurement of variations in cellular metabolites, excreted or secreted therefrom, between treated and untreated cells is included in this definition. In a preferred embodiment, alterations in cells or cell activity are measured by determining a profile of changes in cellular metabolites having a molecular weight of less than 3000 Daltons, more particularly between 10 and 1500 Daltons, and even more particularly between 100 and 1000 Daltons, in a treated versus untreated cell as illustrated in FIGS. 1A through 1C.


The term “correlating” as used herein refers to the positive correlation or matching of alterations in cellular metabolites including but not limited to sugars, organic acids, amino acids, fatty acids, and low molecular weight compounds excreted or secreted from hES cells or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells, to an in vivo toxic response. The screened cellular metabolites can be involved in a wide range of biochemical pathways in the cells and related to a variety of biological activities including, but not limited to inflammation, anti-inflammatory response, vasodilation, neuroprotection, oxidative stress, antioxidant activity, DNA replication and cell cycle control, methylation, and biosynthesis of, inter alia, nucleotides, carbohydrates, amino acids and lipids, among others. Alterations in specific subsets of cellular metabolites can correspond to a particular metabolic or developmental pathway and thus reveal effects of a test compound on in vivo development.


The term “physical separation method” as used herein refers to any method known to those with skill in the art sufficient to produce a profile of changes and differences in small molecules produced in hESCs or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells, contacted with a toxic, teratogenic or test chemical compound according to the methods of this invention. In a preferred embodiment, physical separation methods permit detection of cellular metabolites including but not limited to sugars, organic acids, amino acids, fatty acids, hormones, vitamins, and oligopeptides, as well as ionic fragments thereof and low molecular weight compounds (preferably with a molecular weight less than 3000 Daltons, more particularly between 10 and 1500 Daltons, and even more particularly between 100 and 1000 Daltons). In particular embodiments, this analysis is performed by liquid chromatography/electrospray ionization time of flight mass spectrometry (LC/ESI-TOF-MS), however it will be understood that cellular metabolites as set forth herein can be detected using alternative spectrometry methods or other methods known in the art for analyzing these types of cellular compounds in this size range.


Data for statistical analysis were extracted from chromatograms (spectra of mass signals) using the Agilent Mass Hunter software (Product No. G3297AA, Agilent Technologies, Inc., Santa Clara, Calif.); it will be understood that alternative statistical analysis methods can be used. Masses were binned together if they were within 10 ppm and eluted within a 2 minutes retention time window. A binned mass was considered to be the same molecule across different LC/ESI-TOF-MS analyses (referred to herein as an “exact mass,” which will be understood to be ±10 ppm). Binning of the data is required for statistical analysis and comparison of masses across the entire experiment. If multiple peaks with the same mass at the same retention time within a single sample were detected by Mass Hunter, they were averaged to assist data analysis. Masses lacking a natural isotopic distribution or with a signal-to-noise ratio of less than 3 were removed from the data prior to analysis. One of skill in the art will appreciate that the results from this assay provide relative values that are assessed according to annotated values within 10 ppm to provide an identity for the molecular weight detected. Thus, a mass shift within 10 ppm is considered consistent with determining the identity of a specific cellular metabolite annotated known in the art due to differences in ionization source and instrumentation, e.g. between different experiments or using different instruments.


As used herein, a mass was considered to be the same across LC/ESI-TOF-MS runs using a simple algorithm that first sorts the data by mass and retention time. After sorting, a compound was considered unique if it had a retention time difference of less than or equal to three minutes and a mass difference less than or equal the weighted formula (0.000011× mass). If a series of measurements fit this definition it was considered to be from the same compound. If either the mass or the retention time varied by more than the limits listed above it was considered to be a different compound and given a new unique designation.


Significance tests were determined by performing ANOVAs on the log base 2 transformed abundance values of unique compounds present in treated and untreated media at each time point. A randomized complete block design was used with the ANOVA model including the effects of treatment, experiments, and a residual term, with the following formula: Log2(abundancetb)=treatmentt+experimentb+errortb.


Missing data were omitted from the test changing the degrees of freedom rather than assuming the missing data were absent. This assumption was made because the extensive filtering performed by the Mass Hunter software may miss or filter certain peaks because they are below a certain abundance threshold and not zero. The ANOVA F-test was considered significant if its p-value was less than 0.05. Fold changes were calculated using the least squared means for a given time and treatment.


The term “biomarker” as used herein refers to cellular metabolites that exhibit significant alterations between treated and untreated controls. In preferred embodiments, biomarkers are identified as set forth above, by methods including LC/ESI-TOF-MS. Metabolomic biomarkers are identified by their unique molecular mass and consistency with which the marker is detected in response to a particular toxic, teratogenic or test chemical compound; thus the actual identity of the underlying compound that corresponds to the biomarker is not required for the practice of this invention. Alternatively, certain biomarkers can be identified by, for example, gene expression analysis, including real-time PCR, RT-PCR, Northern analysis, and in situ hybridization, but these will not generally fall within the definition of the term “cellular metabolites” as set forth herein.


The basal metabolome of undifferentiated hESCs served as a collection of biochemical signatures of functional pathways that are relevant for sternness and self-renewal. Metabolite profiling was conducted on excreted or secreted cellular metabolites as opposed to intracellular compounds. Ultimately, biomarkers discovered in vitro are expected to be useful for analyzing in vivo biofluids such as serum, amniotic fluid and urine, complex mixtures of extracellular biomolecules. This is advantageous over invasive procedures such as tissue biopsies because small molecules in biofluids can be detected non-invasively (in contrast to intracellular compounds). In addition, processing cellular supernatant for mass spectrometry is more robust and less laborious than cellular extracts. However, cellular extracts (from, for example, lysed cells) can be utilized in the methods of the invention.


The term “biomarker profile” as used herein refers to a plurality of biomarkers identified by the inventive methods. Biomarker profiles according to the invention can provide a molecular “fingerprint of the toxic and teratogenic effects of a test compound and convey what cellular metabolites, specifically excreted and secreted cellular metabolites, were significantly altered following test compound administration to hESCs or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells. In these embodiments, each of the plurality of biomarkers is characterized and identified by its unique molecular mass and consistency with which the biomarker is detected in response to a particular toxic, teratogenic or test chemical compound; thus the actual identity of the underlying compound that corresponds to the biomarker is not required for the practice of this invention.


The term “biomarker portfolio” as used herein refers to a collection of individual biomarker profiles. The biomarker portfolios may be used as references to compare biomarker profiles from novel or unknown compounds. Biomarker portfolios can be used for identifying common pathways, particularly metabolic or developmental pathways, of toxic or teratogenic response.


These results set forth herein demonstrated that human embryonic stem cell metabolomics, and metabolomics from hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells, can be used in biomarker discovery and pathway identification. Metabolomics detected small molecules secreted by hESCs or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells, produced therefrom and the identified biomarkers can be used for at least two purposes: first, to determine specific metabolic or developmental pathways that respond to or are affected by toxin or teratogen exposure, particularly said pathways utilized or affected during early development that are sensitive to toxic, teratogenic or test chemical compounds that are developmental disruptors and participate in the ontogenesis of birth defects; and second, to provide cellular metabolites that can be measured in biofluids to assist management and diagnosis of toxic exposure, birth defects or other disease.


A biomarker portfolio from hESCs or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells, produced therefrom can also serve as a high throughput screening tool in preclinical phases of drug discovery. In addition, this approach can be used to detect detrimental effects of environmental (heavy metals, industrial waste products) and nutritional chemicals (such as alcohol) on human development. Ultimately, the methods of this invention utilizing the hESC metabolome or the metabolome of or hESC-derived lineage-specific cells, such as neural stem cells, neural precursor cells and neural cells, can assist pharmaceutical, biotechnology and environmental agencies on decision-making towards development of compounds and critical doses for human exposure. The integration of chemical biology to embryonic stem cell technology also offers unique opportunities to strengthen understanding of human development and disease. Metabolomics of cells differentiated from hESC should serve similar roles and be useful for elucidating mechanisms of toxicity and disease with greater sensitivity for particular cell or tissue types, and in a human-specific manner. For example, key metabolic pathways, including as set forth herein folate, glutamate and tryptophan synthesis and degradation, may be differentially disrupted in earlier versus later stages of human development. In addition, metabolite profiles of neural precursor cells or neuronal cell populations can reveal biomarkers of neurodevelopmental disorders in target cell types. The association of metabolomics to stem cell biology can inform the mechanisms of action of folic acid and neural tube defects in the early human embryo.


Biomarker portfolios produced using the hESC-dependent and hESC-derived lineage-specific cell-dependent methods of this invention can also be used in high throughput screening methods for preclinical assessment of drug candidates and lead compounds in drug discovery. This aspect of the inventive methods produces minimal impact on industry resources in comparison to current developmental toxicology models, since implementation of this technology does not require experimental animals. The resulting positive impact on productivity enables research teams in the pharmaceutical industry to select and advance compounds into exploratory development with greater confidence and decreased risk of encountering adverse developmental effects.


The term “developmental pathway” as used herein refers to developmental or metabolic pathways in embryonic and fetal development.


“Supernatant” as used herein may include but is not limited to extracellular media, co-cultured media, cells, or a solution of fractionated or lysed cells.


Cellular metabolite profiles obtained from analysis of toxins, teratogens, alcohol, and test chemical compounds can be used to compose a library of biomarker portfolios. These portfolios can then be used as a reference for toxicological analysis of unknown chemical compounds. A similar strategy has been validated as a means to determine cellular changes that arise in response to chemicals in non-hESC systems (Daston & Nacliff, 2005, Reprod Toxicolog 19:381-94; Fella et al., 2005, Proteomics 5:1914-21). Metabolic profiles of novel compounds can be compared to known biomarker portfolios to identify common mechanisms of toxic response. This approach can reveal functional markers of toxic response, which serve as screening molecules that are shared at least in part as a consequence of exposure to various different toxic and teratogenic compounds. Such hESC-derived small molecules can be used as measurable mediators of toxic response that refine or replace costly and complex screening systems (such as in vivo animal models) and have the additional advantage of being specific for human cells and human metabolic and developmental pathways.


EXAMPLES

The Examples which follow are illustrative of specific embodiments of the invention, and various uses thereof. They are set forth for explanatory purposes only, and are not to be taken as limiting the invention.


Example 1
Developmental Toxicology Screening

To demonstrate the efficacy of hESCs as a model system for developmental toxicity testing, hESCs were treated with a known teratogen, valproate (VPA). Valproate is a common mood stabilizer and anti-convulsant drug with clinical indications in epilepsy and bipolar disorder (Williams et al., 2001, Dev Med Child Neuro 43:202-6) that has been associated with developmental abnormalities (Meador et al., 2006, Neurology 67: 407-412). The mechanism by which valproate produces developmental defects, however, is not fully understood, despite the increased susceptibility of the nervous system (Bjerkedal et al., 1982, Lance 2:109: Wyszynski et al., 2005, Neurology 64:961-5; Rasalam et al., 2005, Dev Med Child Neuro 47:551-555). Exposure to valproate results in a pronounced increase in spina bifida and neural tube defects (NTDs; Bjerkedal et al., 1982, Lancet 2:109) at ten-to-twenty times that of the general population, as well as cognitive disorders such as autism (Adab et al., 2004, J Neurol Neurosurg Psychiatry 75:1575-83). However, since VPA is an anti-convulsant drug with clinical indications in epilepsy and bipolar disorder (Williams et al., 2001, Dev Med Child Neurol 43:202-06), treatment generally must be sustained throughout pregnancy.


Folic acid supplementation prior to pregnancy reduces the incidence of spina bifida by 70% (Shaw et al., 1995, Epidemiolog 6:219-226) although its precise mechanism of action is unknown. In addition, homocysteine and glutathione have also been implicated in NTDs (Zhao et al., 2006, Birth Defects Res A Clin Mol Teratol 76:230-6). Thus, metabolite profiles of folate and related pathways were candidates for changes in response to valproate. In the results set forth herein, folic acid was significantly increased (by 16%) in the extracellular media of hES cells treated with valproate (p=0.022 at eight days, Table 3 and FIG. 4) but not its derivative dihydrofolate. Since mammalian cells do not synthesize folic acid, valproate may act by interfering with cellular uptake of folic acid.


Exposure of hESCs was performed as follows. H1 hESC (passage 41) were cultured on Matrigel (BD Scientific, San Jose, Calif.) in the absence of a feeder layer. hESCs were maintained in conditioned medium (CM) collected from mouse embryonic fibroblasts (MEFs) (80% DMEM/F12, Invitrogen, Carlsbad, Calif.) and 20% KNOCKOUT serum replacement (Invitrogen) supplemented with 1 mM L-glutamine (Invitrogen), 1% MEM non-essential amino acids (Invitrogen), and 0.1 mM 2-mercaptoethanol (Sigma, Chemical Co., St. Louis, Mo.). Prior to feeding hESCs, the culture medium was supplemented with 4 ng/mL human recombinant basic fibroblast growth factor (Invitrogen). hESCs were passaged when the wells were ˜80% confluent. To passage, hESCs were incubated in a 1 mg/mL dispase (Invitrogen)/DMEM/F12 solution for 7-10 minutes at 37° C. After this treatment hESCs were washed and seeded on fresh Matrigel coated plates. In parallel studies disclosed herein, H1 and H9 cells were cultured in defined medium known as TeSR (Ludwig et al., 2006, Id.).


H1 and H9 (equivalent to NIH code WA01/WA09) hESC were treated with valproate (VPA) (22 μM and 1 mM) (Sigma # P4543) according to the procedure outlined below; each experiment involved three separate VPA treatments, and each treatment group had a parallel control group with a total of six 6-well culture dishes (Nunc, Naperville, Ill.) per experiment (two 6-well culture dishes per treatment). Treatment 1 (labeled 24 H) exposed hESC cells to 1 mM VPA (Sigma) for 24 hours followed by collection of supernatant and cell pellets. In a second treatment group (labeled 4 D), hESC cells were exposed to 22 μM or 1 mM VPA for 4 days and harvested on day 4. In a third treatment group (labeled extended culture, EC), hESC cells received 22 μM or 1 mM VPA for 4 days followed by culture in standard hESC media for an additional four days. For this group, cells and supernatant were harvested on day eight.


To assess the effects of teratogenic VPA treatment on hESCs, the treated cells were analyzed as set forth below to determine changes in a total dynamic set of small molecules present in cells according to health and disease or insult states. Small molecules including but not limited to sugars, organic acids, amino acids, fatty acids, hormones, vitamins, oligopeptides (less than about 100 amino acids in length), as well as ionic fragments thereof and signaling low molecular weight compounds were known to participate in and reveal functional mechanisms of cellular response to pathological or chemical insult. These analyses were also used to identify active pathways following molecular changes predicted by other analyses including for example transcriptomics and proteomics.


Supernatant from VPA-treated and control hESCs were subjected to liquid chromatography and electrospray ionization time of flight mass spectrometry (LC/ESI-TOF-MS) to assess changes and differences in small molecules (as defined herein) produced by the cells in the presence and absence of VPA treatment. Supernatant was collected from control and treated plates of hESCs at 24 H, 4 D, and 8 D, and CM was collected as a “no treatment” control. The supernatant and media were stored at −80° C. until preparation for mass spectrometry analysis. For analysis, samples were prepared in a 20% Acetonitrile (Fisher Scientific Co., Pittsburgh, Pa.) solution (comprising 500 μL of supernatant, 400 μL acetonitrile and 1.1 mL distilled water) and centrifuged through a Millipore 3 kDa Centricon column (Millipore, Billerica, Mass.) for 3 hours at 4575×g to remove proteins. The flow-through was retained for analysis, as it contains small molecules free of high molecular weight compounds such as proteins. In each analysis, three replicates for each sample were injected into a 2.1×200 mm C18 column using a 90 minute gradient from 5% Acetonitrile, 95% Water, 0.1% Formic Acid to 100% Acetonitrile, 0.1% Formic Acid at a flow rate of 40 μL/min. ESI-TOF-MS (TOF) was performed on the flow-through using an Agilent ESI-TOF mass spectrometer. Data was collected from 100-3600 m/z, and particularly in the 0-1500 m/z range. The raw data was analyzed to identify the separated small molecules using a computer compilation and analysis program (Mass Hunter) provided by the manufacturer and according to manufacturer's instructions (Agilent; statistical analyses were performed as described above in the Detailed Description and Preferred Embodiments. This analysis generated lists of retention time/accurate mass pair feature. Another program (Mass Profiler, Agilent) was used to compare multiple run sets to find ion intensity changes of features that changed between the sample conditions. Significance tests were determined by performing ANOVAs on the log base 2 transformed abundance values of unique compounds present in treated and untreated media at each time point.


The plurality of small molecules identified using these methods were then compared with exact mass and retention time from ESI-TOF-MS using public databases (for example, at http://metlin.scripps.edu., www.nist.gov/srd/chemistry.htm; http://www.metabolomics.ca/). Mass spectrometry analysis also included predicted chemical structures of small molecules based upon exact mass, although currently-available public databases do not in every instance include matching small molecules due to database limitations. In addition, more comprehensive private databases are available for comparative analysis, such as the NIST/EPA/NIH Mass Spectral Library: 05. NIST ASCII Version.


The results of these analyses are shown in FIGS. 1A through 1C and FIG. 2A through 2C. In FIGS. 1A through 1C each feature on the plot corresponds to a small molecule with specific exact mass and retention time. The plots summarize significant differences found between treated (blue) and untreated (red) groups at different time points. As shown in the Figure, at 24 hours (24 H) there was consistent down-regulation of the secreted biomolecules in treated (blue) cells in comparison to untreated (red) controls. At four days (4 D) and eight days (EC), treated (blue) cells secreted a higher number of small molecules in comparison to untreated cells (red); said small molecules were thus considered as candidate biomarkers. In particular, metabolites from the folate pathway, including tetrahydrofolate (exact mass 444) and dihydrofolate (exact mass 441) were detected. These findings were considered significant, since they show for the first time that hESCs contacted with a known teratogen (VPA) that causes a birth defect (spina bifida) respond by up-regulating a metabolic pathway that produces a compound (folate) known to ameliorate the effects of the teratogen when administered to a woman bearing a developing embryo or fetus.


Further, the results shown in FIGS. 1A through 1C revealed approximately 40 small molecules that were absent in treated groups, suggesting that multiple cellular pathways were “silenced” in response to VPA at 24 hours in comparison to untreated controls. At four and eight days after treatment, however, multiple candidate biomarkers were upregulated in treated versus untreated human embryonic stem cells; these results are shown in Table 1. Candidate biomarkers were identified as small molecules showing a change in treated versus untreated cells measured to be at least a two-fold difference. In many instances, these small molecules are absent or detected at very low concentrations in untreated human embryonic stem cells.


These studies demonstrated that the claimed methods for assessing developmental toxicity and the identification of biomarkers using hESCs provided robust information on changes in small molecule content of cells in response to being contacted with a known teratogen, VPA. The results concerning a compound (VPA) that is involved in the etiology of spina bifida and neural tube defects (NTDs) (Bjerkedal et al., 1982, Lancet 2:109) when exposed to a developing human conceptus are particularly striking. The results shown here indicated a marked increase (2 to 8 fold) in key metabolites of the folate pathway (dihydrofolic acid, tetrahydrofolic acid, S-adenosylmethionine) following treatment with VPA (in comparison to untreated cells). These methods were reproducible, having been repeated with consistent results obtained in three independent studies using hESCs and on non-embryonic cells (human fibroblasts) as controls (data not shown), and suggested a heretofore unknown adaptive response of the fetus to the chemical/environmental insult and identified sensitive markers for said insult(s).


The mechanism for VPA developmental defects, however, is not fully understood despite the fact that the nervous system is particularly sensitive to its effects (Bjerkedal et al., 1982, Lancet 2:109; Narita et al., 2000, Pediatric Res 52:576-79; Rasalam et al., 2005, Dev Med Child Neurol 47:551-55). Folic acid supplementation prior to pregnancy prevents the incidence of spina bifida by 70% (Shaw et al., 1995, Epidemiolog 6:219-226), although the exact mechanism of action is also unknown. The information obtained herein can be used to elucidate mechanisms of action of folic acid and neural tube defects in the early human embryo. These methods can also be applied to other known teratogens, such as retinoic acid, warfarin, and thalidomide (Franks et al., 2004, Lancet 363:1802-11) to validate the predictive ability of hESCs using the methods of the invention.


Table 1: Candidate small molecules (biomarkers) of developmental toxicity detected in undifferentiated human embryonic stem cells treated with 1 mM valproate in comparison to untreated controls.









TABLE 1







Candidate small molecules (biomarkers) of developmental toxicity detected


in undifferentiated human embryonic stem cells treated with 1 mM


valproate in comparison to untreated controls.


Change in VPA Treated hESCs in comparison to untreated controls












Exact mass
RT
24 Hours
4 Days
8 Days
Candidate Biomarker















355.066
16

UP

SAM







S-ADENOSYLMETHIONINAMINE


355.12
30

UP

SAM


381.1574
12

UP
UP
GLUTATHIONE


398.21
39
DOWN
UP

SAM OXOBUTANOATE


441.8831
12


UP
DIHYDROFOLIC ACID


444.1729
17

UP
UP
TETRAHYDROFOLIC ACID


472.16
17
ZERO
UP
UP
TETRAHYDROFOLATE


612.15
17
DOWN
DOWN
UP
GLUTATHIONE OXIDIZED





RT = retention time


Small molecule detection was conducted with LC/ESI-TOF-MS in triplicate samples of supernatant processed independently.






As discussed above, metabolite profiles were determined at 24 hours, four days and eight days after valproate treatment. At four days after treatment, multiple candidate biomarkers were upregulated in treated versus untreated human embryonic stem cells (shown in FIGS. 2A through 2C). In addition to the results set forth above regarding increased levels of certain metabolites, multiple metabolite peaks were down-regulated in response to valproate at 24 hours in comparison to untreated controls (FIGS. 2A through 2C).


hESCs were cultured in conditioned media from mouse embryonic fibroblasts, which generated 1277 of the 3241 measured compounds. Many metabolites in human development and disease are likely present in conditioned media from mouse embryonic fibroblasts due to common metabolic pathways. Rigorous investigation is required to validate candidate biomarkers that are not exclusive to hESCs and are also present in the media.


Example 2
Gene Expression Analysis

The efficacy of the analysis shown in Example 1 was confirmed by gene expression studies, wherein changes in gene expression were observed following VPA treatment of hESCs. VPA treatment was not detrimental to hESCs, which remained viable for multiple passages following teratogen exposure, thus enabling gene expression analysis to be performed.


Treated and control H1/NIH code WA01 hES cells (passage 41) were analyzed by real-time PCR, and each treatment group was paired with a corresponding control group that received the standard growth media combination of CM+bFGF without VPA. In these studies, total cellular RNA was extracted from cells harvested at 24 hours (24 H), 4 days (4 D) and 8 days (EC) using the RNA Easy Kit (Qiagen, Valencia, Calif.) according to the manufacturer's instructions.


Expression levels of candidate test genes and a housekeeping gene (Beta-2-microglobulin) were evaluated by quantitative real-time PCR using a DNA Engine-Opticon 2 Detection System (MJ Research, Watertown, Mass.). The housekeeping gene acts as an internal control for normalization of RNA levels. The primers used for real-time PCR reactions were designed using Beacon Designer software (Premier Biosoft International, Palo Alto, Calif.). RNA was reverse transcribed using iScript cDNA Synthesis kit (Bio-Rad, Hercules, Calif.), wherein each cDNA synthesis reaction (20 μL) included 4 μL of 5× iScript reaction mix, 1 μL of iScript reverse transcriptase, and 2 μL of RNA. PCR was performed on cDNA in PCR reaction mixtures (25 μL) each containing 12.5 μL of Supermix (contains dNTPs, Taq DNA polymerase, SYBR Green I, and fluorescein), 250 nM forward primer, 250 nM reverse primer, and 1.6 μL RT-PCR products. Melting curve analysis and agarose gel electrophoresis were performed after real-time PCR reaction to monitor PCR specificity, wherein PCR products were detected with SYBR Green I using the iQ SYBR Green Supermix kit (Bio-Rad).


Quantifying the relative expression of real-time PCR was performed using the 2-ΔΔCt method (Livak & Schmittgen, 2001, Methods 25:402-8), and a general linear model was employed to fit the expression data. The PROC GLM procedure in SAS (version 8.2; SAS Institute, Cary, N.C.) was used to estimate least squares means in expression between treated and untreated hESCs and P<0.05 was considered statistically significant


Real-time PCR was conducted on samples from 24 hours (24 H), 4 days (4 D) and 8 days (EC) after VPA treatment to investigate expression levels of epigenetic regulators (such as DNA methyltransferase-1, DNMT-1, BMI-1, EED) and critical transcription factors responsible for embryonic patterning and neurodevelopment (RUNX2, BMP7, FGF8, CBX2, GLI3, SSH and SP8) in human embryonic stem cells. These experiments showed hESCs treated with VPA were subject to marked changes in their transcriptional activity following teratogen treatment. VPA induced overall marked (2 to 30 fold) downregulation of transcription levels as early as 24 hours after exposure in all genes tested (with the exception of DNMT-1 and Shh). At 4 days after treatment, however, expression of the ubiquitous DNA methyltransferase-1 was almost abolished, and sonic hedgehog, which is absolutely critical for neurogenesis (Ye et al., 1998, Cell 93:755-66), was down-regulated five-fold in comparison to untreated controls. At 8 days after VPA treatment, the majority of the genes were upregulated in comparison to untreated controls.


These results embodied two major implications for developmental toxicology. First, VPA induced persistent changes in key epigenetic modulators that also participate in differentiation of other tissues, such as DNMT-1 and the polycomb family member EED. Second, the effects of teratogens persisted in hESCs during critical stages of neurogenesis and organogenesis. For example, genes whose expression was affected as shown herein (including sonic hedgehog and FGF-8) are known to be master regulators of differentiation of serotonergic neurons in the brain (Ye et al., 1998, Cell 93:755-66). Of particular notice is the fact that DNMT-1 expression is almost abolished at four days after treatment. In vivo, disruption of this enzyme is lethal to embryos, since it is the major maintenance methyltransferase during DNA replication (Li et al., 1992, Cell 69:915-26).


Following teratogen exposure, temporal-specific alterations in developmental gene expression were observed. Developmental genes differ in their susceptibility to teratogens at different times. This indication may be critical to understanding specificity of epigenetic disruptors on certain organs or tissues. RUNX2, for example, is a transcriptional activator of bone development (Napierala et al., 2005, Mol Genet Metab 86:257-68), and is more sensitive to VPA-mediated up-regulation at very early or late stages following exposure. Real-time PCR results from hESCs disclosed herein were correlated to previous findings in vivo in mice (Okada et al., 2004, Birth Defects Res A Clin Mol Teratol 70:870-879) and rats (Miyazaki et al., 2005, Int J Devl Neuroscience 23:287-97). In these animal studies, VPA inhibited the expression of Polycomb genes, Eed, Bmil and Cbx2 and induced downregulation of Shh while FGF8 levels remained unchanged. The results shown here at four days following VPA treatment (Table 2) were consistent with these observations using other developmental model systems.









TABLE 2







1 mM VPA treatment resulted in marked changes in the expression of


epigenetic regulators and developmental genes that are critical for


embryonic patterning and differentiation of neurons.















2-24 H

4-4 D

6-EC



1-24 H
VPA
3-4 D
VPA
5-EC
VPA


Gene
control
treated
control
treated
control
treated
















BMI-1
0.543
0.252
1.651
0.112
1.020
1.071


DNMT1
0.664
0.624
1.742
0.002
0.731
1.124


EED
0.757
0.342
1.501
0.185
1.381
1.769


H19
0.207
0.006
0.144
0.846
10.660
2.756


RUNX2
0.325
1.769
5.198
4.020
1.177
2.434


BMP7
0.511
0.093
0.397
0.342
0.731
1.664


FGF8
2.544
0.801
0.384
0.314
0.16
0.837


CBX2
1.113
0.245
1.221
1.1881
0.81
1.946


GLI3
0.202
0.015
0.016
0.774
0.950
1.918


Shh
0.562
0.562
2.772
0.533
1.369



SP8
0.49
0.235
0.25
1.703
2.132
5.808





Gene expression levels are relative to a housekeeping gene (target gene/Beta-2-Microglobulin).






Example 3
Human Embryonic Stem Cell Metabolome: Metabolite Profiles Following Teratogen Exposure

Exposure of hES cells to the teratogen valproate induced significant changes in different metabolic pathways, including pathways important during pregnancy and development. An alternative metabolic pathway activated during pregnancy are shown in FIG. 5, wherein tryptophan is converted to kynurenine. To investigate this aspect of the invention, hESCs were cultured as described in Example 1, and the procedure for valproate treatment was performed as described therein. Treatment 1 (24 hours) exposed hES cells to 22 μM valproate for 24 hours followed by collection of supernatant and cell pellets. In the second treatment group (4 days), hES cells were exposed to 22 μM valproate for 4 days and harvested on day 4. In the third treatment or extended culture (EC, 8 days), hES cells received valproate for 4 days followed by culture in standard hES cell media for an additional four days. Cells and supernatant were harvested on day eight. Each treatment had a parallel control group with a total of six 6-well culture dishes per experiment (two 6-well culture dishes per treatment).


Metabolome analysis was performed as described in Example 1 (Wu and McAllister, 2003, J Mass Spectrom 38:1043-53). Complex mixtures were separated by liquid chromatography (LC) prior to electrospray ionization (ESI) time of flight (TOF) mass spectrometry according to the methods described in this Example and Example 1. Mass Hunter (Agilent) software was applied to deconvolute the data and determine the abundance of each mass. Data were extracted from the entire mass spectrum using the m/z range of 0 to 1500 and the top 2 million most abundant mass peaks from each sample were used for data deconvolution. The minimum signal-to-noise ratio was set to 5. The masses with a minimum relative abundance greater than 0.1% were exported from the Mass Hunter software and used for further analysis.


hESCs treated with 22 μM valproate resulted in 3,241 detected mass signals 42 injections. Of the total of 3,241 mass signals detected in these experiments, 1,963 compounds were measured solely in hES cells and 1,278 compounds were also present in conditioned media; 443 of these were only measured in 1 of 42 injections. 110 compounds (3%) had statistically-significant differences in at least one time point in valproate-treated hESCs compared with control. Fold changes as high as seven- to thirteen-fold were measured after valproate treatment, but these mass signals exhibited high variability across experiments. Representative masses identified following treatment of cells with 1 mM and 22 μM VPA are summarized in Tables 3 and 4, respectively. Several peaks (1,963) were detected in hES cells but not in conditioned media. One of these small molecules was kynurenine, a compound produced by an alternative tryptophan metabolic pathway, activated during pregnancy and immune response. The levels of kynurenine increased by 44% (p value=0.004 at four days, Table 5) following valproate treatment. Kynurenine was detected exclusively in hES cells and absent in conditioned media. The chemical identity of this peak was confirmed by comparative mass spectrometry in the presence of the chemical standard (FIG. 4).


The results of these experiments suggested that kynurenine is a candidate biomarker for neurodevelopmental disorders, in particular those originated by exposure of the human embryo to anti-epileptic drugs such as VPA (Ornoy et al., 2006, Reproductive Toxicol 21:399-409). Strikingly, recent studies have suggested that kynurenine metabolism may be a novel target for the mechanism of action of anti-epileptic drugs (Kocki et al., 2006, Eur J Pharmacol 542:147-51). Cognitive and behavioral disorders are known adverse effects of antiepileptic exposure during pregnancy. Tryptophan is the precursor of serotonin, a key neurotransmitter in the pathogenesis of these and other diseases, such as depression. In addition, increased plasma levels of kynurenine have been linked to postpartum depression (Kohl et al., 2005, J Affect Disord 86:135-42). The alteration in tryptophan metabolism detected herein is a means for examining novel mechanisms in pathogenesis of serotonin-related behavioral disorders such as autism (Chugani, 2004, Ment Retard Dev Disabil Res Rev 10:112-116). An increase in kynurenine levels during development may reduce the bioavailability of tryptophan and consequently serotonin, leading to cognitive dysfunction.


Glutamate and pyroglutamic acid were also elevated in hESCs treated with valproate. Glutamate and pyroglutamic acid were elevated in response to valproate (20% and 27%, respectively), although only pyroglutamic acid exhibited statistically significant changes (p=0.021 at 4 days, FIGS. 3A through 3D). Glutathione (GSH) is metabolized by gamma-glutamyltranspeptidase into glutamate, a neurotransmitter of NMDA receptors, and cysteinylglycine (Cys-Gly). Glutathione (exact neutral mass 612.15) and S-adenosyl-homocysteine (exact neutral mass 384.12) were detected at very low levels in comparison to other mass signals (data not shown). For these experiments for low level detection, small molecules were identified by comparative ESI-TOF-MS with chemical standards that were “spiked” into conditioned media at different concentrations and used to confirm neutral exact masses and retention times of experimental mass signals (FIGS. 3A through 3D). Neutral exact masses and/or empirical chemical formulas generated by ESI-TOF-MS were searched in public databases (including, for example, metlin.scripps.edu., www.nist.gov/srd/chemistry.htm, www.metabolomics.ca) for candidate compounds.


These results suggested that valproate affects the glutamate synthesis pathway in the developing human embryo. The affinity of anti-epileptic drugs towards glutamate targets has been previously suggested (Rogawski and Loscher, 2004, Nat Rev Neurosci 2004 5:553-64). Abnormal levels of glutamate metabolites were measured in maternal serum and amniotic fluid of pregnant women whose infants were diagnosed spina bifida (Groenen et al., 2004, Eur J Obstet Gynecol Reprod Biol.; 112:16-23) with nuclear magnetic resonance (NMR). The levels of glutamine and hydroxyproline were significantly higher in NTDs, and as a result the hESC methods provided herein provide a robust resource to model in vivo alterations of development.


Table 5. Changes in metabolic profiles of four compounds in hES cells treated with valproate versus untreated controls at 24 hours (24 h), 4 days (4 D), and eight days (8 D) after treatment.









TABLE 5







Changes in metabolic profiles of four compounds in


hES cells treated with valproate versus untreated controls


at 24 hours (24 h), 4 days (4 D), and eight days (8 D) after treatment.
















24 h P-

4 D P-

8 D P-





Molecule
value
24 h fold
value
4 D fold
value
8 D fold
Mass
RT





Pyroglutamic
0.242
57%

0.021

27% increase
0.917
 3%
129.0426
19.9


acid

decrease



decrease


Folic acid
0.638
 3%
0.626
 4% increase

0.022

16%
441.1395
32.7




increase



increase


Glutamate
0.969
 1%
0.108
24% increase
0.651
10%
147.0535
20.0




increase



increase


Kynurenine
0.087
29%

0.004

44% increase
N.D.
N.D.
208.0850
25.9




increase





RT = retention time


Fold changes are represented as percent difference of the least squared means of valproate treated and untreated hES cells. p-values were determined by ANOVA. The mass is the average neutral mass detected by ESI-TOF-MS and the RT is the average retention time the molecule eluted at. P-values less than 0.05 are in bold.






Example 4
Kynurenine: Biomarker for Diagnosis and Treatment of Developmental Toxicity and CNS Disorders

Kynurenine was shown in Example 3 to be detected in valproate-treated hES cells. Kynurenine (along with glutamate and pyroglutamic acid) was differentially produced in valproate-treated human embryonic stem cells (hES) versus controls. Kynurenine is a novel biomarker useful for the identification of neurodevelopmental disorders in infants and in vitro developmental toxicity of chemicals. This example describes the identification of biomarkers for neurodevelopmental disorders, including cellular products differentially produced in teratogen-treated hESCs.


The amino acid tryptophan (TRP) is a precursor of the neurotransmitter serotonin, a key mediator of numerous CNS disorders, such as depression, neurodegeneration and cognitive impairment. Tryptophan catabolism into kynurenic acid is an alternative route for tryptophan metabolism (FIG. 5), that is activated in specific circumstances such as inflammatory response or pregnancy. Up-regulation of the kynurenine pathway is correlated with psychosis in adult diseases such as schizophrenia and bipolar disorder, an indication that increased levels of pathway intermediates may trigger psychotic features (Miller et al., 2006, Brain Res 16:25-37). Significantly, metabolism using the kynurenine pathway is accompanied by decreased tryptophan metabolism using the serotonin pathway (in the absence of exogenous tryptophan, an essential amino acid not synthesized by mammals including man). An increase in kynurenine levels during development can reduce the bioavailability of tryptophan and consequently serotonin, leading to cognitive dysfunction.


In addition, kynurenic acid (KYNA), one of the end products of this tryptophan metabolic pathway, is an antagonist of glutamate neurotransmission and N-methyl-D-aspartate (NMDA) receptors. Recent studies have demonstrated that kynurenic acid is a druggable target via its role in the activation of the previously orphan GPCR receptor GPR35 (Wang et al., 2006, J Biol Chem 281:22021-8). Quinolinic acid (QUIN), another end product of the pathway (FIG. 5), and 3-hydroxy-kynurenine, an intermediate, act as neurotoxicants (Guillemin et al., 2005, J Neuroinflammation 26:16; Chiarugui et al., 2001, J Neurochem 77:1310-8). QUIN is involved in the pathogenesis of Alzheimer's disease where its neurotoxicity may be involved in increased inflammation and in convulsions by interacting with the N-methyl-D-aspartate (NMDA) receptor complex, a type of glutamate receptor (Guillemin et al., 2002, J Neuroinflammation 26:16; Nemeth et al., 2005, Curr Neurovasc Res 2:249-60). Kynurenin (KYN), another pathway intermediate, is synthesized in the brain and is transported across the blood-brain barrier (Nemeth et al., 2005, Curr Neurovasc Res 2:249-60). KYN is metabolized to the neurotoxic quinolinic acid (QUIN) and the neuroprotective kynurenic acid (KYNA) (FIG. 5). Increased serum levels of KYN have been correlated to clinical manifestation of depression with different etiologies, such as post-partum disorder (Kohl et al., 2005, J Affect Disord 86:135-42) and interferon-alpha treatment (Capuron et al., 2003, Biol Psychiatry 54:906-14).


Exposure of hES cells to valproate, a disruptor of human development, induced significant changes in different metabolic pathways, including the production of kynurenine (exact neutral mass 208.08), which was significantly upregulated in response to valproate as detected by liquid chromatography electrospray ionization time of flight mass spectrometry (LC/ESI-TOF-MS) as described in Example 4. Additionally, novel chemical entities, having exact neutral masses of 328.058, 336.163, 343.080, were detected and are not yet catalogued in public databases.


When neural precursors derived from hESCs were exposed to 1 mM valproate, a marked decrease in both serotonin (176.0946) and indoleacetaldehyde (159.0689), a downstream sub-product of serotonin generated by monoaminoxoidase activity (MAO) was observed (Table 6). Glutamate and pyroglutamic acid or hydroxyproline (p=0.021) were also elevated in hES cells treated with valproate. These results suggest that valproate affects the glutamate synthesis pathway in the developing human embryo. This finding emulates in vivo neurophysiology, where compounds from the kynurenine pathway modulate activity at NMDA glutamate receptors and produce epileptic phenotypes, including seizures (Perkins and Stone, 1982, Brain Res 247:184-187.).


As a consequence of the identification of kynurenine herein, chemical inhibitors of kynurenine synthesis can be used as novel therapeutics in mood disorders; for example, small molecules that antagonize indoleamine 2,3-dioxygenase (IDO) or kynurenine formylase activities, which converts tryptophan (TRP) into kynurenine (KYN). Inhibition of TRP catabolism to KYN can be used to ameliorate disease symptoms in cognitive and neurodegenerative disorders by increasing serotonin levels, via elevated synthesis of this neurotransmitter or reduced depletion through the kynurenine pathway.


Collectively, the metabolite changes detected in hES cells in response to valproate converge functionally towards folate, kynurenine and glutamate pathways. FIG. 6 illustrates the hierarchical clustering of the fold change differences from 22,573 unique masses. Changes in the above-mentioned pathways were consistent and reproducible in multiple independent studies of 1 mM VPA treated hESCs, and neural precursors produced from hESCs (FIG. 6).


Example 5
Gene Expression Analysis of Kynurenine Pathway

The efficacy of the analysis in Example 4 was confirmed by gene expression studies, wherein changes in gene expression were observed following VPA treatment of hESC. Valproate treatment of human embryonic stem cells induced a marked upregulation in the small molecule kynurenine, an intermediate metabolite in the catabolism of tryptophan. Tryptophan is the precursor of the neurotransmitter serotonin (5HT). Thus, whether expression of enzymes in the metabolism of tryptophan to kynurenine and its opposite route, serotonin synthesis, was altered in human embryonic stem cells was investigated to examine the mechanistic properties of the kynurenine pathway and its response to valproate.


Human embryonic stem cells treated with 1 mM valproate and untreated controls were harvested at four days after treatment and stored at −80° C. prior to RNA isolation using RNeasy (Qiagen). 5 μg of RNA templates were reverse transcribed and amplified (QIAGEN OneStep RT-PCR) according to the manufacturer's instructions using primers designed for transcribed human sequences of the following genes: INDO, indoleamine 2,3 dioxygenase, TDO or TDO2, tryptophan 2,3-dioxygenase, AFMID, arylformamidase, TPH1, tryptophan hydroxylase the rate-limiting enzyme in serotonin biosynthesis, AADAT, aminoadipate aminotransferase, KYNU, kynunreninase, KMO, kynurenine 3-monooxygenase, GAPDH, glyceraldehyde 3-phosphate dehydrogenase.


The results of this study showed that the majority of enzymes in the kynurenine pathway and serotonin synthesis were expressed in hES cells at four days after treatment of hES cells with 1 mM valproate (FIG. 7). Indoleamine 2,3 dioxygenase INDO, catabolizes tryptophan into the kynurenine pathway, and produces kynurenine as an end product. The expression of tryptophan 2,3 dioxygenase (TDO or TDO2) was also examined. TDO2, like INDO, catalyzes the first step in the kynurenine pathway. These data suggested that TDO2 expression was upregulated in hES cells treated with valproate in comparison to untreated controls. The rate limiting enzyme in 5HT synthesis, TPH1, was also expressed in hES cells (FIG. 7). Expression of these enzymes supported the conclusion that hES cells recapitulate metabolic pathways of tryptophan catabolism and serotonin synthesis. Interestingly, VPA induced pronounced expression of rate-limiting enzymes in this pathway.


Example 6
Developmental Toxicology Screening for Prenatal Alcohol Exposure

To identify differentially secreted metabolites in response to alcohol, as well as the pathways involved in fetal alcohol syndrome, human embryonic stem cells were treated with 0, 0.1 and 0.3% ethanol for four days followed by LC/ESI-TOF mass spectrometry according to the general methods described above for valproate in Example 1. Extracellular media was collected and processed at 24 hours and four days after treatment, and 49,481 mass signals were detected following three technical replications. Of the 49,481 mass signals, 1,860 compounds were significantly different (p<0.05) in at least one treatment and had a significant time change (<1 or >1). (Table 7). Binned masses were annotated in silico by querying the neutral masses in several different databases. These databases included Metlin, Biological Magnetic Resonance Data Bank (BMRB), NIST Chemistry WebBook, and the Human Metabolome Database. A mass was considered identified when its neutral mass was within 10 ppm of a known compound annotated in one of the databases listed above.


The putative kynurenine compound (measured exact neutral mass 208.0816) was upregulated three-fold at day four, but not 24 hours, in both treatments (0.1%, p=0.001 and 0.3% p=0.002, respectively). Another putative metabolite in the kynurenine pathway, 8-methoxykynurenate (219.0532) was also upregulated at four days in response to both 0.1% and 0.3% alcohol treatment (p<0.05). The analysis also detected a significant downregulation of 5-hydroxy-L-tryptophan (220.0848) at four days following 0.3% alcohol treatment (p<0.05) in comparison to untreated controls. 5-hydroxy-L-tryptophan is the only intermediate metabolite between tryptophan and serotonin and its synthesis is mediated by tryptophan hydroxylase, the rate limiting enzyme in serotonin synthesis. These results suggest that alcohol exposure during human development can affect serotonin bioavailability due to upregulation of tryptophan catabolism into kynurenines. In addition, alcohol exposure induced significant changes in metabolic pathways and small molecules involved in neural development such as glutamate, gabapentin, adrenaline and glutathione.


Example 7
Developmental Toxicology Screening of Neuronal Precursor Cells

Metabolomic assessment of teratogens on embryonic development is not limited exclusively to hESCs. The methods of the invention are also useful with other progenitor stem cells, including lineage-restricted stem cells such as neural precursor cells. To illustrate the efficacy of toxicology screening on lineage-specific stem cells, neuronal precursors derived from hESCs were treated with 1 mM valproate according to the methods described in Example 1.


Approximately 135 compounds were differentially secreted in VPA-treated neuronal precursors versus control. (See Table 6). The results of this study illustrated that the methods of the invention reveal alterations in the metabolic profile of lineage-specific stem cells in response to teratogen exposure.


The results disclosed herein are set forth in the following tables









TABLE 3







Cellular metabolites measured in human embryonic stem cells treated with 1 mM of valproate















EXP
RT
roundMASS
time
trt
Fold
Probt
annotation.1
annotation.2


















1 mM
8.31910526
103.056358
4 D
1 mM
1.987286671
0.01734377
gamma-Aminobutryic acid



VPA



VPA


1 mM
6.78779869
103.098349
4 D
1 mM
2.143101233
0.00047552
2-Aminoisobutyric acid


VPA



VPA


1 mM
8.39854546
113.082093
4 D
1 mM
16.4054129
0.01342684
1-Pyrroline-5-carboxylic acid


VPA



VPA


1 mM
11.7534444
120.043328
4 D
1 mM
1.355758298
0.03951319
3,4-Dihydroxybutyric acid


VPA



VPA


1 mM
85.7330833
121.088708
24 H
1 mM
10.30519572
0.02442001
Phenylethylamine


VPA



VPA


1 mM
7.307128
122.071261
4 D
1 mM
−2.2989897
0.01870947
Unknown


VPA



VPA


1 mM
38.1047857
129.070626
8 D
1 mM
3.023878137
0.03988213
2-Ketobutyric acid; 2-


VPA



VPA


Oxobutyric acid;









alpha-Ketobutyric acid; alpha-









Ketobutyrate


1 mM
14.2761702
136.038753
8 D
1 mM
2.696709281
0.00083818
Hypoxanthine
Allopurinol


VPA



VPA


1 mM
31.3610896
141.114252
8 D
1 mM
1.865419366
0.02273706
Unknown


VPA



VPA


1 mM
43.9201842
143.095482
8 D
1 mM
2.064797071
0.03120757
1-


VPA



VPA


Aminocyclohexanecarboxylic









acid


1 mM
51.283453
144.113677
24 H
1 mM
4.820891632
0.02775836
Caprylic acid
Valproic acid


VPA



VPA


1 mM
51.283453
144.113677
4 D
1 mM
8.26720694
0.0011089
Caprylic acid
Valproic acid


VPA



VPA


1 mM
16.307931
147.068314
4 D
1 mM
−2.05380612
0.03872229
3-Methyloxindole


VPA



VPA


1 mM
16.307931
147.068314
24 H
1 mM
−1.80875876
0.037812
3-Methyloxindole


VPA



VPA


1 mM
22.5095926
153.079352
4 D
1 mM
−2.65737163
0.01268393
Dopamine


VPA



VPA


1 mM
5.36288806
155.068364
8 D
1 mM
−1.34957018
0.0476914
L-Histidine


VPA



VPA


1 mM
20.6395854
155.072941
4 D
1 mM
3.82298622
0.00676609
L-Histidine


VPA



VPA


1 mM
14.2071091
160.060653
8 D
1 mM
12.348809
1.23E-06
Unknown


VPA



VPA


1 mM
14.3670392
161.081539
8 D
1 mM
4.777314979
0.0001252
Unknown


VPA



VPA


1 mM
44.8165285
162.067353
4 D
1 mM
1.640573238
0.01289447
Unknown


VPA



VPA


1 mM
31.5154611
162.124096
24 H
1 mM
1.911228139
0.01933211
Unknown


VPA



VPA


1 mM
31.3624074
165.079533
8 D
1 mM
1.705269784
0.00206584
4-(3-Pyridyl)-butanoic acid


VPA



VPA


1 mM
32.0426154
167.094942
8 D
1 mM
−2.20640862
0.01874726
Methyldopamine


VPA



VPA


1 mM
20.0098065
173.083484
4 D
1 mM
5.458861144
0.00198632
2-Oxoarginine


VPA



VPA


1 mM
15.3496532
177.082617
8 D
1 mM
2.397781171
0.01291216
Unknown


VPA



VPA


1 mM
24.1314286
179.094351
4 D
1 mM
1.851635336
0.03464009
Salsolinol
Homophenylalanine


VPA



VPA


1 mM
21.8046482
187.064183
8 D
1 mM
2.839427352
0.00590774
Unknown


VPA



VPA


1 mM
21.8046482
187.064183
4 D
1 mM
3.356831218
1.24E-05
Unknown


VPA



VPA


1 mM
23.317
187.08492
4 D
1 mM
3.781608467
0.03987705
6-Acetamido-3-


VPA



VPA


oxohexanoate


1 mM
27.7865556
189.042631
8 D
1 mM
2.865724657
0.02214848
Kynurenic acid


VPA



VPA


1 mM
61.5462473
196.090684
4 D
1 mM
3.519815968
0.01102697
Unknown


VPA



VPA


1 mM
24.0551398
197.105003
4 D
1 mM
2.231478645
0.00076838
L-Metanephrine


VPA



VPA


1 mM
20.0989286
197.175657
8 D
1 mM
4.237754463
0.00034728
Unknown


VPA



VPA


1 mM
73.9582188
198.16015
4 D
1 mM
2.039619449
0.01232495
5-Dodecenoic acid


VPA



VPA


1 mM
29.2935714
201.100569
4 D
1 mM
5.966976107
0.00328699
Unknown


VPA



VPA


1 mM
28.6036393
203.115212
8 D
1 mM
1.872544495
0.00040874
L-Glutamic acid n-butyl ester
Acetylcarnitine


VPA



VPA


1 mM
9.07926923
209.06985
8 D
1 mM
−12.4054314
0.01848957
4-Carboxyphenylglycine


VPA



VPA


1 mM
48.3434453
213.079468
8 D
1 mM
2.512458907
0.02116099
Unknown


VPA



VPA


1 mM
44.6001887
214.064259
4 D
1 mM
1.446032522
0.02767084
Unknown


VPA



VPA


1 mM
44.6001887
214.064259
8 D
1 mM
1.783609761
0.00082206
Unknown


VPA



VPA


1 mM
69.6687917
214.064356
24 H
1 mM
1.316493137
0.0171064
Unknown


VPA



VPA


1 mM
18.7504371
216.094569
4 D
1 mM
2.349086763
0.01043169
Unknown


VPA



VPA


1 mM
30.5773235
216.100485
4 D
1 mM
2.050108123
0.04358571
Unknown


VPA



VPA


1 mM
6.39474737
218.076897
4 D
1 mM
1.737243521
0.02003307
Unknown


VPA



VPA


1 mM
6.68071429
219.144891
24 H
1 mM
−1.58008262
0.02066251
Unknown


VPA



VPA


1 mM
10.5609423
220.085746
4 D
1 mM
−2.39827983
1.63E−06
5-Hydroxytryptophan


VPA



VPA


1 mM
53.8814512
222.078039
4 D
1 mM
2.882259036
0.02550855
Unknown


VPA



VPA


1 mM
73.0997018
223.049411
8 D
1 mM
−4.31392173
0.04819747
7,8-Dihydro-7,8-


VPA



VPA


dihydroxykynurenate


1 mM
6.45641791
229.095757
8 D
1 mM
2.4471457
0.00094873
Malonylcarnitine


VPA



VPA


1 mM
23.7927189
229.095855
4 D
1 mM
2.057653416
0.00038761
Malonylcarnitine


VPA



VPA


1 mM
55.5371429
229.145042
4 D
1 mM
2.032140286
0.00236036
Unknown


VPA



VPA


1 mM
19.9783175
229.164555
8 D
1 mM
3.779774064
1.34E−08
Unknown


VPA



VPA


1 mM
32.6065714
229.201979
4 D
1 mM
3.088058322
0.00439209
Unknown


VPA



VPA


1 mM
9.79255
230.080163
4 D
1 mM
−1.383766
0.02197836
Unknown


VPA



VPA


1 mM
7.80846914
233.123128
8 D
1 mM
6.784300156
0.00043647
Unknown


VPA



VPA


1 mM
14.3537949
236.080213
4 D
1 mM
−3.35334287
0.00032832
N′-Formylkynurenine


VPA



VPA


1 mM
45.2867439
238.12327
8 D
1 mM
3.718961983
0.01466842
2-Amino-3-methylbutyric


VPA



VPA


acid


1 mM
12.1171264
244.109135
4 D
1 mM
1.659329044
0.01962434
Unknown


VPA



VPA


1 mM
12.127642
245.119507
4 D
1 mM
2.061936638
0.02383097
Unknown


VPA



VPA


1 mM
19.8036863
246.100428
4 D
1 mM
4.924577653
0.02636633
N-Acetyl-D-tryptophan


VPA



VPA


1 mM
8.947
247.140975
8 D
1 mM
2.877468231
0.01777412
Unknown


VPA



VPA


1 mM
19.7590488
247.173942
8 D
1 mM
3.071620539
3.15E−06
Unknown


VPA



VPA


1 mM
48.7837308
248.191881
4 D
1 mM
2.692786782
0.00724013
Unknown


VPA



VPA


1 mM
8.00665714
249.119037
4 D
1 mM
1.948008537
0.01865508
Unknown


VPA



VPA


1 mM
53.1723271
256.1093
8 D
1 mM
3.068428571
0.00024804
D-2-Amino-3-hydroxybutyric
gamma-Amino-


VPA



VPA


acid
beta-hydroxybutyric










acid


1 mM
23.22678
257.099256
8 D
1 mM
2.601240877
0.00033049
5-Methylcytidine


VPA



VPA


1 mM
5.57045
257.891738
24 H
1 mM
−1.17015529
0.01640996
Unknown


VPA



VPA


1 mM
7.08067539
258.019715
24 H
1 mM
1.315125063
0.02206679
Unknown


VPA



VPA


1 mM
22.8759189
258.121153
4 D
1 mM
1.510263204
0.01588551
Unknown


VPA



VPA


1 mM
28.8676889
258.133722
24 H
1 mM
5.578974665
0.03000729
Unknown


VPA



VPA


1 mM
47.6525584
258.133727
4 D
1 mM
−1.91733177
0.01442461
Unknown


VPA



VPA


1 mM
18.7499759
259.11867
4 D
1 mM
1.504620863
0.02037249
N-(gamma-L-


VPA



VPA


Glutamyl)amino-D-proline


1 mM
13.2221957
260.083648
8 D
1 mM
2.984522231
0.02760558
Unknown


VPA



VPA


1 mM
22.373
264.109282
4 D
1 mM
−1.74811488
0.01791457
Acetyl-N-formyl-5-


VPA



VPA


methoxykynurenamine


1 mM
58.8093824
265.132541
8 D
1 mM
2.363623094
0.03359569
(2R,3S)-rel-2,3-dihydroxy--


VPA



VPA


Butanoic acid


1 mM
27.779593
271.112691
4 D
1 mM
1.685060044
0.03867385
Unknown


VPA



VPA


1 mM
24.7259575
272.124009
4 D
1 mM
2.036511555
0.02960407
Unknown


VPA



VPA


1 mM
44.0582051
272.168272
8 D
1 mM
2.056227653
0.00325332
Unknown


VPA



VPA


1 mM
41.65612
272.211662
8 D
1 mM
−5.12943527
0.00643051
3-Oxo-delta1-steroid


VPA



VPA


1 mM
39.378469
273.105953
4 D
1 mM
2.674742484
0.00030929
Unknown


VPA



VPA


1 mM
8.93373171
276.136639
4 D
1 mM
5.215118375
0.0006752
Unknown


VPA



VPA


1 mM
67.6599775
280.237772
24 H
1 mM
2.086232575
0.04410145
Linoleic acid
Octadecadienoic


VPA



VPA



acid


1 mM
14.2211017
281.125398
8 D
1 mM
8.170361997
1.56E−06
1-Methyladenosine


VPA



VPA


1 mM
71.5568571
282.225649
4 D
1 mM
4.282045127
0.00101203
Unknown


VPA



VPA


1 mM
72.7757434
282.253397
8 D
1 mM
−1.86257691
0.03054583
Oleic acid
Elaidic acid


VPA



VPA


1 mM
59.4208378
284.19613
4 D
1 mM
5.253576839
0.0351483
Unknown


VPA



VPA


1 mM
5.70108824
284.980449
4 D
1 mM
1.366608495
0.03819988
Unknown


VPA



VPA


1 mM
6.9018125
285.140063
4 D
1 mM
15.96344365
0.00293691
Unknown


VPA



VPA


1 mM
64.3362162
286.186749
4 D
1 mM
2.524154118
0.04701735
N-Acetyl-leucyl-leucine


VPA



VPA


1 mM
64.3362162
286.186749
24 H
1 mM
2.577549261
0.00532464
N-Acetyl-leucyl-leucine


VPA



VPA


1 mM
75.3938769
288.263273
4 D
1 mM
2.556553115
0.0003234
Unknown


VPA



VPA


1 mM
26.6263806
289.137569
8 D
1 mM
7.105814367
0.00077408
Unknown


VPA



VPA


1 mM
15.0419293
289.139413
8 D
1 mM
3.953690666
0.00671585
Unknown


VPA



VPA


1 mM
15.8950204
295.128678
8 D
1 mM
2.286752138
1.23E−06
N6,N6-Dimethyladenosine


VPA



VPA


1 mM
6.02850649
301.172858
4 D
1 mM
5.302600282
0.00165331
Unknown


VPA



VPA


1 mM
59.5394364
301.222733
4 D
1 mM
4.091131755
0.01328711
Unknown


VPA



VPA


1 mM
72.4551579
304.237816
8 D
1 mM
−5.09223853
0.00158305
Arachidonic acid


VPA



VPA


1 mM
44.6849231
305.936181
8 D
1 mM
2.13864941
0.00372138
3-Iodo-4-


VPA



VPA


hydroxyphenylpyruvate


1 mM
7.93489796
306.092269
24 H
1 mM
−2.59907813
0.00116532
Unknown


VPA



VPA


1 mM
22.339
306.121765
24 H
1 mM
2.666042908
0.00540921
Z-Gly-Pro; Z-Gly-Pro-OH


VPA



VPA


1 mM
59.461
306.180711
4 D
1 mM
2.390810858
0.01473431


VPA



VPA


1 mM
12.9788342
307.161748
8 D
1 mM
5.76411852
0.00135244
Unknown


VPA



VPA


1 mM
4.76167568
308.158497
8 D
1 mM
3.212062578
7.02E−05
Unknown


VPA



VPA


1 mM
7.58973529
316.131974
4 D
1 mM
1.861931503
0.01887819
Unknown


VPA



VPA


1 mM
66.9950694
316.200989
4 D
1 mM
2.178145003
0.00392399
Gibberellin A12 aldehyde


VPA



VPA


1 mM
62.665
319.244008
24 H
1 mM
3.088914632
0.0457215
Unknown


VPA



VPA


1 mM
19.019754
320.137541
4 D
1 mM
2.083198045
0.04299189
Unknown


VPA



VPA


1 mM
67.8541343
320.230187
4 D
1 mM
1.784846494
0.03271491
Unknown


VPA



VPA


1 mM
67.8541343
320.230187
24 H
1 mM
1.981647012
0.01061379
Unknown


VPA



VPA


1 mM
10.672
321.168775
24 H
1 mM
2.153375627
0.00361195
Unknown


VPA



VPA


1 mM
35.4656491
324.169472
4 D
1 mM
2.684214566
0.00585101
Unknown


VPA



VPA


1 mM
63.932859
326.0008
24 H
1 mM
1.479797739
0.00340947
Unknown


VPA



VPA


1 mM
63.932859
326.0008
4 D
1 mM
1.541142217
0.01010729
Unknown


VPA



VPA


1 mM
62.4897344
328.242558
4 D
1 mM
1.831213495
0.03531113
Docosahexaenoic acid


VPA



VPA


1 mM
55.092
329.001202
24 H
1 mM
1.889887032
0.01315641
Unknown


VPA



VPA


1 mM
6.02840404
330.105879
8 D
1 mM
4.856779538
0.01414085
Unknown


VPA



VPA


1 mM
12.8257065
330.153322
4 D
1 mM
−1.46094311
0.02278769
Unknown


VPA



VPA


1 mM
47.63185
330.240548
4 D
1 mM
2.777910272
0.01585359
Unknown


VPA



VPA


1 mM
67.7267647
330.242694
4 D
1 mM
3.168939244
0.02399703
Unknown


VPA



VPA


1 mM
9.01253333
331.103633
8 D
1 mM
5.010657754
0.00879812
Unknown


VPA



VPA


1 mM
18.8430244
334.151446
24 H
1 mM
7.598422851
0.04853637
Unknown


VPA



VPA


1 mM
4.05694118
336.031706
4 D
1 mM
−23.1557728
5.36E−05
Unknown


VPA



VPA


1 mM
6.7701658
336.15353
4 D
1 mM
2.062222503
0.01789166
Unknown


VPA



VPA


1 mM
54.915974
347.982073
4 D
1 mM
16.74896451
0.02976287
Unknown


VPA



VPA


1 mM
45.6079091
348.203076
4 D
1 mM
3.375263185
0.00190076
Unknown


VPA



VPA


1 mM
6.04629167
349.134979
8 D
1 mM
1.449645356
0.02177991
Unknown


VPA



VPA


1 mM
67.3780816
352.221576
24 H
1 mM
2.329951622
0.01190993
Prostaglandin


VPA



VPA


1 mM
22.8247245
353.157641
4 D
1 mM
3.01822425
0.00974537
2-Keto-3-Methylvaleric acid


VPA



VPA


1 mM
19.103773
353.158931
4 D
1 mM
2.134354771
0.00286811
Unknown


VPA



VPA


1 mM
29.94892
355.242828
4 D
1 mM
3.751584361
0.01212028
Unknown


VPA



VPA


1 mM
15.1070313
356.156972
4 D
1 mM
5.181249294
0.00024122
I-Glutamic-gamma-


VPA



VPA


semialdehyde


1 mM
59.1895507
358.229755
4 D
1 mM
4.389936283
0.00450968
Unknown


VPA



VPA


1 mM
7.78296
359.071286
8 D
1 mM
3.504721971
0.02819084
Unknown


VPA



VPA


1 mM
27.8286847
359.198793
4 D
1 mM
2.67566964
0.04513681
Unknown


VPA



VPA


1 mM
7.67294845
362.15214
24 H
1 mM
3.677690313
0.01613594
Aminohexanoic acid


VPA



VPA


1 mM
6.16412
364.18324
4 D
1 mM
4.422922613
0.01590116
Unknown


VPA



VPA


1 mM
19.3098372
364.185514
8 D
1 mM
2.529233091
0.00135633
Gibberellin A44


VPA



VPA


1 mM
53.9854054
366.239292
4 D
1 mM
6.176116644
3.03E−05
3b-Allotetrahydrocortisol


1 mM
17.7238836
372.188649
4 D
1 mM
3.32395304
2.43E−07
Ornithine


VPA



VPA


1 mM
11.4481111
374.168865
8 D
1 mM
3.707636994
0.00715743
Unknown


VPA



VPA


1 mM
13.8172619
374.207426
8 D
1 mM
2.50185816
0.03397986
Unknown


VPA



VPA


1 mM
17.6750468
388.183189
8 D
1 mM
3.124878291
0.00060074
Malic acid
Diglycolic acid


VPA



VPA


1 mM
21.3150329
392.209899
4 D
1 mM
2.402938958
0.02146723
Unknown


VPA



VPA


1 mM
79.7277263
404.258123
4 D
1 mM
2.231633324
0.02122436
7a,12a-Dihydroxy-3-oxo-4-


VPA



VPA


cholenoic acid


1 mM
24.7042427
407.206755
4 D
1 mM
2.564362115
0.03457095
Unknown


VPA



VPA


1 mM
16.9907536
408.172332
8 D
1 mM
1.47549599
0.01779219
4-


VPA



VPA


Hydroxyphenylacetaldehyde;


1 mM
16.9907536
408.172332
4 D
1 mM
1.84894204
0.00218606
4-


VPA



VPA


Hydroxyphenylacetaldehyde;


1 mM
29.02944
411.227331
4 D
1 mM
3.412904392
0.00663705
Gln His Lys


VPA



VPA


1 mM
31.0764706
411.788303
4 D
1 mM
4.812211329
0.01959219
Unknown


VPA



VPA


1 mM
9.74277941
412.191819
8 D
1 mM
4.778970957
0.02280244
Unknown


VPA



VPA


1 mM
24.0870602
416.213608
8 D
1 mM
1.904483779
0.00013882
Unknown


VPA



VPA


1 mM
13.7165
420.160178
4 D
1 mM
4.500233939
0.04166145
Unknown


VPA



VPA


1 mM
27.4410904
421.219685
4 D
1 mM
2.92999865
0.01453378
Unknown


VPA



VPA


1 mM
84.9993429
424.278966
4 D
1 mM
2.302178983
0.02079967
1b,3a,7a,12a-Tetrahydroxy-


VPA



VPA


5b-cholanoic acid


1 mM
84.9993429
424.278966
24 H
1 mM
2.318995467
0.00016902
1b,3a,7a,12a-Tetrahydroxy-


VPA



VPA


5b-cholanoic acid


1 mM
54.5975206
429.099036
4 D
1 mM
3.524698852
2.05E−05
Unknown


VPA



VPA


1 mM
25.5684706
430.183077
4 D
1 mM
1.148698355
0.00012401
Unknown


VPA



VPA


1 mM
47.39725
432.071275
4 D
1 mM
2.645059178
0.01175067
Unknown


VPA



VPA


1 mM
14.5288987
445.217914
8 D
1 mM
2.820595921
0.00824753
Unknown


VPA



VPA


1 mM
7.5585
445.286693
4 D
1 mM
−1.13705339
0.04453994
Unknown


VPA



VPA


1 mM
19.9357624
455.226453
8 D
1 mM
2.768491323
0.0146344
Adipate


VPA



VPA


1 mM
84.7522195
470.350048
4 D
1 mM
3.767741534
0.00027941
Unknown


VPA



VPA


1 mM
8.479
471.146232
24 H
1 mM
2.569343893
0.02598742
10-Formyldihydrofolate


VPA



VPA


1 mM
22.7650396
471.202698
4 D
1 mM
2.257302866
1.30E−06
Unknown


VPA



VPA


1 mM
15.4262845
491.253192
8 D
1 mM
4.916392167
0.00321994
Unknown


VPA



VPA


1 mM
60.5202059
493.458959
4 D
1 mM
2.789487333
0.00131052
Unknown


VPA



VPA


1 mM
44.8878444
502.216027
4 D
1 mM
1.922921676
0.00968802
Unknown


VPA



VPA


1 mM
14.5675854
502.227438
8 D
1 mM
3.101787817
0.00862582
Unknown


VPA



VPA


1 mM
31.0262667
504.2848
4 D
1 mM
5.119489655
7.48E−05
Unknown


VPA



VPA


1 mM
17.4495833
516.244788
4 D
1 mM
2.722628233
0.00035163
Unknown


VPA



VPA


1 mM
44.14925
527.321492
8 D
1 mM
2.213454933
0.00740287
Unknown


VPA



VPA


1 mM
70.8363171
528.362659
4 D
1 mM
2.941801698
0.03554601
Unknown


VPA



VPA


1 mM
74.25245
530.344375
24 H
1 mM
3.680750602
0.03848341
Unknown


VPA



VPA


1 mM
9.15167857
532.249475
8 D
1 mM
7.170133597
0.00736475
Unknown


VPA



VPA


1 mM
29.9863488
535.254098
8 D
1 mM
6.049014001
0.00097203
Unknown


VPA



VPA


1 mM
87.9394
535.392963
4 D
1 mM
1.80125196
0.03183737
Unknown


VPA



VPA


1 mM
8.02928261
549.20135
8 D
1 mM
11.08087574
0.00035145
Unknown


VPA



VPA


1 mM
19.5000458
550.228302
4 D
1 mM
2.35969435
0.00064579
Unknown


VPA



VPA


1 mM
24.7983934
551.248871
24 H
1 mM
1.396388132
0.01890342
Unknown


VPA



VPA


1 mM
74.3730889
552.326244
24 H
1 mM
1.885569072
0.031072
Lithocholate 3-O-glucuronide


VPA



VPA


1 mM
75.3072222
561.322428
4 D
1 mM
5.181249294
0.00798648
Unknown


VPA



VPA


1 mM
14.1881491
565.230107
4 D
1 mM
2.651300141
0.04312251
Unknown


VPA



VPA


1 mM
5.97658065
574.262774
8 D
1 mM
2.982867719
0.00682514
Unknown


VPA



VPA


1 mM
70.4439429
594.37144
4 D
1 mM
2.591881931
0.04970674
2-Hydroxyadenine


VPA



VPA


1 mM
15.895551
598.283549
8 D
1 mM
4.074717385
0.00446383
2-Hydroxyadenine


VPA



VPA


1 mM
76.5242159
599.574322
8 D
1 mM
2.569165805
2.63E−05
Unknown


VPA



VPA


1 mM
76.2647
600.576755
4 D
1 mM
1.998614186
0.00464652
Unknown


VPA



VPA


1 mM
76.2647
600.576755
8 D
1 mM
2.690920931
0.00059418
Unknown


VPA



VPA


1 mM
79.7894576
613.589997
8 D
1 mM
3.099853425
0.01314731
Unknown


VPA



VPA


1 mM
8.59329167
658.254492
8 D
1 mM
13.32441233
0.02367066
Unknown


VPA



VPA


1 mM
60.8503
688.51026
4 D
1 mM
3.690969971
0.00301918
Unknown


VPA



VPA


1 mM
69.7080715
690.409258
4 D
1 mM
3.89061979
0.001728
Unknown


VPA



VPA


1 mM
65.32996
738.583348
4 D
1 mM
3.877159268
0.00021681
Unknown


VPA



VPA


1 mM
69.7792917
810.640892
4 D
1 mM
3.934008296
0.00141534
Unknown


VPA



VPA


1 mM
21.6729286
921.002586
24 H
1 mM
10.91318268
0.00761215
Unknown


VPA



VPA


1 mM
5.86856
1007.84992
4 D
1 mM
23.49041018
0.04324009
3-Dehydrocarnitine


VPA



VPA
















TABLE 4







Cellular metabolites produced in hESCs treated with 22 μM valproate















cpdID
RT
MASSavg
time
_trt
Fold
P-value
Compound 1
Compound2



















77
28.21
99.0681
4
days
VPA
−1.81

0.020

N-Methyl-2-pyrrolidinone



103
12.00
103.0991
4
days
VPA
−2.24

0.028

Gamma-Aminobutryic acid
2-Aminoisobutyric acid


141
34.03
113.0840
4
days
VPA
−1.43

0.013

Unknown


189
12.08
119.0473
8
days
VPA
1.22

0.040

4-Amino-3-hydroxybutanoate


210
96.44
120.0436
4
days
VPA
−4.22

0.006

3,4-Dihydroxybutyric acid


263
19.93
129.0426
4
days
VPA
−1.27

0.021

Pyroglutamic acid
1-Pyrroline-4-hydroxy-2-











carboxylate


323
29.83
134.0939
4
days
VPA
−1.43

0.034

Unknown


329
16.96
136.0384
24
hours
VPA
−2.09

0.038

Hypoxanthine
Allopurinol


343
12.98
141.0412
4
days
VPA
−1.24

0.011

1,4,4,6-Tetrahydro-6-
2-Aminomuconate










oxonicotinate
semialdehyde


362
11.40
141.9381
4
days
VPA
1.19

0.034

Unknown


396
11.97
146.0683
4
days
VPA
−1.02

0.002

Glutamine


413
44.84
148.0638
8
days
VPA
−2.72

0.004

Unknown


444
12.37
144.0687
8
days
VPA
−1.42

0.014

Unknown


449
20.19
146.0066
8
days
VPA
−1.24

0.002

2,4-dicarboxylic acid


496
30.40
161.0688
8
days
VPA
−1.23

0.019

4-Methyl-L-glutamate
2,2′-Iminodipropanoate


431
24.83
164.4009
4
days
VPA
−1.17

0.049

Unknown


603
72.83
173.9844
8
days
VPA
−1.80

0.017

Unknown


604
20.34
174.0160
4
days
VPA
−1.36

0.003

cis-Aconitate
Dehydroascorbate


636
42.18
178.0994
8
days
VPA
1.47
0.002
Phenylvaleric acid


646
24.00
181.0740
4
days
VPA
−1.11

0.004

Salsolinol
Homophenylalanine


671
24.90
187.0609
4
days
VPA
−1.40

0.018

Unknown


674
36.08
187.0973
4
days
VPA
2.14

0.042

Unknown


812
29.93
204.0899
8
days
VPA
1.08

0.034

L-Tryptophan


843
24.94
208.0840
4
days
VPA
−1.14

0.004

Kynurenine
Formyl-4-











hydroxykynurenamine


893
44.64
214.1680
8
days
VPA
−2.11
0.005
Fenamic acid


1089
47.40
242.0808
8
days
VPA
1.87
0.02
Unknown


1104
7.98
243.9760
4
days
VPA
1.92
0.032
Unknown


1282
44.30
274.0947
8
days
VPA
1.78
0.019
3-Oxo-delta4-steroid


1447
43.40
300.2784
8
days
VPA
−2.22

0.033

Unknown


1440
27.94
314.2032
4
day
VPA
−1.12

0.012

Unknown


1637
24.91
330.1480
4
day
VPA
−1.42

0.004

Unknown


1684
11.94
336.1634
4
days
VPA
−1.13

0.023

Unknown


1691
34.87
338.0974
4
days
VPA
1.74

0.033

Unknown


1776
39.67
342.1130
4
day
VPA
1.46

0.044

Unknown


1816
24.40
348.1139
8
days
VPA
2.56
0.025
Unknown


1838
11.00
361.9194
4
days
VPA
−1.08

0.004

Unknown


1948
12.00
384.1664
8
days
VPA
1.38

0.018

Unknown


1949
14.98
387.1498
4
days
VPA
−1.26

0.001

Unknown


2084
64.24
414.2934
4
days
VPA
−1.20

0.031

Unknown


2131
88.14
426.2983
4
days
VPA
1.85
0.022
Cholanoic acid


2134
74.20
427.1200
8
day
VPA
−1.88

0.044

Unknown


2138
26.91
428.2423
8
day
VPA
1.70

0.003

Unknown


2144
34.14
431.2733
4
days
VPA
−1.24

0.041

Unknown


2186
32.68
441.1394
8
days
VPA
−1.16

0.022

Folate
Folic acid


2191
64.67
442.2934
8
days
VPA
1.79

0.001

Unknown


2214
92.89
440.3448
8
days
VPA
−1.84

0.037

Unknown


2233
12.00
444.0841
8
days
VPA
−1.30

0.041

Unknown


2244
64.41
449.3198
24
hours
VPA
−1.78

0.024

Unknown


2291
87.74
470.3249
4
days
VPA
−0.18

0.002

Unknown


2244
30.91
467.2631
8
days
VPA
1.69

0.004

Unknown


 743
13.81
197.0186
8
day
VPA
−1.39

0.016

Unknown


 636
42.18
178.0994
8
days

1.47

0.010

Unknown
















TABLE 6







Cellular metabolites measured in neural precursors derived from hESells treated with 1 mM of valproate














EXP
RT
roundMASS
time
trt
Fold
annotation.1
annotation.2

















NS 1 mM
36.648
102.0322438
2 d
NS 1 mM
−2.23119
2-Ketobutyric acid
Acetoacetic acid


VPA



VPA


NS 1 mM
36.648
102.0322438
4 d
NS 1 mM
−1.83846
2-Ketobutyric acid
Acetoacetic acid


VPA



VPA


NS 1 mM
9.33225
119.958645
4 d
NS 1 mM
6.98086
Unknown


VPA



VPA


NS 1 mM
12.2841
121.0621387
4 d
NS 1 mM
3.502341
Unknown


VPA



VPA


NS 1 mM
24.10558
125.0838833
2 d
NS 1 mM
1.79316
Unknown


VPA



VPA


NS 1 mM
30.43985
125.08394
2 d
NS 1 mM
1.529012
1-Methylhistamine


VPA



VPA


NS 1 mM
30.43985
125.08394
4 d
NS 1 mM
1.576622
1-Methylhistamine


VPA



VPA


NS 1 mM
23.33772
129.0573222
2 d
NS 1 mM
1.543375
Pyroglutamic acid


VPA



VPA


NS 1 mM
23.33772
129.0573222
4 d
NS 1 mM
1.663008
Pyroglutamic acid


VPA



VPA


NS 1 mM
12.13216
131.0941359
4 d
NS 1 mM
1.577796
L-Isoleucine
Aminocaproic acid


VPA



VPA


NS 1 mM
12.13216
131.0941359
2 d
NS 1 mM
2.474877
L-Isoleucine
Aminocaproic acid


VPA



VPA


NS 1 mM
8.881211
136.0366263
2 d
NS 1 mM
2.287439
Erythronic acid
Erythronic acid


VPA



VPA


NS 1 mM
8.881211
136.0366263
4 d
NS 1 mM
2.653537
Erythronic acid
Erythronic acid


VPA



VPA


NS 1 mM
12.00967
136.0376917
2 d
NS 1 mM
2.346054
Erythronic acid
Erythronic acid


VPA



VPA


NS 1 mM
12.00967
136.0376917
4 d
NS 1 mM
2.914393
Erythronic acid
Erythronic acid


VPA



VPA


NS 1 mM
3.9669
138.04396
2 d
NS 1 mM
1.521407
Urocanic acid
Nicotinamide N-


VPA



VPA


oxide


NS 1 mM
3.9669
138.04396
4 d
NS 1 mM
2.642558
Urocanic acid
Nicotinamide N-


VPA



VPA


oxide


NS 1 mM
4.28225
141.9392625
2 d
NS 1 mM
1.077336
5,10-Methylenetetrahydrofolate


VPA



VPA


NS 1 mM
4.28225
141.9392625
4 d
NS 1 mM
1.111532
5,10-Methylenetetrahydrofolate


VPA



VPA


NS 1 mM
23.33784
143.0734947
2 d
NS 1 mM
1.728349
Unknown


VPA



VPA


NS 1 mM
23.33784
143.0734947
4 d
NS 1 mM
1.986515
Unknown


VPA



VPA


NS 1 mM
55.5845
144.1153313
4 d
NS 1 mM
10.83178
Caprylic acid
Valproic acid


VPA



VPA


NS 1 mM
55.5845
144.1153313
2 d
NS 1 mM
11.64535
Caprylic acid
Valproic acid


VPA



VPA


NS 1 mM
5.609182
145.1572818
2 d
NS 1 mM
1.00993
Spermidine


VPA



VPA


NS 1 mM
5.609182
145.1572818
4 d
NS 1 mM
1.117314
Spermidine


VPA



VPA


NS 1 mM
33.6357
148.03738
4 d
NS 1 mM
−5.75294
Citramalic acid
Hydroxyglutaric


VPA



VPA


acid


NS 1 mM
33.6357
148.03738
2 d
NS 1 mM
−1.49356
Citramalic acid
Hydroxyglutaric


VPA



VPA


acid


NS 1 mM
62.42614
152.1201762
4 d
NS 1 mM
2.50602
Unknown


VPA



VPA


NS 1 mM
62.42614
152.1201762
2 d
NS 1 mM
3.371426
Unknown


VPA



VPA


NS 1 mM
8.862333
158.0177333
2 d
NS 1 mM
1.596402
Unknown


VPA



VPA


NS 1 mM
8.862333
158.0177333
4 d
NS 1 mM
2.236076
Unknown


VPA



VPA


NS 1 mM
8.269857
158.1374571
4 d
NS 1 mM
3.106829
Unknown


VPA



VPA


NS 1 mM
8.269857
158.1374571
2 d
NS 1 mM
3.626498
Unknown


VPA



VPA


NS 1 mM
10.07033
159.0688667
2 d
NS 1 mM
−2.87026
Indoleacetaldehyde


VPA



VPA


NS 1 mM
10.07033
159.0688667
4 d
NS 1 mM
−1.35298
Indoleacetaldehyde


VPA



VPA


NS 1 mM
12.85888
161.0509118
2 d
NS 1 mM
2.601443
Unknown


VPA



VPA


NS 1 mM
12.85888
161.0509118
4 d
NS 1 mM
5.136057
Unknown


VPA



VPA


NS 1 mM
6.713565
166.0840609
4 d
NS 1 mM
33.80296
Unknown


VPA



VPA


NS 1 mM
6.713565
166.0840609
2 d
NS 1 mM
90.97629
Unknown


VPA



VPA


NS 1 mM
23.58909
168.0687909
2 d
NS 1 mM
4.649885
Unknown


VPA



VPA


NS 1 mM
23.58909
168.0687909
4 d
NS 1 mM
5.02165
Unknown


VPA



VPA


NS 1 mM
31.08471
171.1250706
4 d
NS 1 mM
1.626943
Unknown


VPA



VPA


NS 1 mM
62.57554
172.1454
4 d
NS 1 mM
1.745543
Capric acid
Decanoic acid


VPA



VPA


NS 1 mM
62.57554
172.1454
2 d
NS 1 mM
1.8794
Caprica cid
Decanoic acid


VPA



VPA


NS 1 mM
20.68721
175.0830857
2 d
NS 1 mM
1.153935
N-Carboxyethyl-gamma-


VPA



VPA

aminobutyric acid


NS 1 mM
20.68721
175.0830857
4 d
NS 1 mM
2.294392
N-Carboxyethyl-gamma-


VPA



VPA

aminobutyric acid


NS 1 mM
41.71109
176.0946
2 d
NS 1 mM
−1.60014
Serotonin


VPA



VPA


NS 1 mM
41.71109
176.0946
4 d
NS 1 mM
−1.23797
Serotonin


VPA



VPA


NS 1 mM
25.29
177.0469231
2 d
NS 1 mM
3.379693
N-Formyl-L-methionine


VPA



VPA


NS 1 mM
25.29
177.0469231
4 d
NS 1 mM
3.82485
N-Formyl-L-methionine


VPA



VPA


NS 1 mM
26.75621
177.0789684
2 d
NS 1 mM
1.26513
5-Hydroxytryptophol


VPA



VPA


NS 1 mM
26.75621
177.0789684
4 d
NS 1 mM
1.423219
5-Hydroxytryptophol


VPA



VPA


NS 1 mM
8.503333
177.113375
2 d
NS 1 mM
−6.74695
Unknown


VPA



VPA


NS 1 mM
8.503333
177.113375
4 d
NS 1 mM
−2.88736
Unknown


VPA



VPA


NS 1 mM
27.53982
179.0938118
2 d
NS 1 mM
−2.71897
Salsolinol
Homophenylalanine


VPA



VPA


NS 1 mM
27.53982
179.0938118
4 d
NS 1 mM
−1.71231
Salsolinol
Homophenylalanine


VPA



VPA


NS 1 mM
55.15089
179.0949632
4 d
NS 1 mM
−1.64525
Salsolinol
Homophenylalanine


VPA



VPA


NS 1 mM
55.15089
179.0949632
2 d
NS 1 mM
−1.39458
Salsolinol
Homophenylalanine


VPA



VPA


NS 1 mM
37.08443
185.1406571
4 d
NS 1 mM
−2.39254
Unknown


VPA



VPA


NS 1 mM
23.33726
187.0635211
2 d
NS 1 mM
1.674013
Unknown


VPA



VPA


NS 1 mM
23.33726
187.0635211
4 d
NS 1 mM
1.921765
Unknown


VPA



VPA


NS 1 mM
28.77111
187.1206333
2 d
NS 1 mM
2.457813
8-Amino-7-oxononanoic acid


VPA



VPA


NS 1 mM
28.77111
187.1206333
4 d
NS 1 mM
3.559361
8-Amino-7-oxononanoic acid


VPA



VPA


NS 1 mM
62.50765
190.1720118
4 d
NS 1 mM
1.758553
Unknown


VPA



VPA


NS 1 mM
62.50765
190.1720118
2 d
NS 1 mM
1.940004
Unknown


VPA



VPA


NS 1 mM
7.850167
196.0933333
4 d
NS 1 mM
1.937281
Unknown


VPA



VPA


NS 1 mM
7.850167
196.0933333
2 d
NS 1 mM
6.390957
Unknown


VPA



VPA


NS 1 mM
45.36418
197.1060727
2 d
NS 1 mM
1.280472
L-Metanephrine


VPA



VPA


NS 1 mM
45.36418
197.1060727
4 d
NS 1 mM
1.62879
L-Metanephrine


VPA



VPA


NS 1 mM
8.363925
199.0952975
2 d
NS 1 mM
10.44025
Unknown


VPA



VPA


NS 1 mM
8.363925
199.0952975
4 d
NS 1 mM
10.88407
Unknown


VPA



VPA


NS 1 mM
22.22829
206.06375
4 d
NS 1 mM
2.263839
Unknown


VPA



VPA


NS 1 mM
22.22829
206.06375
2 d
NS 1 mM
4.317383
Unknown


VPA



VPA


NS 1 mM
62.46678
208.1829217
4 d
NS 1 mM
2.052914
Unknown


VPA



VPA


NS 1 mM
62.46678
208.1829217
2 d
NS 1 mM
2.734885
Unknown


VPA



VPA


NS 1 mM
9.2636
211.0349075
4 d
NS 1 mM
1.516795
Creatine phosphate


VPA



VPA


NS 1 mM
9.2636
211.0349075
2 d
NS 1 mM
1.893074
Creatine phosphate


VPA



VPA


NS 1 mM
44.11333
212.1400167
4 d
NS 1 mM
−9.35257
Unknown


VPA



VPA


NS 1 mM
44.11333
212.1400167
2 d
NS 1 mM
−6.85493
Unknown


VPA



VPA


NS 1 mM
7.746115
217.1048885
2 d
NS 1 mM
2.916422
N-a-Acetylcitrulline


VPA



VPA


NS 1 mM
7.746115
217.1048885
4 d
NS 1 mM
23.86569
N-a-Acetylcitrulline


VPA



VPA


NS 1 mM
22.26729
217.1307097
2 d
NS 1 mM
2.122093
Propionylcarnitine


VPA



VPA


NS 1 mM
22.26729
217.1307097
4 d
NS 1 mM
2.236406
Propionylcarnitine


VPA



VPA


NS 1 mM
16.1278
220.0841
2 d
NS 1 mM
−1.25214
5-Hydroxytryptophan
5-Hydroxy-L-


VPA



VPA


tryptophan


NS 1 mM
16.1278
220.0841
4 d
NS 1 mM
1.215413
5-Hydroxytryptophan
5-Hydroxy-L-


VPA



VPA


tryptophan


NS 1 mM
9.809786
220.0845
2 d
NS 1 mM
−1.06102
5-Hydroxytryptophan
5-Hydroxy-L-


VPA



VPA


tryptophan


NS 1 mM
9.809786
220.0845
4 d
NS 1 mM
1.371126
5-Hydroxytryptophan
5-Hydroxy-L-


VPA



VPA


tryptophan


NS 1 mM
12.15958
220.0845895
2 d
NS 1 mM
−1.54275
5-Hydroxytryptophan
5-Hydroxy-L-


VPA



VPA


tryptophan


NS 1 mM
12.15958
220.0845895
4 d
NS 1 mM
1.162644
5-Hydroxytryptophan
5-Hydroxy-L-


VPA



VPA


tryptophan


NS 1 mM
8.4172
223.92951
2 d
NS 1 mM
−3.24844
Unknown


VPA



VPA


NS 1 mM
8.4172
223.92951
4 d
NS 1 mM
−2.85631
Unknown


VPA



VPA


NS 1 mM
22.009
225.62685
4 d
NS 1 mM
2.716119
Unknown


VPA



VPA


NS 1 mM
22.009
225.62685
2 d
NS 1 mM
3.854852
Unknown


VPA



VPA


NS 1 mM
10.0963
227.01938
4 d
NS 1 mM
1.631698
L-Glutamic acid 5-phosphate


VPA



VPA


NS 1 mM
6.0771
227.09052
4 d
NS 1 mM
−5.41292
Deoxycytidine


VPA



VPA


NS 1 mM
6.0771
227.09052
2 d
NS 1 mM
−2.98012
Deoxycytidine


VPA



VPA


NS 1 mM
14.51476
228.05894
4 d
NS 1 mM
3.339111
Unknown


VPA



VPA


NS 1 mM
14.51476
228.05894
2 d
NS 1 mM
6.425869
Unknown


VPA



VPA


NS 1 mM
67.13919
230.1515667
4 d
NS 1 mM
−5.02528
Dodecanedioic acid


VPA



VPA


NS 1 mM
67.13919
230.1515667
2 d
NS 1 mM
−2.98776
Dodecanedioic acid


VPA



VPA


NS 1 mM
19.28286
234.1010143
2 d
NS 1 mM
−1.25569
5-Methoxytryptophan


VPA



VPA


NS 1 mM
19.28286
234.1010143
4 d
NS 1 mM
−1.18869
5-Methoxytryptophan


VPA



VPA


NS 1 mM
10.51438
236.0815625
4 d
NS 1 mM
1.367658
N′-Formylkynurenine


VPA



VPA


NS 1 mM
17.826
238.0864167
2 d
NS 1 mM
5.397657
Propanoic acid


VPA



VPA


NS 1 mM
17.826
238.0864167
4 d
NS 1 mM
5.703771
Propanoic acid


VPA



VPA


NS 1 mM
7.8115
239.087425
4 d
NS 1 mM
1.950568
Unknown


VPA



VPA


NS 1 mM
7.8115
239.087425
2 d
NS 1 mM
30.57925
Unknown


VPA



VPA


NS 1 mM
42.05716
246.1469838
4 d
NS 1 mM
−2.28801
3-Hydroxydodecanedioic acid


VPA



VPA


NS 1 mM
42.05716
246.1469838
2 d
NS 1 mM
−1.71537
3-Hydroxydodecanedioic acid


VPA



VPA


NS 1 mM
30.669
256.09664
4 d
NS 1 mM
1.692487
Aryl beta-D-glucoside


VPA



VPA


NS 1 mM
30.669
256.09664
2 d
NS 1 mM
1.966122
Aryl beta-D-glucoside


VPA



VPA


NS 1 mM
59.82681
256.1080938
2 d
NS 1 mM
2.962348
Unknown


VPA



VPA


NS 1 mM
59.82681
256.1080938
4 d
NS 1 mM
3.845884
Unknown


VPA



VPA


NS 1 mM
69.57173
258.18226
4 d
NS 1 mM
4.075358
Tetradecanedioic acid


VPA



VPA


NS 1 mM
69.57173
258.18226
2 d
NS 1 mM
5.744182
Tetradecanedioic acid


VPA



VPA


NS 1 mM
22.0274
264.11209
2 d
NS 1 mM
1.230997
Acetyl-N-formyl-5-


VPA



VPA

methoxykynurenamine


NS 1 mM
22.0274
264.11209
4 d
NS 1 mM
1.338241
Acetyl-N-formyl-5-


VPA



VPA

methoxykynurenamine


NS 1 mM
11.94583
268.0806
4 d
NS 1 mM
3.240011
3-Deoxy-D-glycero-D-galacto-2-


VPA



VPA

nonulosonic acid


NS 1 mM
11.94583
268.0806
2 d
NS 1 mM
3.329815
3-Deoxy-D-glycero-D-galacto-2-


VPA



VPA

nonulosonic acid


NS 1 mM
20.58271
270.1203286
2 d
NS 1 mM
1.808333
L-gamma-Glutamyl-L-hypoglycin;


VPA



VPA


NS 1 mM
20.58271
270.1203286
4 d
NS 1 mM
1.890677
L-gamma-Glutamyl-L-hypoglycin;


VPA



VPA


NS 1 mM
56.5351
272.08566
4 d
NS 1 mM
1.178071
5-S-Cysteinyldopamine


VPA



VPA


NS 1 mM
56.5351
272.08566
2 d
NS 1 mM
1.718998
5-S-Cysteinyldopamine


VPA



VPA


NS 1 mM
64.11407
278.0251024
4 d
NS 1 mM
5.17024
Unknown


VPA



VPA


NS 1 mM
64.11407
278.0251024
2 d
NS 1 mM
6.667641
Unknown


VPA



VPA


NS 1 mM
28.90879
290.1501643
4 d
NS 1 mM
3.329013
Unknown


VPA



VPA


NS 1 mM
28.90879
290.1501643
2 d
NS 1 mM
8.490919
Unknown


VPA



VPA


NS 1 mM
26.42889
295.1063913
2 d
NS 1 mM
7.265582
Unknown


VPA



VPA


NS 1 mM
26.42889
295.1063913
4 d
NS 1 mM
8.896581
Unknown


VPA



VPA


NS 1 mM
73.28533
315.2406111
4 d
NS 1 mM
2.599877
Decanoylcarnitine


VPA



VPA


NS 1 mM
73.28533
315.2406111
2 d
NS 1 mM
3.899691
Decanoylcarnitine


VPA



VPA


NS 1 mM
77.38144
318.2193688
4 d
NS 1 mM
1.932263
Leukotriene A4


VPA



VPA


NS 1 mM
77.38144
318.2193688
2 d
NS 1 mM
2.342543
Leukotriene A4


VPA



VPA


NS 1 mM
41.33024
324.1144588
4 d
NS 1 mM
3.317923
Acetohexamide


VPA



VPA


NS 1 mM
41.33024
324.1144588
2 d
NS 1 mM
3.713445
Acetohexamide


VPA



VPA


NS 1 mM
33.60576
330.1013765
4 d
NS 1 mM
2.25561
Unknown


VPA



VPA


NS 1 mM
33.60576
330.1013765
2 d
NS 1 mM
2.310447
Unknown


VPA



VPA


NS 1 mM
35.06233
331.1049867
4 d
NS 1 mM
2.719086
Unknown


VPA



VPA


NS 1 mM
35.06233
331.1049867
2 d
NS 1 mM
3.041317
Unknown


VPA



VPA


NS 1 mM
52.557
349.22592
4 d
NS 1 mM
2.41993
Unknown


VPA



VPA


NS 1 mM
52.557
349.22592
2 d
NS 1 mM
6.652089
Unknown


VPA



VPA


NS 1 mM
53.57858
350.2096
4 d
NS 1 mM
1.508076
Prostaglandin E3


VPA



VPA


NS 1 mM
53.57858
350.2096
2 d
NS 1 mM
1.612834
Prostaglandin E3


VPA



VPA


NS 1 mM
65.76353
356.2702895
4 d
NS 1 mM
2.05875
Tetracosahexaenoic acid


VPA



VPA


NS 1 mM
65.76353
356.2702895
2 d
NS 1 mM
2.405825
Tetracosahexaenoic acid


VPA



VPA


NS 1 mM
81.79271
369.2880824
4 d
NS 1 mM
6.636435
cis-5-Tetradecenoylcarnitine


VPA



VPA


NS 1 mM
81.79271
369.2880824
2 d
NS 1 mM
9.965816
cis-5-Tetradecenoylcarnitine


VPA



VPA


NS 1 mM
27.34076
374.1222235
4 d
NS 1 mM
2.300022
Unknown


VPA



VPA


NS 1 mM
27.34076
374.1222235
2 d
NS 1 mM
2.889783
Unknown


VPA



VPA


NS 1 mM
8.881
380.164
4 d
NS 1 mM
2.519949
Unknown


VPA



VPA


NS 1 mM
8.881
380.164
2 d
NS 1 mM
2.633667
Unknown


VPA



VPA


NS 1 mM
22.46583
385.1025667
4 d
NS 1 mM
1.45497
S-Inosyl-L-homocysteine


VPA



VPA


NS 1 mM
22.46583
385.1025667
2 d
NS 1 mM
1.533705
S-Inosyl-L-homocysteine


VPA



VPA


NS 1 mM
68.31689
386.23145
4 d
NS 1 mM
6.386163
1-tridecanoyl-sn-glycero-3-


VPA



VPA

phosphate


NS 1 mM
68.31689
386.23145
2 d
NS 1 mM
7.117538
1-tridecanoyl-sn-glycero-3-


VPA



VPA

phosphate


NS 1 mM
89.1946
390.27608
2 d
NS 1 mM
1.682855
7-Hydroxy-3-oxocholanoic acid


VPA



VPA


NS 1 mM
89.1946
390.27608
4 d
NS 1 mM
3.296512
7-Hydroxy-3-oxocholanoic acid


VPA



VPA


NS 1 mM
26.42904
394.2127308
2 d
NS 1 mM
2.670186
Unknown


VPA



VPA


NS 1 mM
26.42904
394.2127308
4 d
NS 1 mM
3.50273
unknown


VPA



VPA


NS 1 mM
76.06971
398.2439857
4 d
NS 1 mM
2.845315
Unknown


VPA



VPA


NS 1 mM
76.06971
398.2439857
2 d
NS 1 mM
3.609136
Unknown


VPA



VPA


NS 1 mM
33.53038
399.2100125
2 d
NS 1 mM
6.345173
unknown


VPA



VPA


NS 1 mM
33.53038
399.2100125
4 d
NS 1 mM
8.777833
unknown


VPA



VPA


NS 1 mM
8.9305
406.1058875
4 d
NS 1 mM
1.976577
unknown


VPA



VPA


NS 1 mM
8.9305
406.1058875
2 d
NS 1 mM
2.00634
unknown


VPA



VPA


NS 1 mM
65.76447
409.3155632
4 d
NS 1 mM
4.662331
Unknown


VPA



VPA


NS 1 mM
65.76447
409.3155632
2 d
NS 1 mM
5.930421
Unknown


VPA



VPA


NS 1 mM
18.93053
416.0834333
4 d
NS 1 mM
3.527468
Unknown


VPA



VPA


NS 1 mM
18.93053
416.0834333
2 d
NS 1 mM
4.202864
Unknown


VPA



VPA


NS 1 mM
8.6127
416.20208
2 d
NS 1 mM
3.29783
Lactone


VPA



VPA


NS 1 mM
8.6127
416.20208
4 d
NS 1 mM
3.495266
Lactone


VPA



VPA


NS 1 mM
14.963
420.05275
2 d
NS 1 mM
−3.434
Unknown


VPA



VPA


NS 1 mM
14.963
420.05275
4 d
NS 1 mM
−3.09195
Unknown


VPA



VPA


NS 1 mM
62.93221
427.1025357
2 d
NS 1 mM
3.882014
Unknown


VPA



VPA


NS 1 mM
62.93221
427.1025357
4 d
NS 1 mM
6.045912
Unknown


VPA



VPA


NS 1 mM
33.59771
430.1185143
2 d
NS 1 mM
3.469797
N-Ethylmaleimide-S-glutathione


VPA



VPA


NS 1 mM
33.59771
430.1185143
4 d
NS 1 mM
3.98295
N-Ethylmaleimide-S-glutathione


VPA



VPA


NS 1 mM
24.9718
434.19845
4 d
NS 1 mM
3.713915
Unknown


VPA



VPA


NS 1 mM
24.9718
434.19845
2 d
NS 1 mM
3.76882
Unknown


VPA



VPA


NS 1 mM
23.07
434.1985875
2 d
NS 1 mM
2.416021
Unknown


VPA



VPA


NS 1 mM
23.07
434.1985875
4 d
NS 1 mM
3.44524
Unknown


VPA



VPA


NS 1 mM
37.33089
438.1460579
2 d
NS 1 mM
2.829002
Unknown


VPA



VPA


NS 1 mM
37.33089
438.1460579
4 d
NS 1 mM
3.253909
Unknown


VPA



VPA


NS 1 mM
5.410909
441.9424
4 d
NS 1 mM
−3.5345
Unknown


VPA



VPA


NS 1 mM
5.410909
441.9424
2 d
NS 1 mM
−2.45689
Unknown


VPA



VPA


NS 1 mM
34.58505
443.2362947
2 d
NS 1 mM
2.648862
Unknown


VPA



VPA


NS 1 mM
34.58505
443.2362947
4 d
NS 1 mM
3.427563
Unknown


VPA



VPA


NS 1 mM
33.85267
445.1694
2 d
NS 1 mM
−1.31487
Tetrahydrofolic acid
Tetrahydrofolate


VPA



VPA


NS 1 mM
33.85267
445.1694
4 d
NS 1 mM
−1.04073
Tetrahydrofolic acid
Tetrahydrofolate


VPA



VPA


NS 1 mM
38.63717
449.1638333
2 d
NS 1 mM
3.04704
Unknown


VPA



VPA


NS 1 mM
38.63717
449.1638333
4 d
NS 1 mM
4.206864
Unknown


VPA



VPA


NS 1 mM
21.9772
456.2448
4 d
NS 1 mM
4.145738
unknown


VPA



VPA


NS 1 mM
21.9772
456.2448
2 d
NS 1 mM
8.390862
unknown


VPA



VPA


NS 1 mM
42.40369
467.1731077
2 d
NS 1 mM
−10.3323
Unknown


VPA



VPA


NS 1 mM
42.40369
467.1731077
4 d
NS 1 mM
−4.42263
Unknown


VPA



VPA


NS 1 mM
23.41189
474.1090778
4 d
NS 1 mM
2.094815
Unknown


VPA



VPA


NS 1 mM
23.41189
474.1090778
2 d
NS 1 mM
2.928466
Unknown


VPA



VPA


NS 1 mM
22.666
482.1554563
4 d
NS 1 mM
2.075721
Unknown


VPA



VPA


NS 1 mM
22.666
482.1554563
2 d
NS 1 mM
2.519832
Unknown


VPA



VPA


NS 1 mM
75.55014
493.3252405
4 d
NS 1 mM
2.09415
1-(9E-hexadecenoyl)-sn-glycero-3-


VPA



VPA

phosphocholine


NS 1 mM
75.55014
493.3252405
2 d
NS 1 mM
2.34894
1-(9E-hexadecenoyl)-sn-glycero-3-


VPA



VPA


phosphocholine


NS 1 mM
37.34533
506.1856556
2 d
NS 1 mM
2.031088
Unknown


VPA



VPA


NS 1 mM
37.34533
506.1856556
4 d
NS 1 mM
2.405509
unknown


VPA



VPA


NS 1 mM
23.67792
514.162208
2 d
NS 1 mM
2.2744
unknown


VPA



VPA


NS 1 mM
23.67792
514.162208
4 d
NS 1 mM
3.27837
unknown


VPA



VPA


NS 1 mM
36.44195
514.2430667
4 d
NS 1 mM
4.332807
Unknown


VPA



VPA


NS 1 mM
36.44195
514.2430667
2 d
NS 1 mM
4.565629
Unknown


VPA



VPA


NS 1 mM
41.29621
527.3552786
2 d
NS 1 mM
9.44893
Unknown


VPA



VPA


NS 1 mM
41.29621
527.3552786
4 d
NS 1 mM
12.3251
Unknown


VPA



VPA


NS 1 mM
21.94381
534.2784846
4 d
NS 1 mM
2.818876
unknown


VPA



VPA


NS 1 mM
21.94381
534.2784846
2 d
NS 1 mM
2.912693
unknown


VPA



VPA


NS 1 mM
26.05061
546.3146929
2 d
NS 1 mM
1.574871
Unknown


VPA



VPA


NS 1 mM
26.05061
546.3146929
4 d
NS 1 mM
3.130802
Unknown


VPA



VPA


NS 1 mM
25.92929
556.13945
4 d
NS 1 mM
4.837329
unknown


VPA



VPA


NS 1 mM
25.92929
556.13945
2 d
NS 1 mM
5.293236
unknown


VPA



VPA


NS 1 mM
9.093727
575.1451545
4 d
NS 1 mM
2.795937
Unknown


VPA



VPA


NS 1 mM
9.093727
575.1451545
2 d
NS 1 mM
4.232054
Unknown


VPA



VPA


NS 1 mM
36.92372
575.3159222
2 d
NS 1 mM
2.816601
Unknown


VPA



VPA


NS 1 mM
36.92372
575.3159222
4 d
NS 1 mM
3.446719
unknown


VPA



VPA


NS 1 mM
80.9297
583.44194
2 d
NS 1 mM
1.503812
Unknown


VPA



VPA


NS 1 mM
80.9297
583.44194
4 d
NS 1 mM
4.532225
Unknown


VPA



VPA


NS 1 mM
4.824
594.2327
4 d
NS 1 mM
2.212473
Unknown


VPA



VPA


NS 1 mM
4.824
594.2327
2 d
NS 1 mM
4.279664
Unknown


VPA



VPA


NS 1 mM
41.278
632.232825
2 d
NS 1 mM
3.171377
Unknown


VPA



VPA


NS 1 mM
41.278
632.232825
4 d
NS 1 mM
4.764468
Unknown


VPA



VPA


NS 1 mM
14.97571
659.1506941
4 d
NS 1 mM
3.054219
Unknown


VPA



VPA


NS 1 mM
23.39707
660.1513786
2 d
NS 1 mM
3.542683
Unknown


VPA



VPA


NS 1 mM
23.39707
660.1513786
4 d
NS 1 mM
4.100844
Unknown


VPA



VPA


NS 1 mM
14.884
682.2853
2 d
NS 1 mM
2.823221
Unknown


VPA



VPA


NS 1 mM
14.884
682.2853
4 d
NS 1 mM
5.153298
Unknown


VPA



VPA


NS 1 mM
33.64471
822.2805429
2 d
NS 1 mM
2.668941
Unknown


VPA



VPA


NS 1 mM
33.64471
822.2805429
4 d
NS 1 mM
3.816104
Unknown


VPA



VPA


NS 1 mM
83.24742
907.54555
4 d
NS 1 mM
1.507945
Unknown


VPA



VPA


NS 1 mM
83.24742
907.54555
2 d
NS 1 mM
1.586431
Unknown


VPA



VPA


NS 1 mM
31.5316
908.22015
2 d
NS 1 mM
1.640148
Unknown


VPA



VPA


NS 1 mM
31.5316
908.22015
4 d
NS 1 mM
1.998983
Unknown


VPA



VPA


NS 1 mM
33.44333
1028.3246
2 d
NS 1 mM
5.833998
Unknown


VPA



VPA


NS 1 mM
33.44333
1028.3246
4 d
NS 1 mM
8.654592
Unknown


VPA



VPA


NS 1 mM
4.649125
1291.75965
2 d
NS 1 mM
1.739338
beta-D-Glucosyl-1,4-N-acetyl-D-


VPA



VPA

glucosaminyldiphosphoundecaprenol


NS 1 mM
4.649125
1291.75965
4 d
NS 1 mM
1.793695
beta-D-Glucosyl-1,4-N-acetyl-D-


VPA



VPA

glucosaminyldiphosphoundecaprenol
















TABLE 7







Cellular metabolites measured in hES cells treated with alcohol















Retention








Experiment
time
Mass
Time
Fold
p-value
Compound 1
Compound 2

















ETOH 0.1
15.48433
99.0689
4 D
1.434154
0.034571
N-Methyl-2-pyrrolidinone



ETOH 0.1
52.01225
99.1043
4 D
2.703447
0.012638
Unknown


ETOH 0.1
13.40565
120.2112
4 D
4.847027
0.029776
Unknown


ETOH 0.1
16.73904
129.0452
24 H
1.502328
0.002871
3,4-Dihydroxybutyric acid


ETOH 0.1
88.64043
130.9541
24 H
1.631614
0.046779
Unknown


ETOH 0.1
22.22892
131.0746
24 H
−1.85703
0.037466
3-Methylindole


ETOH 0.1
14.35336
131.076
4 D
3.62907
0.014778
Unknown


ETOH 0.1
3.958833
148.0052
24 H
−1.94841
0.034059
Unknown


ETOH 0.1
52.88652
148.016
4 D
−2.44409
0.047122
2-Oxo-4-








methylthiobutanoic acid


ETOH 0.1
19.18355
168.0434
4 D
−1.46785
0.019426
Homogentisic acid
Vanillic acid


ETOH 0.1
26.70635
171.1244
24 H
2.376107
0.008413
GABA analogue


ETOH 0.1
22.17997
187.1343
24 H
1.48782
0.045452
(+/−)-2-(4′-








Isobutylphenyl)propionitrile


ETOH 0.1
46.31086
187.1348
4 D
2.329144
4.21E−05
(+/−)-2-(4′-








Isobutylphenyl)propionitrile


ETOH 0.1
5.935143
194.073
4 D
−1.38924
0.003217
Phenanthrene-9,10-oxide


ETOH 0.1
31.19917
195.124
4 D
−2.22499
0.004386
Benzenemethanol, 2-(2-
a-[1-








aminopropoxy)-3-methyl-
(ethylamino)ethyl]-p-









hydroxy-Benzyl









alcohol


ETOH 0.1
38.99212
195.1253
4 D
2.158606
0.00953
Benzenemethanol, 2-(2-
a-[1-








aminopropoxy)-3-methyl-
(ethylamino)ethyl]-p-









hydroxy-Benzyl









alcohol


ETOH 0.1
48.37093
197.1769
4 D
−3.11904
0.016197
Unknown


ETOH 0.1
9.675726
203.1138
4 D
−1.70728
0.023636
Acetylcarnitine
L-Glutamic acid n-









butyl ester


ETOH 0.1
6.747279
205.1304
4 D
−1.2578
0.005318
Pantothenol
dimethylbutanamide


ETOH 0.1
36.18938
210.0922
4 D
1.864256
0.040527
3-(2,5-Dimethoxy








phenylpropionic acid


ETOH 0.1
24.52067
229.0949
24 H
−2.33044
0.008877
Malonylcarnitine


ETOH 0.1
17.7027
243.1089
4 D
−2.18071
0.016141
Unknown


ETOH 0.1
64.66999
266.1613
24 H
−1.51898
0.047652
Unknown


ETOH 0.1
42.3656
268.2487
4 D
−1.54971
0.015019
Unknown


ETOH 0.1
4.86619
271.9364
24 H
2.629339
0.04245
Unknown


ETOH 0.1
43.99398
272.16
24 H
1.929598
0.032191
Unknown


ETOH 0.1
43.99398
272.16
4 D
2.186768
0.003018
Unknown


ETOH 0.1
63.00428
285.2285
24 H
4.002774
0.018095
Unknown


ETOH 0.1
37.97297
292.1862
4 D
2.239381
0.0496
Unknown


ETOH 0.1
4.014175
293.9773
4 D
1.938848
0.036775
Unknown


ETOH 0.1
6.160071
294.0957
24 H
1.269183
0.005089
Unknown


ETOH 0.1
8.967061
295.1521
4 D
1.513407
0.042025
Unknown


ETOH 0.1
71.55535
296.2308
24 H
3.545035
0.003758
Unknown


ETOH 0.1
50.75387
298.174
4 D
−3.00237
0.045113
Unknown


ETOH 0.1
18.88505
300.1147
4 D
2.686262
0.023485
Unknown


ETOH 0.1
17.18696
300.1656
24 H
1.548853
0.036582
Unknown


ETOH 0.1
7.719471
301.1345
4 D
6.648828
0.030822
Unknown


ETOH 0.1
15.22357
312.1341
4 D
−2.01503
0.041156
Unknown


ETOH 0.1
26.51229
315.6732
4 D
2.014609
0.010998
Unknown


ETOH 0.1
18.82373
325.2711
4 D
−1.75625
0.013853
Unknown


ETOH 0.1
20.94557
325.2714
4 D
−2.07426
0.00333
Unknown


ETOH 0.1
8.542672
337.2012
24 H
1.402499
0.000372
Unknown


ETOH 0.1
3.85935
353.2765
4 D
2.622059
0.002006
Unknown


ETOH 0.1
25.16993
357.1781
4 D
2.217294
0.001346
Unknown


ETOH 0.1
24.01428
359.1532
4 D
1.535704
0.033
Unknown


ETOH 0.1
18.50245
360.1321
4 D
2.11023
0.004465
Unknown


ETOH 0.1
83.72506
362.2787
24 H
2.819814
0.04795
Unknown


ETOH 0.1
83.72506
362.2787
4 D
2.916423
0.023844
Unknown


ETOH 0.1
27.98054
368.2122
4 D
1.69537
0.02565
Unknown


ETOH 0.1
20.76168
379.1771
24 H
−1.72285
0.021135
Unknown


ETOH 0.1
20.76168
379.1771
4 D
1.539861
0.019592
Unknown


ETOH 0.1
15.20829
383.1721
4 D
1.914543
0.043581
Unknown


ETOH 0.1
23.38956
384.2127
4 D
−2.55567
0.025704
Unknown


ETOH 0.1
51.65871
386.1724
4 D
5.308852
0.032774
(+)-Eudesmin


ETOH 0.1
19.97914
387.0812
4 D
−1.97698
0.024641
Unknown


ETOH 0.1
19.97914
387.0812
24 H
1.739051
0.018391
Unknown


ETOH 0.1
17.53242
388.1815
24 H
−1.44894
0.012322
Unknown


ETOH 0.1
46.346
388.2349
4 D
1.946524
0.002762
Unknown


ETOH 0.1
15.90129
393.1889
24 H
−1.43098
0.022977
Unknown


ETOH 0.1
6.259963
396.1687
24 H
1.717607
0.047952
Unknown


ETOH 0.1
51.66325
403.1978
4 D
3.11601
0.048224
Unknown


ETOH 0.1
30.70733
405.2001
4 D
2.668076
0.001676
Unknown


ETOH 0.1
16.21743
408.1636
4 D
1.965641
0.028858
Unknown


ETOH 0.1
21.14975
417.2386
4 D
−1.97972
0.007183
Unknown


ETOH 0.1
33.09057
417.2338
4 D
2.032563
0.016902
Unknown


ETOH 0.1
26.77212
420.1862
4 D
3.282511
0.030236
Unknown


ETOH 0.1
18.03482
429.2533
4 D
−1.80751
0.006213
Unknown


ETOH 0.1
30.24237
429.2535
4 D
1.804876
0.044332
Unknown


ETOH 0.1
35.58196
431.2501
4 D
1.532408
0.037928
Unknown


ETOH 0.1
32.18393
437.2042
24 H
24.53212
0.001124
Unknown


ETOH 0.1
4.808947
440.0223
4 D
−1.52785
0.03034
Unknown


ETOH 0.1
24.13915
443.2381
4 D
2.985557
0.023682
Unknown


ETOH 0.1
67.0705
443.3216
4 D
1.751997
0.037074
Unknown


ETOH 0.1
51.58546
444.2237
4 D
2.130512
0.031074
Unknown


ETOH 0.1
33.51823
460.9391
4 D
−4.51805
0.005949
Unknown


ETOH 0.1
22.95657
462.2217
24 H
−1.98563
0.0437
Unknown


ETOH 0.1
25.3287
464.225
24 H
−1.63071
0.025852
Unknown


ETOH 0.1
46.51446
467.3804
4 D
2.068091
0.042613
Unknown


ETOH 0.1
51.6158
468.2002
4 D
1.875012
0.015762
Unknown


ETOH 0.1
30.37291
471.1928
4 D
2.001387
0.022662
glucuronide


ETOH 0.1
30.72707
471.7804
4 D
−2.83569
0.037476
Unknown


ETOH 0.1
30.28867
478.2761
4 D
1.698899
0.000475
Unknown


ETOH 0.1
72.7735
482.3062
24 H
−1.95925
0.042853
Unknown


ETOH 0.1
6.676207
485.2069
24 H
−2.01419
0.013732
Unknown


ETOH 0.1
66.73744
487.3472
4 D
2.931014
0.007475
Unknown


ETOH 0.1
21.72729
489.2127
4 D
−1.51037
0.0314
Unknown


ETOH 0.1
31.22083
510.8202
4 D
2.488196
0.011267
Unknown


ETOH 0.1
34.35986
521.9924
24 H
−1.44593
0.032994
Unknown


ETOH 0.1
34.57864
525.3161
4 D
1.551324
0.037545
Unknown


ETOH 0.1
51.73057
526.2773
4 D
3.445707
0.006877
Unknown


ETOH 0.1
23.87065
530.314
4 D
1.964552
0.006366
L-Oleandrosyl-oleandolide


ETOH 0.1
32.50661
531.2876
4 D
2.106138
0.024689
Unknown


ETOH 0.1
35.58454
531.3191
4 D
−1.25162
0.027019
Unknown


ETOH 0.1
66.31491
531.3736
4 D
3.862674
0.01116
Unknown


ETOH 0.1
32.24719
541.3274
4 D
2.161601
0.038319
Unknown


ETOH 0.1
17.6573
545.3029
4 D
−1.39484
0.043629
Unknown


ETOH 0.1
31.891
554.8471
4 D
2.038489
0.037688
Unknown


ETOH 0.1
15.78741
555.2406
4 D
1.835025
0.014923
Unknown


ETOH 0.1
5.742094
555.8505
4 D
−1.28922
0.017625
Unknown


ETOH 0.1
88.02533
556.3971
4 D
−3.11839
0.016192
Unknown


ETOH 0.1
31.97996
559.8329
4 D
−1.7213
0.049678
Unknown


ETOH 0.1
24.7039
574.3397
4 D
1.58436
0.02116
Unknown


ETOH 0.1
31.71105
574.3427
4 D
1.750055
0.026643
Unknown


ETOH 0.1
47.90467
576.096
4 D
1.361314
0.021201
Unknown


ETOH 0.1
16.90923
577.2825
24 H
1.727637
0.047154
Unknown


ETOH 0.1
35.26918
589.6938
4 D
1.819573
0.027966
Unknown


ETOH 0.1
31.54325
591.3789
4 D
1.578222
0.000714
Unknown


ETOH 0.1
25.14927
596.3543
4 D
1.395808
0.049214
L-Urobilinogen;


ETOH 0.1
32.67372
603.3535
4 D
−2.62952
0.015253
Unknown


ETOH 0.1
8.056862
612.1509
24 H
−1.47366
0.02889
Oxidized glutathione
Oxidized glutathione;









Glutathione disulfide;









GSSG; Oxiglutatione


ETOH 0.1
33.68866
619.3409
4 D
1.856648
0.030722
Unknown


ETOH 0.1
32.73907
620.8861
4 D
2.248558
0.00893
Unknown


ETOH 0.1
32.08734
635.4065
4 D
1.392618
0.030885
Unknown


ETOH 0.1
5.903429
646.7084
4 D
−1.27147
0.020652
Unknown


ETOH 0.1
26.7452
661.3846
4 D
1.295402
0.046573
Unknown


ETOH 0.1
33.48766
677.9101
24 H
−2.22083
0.028347
Unknown


ETOH 0.1
31.11764
693.4124
4 D
2.318353
0.028562
Unknown


ETOH 0.1
28.2045
695.4286
24 H
−32.9384
0.027453
Unknown


ETOH 0.1
33.70266
699.9225
4 D
1.719036
0.039493
Unknown


ETOH 0.1
40.84822
702.2497
4 D
−2.76945
0.001031
Neu5Acalpha2-3Galbeta1-
Neu5Acalpha2-








4Glcbeta-Sp
6Galbeta1-4Glcbeta-









Sp


ETOH 0.1
34.62439
707.3928
4 D
2.136871
0.0353
Unknown


ETOH 0.1
56.18269
707.4296
24 H
1.489574
0.046762
Unknown


ETOH 0.1
33.73428
708.9387
4 D
2.159654
0.006959
Unknown


ETOH 0.1
4.826824
711.8344
24 H
−3.02053
0.013448
Unknown


ETOH 0.1
33.89008
730.4494
4 D
2.613893
0.009133
Unknown


ETOH 0.1
47.76987
731.0954
4 D
−2.77579
0.004811
Unknown


ETOH 0.1
5.918027
732.007
4 D
1.795393
0.021782
Unknown


ETOH 0.1
35.028
751.4193
4 D
1.87008
0.032616
Unknown


ETOH 0.1
34.12668
752.4629
4 D
2.066515
0.031345
Unknown


ETOH 0.1
69.32865
765.5211
24 H
1.873064
0.033127
Unknown


ETOH 0.1
34.33545
774.4767
4 D
2.103658
0.020363
Unknown


ETOH 0.1
89.29926
774.5055
4 D
−2.40077
0.006755
Unknown


ETOH 0.1
5.886782
780.241
4 D
−1.31403
0.025516
Unknown


ETOH 0.1
34.52749
796.4891
4 D
1.926524
0.049615
Unknown


ETOH 0.1
34.60124
796.9917
4 D
1.818186
0.015806
Unknown


ETOH 0.1
4.613879
820.8181
4 D
−1.47009
0.047535
Unknown


ETOH 0.1
5.259716
888.8041
4 D
−1.45771
0.021932
Unknown


ETOH 0.1
8.502051
909.5934
24 H
2.274264
0.037836
Unknown


ETOH 0.1
5.217833
913.8074
24 H
−1.86064
0.028059
Unknown


ETOH 0.1
5.399211
921.0025
4 D
1.677834
0.001526
Unknown


ETOH 0.1
3.646902
994.0917
24 H
1.441829
0.019979
Unknown


ETOH 0.1
3.705141
1008.072
4 D
1.30378
0.048393
Unknown


ETOH 0.1
5.177162
1038.786
4 D
1.677834
0.030851
Unknown


ETOH 0.3
85.57399
83.0372
24 H
2.472036
0.010882
Unknown


ETOH 0.3
15.48433
99.0689
4 D
1.337742
0.043286
N-Methyl-2-pyrrolidinone


ETOH 0.3
15.48433
99.0689
24 H
1.467845
0.043638
N-Methyl-2-pyrrolidinone


ETOH 0.3
52.01225
99.1043
24 H
3.331103
0.000378
Unknown


ETOH 0.3
10.21225
101.1201
24 H
2.191927
0.043209
Hexylamine


ETOH 0.3
4.032816
111.9839
4 D
−8.67642
0.018374
Thiosulfate


ETOH 0.3
3.767232
120.0436
4 D
1.936297
0.034585
3,4-Dihydroxybutyric acid


ETOH 0.3
13.40565
120.2112
4 D
3.90007
0.046375
Unknown


ETOH 0.3
16.73904
129.0452
24 H
1.795891
3.32E−05
3,4-Dihydroxybutyric acid


ETOH 0.3
88.64043
130.9541
24 H
2.024969
0.006982
Unknown


ETOH 0.3
22.22892
131.0746
4 D
2.502205
0.049833
3-Methylindole


ETOH 0.3
14.35336
131.076
4 D
4.050219
0.020549
Unknown


ETOH 0.3
3.958833
148.0052
24 H
−1.72967
0.043053
Unknown


ETOH 0.3
7.479235
149.0511
4 D
−1.30477
0.014313
Amino-4methylthiobutyric








acid


ETOH 0.3
27.80141
153.0811
24 H
−1.6976
0.025771
Unknown


ETOH 0.3
5.559732
155.0681
4 D
1.637846
0.022817
L-Histidine
4-propionic acid


ETOH 0.3
14.22357
161.0805
24 H
−6.43527
0.032474
Unknown


ETOH 0.3
44.88033
162.0662
4 D
1.799131
0.037703
Unknown


ETOH 0.3
23.6763
167.0941
24 H
−2.83
0.012984
3-Methoxytyramine
Phenylephrine


ETOH 0.3
19.18355
168.0434
4 D
1.281914
0.028006
Homogentisic acid
Vanillic acid


ETOH 0.3
26.70635
171.1244
24 H
3.755227
0.001253
GABA analogue


ETOH 0.3
20.23014
173.084
24 H
−1.43983
0.019446
1,3-Dimethyl-8-








isoquinolinol


ETOH 0.3
28.52393
178.5546
24 H
−2.76389
0.001401
Unknown


ETOH 0.3
5.935143
194.073
4 D
−1.39988
0.002956
Phenanthrene-9,10-oxide
9-









Hydroxyphenanthrene;









9-Phenanthrol


ETOH 0.3
22.61355
194.0836
24 H
−1.70303
0.030955
Unknown


ETOH 0.3
31.19917
195.124
4 D
−1.86013
0.015911
Benzenemethanol, 2-(2-
a-[1-








aminopropoxy)-3-methyl-
(ethylamino)ethyl]-p-









hydroxy-Benzyl









alcohol


ETOH 0.3
19.48063
201.1709
4 D
−2.97874
0.009458
Unknown


ETOH 0.3
6.747279
205.1304
4 D
−1.33858
0.014168
Pantothenol
dimethylbutanamide;


ETOH 0.3
36.18938
210.0922
4 D
1.849968
0.042032
3-(2,5-Dimethoxy








phenylpropionic acid


ETOH 0.3
6.62669
218.0762
4 D
−1.77129
0.047105
Unknown


ETOH 0.3
27.57188
222.0401
24 H
−2.11155
0.040386
Unknown


ETOH 0.3
13.6845
223.119
24 H
−2.73967
0.024694
Unknown
Unknown


ETOH 0.3
24.52067
229.0949
4 D
−1.74038
0.010344
Malonylcarnitine
Malonylcarnitine


ETOH 0.3
55.50731
229.1457
4 D
−1.53336
0.028395
Unknown


ETOH 0.3
32.9941
229.2025
24 H
−1.37697
0.03113
Unknown


ETOH 0.3
47.0879
234.125
24 H
−1.63184
0.029169
5-Methoxytryptophan


ETOH 0.3
53.26863
234.1253
4 D
−1.62383
0.026291
5-Methoxytryptophan


ETOH 0.3
3.673694
237.0041
24 H
2.989077
0.011016
Unknown


ETOH 0.3
5.176232
239.9592
24 H
1.640005
0.018097
Unknown


ETOH 0.3
27.39631
243.11
4 D
−1.49547
0.024259
Unknown


ETOH 0.3
6.626769
247.1049
4 D
−4.47566
0.039425
Unknown


ETOH 0.3
9.0276
247.1408
4 D
−2.75089
0.000424
Unknown


ETOH 0.3
18.84552
256.1066
4 D
−2.14073
0.02288
5-Ethyl-5-(1-methyl-3-








carboxypropyl)barbituric








acid


ETOH 0.3
40.75868
267.2543
4 D
−1.6481
0.029485
Unknown


ETOH 0.3
40.75868
267.2543
24 H
−1.49599
0.021245
Unknown


ETOH 0.3
42.3656
268.2487
4 D
−1.51708
0.030774
Unknown


ETOH 0.3
4.86619
271.9364
24 H
4.069637
0.02742
Unknown


ETOH 0.3
22.86183
275.1193
24 H
−2.23674
0.044504
Unknown


ETOH 0.3
5.69776
284.9798
4 D
−1.2223
0.026683
Unknown


ETOH 0.3
14.88092
286.1519
4 D
−1.86167
0.033393
Unknown


ETOH 0.3
75.76147
288.2632
24 H
1.96905
0.001271
Unknown


ETOH 0.3
66.86661
293.1952
4 D
−2.15382
0.004487
Unknown


ETOH 0.3
4.014175
293.9773
4 D
−2.26718
0.013307
Unknown


ETOH 0.3
20.67831
294.1535
4 D
−1.42237
0.008416
Unknown


ETOH 0.3
24.21651
294.1531
24 H
−1.89159
0.02267
Unknown


ETOH 0.3
8.967061
295.1521
4 D
1.467032
0.021323
Unknown


ETOH 0.3
66.35884
298.1537
24 H
3.758351
0.016783
Unknown


ETOH 0.3
19.66398
299.1929
24 H
−1.57058
0.041283
Unknown


ETOH 0.3
7.719471
301.1345
4 D
2.678267
0.046654
Unknown


ETOH 0.3
4.954547
303.8875
24 H
2.069669
0.049847
Unknown


ETOH 0.3
44.09424
313.199
24 H
2.291989
0.005146
Unknown


ETOH 0.3
26.51229
315.6732
4 D
−2.86533
0.000573
Unknown


ETOH 0.3
23.90107
322.1166
4 D
−2.4215
0.010241
Unknown


ETOH 0.3
30.19245
324.1666
24 H
−1.59251
0.037632
Unknown


ETOH 0.3
20.72194
332.1367
4 D
−2.077
0.009795
Unknown


ETOH 0.3
8.542672
337.2012
24 H
1.287435
0.004465
Unknown


ETOH 0.3
5.033976
340.9252
24 H
−1.83604
0.037709
Unknown


ETOH 0.3
5.033976
340.9252
4 D
2.624968
0.049915
Unknown


ETOH 0.3
68.02448
342.1482
24 H
−1.85279
0.043066
Unknown


ETOH 0.3
3.85935
353.2765
4 D
4.904139
0.000229
Unknown


ETOH 0.3
18.50245
360.1321
24 H
−2.28881
0.005116
Unknown


ETOH 0.3
83.72506
362.2787
24 H
−2.54153
0.005266
Unknown


ETOH 0.3
20.16372
365.1606
4 D
−1.92519
0.027055
Unknown


ETOH 0.3
11.47109
375.1898
4 D
2.131693
0.028486
Unknown


ETOH 0.3
26.07722
375.1886
4 D
−4.75123
0.000746
Unknown


ETOH 0.3
41.28494
378.2956
24 H
1.636485
0.027631
Unknown


ETOH 0.3
15.20829
383.1721
4 D
3.377369
0.002214
Unknown


ETOH 0.3
51.65871
386.1724
4 D
4.85106
0.031786
(+)-Eudesmin
(+)-Eudesmin


ETOH 0.3
19.97914
387.0812
4 D
−1.69949
0.015257
Unknown


ETOH 0.3
46.346
388.2349
4 D
−1.53209
0.040255
Unknown


ETOH 0.3
15.90129
393.1889
24 H
−1.51089
0.011717
Unknown


ETOH 0.3
19.69092
393.1886
4 D
−2.05894
0.011258
Unknown


ETOH 0.3
6.259963
396.1687
4 D
2.422002
0.013544
Unknown


ETOH 0.3
17.27421
403.1984
4 D
−2.30266
0.00281
Unknown


ETOH 0.3
21.14975
417.2386
4 D
−1.57309
0.03368
Unknown


ETOH 0.3
33.09057
417.2338
4 D
−1.77978
0.026439
Unknown


ETOH 0.3
13.35295
420.0513
4 D
−1.90198
0.003417
Unknown


ETOH 0.3
27.46219
421.2201
4 D
−2.27332
0.012803
Unknown


ETOH 0.3
18.03482
429.2533
4 D
−2.20091
0.002807
Unknown


ETOH 0.3
54.46495
440.0284
24 H
2.51037
0.011972
Unknown


ETOH 0.3
30.87201
443.2339
4 D
2.171362
0.0186
Unknown


ETOH 0.3
67.0705
443.3216
4 D
1.688451
0.048544
Unknown


ETOH 0.3
51.58546
444.2237
24 H
2.241866
0.044444
Unknown


ETOH 0.3
51.58546
444.2237
4 D
2.030169
0.032667
Unknown


ETOH 0.3
30.05687
444.2789
24 H
−1.83503
0.021764
Unknown


ETOH 0.3
54.8719
446.0431
24 H
−2.22145
0.049006
Unknown


ETOH 0.3
54.8719
446.0431
4 D
1.933882
0.047398
Unknown


ETOH 0.3
29.86415
447.2509
4 D
−1.85819
0.025964
Unknown


ETOH 0.3
29.86415
447.2509
24 H
2.10322
0.036254
Unknown


ETOH 0.3
30.45343
449.2653
4 D
−2.41429
0.016795
Unknown


ETOH 0.3
44.98056
449.2611
24 H
−3.47136
0.038457
Unknown


ETOH 0.3
28.27806
455.2052
24 H
−2.50898
0.005338
Unknown


ETOH 0.3
33.51823
460.9391
4 D
−3.60151
0.010558
Unknown


ETOH 0.3
22.95657
462.2217
4 D
1.935626
0.03474
Unknown


ETOH 0.3
33.5733
463.2914
24 H
−1.66521
0.034862
Unknown


ETOH 0.3
25.3287
464.225
24 H
−1.71665
0.033532
Unknown


ETOH 0.3
30.46172
466.2921
24 H
−1.95938
0.012601
Unknown


ETOH 0.3
33.68894
466.615
24 H
−3.27865
0.008212
Unknown


ETOH 0.3
46.51446
467.3804
24 H
−2.13465
0.013009
Unknown


ETOH 0.3
51.6158
468.2002
4 D
1.919859
0.003122
Unknown


ETOH 0.3
30.37291
471.1928
4 D
2.725649
0.008164
glucuronide


ETOH 0.3
30.72707
471.7804
4 D
−3.44069
0.010281
Unknown


ETOH 0.3
30.28867
478.2761
4 D
1.509949
0.018484
Unknown


ETOH 0.3
10.82859
482.1942
24 H
−1.52795
0.033711
Unknown


ETOH 0.3
72.7735
482.3062
24 H
−2.61806
0.0161
Unknown


ETOH 0.3
10.8217
485.204
24 H
2.038065
0.038466
Unknown


ETOH 0.3
66.73744
487.3472
4 D
2.877867
0.020235
Unknown


ETOH 0.3
30.83472
488.305
24 H
−2.18525
0.009407
Unknown


ETOH 0.3
30.88032
488.8071
24 H
−1.91959
0.040672
Unknown


ETOH 0.3
21.72729
489.2127
4 D
2.372158
0.000369
Unknown


ETOH 0.3
13.78553
502.2258
4 D
1.866325
0.010364
Unknown


ETOH 0.3
18.36887
505.2616
4 D
2.008892
0.036368
Unknown


ETOH 0.3
5.891069
509.6704
4 D
1.467845
0.0228
Unknown


ETOH 0.3
31.20706
510.3182
24 H
−2.26373
0.006715
Unknown


ETOH 0.3
31.22083
510.8202
24 H
−2.04514
0.041219
Unknown


ETOH 0.3
31.22083
510.8202
4 D
2.502378
0.010461
Unknown


ETOH 0.3
46.57666
518.3914
4 D
2.288814
0.002533
Unknown


ETOH 0.3
46.57666
518.3914
24 H
−2.70682
0.017765
Unknown


ETOH 0.3
34.35986
521.9924
24 H
−1.58403
0.024454
Unknown


ETOH 0.3
31.53434
523.8187
24 H
−2.17272
0.02888
Unknown


ETOH 0.3
51.73057
526.2773
4 D
2.714525
0.010415
Unknown


ETOH 0.3
71.36012
528.3631
4 D
2.361003
0.026297
Unknown


ETOH 0.3
23.87065
530.314
4 D
2.211921
0.001298
L-Oleandrosyl-oleandolide


ETOH 0.3
32.50661
531.2876
4 D
2.36084
0.014947
Unknown


ETOH 0.3
35.58454
531.3191
4 D
−3.0409
0.000281
Unknown


ETOH 0.3
66.31491
531.3736
4 D
2.87388
0.031879
Unknown


ETOH 0.3
31.58889
532.8335
24 H
−2.16926
0.015971
Unknown


ETOH 0.3
51.52268
539.4374
24 H
−1.92987
0.031525
Unknown


ETOH 0.3
32.24719
541.3274
24 H
−2.12255
0.01445
Unknown


ETOH 0.3
31.8519
554.3444
24 H
−2.36953
0.00655
Unknown


ETOH 0.3
31.891
554.8471
24 H
−2.29708
0.010734
Unknown


ETOH 0.3
15.78741
555.2406
4 D
2.470837
0.001092
Unknown


ETOH 0.3
5.742094
555.8505
4 D
−1.3396
0.023948
Unknown


ETOH 0.3
5.742094
555.8505
24 H
−1.51803
0.031838
Unknown


ETOH 0.3
88.02533
556.3971
4 D
−2.38386
0.035829
Unknown


ETOH 0.3
31.97996
559.8329
4 D
−2.56596
0.002155
Unknown


ETOH 0.3
14.9927
566.2265
4 D
1.624054
0.006806
Unknown


ETOH 0.3
24.7039
574.3397
4 D
1.523934
0.011558
Unknown


ETOH 0.3
47.90467
576.096
4 D
1.557573
0.020904
Unknown


ETOH 0.3
32.15777
576.3582
24 H
−2.20886
0.012421
Unknown


ETOH 0.3
16.90923
577.2825
4 D
−8.91726
0.02781
Unknown


ETOH 0.3
5.903169
579.2519
4 D
−2.11184
0.001075
Ethanesulfonic acid


ETOH 0.3
5.903169
579.2519
24 H
−1.48021
0.01083
Ethanesulfonic acid


ETOH 0.3
31.54325
591.3789
24 H
−1.98165
0.010883
Unknown


ETOH 0.3
25.14927
596.3543
4 D
1.545421
0.015277
L-Urobilinogen;


ETOH 0.3
25.14927
596.3543
24 H
1.834898
0.021555
L-Urobilinogen;


ETOH 0.3
32.67372
603.3535
4 D
−2.93997
0.007904
Unknown


ETOH 0.3
56.3513
611.4952
24 H
−1.9811
0.007557
Unknown


ETOH 0.3
4.936704
611.8727
4 D
2.009588
0.018619
Unknown


ETOH 0.3
32.70236
611.871
24 H
−2.19208
0.044039
Unknown


ETOH 0.3
8.056862
612.1509
24 H
−1.59538
0.010611
Oxidized glutathione


ETOH 0.3
33.68866
619.3409
4 D
2.125939
0.015211
Unknown


ETOH 0.3
32.73907
620.8861
24 H
−2.32076
0.039661
Unknown


ETOH 0.3
32.08734
635.4065
4 D
1.394744
0.031645
Unknown


ETOH 0.3
32.95522
642.397
24 H
−2.21146
0.035834
Unknown


ETOH 0.3
5.903429
646.7084
4 D
2.946495
2.66E−05
Unknown


ETOH 0.3
8.787827
658.2544
4 D
−3.20961
0.030138
Unknown


ETOH 0.3
26.7452
661.3846
4 D
1.546707
0.010714
Unknown


ETOH 0.3
16.3338
666.3836
24 H
−1.37135
0.037278
Unknown


ETOH 0.3
33.48766
677.9101
24 H
−2.64653
0.009907
Unknown


ETOH 0.3
40.84822
702.2497
24 H
1.283337
0.019733
Neu5Acalpha2-3Galbeta1-








4Glcbeta-Sp


ETOH 0.3
40.84822
702.2497
4 D
−2.21591
0.004389
Neu5Acalpha2-3Galbeta1-








4Glcbeta-Sp


ETOH 0.3
30.43889
707.3933
24 H
−1.79166
0.048232
Unknown


ETOH 0.3
56.18269
707.4296
24 H
−2.43361
0.009442
Unknown


ETOH 0.3
4.826824
711.8344
24 H
−2.25605
0.017007
Unknown


ETOH 0.3
47.76987
731.0954
4 D
−3.25036
0.027339
Unknown


ETOH 0.3
5.918027
732.007
4 D
1.76125
0.038454
Unknown


ETOH 0.3
35.028
751.4193
24 H
−1.70279
0.045682
Unknown


ETOH 0.3
35.028
751.4193
4 D
1.845101
0.0375
Unknown


ETOH 0.3
69.32865
765.5211
24 H
1.884393
0.027105
Unknown


ETOH 0.3
34.33545
774.4767
24 H
−2.34161
0.036388
Unknown


ETOH 0.3
34.60124
796.9917
4 D
1.688919
0.047852
Unknown


ETOH 0.3
4.613879
820.8181
24 H
−1.85112
0.038895
Unknown


ETOH 0.3
4.613879
820.8181
4 D
−1.57113
0.014605
Unknown


ETOH 0.3
5.259716
888.8041
24 H
1.221624
0.043348
Unknown


ETOH 0.3
5.217833
913.8074
24 H
−1.88465
0.026148
Unknown


ETOH 0.3
5.399211
921.0025
4 D
1.944905
2.78E−05
Unknown


ETOH 0.3
5.387775
922.0048
24 H
−2.75471
0.015691
Unknown


ETOH 0.3
3.680188
980.075
4 D
1.480926
0.012893
Unknown


ETOH 0.3
3.646902
994.0917
4 D
1.604696
0.000395
Unknown


ETOH 0.3
3.705141
1008.072
4 D
1.415783
0.021503
Unknown


ETOH 0.3
5.177162
1038.786
4 D
1.588208
0.030971
Unknown


ETOH 0.3
5.8905
1040.323
4 D
−1.47887
0.009656
Unknown










All references cited herein are incorporated by reference. In addition, the invention is not intended to be limited to the disclosed embodiments of the invention. It should be understood that the foregoing disclosure emphasizes certain specific embodiments of the invention and that all modifications or alternatives equivalent thereto are within the spirit and scope of the invention as set forth in the appended claims.

Claims
  • 1. A method for identifying one or a plurality of cellular metabolites having a molecular weight of from about 10 to about 1500 Daltons that is differentially produced in human embryonic stem cells (hESCs) or human pluripotent stem cells contacted with a test compound from a population of secreted cellular metabolites, the method comprising the steps of: a) culturing hESCs or human pluripotent stem cells in the presence or absence of a test compound;b) separating members of the population of cellular metabolites having a molecular weight of from about 10 to about 1500 Daltons that are secreted from hESCs or human pluripotent stem cells;c) detecting one or a plurality of differentially produced cellular metabolites having a molecular weight of from about 10 to about 1500 Daltons from hESCs or human pluripotent stem cells; andd) identifying at least one cellular metabolite having a molecular weight of from about 10 to about 1500 Daltons that is differentially produced in cells cultured in the presence of the test compound.
  • 2. A method according to claim 1, wherein at least one of the cellular metabolites is produced in greater amounts in the presence of the test compound than in the absence of the test compound.
  • 3. A method according to claim 1, wherein at least one of the cellular metabolites is produced in greater amounts in the absence of the test compound than in the presence of the test compound.
  • 4. A method according to claim 1, wherein the cellular metabolite has a molecular weight of from about 100 to about 1000 Daltons.
  • 5. A method according to claim 1, wherein the test compound is a toxic or teratogenic compound.
  • 6. A method according to claim 1, wherein one or a plurality of cellular metabolites is separated using a physical separation method.
  • 7. A method according to claim 6, wherein the physical separation method is liquid chromatography/electrospray ionization time of flight mass spectrometry.
  • 8. A method according to claim 1, wherein the cellular metabolites are tetrahydrofolate, dihydrofolate or other metabolites in the folate metabolic pathway, glutathione, or oxidized glutathione.
  • 9. A method according to claim 1, wherein the cellular metabolites are kynurenine, 8-methoxykynurenate, N′-formylkynurenine 7,8-dihydro-7,8-dihydroxykynurenate, 5-Hydroxytryptophan, N-acetyl-D-tryptophan, glutamate, pyroglutamic acid or other metabolites in the tryptophan or glutamate metabolic pathways, histamine, dopamine, 3,4-dihydroxybutyric acid, serotonin, or gamma-aminobutyric acid (GABA).
  • 10. A method according to claim 1, wherein a plurality of cellular metabolites are identified.
  • 11. A method according to claim 10 wherein the plurality of identified cellular metabolites comprise a biomarker profile.
  • 12. A method according to claim 11, wherein one of the cellular metabolites comprising a biomarker profile is kynurenine.
  • 13. A method according to claim 10, wherein the test compound is a toxic or teratogenic compound.
  • 14. A method according to claim 13, wherein the plurality of identified cellular metabolites comprise a biomarker profile characteristic of hESC or human pluripotent stem cell response to a toxic or teratogenic compound.
  • 15. A method of claim 1, further comprising the step of identifying at least one cellular metabolite having a molecular weight of from about 10 to about 1500 Daltons that is differentially produced in the cells in the presence or absence of the test compound in a biomarker profile comprising one or a plurality of cellular metabolites having a molecular weight of from about 10 to about 1500 Daltons that are differentially produced in human embryonic stem cells (hESCs) or human pluripotent stem cells contacted with a toxic compound or compounds.
  • 16. The method of claim 1, wherein at least two cellular metabolites having a molecular weight of from about 10 to about 1500 Daltons that are differentially produced in the cells in the presence or absence of the test compound are detected.
  • 17. A method for screening a test compound to identify an effect of the compound on human embryonic stem cells (hESCs) or human pluripotent stem cells contacted with the test compound, the method comprising the steps of: a) culturing hESCs or human pluripotent stem cells in the presence or absence of a test compound;b) separating members of a population of cellular metabolites having a molecular weight of from about 10 to about 1500 Daltons that are secreted from hESCs or human pluripotent stem cellsc) detecting one or a plurality of differentially produced cellular metabolites having a molecular weight of from about 10 to about 1500 Daltons; andd) identifying the effect of a compound on human embryonic stem cells (hESCs) or human pluripotent stem cells by identifying at least one cellular metabolite having a molecular weight of from about 10 to about 1500 Daltons that is differentially secreted between cells cultured in the presence versus the absence of the test compound.
  • 18. A method according to claim 17, wherein at least one of the cellular metabolites is produced in greater amounts in the presence of the test compound than in the absence of the test compound.
  • 19. A method according to claim 17, wherein at least one of the cellular metabolites is produced in greater amounts in the absence of the test compound than in the presence of the test compound.
  • 20. A method according to claim 17, wherein at least one of the cellular metabolites has a molecular weight of from about 100 to about 1000 Daltons.
  • 21. A method according to claim 17, wherein the test compound is a toxic or teratogenic compound.
  • 22. A method according to claim 17, wherein one or a plurality of cellular metabolites is separated using a physical separation method.
  • 23. A method according to claim 22, wherein the physical separation method is liquid chromatography/electrospray ionization time of flight mass spectrometry.
  • 24. A method according to claim 17, wherein the cellular metabolites are tetrahydrofolate, dihydrofolate or other metabolites in the folate metabolic pathway, glutathione, or oxidized glutathione.
  • 25. A method according to claim 17, wherein the cellular metabolites are kynurenine, 8-methoxykynurenate, N′-formylkynurenine 7,8-dihydro-7,8-dihydroxykynurenate, 5-Hydroxytryptophan, N-acetyl-D-tryptophan, glutamate, pyroglutamic acid or other metabolites in the tryptophan or glutamate metabolic pathways, histamine, dopamine, serotonin, gamma-aminobutyric acid (GABA) or other butyric acid species.
  • 26. A method according to claim 17 wherein a plurality of cellular metabolites are identified.
  • 27. A method according to claim 26, wherein the plurality of identified cellular metabolites comprise a biomarker profile.
  • 28. A method according to claim 27, wherein one of the cellular metabolites comprising a biomarker profile is kynurenine.
  • 29. A method according to claim 27, wherein the test compound is a toxic or teratogenic compound.
  • 30. A method according to claim 29, wherein the plurality of identified cellular metabolites comprise a biomarker profile characteristic of hESC or human pluripotent stem cells response to a toxic or teratogenic compound.
  • 31. A method of claim 17, further comprising the step of identifying at least one cellular metabolite having a molecular weight of from about 10 to about 1500 Daltons that is differentially produced in the cells in the presence or absence of the test compound in biomarker profile comprising one or a plurality of cellular metabolites having a molecular weight of from about 10 to about 1500 Daltons that are differentially produced in human embryonic stem cells (hESCs) or human pluripotent stem cells contacted with a toxic compound or compounds.
  • 32. The method of claim 17, wherein at least two cellular metabolites having a molecular weight of from about 10 to about 1500 Daltons that are differentially produced in the cells in the presence or absence of the test compound are detected.
  • 33. A method for assaying a test compound for toxicity or teratogenicity to hESC-derived lineage-specific cells or human pluripotent stem cell-derived lineage-specific cells contacted with the test compound, the method comprising the steps of: a) culturing hESC-derived lineage-specific cells or human pluripotent stem cell-derived lineage-specific cells in the presence or absence of a test compound;b) separating members of a population of cellular metabolites having a molecular weight of from about 10 to about 1500 Daltons secreted from or hESC-derived lineage-specific cells or human pluripotent stem cell-derived lineage-specific cells;c) detecting one or a plurality of cellular metabolites having a molecular weight of from about 10 to about 1500 Daltons produced by hESC-derived lineage-specific cells or human pluripotent stem cell-derived lineage-specific cells contacted with a compound; andd) identifying the toxicity or teratogenicity of the test compounds wherein hESC-derived lineage-specific cells or human pluripotent stem cell-derived lineage-specific cells contacted with a test compound differentially produce one or a plurality of cellular metabolites having a molecular weight of from about 10 to about 1500 Daltons.
  • 34. A method according to claim 33, wherein at least one of the cellular metabolites is produced in greater amounts in the presence of the test compound than in the absence of the test compound.
  • 35. A method according to claim 33, wherein at least one of the cellular metabolites is produced in greater amounts in the absence of the test compound than in the presence of the test compound.
  • 36. A method according to claim 33, wherein the cellular metabolite has a molecular weight of from about 100 to about 1000 Daltons.
  • 37. A method according to claim 33, wherein the test compound is a toxic or teratogenic compound.
  • 38. A method according to claim 33, wherein one or a plurality of cellular metabolites is separated using a physical separation method.
  • 39. A method according to claim 38, wherein the physical separation method is liquid chromatography/electrospray ionization time of flight mass spectrometry.
  • 40. A method according to claim 33, wherein the cellular metabolites are tetrahydrofolate, dihydrofolate or other metabolites in the folate metabolic pathway, glutathione, or oxidized glutathione.
  • 41. A method according to claim 33, wherein the cellular metabolites are kynurenine, 8-methoxykynurenate, N′-formylkynurenine 7,8-dihydro-7,8-dihydroxykynurenate 5-Hydroxytryptophan, N-acetyl-D-tryptophan, glutamate, pyroglutamic acid or other metabolites in the tryptophan or glutamate metabolic pathways, histamine, dopamine, 3,4-dihydroxybutyric acid, serotonin, gamma-aminobutyric acid (GABA) or other butyric acid species.
  • 42. A method according to claim 33, wherein a plurality of cellular metabolites are identified.
  • 43. A method according to claim 42, wherein the plurality of identified cellular metabolites comprise a biomarker profile.
  • 44. A method according to claim 43, wherein one of the cellular metabolites comprising a biomarker profile is kynurenine.
  • 45. A method according to claim 44, wherein the test compound is a toxic or teratogenic compound.
  • 46. A method according to claim 33, wherein the plurality of identified cellular metabolites comprise a biomarker profile characteristic of hESC response to a toxic or teratogenic compound.
  • 47. A method of claim 33, further comprising the step of identifying at least one cellular metabolite having a molecular weight of from about 10 to about 1500 Daltons that is differentially produced in the cells in the presence or absence of the test compound in a biomarker profile comprising one or a plurality of cellular metabolites having a molecular weight of from about 10 to about 1500 Daltons that are differentially produced in hESC-derived lineage-specific cells or human pluripotent stem cell-derived lineage-specific cells contacted with a toxic compound or compounds.
  • 48. The method of claim 33, wherein at least two cellular metabolites having a molecular weight of from about 10 to about 1500 Daltons that are differentially produced in the cells in the presence or absence of the test compound are detected.
Parent Case Info

This application claims the priority benefit of U.S. provisional patent applications, Ser. Nos. 60/790,647, filed Apr. 10, 2006, and 60/822,163, filed Aug. 11, 2006, the entirety of which are incorporated by reference herein.

US Referenced Citations (6)
Number Name Date Kind
6197575 Griffith et al. Mar 2001 B1
6200806 Thomson Mar 2001 B1
20020019023 Dasseux et al. Feb 2002 A1
20030219866 Kruijer et al. Nov 2003 A1
20040073958 Katsuki et al. Apr 2004 A1
20040121305 Wiegand et al. Jun 2004 A1
Foreign Referenced Citations (10)
Number Date Country
2560334 Oct 2005 CA
0937779 Aug 1999 EP
0194616 Dec 2001 WO
03005628 Jan 2003 WO
03018760 Mar 2003 WO
03089635 Oct 2003 WO
2004065616 Aug 2004 WO
2005005162 Jan 2005 WO
2005005621 Jan 2005 WO
2005080551 Sep 2005 WO
Non-Patent Literature Citations (84)
Entry
Meisel et al. “Human bone marrow stronal cells inhibit allogeneic T-cell responses by indoleamine 2,3-dioxygenase-mediated tryptophan degradation”, Immunobiology, 2004, 103(12):4619-4621.
Zhang et al. “Mass spectral evidence for carbonate-anion-radical-induced posttranslational modification of tryptophan to kynurenine in human Cu, Zn superoxide dismutase”, Free Radical Biology & Medicine, 2004, 2018-2026.
Trosko, J.E., “Use of human embryonic and adult stem cells for drug screening and safety assessment,” Toxicology, Sep. 1, 2006, 226:31.
John C. Lindon et al., “Contemporary issues in toxicology the role metabonomics in toxicology and its evaluation by the COMET project,” Toxicology and Applied Pharmacology, Mar. 15, 2003 187:3 137-146.
Derek J. Crockford et al., “Statistical Heterospectroscopy, an Approach to the Integrated Analysis of NMR and UPLC-MS Data Sets: Application in Metabonomic Toxicology Studies,” Analytical Chemistry, Jan. 15, 2006, 78:2 363-361.
Lance Hareng et al., “The Integrated Project ReProTect: A novel approach in reproductive toxicity hazard assessment,” Reproductive Toxicology, Sep. 2005, 20:3 441-452.
John McNeish, “Embryonic Stem Cells in Drug Discovery,” Nature Reviews Drug Discovery, 2004 3:1 70-80.
Mark A Viant et al., “NMR-derived developmental metabolic trajectories: an approach for visualizing the toxic actions of trichloroethylene during embryogenesis,” Metabolomics, Apr. 2005 1:2 149-158.
Adab et al., “The longer term outcome of children born to mothers with epilepsy,” 2004, J Neurol Neurosurg Psychiatry 75:1575-83.
Beckman & Brent, “Mechanism of Teratogenesis,” 1984, Annu Rev Pharmacol 24:483-500.
Bjerkedal et al., “Valproic Acid and Spina Bifida,” 1982, Lancet 2:1096.
Brent & Beckman, “Enviromental Teratogens,” Mar.-Apr. 1990, Bull NY Acad Med 66:123-63.
Capuron et al., “Interferon-Alpha-Induced Changes in Tyrptophan Metabolism: Relationship to Depression and Paroxetine Treatment,” 2003, Biol Psychiatry 54:906-14.
Chiarugui et al., “Similarities and differences in the neuronal death processes activated by 3OH-kynurenine and quinolinic acid,” 2001, J Neurochem 77:1310-8.
Chugani, “Serotonin in Autism and Pediatric Epilepsies,” 2004, Ment Retard Dev Disabil Res Rev 10:112-116.
Claudio et al., “NIEHS Investigates Links between Children, the Environment, and Neurotoxicity,” Jun. 2001, Environm Health Perspect 109(6):A254-A261.
Daston & Naciff, “Gene expression changes related to growth and differentiation in the fetal and juvenile reproductive system of the female rat: evaluation of microarray results,” 2005, Reprod Toxicology 19:381-94.
Enviromental Protective Agency (EPA), “What Do We Really Know About the Safety of High Production Volume Chemicals,” 1998, Chemical Hazard Data Availability Study, Office of Pollution Prevention and Toxins.
Fella et al., “Use of two-dimensional gel electrophoresis in predictive toxicology: Identification of potential early protein biomarkers in chemically induced hepatocarcinogenesis,” 2005, Protemics 5:1914-21.
Franks et al., “Thalidomide,” 2004, Lancet 363:1802-11.
General Accounting Office (GAO), “Toxic Substances Control Act: Preliminary Observations on Legislative Changes to Make TSCA More Effective,” 1994, Testimony Jul. 13, 1994, GAO/T-RCED-94-263.
Greaves et al., “First Does of Potential New Medicines to Humans: How Animals Help,” 2004, Nat Rev Drug Discov 3:226-36.
Groenen et al., “High-resolution 1H NMR spectroscopy of amniotic fluids from spina bifida fetuses and controls,” 2004, Eur J Obstet Gynecol Reprod Biol.;112:16-23.
Guillemin et al., “Quinolinic acid selectively induces apoptosis of human astrocytes: potential role in AIDS dementia complex,” 2005, J Neuroinflammation 2:16.
He et al., “Human Embryonic Stem Cells Develop Into Multiple Types of Cardiac Myocytes,” 2003, Circ Res 93:32-9.
Huuskonen, “New models and molecular markers in evaluation of developmental toxicity,” 2005, Toxicology & Applied Pharm 207: S495-S500.
Kocki et al., “Enhancement of brain kynurenic acid production by anticonsulvants—Novel mechanism of antiepileptic activity,” 2006, Eur J Pharmacol 542:147-51.
Kohl et al., “Measurement of tryptophan, kynurenine and neopterin in women with and without postpartum blues,” 2005, J Affect Disord 86:135-42.
Levenstein et al.,“Basic Fibroblast Growth Factor Support of Human Embryonic Stem Cell Self Renewal,” 2005, Stem Cells 24:568-574.
Li et al., “Targeted Mutation of the DNA Methyltransferase Gene Results in Embryonic Lethality,” 1992, Cell 69:915-26.
Li et al., “Expansion of Human Embryonic Stem Cells in Defined Serum-Free Medium Devoid of Animal-Derived Products,” 2005, Biotechnol Bioeng 91:688-698.
Livak & Schmittgen, “Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2-ΔΔCT Method,” 2001, Methods 25:402-8.
Ludwig et al., “Feeder-independent culture of human embryonic stem cells,” 2006, Nat Methods 3: 637-46.
Meador et al., “In utero antiepileptic drug exposure,” 2006, Neurology 67:407-412.
Miller et al, “Upregulation of the initiating step of the kynurenine pathway in postmortem anterior cingulate cortex from individuals with schizophrenia and bipolar disorder,” 2006, Brain Res 16:25-37.
Miyazaki et al., “Maternal administration of thalidomide or valproic acid causes abnormal serotonergic neurons in the offspring: implication for pathogenesis of autism ,” 2005 Int J Devl Neuroscience 23:287-97.
Napierala et al, “Mutations and promoter SNPs in RUNX2, a transcriptional regulator of bone formation,” 2005, Mol Genet Metab 86:257-68.
Narita et al., “Increased Monamine Concentration in the Brain and Blood of Fetal Thalidomide- and Valproic Acid-Exposed Rat: Putative Animal Models for Autism,” 2000, Pediatric Res 52:576-79.
Nemeth et al., “Role of Kynurenines in the Central and Peripherial Nervous Systems,” 2005, Curr Neurovasc Res 2:249-60.
Okada et al., “Polycomb Homologs Are Involved in Teratogenicity Valproic Acid in Mice,” 2004, Birth Defects Res A Clin Mol Teratol 70:870-879.
Ornoy et al., “Fetal effects of primary and secondary cytomegalovirus infection in pregnancy,” 2006, Reproductive Toxicol 21:399-409.
Perkins and Stone, “An iontophoretic investigation of the actions of convulsant kynurenines and their interaction with the endogenous excitant quinolinic acid,” 1982, Brain Res 247:184-187.
Piersma, “Validation of alternative methods for developmental toxicity testing,” 2004, Toxicology Letters 149:147-53.
Rasalam et al., “Characteristics of fetal anticonvulant syndrome associated autistic disorder,” 2005, Dev Med Child Neuro 47:551-555.
Reubinoff et al., “Embryonic stem cell lines from human blastocysts: somatic differentiation in vitro,” 2000, Nature Biotechnology 18:399-404.
Rosano et al., “Infant mortality and congenital anomalies from 1950 to 1994: an international perspective,” 2000, J Epidemiology Community Health 54:660-66.
Sabatine et al., “Metabolomic Identification of Novel Biomarkers of Mycardial Ischemia,” 2005 Circulation 112:3868-875.
Shaw et al., “Periconceptional Vitamin Use, Dietary Folate, and the Occurrence of Neural Tube Defects,” 1995, Epidemology 6:219-226.
Soga et al., “Differential Metabolomics Reveals Ophthalmic Acid as an Oxidative Stress Biomarker Indicating Hepatic Glutathione Consumption,” 2006, J Biol Chem 281:16788-78.
Spielmann et al., “The Embryonic Stem Cell Test, an In Vitro Embryotoxicity Test Using Two Permanent Mouse Cell Lines: 3T3 Fibroblasts and Embryonic Stem Cells,” 1997, In Vitro Toxicology 10:119-27.
Wang et al., “Kynurenic Acid as a Ligand for Orphan G Protein-coupled Receptor GPR35*,” 2006, J Biol Chem 281:22021-22028, published electronically on Jun. 5, 2006.
Want et al., “The Expanding Role of Mass Spectrometry in Metabolite Profiling and Characterization,” 2005 Chem Bio Chem 6:1941-51.
Williams et al., “Fetal valproate syndrome and autism: additional evidence of an assosiation,” 2001, Dev Med Child Neurol 43:202-06.
Wu and McAllister, “Exact mass measurement on an electrospray ionization time-of-flight mass spectrometer: error distribution and selective averaging,” 2003, J Mass Spectrom 38:1043-53.
Wyszynski et al., “Increased rate of major malformations in offspring exposed to valproate during pregnancy,” 2005, Neurology 64:961-5.
Yan et al., “Directed Differentiation of Dopaminergic Neuronal Subtypes from Human Embryonic Stem Cells,” 2005, Stem Cells 22:781-90.
Ye et al., “FGF and Shh Signals Control Dopaminergic and Serotonergic Cell Fate in the Anterior Neural Plate,” 1998, Cell 93:755-66.
Zeng et al., “Dopaminergic Differentiation of Human Embryonic Stem Cells,” 2004, Stem Cell 22:925-40.
Zhao et al., “Neural Tube Defects and Maternal Biomarkers of Folate, Homocysteine, and Glutathione Metabolism,” 2006, Birth Defects Res A Clin Mol Teratol 76:230-6.
Bhogal et al., 2005, Trends in Biotechnology 23:299-307.
Chen et al., 2006, Journal of Proteome Research in Toxicology, 5:995-1002.
Coecke et al., 2006, Environmental Toxicology and Pharmacology, 21:153-167.
Garrod et al., 2005, Chemical Research in Toxicology, 18:115-122.
Pellizzer et al., 2005, ALTEX, 22:47-57.
Lenz et al., 2004, Analyst, 129:535-541.
Scholz et al.,1999 Toxicology In Vitro, 13:675-681.
Barry et al., 2005, “Immunogenicity of adult mesenchymal stem cells: lessons from the fetal allograft.” Stem Cells Dev. 14: 252-65.
Bonda et al., 2010, “Indoleamine 2,3-dioxygenase and 3-hydroxykynurenine modifications are found in the neuropathology of Alzheimer's disease.” Redox Rep. 15: 161-8.
Copland et al., 2008, “CD34 expression on murine marrow-derived mesenchymal stromal cells: impact on neovascularization.” Exp. Hematol. 36: 93-103.
English et al., 2007, “IFN-gamma and TNF-alpha differentially regulate immunomodulation by murine mesenchymal stem cells.” Immunol Lett. 110: 91-100.
Gallo et al., 2007, “Limited plasticity of mesenchymal stem cells cocultured with adult cardiomyocytes.” J Cell Biochem. 100: 86-99.
Jaishankar et al., 2009, “Human embryonic and mesenchymal stem cells express different nuclear proteomes.” Stem Cells Dev. 18: 793-802.
Roche et al., 2009, “Comparative proteomic analysis of human mesenchymal and embryonic stem cells: towards the definition of a mesenchymal stem cell proteomic signature.” Proteomics. 9: 223-32.
Rose et al., 2008, “Bone marrow-derived mesenchymal stromal cells express cardiac-specific markers, retain the stromal phenotype, and do not become functional cardiomyocytes in vitro.” Stem Cells. 26: 2884-92.
Shi et al., 2008, “HRMAS 1H-NMR measured changes of the metabolite profile as mesenchymal stem cells differentiate to targeted fat cells in vitro: implications for non-invasive monitoring of stem cell differentiation in vivo.” J Tissue Eng Regen Med. 2: 482-90.
Stone and Darlington, 2002, “Endogenous kynurenines as targets for drug discovery and development.” Nat Rev Drug Discov. 1: 609-20.
Taylor et al., 1991, “Relationship between interferon-gamma, indoleamine 2,3-dioxygenase, and tryptophan catabolism.” FASEB J. 5: 2516-22.
Thomson et al., 1998, “Embryonic stem cell lines derived from human blastocysts.” Science. 282: 1145-1147.
Yan et al., 2005, “Directed differentiation of dopaminergic neuronal subtypes from human embryonic stem cells.” Stem Cells. 23:781-790.
Yanes et al., 2010, “Metabolic oxidation regulates embryonic stem cell differentiation.” Nat Chem Biol. 6: 411-7.
Harrigan et al., “Medicinal chemistry, metabolic profiling and drug target discovery: a role for metabolic profiling in reverse pharmacology and chemical genetics,” Mini Rev Med Chem., 5(1):13-20 (2005).
Hayman et al., “Proteomic identification of biomarkers expressed by human pluripotent stem cells,” Biochem Biophys Res Commun., 316(3):.018-23 (2004).
Bremmer et al., “The use of embryonic stem cells for regulatory developmental toxicity testing in vitro—the current status of test development,” 2004, Curr Pharm Des., 10:2733-47.
Klemm et at., “Neurotoxicity of active compounds—establishment of hESC-lines and proteomics technologies for human embryo—and neurotoxicity screening and biomarker identification,” 2004, ALTEX, 3:41-8.
Related Publications (1)
Number Date Country
20070248947 A1 Oct 2007 US
Provisional Applications (2)
Number Date Country
60790647 Apr 2006 US
60822163 Aug 2006 US