Patent Application
20230227814
Provided herein is a system for multiplexed genome editing or a two or three-way combinatorial CRISPR screening. Also provided is high-throughput screening of disease-alleviating genetic combinations to identify two-way and three-way synergistic drug combinations as potential treatment regimens. Also provided is a lentiviral three-way combinatorial guide RNA expression cassette and combinatorial guide RNA libraries.
Despite the promise of combination therapies to enhance treatment efficacy for various diseases (Al-Lazikani et al., 2012), only a limited number of effective combinations, especially those comprising three or more drugs (Table S1), have been discovered so far. Drug combination effect is difficult to predict due to unanticipated synergy or antagonism, and is not simply the sum of the effects brought by each drug (Borisy et al., 2003). Microplate arrays are coupled to robotics systems to screen large panels of drug combinations. However, as the number of experiments grows exponentially with the number of drugs and the order of combinatorial complexity being studied, such approach can become prohibitively expensive. RNA interference and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-based genetic perturbation systems have been applied to facilitate the screening of effective drug target pairs (Doench, 2018; Wong et al., 2016b), but no library assembly and screening method has been validated to simultaneously evaluate more than two targets. This could be attributed to the relatively low and variable cleavage efficiency for polycistronic systems to express multiple RNAs (Han et al., 2017; Xu et al., 2017), and/or the characterization of high-order combinations requires large-scale oligo synthesis and high sequencing costs (elaborated in Design). Mathematical models have been developed for predicting three-way and higher-order drug interactions (Cokol et al., 2017; Wood et al., 2012; Zimmer et al., 2016), but high-throughput methods are needed to experimentally validate sets of potential combinations. Breaking through the bottlenecks, here we establish and validate an extensible platform (named CombiGEM-CRISPR v2.0) for rapid screening of disease-alleviating gene knockouts to study high-order genetic interactions, identify potential therapeutic target combinations, and deploy their matching drug regimens for further testing.
Provided is a CRISPR-based multi-gene knockout screening system and new toolkits for extensible assembly of barcoded high-order combinatorial guide RNA libraries en masse. We apply this system for systematically identifying not only pairwise but also three-way synergistic therapeutic target combinations, and successfully validated double and triple combination regimens for suppression on cancer cell growth and protection against Parkinson's disease-associated toxicity. This system overcomes the practical challenges to experiment on a large number of high-order genetic and drug combinations and is applicable for uncovering the rare synergistic interactions between druggable targets.
Systematically characterizing genetic interactions among multiple (i.e. more than two) elements. One application of this system is to enable high-throughput screening of disease alleviating genetic combinations to identify two-way and even three-way synergistic drug combinations as potential treatment regimens. Drug combination effect is difficult to predict due to unanticipated synergy or antagonism and is not simply the sum of the effects brought by each drug. Discovering effective drug combinations for diseases has been a major challenge because of the technical difficulties in systematically screening a vast number of possible combinations. For example, microplate arrays are coupled to robotics systems to screen large panels of drug combinations. However, as the number of experiments grows exponentially with the number of drugs and the order of combinatorial complexity being studied, such approach requiring a large amount of drugs can become prohibitively expensive. Thus, despite the promise of combination therapies to enhance treatment efficacy for various diseases, only a limited number of effective combinations, especially those comprising more than two drugs, have been discovered so far.
Provided herein is a system for multiplexed genome editing or a two or three-way combinatorial CRISPR screening comprising: a lentiviral vector comprising human U6 (hU6) promoter, mouse U6 (mU6) promoter and human H1 (hH1) promoter expressing an array of three or more barcoded guide RNAs (“gRNAs”) oligo pairs, the promoters having a 3′ end comprising modified hU6, mU6 and hH1 promoter sequences for paired annealing of the barcoded gRNAs oligo pairs.
Provided herein is a system for multiplexed genome editing or a two or three-way combinatorial CRISPR screening comprising: a lentiviral vector comprising human U6 (hU6) promoter, mouse U6 (mU6) promoter and human H1 (hH1) promoter expressing an array of three or more barcoded guide RNAs (“gRNAs”) oligo pairs, the hU6 promoter having an unmodified promoter sequence at 3′ end and the mU6 and hH1 promoters having modified promoter sequences at 3′ end for paired annealing of the barcoded gRNAs oligo pairs.
In one embodiment, the paired annealing of the barcoded gRNAs oligo pairs form RNA scaffolds.
In one embodiment, the combinatorial gRNA library is assembled by CombiGEM-CRISPR v2.0.
In one embodiment, the lentiviral vector transfects human cells and the barcoded gRNAs are delivered to the human cells.
In one embodiment, the system further comprising quantitation of barcoded gRNAs using next-generation sequencing at a time point post transfection.
In one embodiment, the three-way combinatorial CRISPR screen is a high-throughput screen.
In one embodiment, the gRNAs form a RNA scaffold sequence comprising the same 3′ end of the modified hU6, mU6 and hH1 promoter sequences as the combinatorial gRNA libraries.
In one embodiment, the gRNAs form a RNA scaffold sequence comprising the same 3′ end of the hU6, mU6 and hH1 promoter sequences as the combinatorial gRNA libraries.
Provided herein is a method to screen for at least a three-way drug target combination; said method comprises: (i) providing a gRNA library targeting druggable genes of HGSOC wherein each gene comprises an array of 3 gRNAs; (ii) transfecting human cells; and (iii) quantifying barcoded gRNAs using next-generation sequencing.
Provided herein is a system to screen for at least a three-way drug target combination comprising: (i) providing a lentiviral three-way combinatorial gRNA expressing construct that express gRNAs; (ii) transfecting human cells with fluorescence reporter gene; and (iii) measuring percentage of cell population positive for fluorescence at a time period post-transfection.
In one embodiment, the fluorescence is measured using a flow cytometry and wherein the fluorescence is GFP, RFP and BFP fluorescence.
In one embodiment, the gRNAs target an exonic regions of green (GFP), red (RFP), and blue (BFP) fluorescent protein reporter genes.
In one embodiment, the human cells are ovarian cancer cells.
In one embodiment, the ovarian cancer cells are high-grade serous ovarian cancer (“HGSOC”) cells.
In one embodiment, the ovarian cancer cells are OVCAR8-ADR and OVCAR8-ADR-Cas9.
Provided herein is a method to screen for at least a three-way drug target combination comprising the steps of: (i) providing a lentiviral three-way combinatorial gRNA expressing construct that express gRNAs; (ii) transfecting human cells with fluorescence reporter gene; and (iii) measuring percentage of cell population positive for fluorescence at a time period post-transfection.
In one embodiment, the method further comprising validation of the three-way drug target combination by matching a drug to the drug target.
In one embodiment, the three-way drug target combinations provides a three-drug regimen for a disease.
In one embodiment, the fluorescence is GFP, RFP or BFP.
In one embodiment, the at least a three-way drug target combination are synergistic combinations.
In one embodiment, the disease is cancer or Parkinson's disease.
Provided herein is a method to treat HGSOC comprising administering drugs that targets PARP1, DNMT1, CDK2, FKBP1A or a combination thereof.
In one embodiment, the drug comprises Olaparib (OLA), azacitdine (AZA), seliciclib (SEL), sirolimus (SIR), or a combination thereof.
In one embodiment, the drug comprises OLA and AZA.
Provided herein is a system for CRISPR-based multi-gene knockout screening comprising a barcoded gRNA expression cassette comprising: (i) a first promoter operatively linked to a first gRNA; (ii) a second promoter operatively linked to a second gRNA; (iii) a third promoter operatively linked to a third gRNA; and (iv) three barcoded gRNA sequencing region, wherein the gRNA expression cassette is in a single vector.
In one embodiment, the promoters are human U6, mouse U6, and Human H1 promoters and the three barcoded gRNA are modified gRNA scaffold variants.
In one embodiment, the promoters comprises a modified 3′ end sequence which are complementary to the modified gRNA scaffold variants, said 3′ end sequence anneals to the modified gRNA scaffold variants.
In one embodiment, the system further comprising: (i) pooled digestion and ligation of the annealed 3′ end sequence and the gRNA scaffold variants to form an assembly of pooled barcoded combinatorial gRNA library.
In one embodiment, the expression cassettes knockout target GFP gene in OVACR8-ADR-Cas9 cells.
In one embodiment, the gRNA scaffold variants comprises: (i) higher on-target activity than wild-type scaffold; (ii) low off-target activities; and (iii) high on-to-off target activity.
Provided herein is a system for CRISPR-based multi-gene knockout screening comprising a barcoded gRNA expression cassette comprising v3.11, v.3.12 or v.3.13.
The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawings will be provided by the Office upon request and payment of the necessary fee.
The workflow starts with the synthesis of barcoded gRNA oligo pairs, which are annealed and cloned into gRNA expression vectors in pooled format. Only one set of oligos is needed for building the libraries of higher-order gRNA combinations for multiplexed CRISPR screens, as the 3′ end of promoters are sequence-adapted to the sticky ends of the annealed oligos. Barcoded combinatorial gRNA library is assembled multiplicatively using one-pot reactions as described in
Lentiviral delivery of combinatorial gRNA expression constructs efficiently disrupt multiple target genes. Flow cytometry was used to measure the percentage of cell populations positive for GFP, RFP, and BFP fluorescence at day 11-14 post-infection in OVCAR8-ADR and OVCAR8-ADR-Cas9 cells. Data are mean±SD, n=3 biological replicates.
(A) Distributions of barcode reads in the plasmid and infected OVCAR8-ADR-Cas9 cell pools. A high-coverage three-way combinatorial gRNA library (99.8% of all expected gRNA combinations; 32,705 out of 32,768) was obtained in both the plasmid and cell pools. Most barcoded gRNA combinations were detected within a 5-fold range from the mean barcode reads per combination (highlighted by the shaded areas).
(B) High correlation between barcode representations (normalized barcode counts) within the plasmid pool and infected cell pool indicates efficient lentiviral delivery of the three-way combinatorial gRNA library into cells. The horizontal dotted lines in the Bland-Altman plots indicate the 95% limits of agreement.
(C-D) High reproducibility for barcode representations between two biological replicates in cells cultured for 15-day (C), and 26-day (D) post-infection with the three-way combinatorial gRNA library. The horizontal dotted lines in the Bland-Altman plots indicate the 95% limits of agreement. The vertical dash line indicates the threshold of 100 raw barcode counts.
(E) The coefficient of variation (CV; defined as SD/mean of the fold changes of normalized barcode counts for 26-day versus 15-day cultured cells) was determined for the two biological replicates. Over 94.8% of pairwise gRNA combinations had a CV of <1 in the screen.
(F) OVCAR8-ADR-Cas9 cells infected with the barcoded three-way combinatorial gRNA library were cultured for 15 and 26 days. Barcode representations within the cell pools were quantified using Illumina HiSeq. The barcoded library vector uses hH1-gRNA-WT scaffold, hU6-gRNA-v1 scaffold, and mU6-gRNA-v2 scaffold in the first, second, and third expression cassettes, respectively.
(G) A plot of screen data showing the abundance changes of each barcoded gRNA combinations at day 26 versus day 15 post-infection (in mean log2 (Fold Change); x-axis) and their genetic interaction (GI3) score (y-axis). Hit combinations, DNMT1+POLA1+EGFR, DNMT1+POLA1+ERBB2, and CDK4+MAP2K1+POLA1, are highlighted in red. Data were collected from two biological replicates.
(H) Comparisons of the mean log2 (Fold Change) of three-way gRNA hit combinations with their constituent single and pairwise gRNA combinations (see STAR Methods for details). Statistical significance was analysed by one-way ANOVA with Dunnett's post hoc test. * indicates P<0.05.
(I) Viability, determined by MTT assay, of OVCAR8-ADR-Cas9 cells infected with the indicated triple-gene knockouts and controls. Data shown are mean±SD from biological replicates (n=4). Statistical significance was analysed by one-way ANOVA with Tukey's post hoc test. * indicates P<0.05; #P<0.05 indicates the comparisons with the safe harbour loci triple knockouts.
(A) Viability, determined by MTT assay, of OVCAR8-ADR cells treated with AZA-, FLU- and/or ERL. Data shown are mean±SD from biological replicates (n=3). Statistical significance was analysed by one-way ANOVA with Dunnett's post hoc test, * indicates P<0.05.
(B) Colony formation assay of AZA-, FLU- and/or ERL-treated OVCAR8-ADR cells. The colony numbers and areas were quantified. Data shown are mean±SD from biological replicates (n=3). Statistical significance was analysed by one-way ANOVA with Dunnett's post hoc test, * indicates P<0.05.
(C) Surface plots depict the drug synergy of AZA+FLU+ERL (orange) and AZA+FLU+LAP (cyan). Circles on the transparent triangular plane indicate the expected IC50 for each two-drug combination, and the expected IC50 for triple-drug treatment is located at the center of this triangle. Gray dots are the observed IC50s for single- and double-drug treatments. Red dots are the observed IC50s for the triple-drug treatments. Concave or convex colored planes indicate synergistic or antagonistic drug interaction, respectively. FIC3 is the fractional inhibitory concentration. Views from two angles are displayed (left and right panels).
(D) Viability, determined by MTT assay (left panels), of OVCAR8-ADR cells treated with RIB-, TRA- and/or FLU. Data shown are mean±SD from biological replicates (n=3). Statistical significance was analysed by one-way ANOVA with Dunnett's post hoc test, * indicates P<0.05. Surface plots (right panels) depict the drug synergy of RIB+TRA+FLU, as presented in (C).
(A) gRNA expression cassettes with different promoters and scaffold variants generate efficient knockout of the target GFP gene in OVCAR8-ADR-Cas9 cells. GFPsg1 was used. Flow cytometry was performed to measure the percentage of cell populations positive for GFP fluorescence. Data are mean±SD, n=3 biological replicates. Statistical significance was analysed by one-way ANOVA with Tukey's post hoc test. Modifications in the gRNA scaffolds v1 and v2 are shown.
(B) Library assembly procedures. Oligo pairs (Oligo-F and Oligo-R, respectively) were synthesized and annealed to create double-stranded inserts with 20 bp gRNA target sequences, two BbsI sites, 8 bp barcodes, and 5′ overhangs at their ends. The inserts were mixed in equal molar ratio and cloned into three BbsI- and Mfe-digested storage vectors, which contain the hH1, hU6, or mU6 promoters, with one-pot ligation reactions via their compatible ends to create the pooled storage vector libraries. The 3′ end of the promoter sequences of hH1 and mU6 were modified such that the same pool of gRNA oligos can be used for building the libraries. Subsequent single-pot ligation reactions were performed with the BbsI-digested pooled storage vector libraries and an insert containing the gRNA scaffold sequence (WT, v1, or v2), BamHI and EcoRI sites, and 5′ overhangs at their ends to assemble the barcoded gRNA library pools.
(A) The efficiency of each gRNA was plotted against its on-target efficacy score predicted by Azimuth 2.0. Efficiency of gRNAs targeting the fluorescent reporter genes were determined using flow cytometry, and data for endogenous genes were obtained from our published data (Wong et al., 2016a).
(B-C) Sequencing of targeted allele for cells infected with gRNA expression construct. OVCAR8-ADR-Cas9 cells were infected with lentiviruses encoding the indicated pairwise (B) and three-way combinatorial (C) gRNA expression constructs. The targeted alleles were amplified from the genomic DNA by PCR and cloned into storage vector for Sanger sequencing. The editing efficiency at each targeted locus and the number of individual clones being sequenced are shown.
The gRNAs selected for the three-way combinatorial CRISPR screen showed a higher average on-target score and a higher average frameshift scores predicted by inDelphi and FORECasT than those used in the pairwise CRISPR screen. The combined effect brought by both the on-target and frameshift predictions was also evaluated.
(A-B) OVCAR8-ADR-Cas9 cells were infected with triple-gRNA combinations that target the indicated genes (A), and the respective single and/or double-gRNA combinations (B). The three safe harbour loci being targeted were PPPIRJ2C, THUMPD3-AS1, and CCR5. The gRNAs used in each combination are listed in Table S5. Cell viability was determined by MTT assay. Data are mean±SD from biological replicates (n=4).
(A) Heatmaps showing the log2 fold changes of the expression of 3,834 genes that were identified with an FDR<0.05 as differentially expressed in OVCAR8-ADR cells treated with the three-drug regimen (AZA+FLU+ERL), when compared to the untreated control. The log2 fold changes of the expression of those genes after treating the cells with the corresponding drug pairs are included. Hierarchical clustering of genes and samples was performed based on the Pearson's correlation.
(B) Matrix showing the mapped pathways for the differentially expressed genes, which were at least 20% up-(orange) or down-(blue) regulated in OVCAR8-ADR cells treated with the three-drug regimen (AZA+FLU+ERL) when compared to the untreated control and also had a fold change of >10%, >5%, or <5% in cells treated with the three-drug regimen over all of those treated with the corresponding two-drug regimens. The bar on top of the x-axis indicates the level of fold change detected by different shades of green. Each darken spot indicates that a gene exists in a particular pathway.
Surface plots depicting the drug interactions of AZA+FLU+ERL (orange) and AZA+FLU+LAP (cyan) and the fractional inhibitory concentration (FIC3) scores are shown. Panel of IC50 is shown in
Surface plots depicting the drug interactions of AZA+FLU+ERL (orange) and AZA+FLU+LAP (cyan) and the fractional inhibitory concentration (FIC3) scores are shown.
(A) Distributions of barcode reads in the plasmid and 9-day post-infected OVCAR8-ADR-Cas9 cell pools. 99.7% (25,201 out of 25,281) and 99.0% (25,027 out of 25,281) of all expected gRNA combinations was obtained in the plasmid and cell pools, respectively. Most barcoded gRNA combinations were detected within a 5-fold range from the mean barcode reads per combination (highlighted by the shaded areas).
(B) High correlation between barcode representations (normalized barcode counts) within the plasmid pool and infected cell pool indicates efficient lentiviral delivery of the pairwise gRNA library into cells. The horizontal dotted lines in the Bland-Altman plots indicate the 95% limits of agreement.
(C-D) High reproducibility for barcode representations between two biological replicates in cells cultured for 15-day (C), and 21-day (D) post-infection with the pairwise gRNA library. The horizontal dotted lines in the Bland-Altman plots indicate the 95% limits of agreement. The vertical dash line indicates the threshold of 100 raw barcode counts.
(E) The coefficient of variation (CV; defined as SD/mean of the fold changes of normalized barcode counts for 21-day versus 15-day cultured cells) was determined for the two biological replicates. Over 99.2% of pairwise gRNA combinations had a CV of <1 in the screen.
(F) OVCAR8-ADR-Cas9 cells infected with the barcoded pairwise gRNA library were cultured for 15 and 21 days. Barcode representations within the cell pools were quantified using Illumina HiSeq. The barcoded library vector uses hH1-gRNA-WT scaffold and hU6-gRNA-v1 scaffold in the first and second expression cassettes, respectively.
(G) A volcano plot for comparing the abundance changes of each barcoded gRNA combinations at day 21 versus day 15 post-infection. Hit combinations, DNMT1+PARP1 and FKBP1A+CDK2, are highlighted in blue and red, respectively. Data were collected from two biological replicates.
(H-J, M-N) Cell viability, determined by MTT assay, of the indicated gRNA-infected OVCAR8-ADR-Cas9 cells (H) and drug-treated OVCAR8-ADR cells (I, J, M, N). In (J and N), percentage of growth inhibition was calculated by comparing each drug-treated group to the untreated control. Drug synergy was measured by the Bliss Independent model and the HSA model. The growth-inhibitory effects brought by treatment with 8 μM of OLA and 1.2 μM of AZA (J), and 5 μM SEL and 0.5 μM SIR (N), were plotted as examples to illustrate, and the dash lines indicate the expected drug combination effects based on the Bliss Independent model. Data shown are mean±SD from biological replicates (n=3 in H; n=6 in I and J; n=8 in M and N).
(K, O) Colony formation assay of OLA- and/or AZA- (K), and SEL- and/or SIR- (O), treated OVCAR8-ADR cells. The colony numbers and areas were quantified. Data shown are mean±SD from biological replicates (n=3).
(L, P) Cell cycle analysis of OLA- and/or AZA- (K), and SEL- and/or SIR- (O), treated OVCAR8-ADR cells. The percentage of cells in each cell cycle phase was quantified. Data shown are mean±SD from biological replicates (n=3).
Statistical significance in H-P was analysed by one-way ANOVA with Tukey's post hoc test. *P<0.05, **P<0.01, and ****P<0.0001; #P<0.05 in J-L and N-O indicates the comparisons with the untreated control.
(A-B) Growth inhibition brought by the indicated drug treatments to OVSAHO (A) and KURAMOCHI (B) cells were measured by MTT assay, and was calculated by comparing each drug treatment to the untreated control. Drug synergy was measured by Bliss Independent model and HSA model. The dash line in the plots in the right panels indicates the expected drug combination effects based on the Bliss Independent model. Data are mean±SD from biological replicates (n=4). Statistical significance was analysed by one-way ANOVA with Tukey's post hoc test. *P<0.05; #P<0.05 indicates the comparisons with the untreated control.
(A) Distributions of barcode reads in the plasmid and infected SK-N-MC-Cas9 cell pools. 99.1% (7,499 out of 7,569) and 98.7% (7,467 out of 7,569) of all expected gRNA combinations was obtained in the plasmid and cell pools, respectively. Most barcoded gRNA combinations were detected within a 5-fold range from the mean barcode reads per combination (highlighted by the shaded areas).
(B) High correlation between barcode representations (normalized barcode counts) within the plasmid pool and infected cell pool indicates efficient lentiviral delivery of the pairwise gRNA library into cells.
(C) High correlation between barcode representations within cell pools cultured for 10 and 22 days indicates the CRISPR-mediated gene knockouts did not result in severe cell death.
(D-E) High reproducibility for barcode representations between two biological replicates in untreated (D) and rotenone-treated (E) cells. The dash lines in (D) indicate the threshold of 20 raw barcode counts. R is the Pearson correlation coefficient.
(F) SK-N-MC-Cas9 cells infected with the barcoded pairwise gRNA library were either treated with rotenone or remained untreated. Barcode representations within the cell pools were quantified using Illumina HiSeq.
(G) Lentiviral delivery of dual-gRNA expression constructs efficiently disrupt multiple target genes in SK-N-MC-Cas9 cells. Flow cytometry was used to measure the percentage of cell populations positive for GFP and RFP fluorescence at day 6 post-infection. Data are mean±SD, n=3 biological replicates.
(H) A volcano plot for comparing the abundance changes of each barcoded gRNA combinations in rotenone-treated versus untreated cell pools. Hit combination, HSP90B1+HDAC2, is highlighted in red. Data were collected from two biological replicates.
(I) Cell viability, determined by MTT assay, of the indicated sgRNA-infected SK-N-MC-Cas9 cells in the presence of rotenone. Data shown are mean±SD (n=4) from biological replicates, and data of left and right panels were obtained from the same experiments.
(J-K) Cell viability of the indicated drug-treated SK-N-MC cells (J) and iPSC-derived dopaminergic neurons (K) in the presence of rotenone, determined by MTT assay and DAPI uptake assay, respectively. Data shown in are mean±SD (n=9 in (J); n=3 in (K)) from biological replicates.
(L) Cell viability, determined by MTT assay, of the indicated drug-treated SK-N-MC cells in the presence of MPP+. Data shown are mean±SD (n=8) from biological replicates.
(M) Quantification of the number of rhabdomeres per ommatidium in wild-type and alpha-synuclein-expressing flies that were fed with the indicated drug(s). Combination of 17-DMAG and vorinostat restored the number of rhabdomeres per ommatidium in alpha-synuclein-expressing Drosophila eyes. Representative images showing the rhabdomeres of wild-type and alpha-synuclein-expressing flies that were fed with the indicated drug(s). Data are mean±SD from at least 100 ommatidia of 5-10 flies.
Statistical significance in (I-M) was analysed by one-way ANOVA with Tukey's post hoc test. *P<0.05, **P<0.01 and ****P<0.0001 represent significant differences between the indicated samples. In (I), #P<0.05, ##P<0.01, ###P<0.001, and ####P<0.0001 indicates the comparisons with the respective no gRNA controls. Dash line indicates the expected drug combination effects based on the Bliss Independent model.
(A) Sequence of gRNA scaffold sequences used.
(B-C) OVCAR8-ADR cells harboring reporter constructs with on-target (B) and off-target (C) sites were infected with lentiviruses encoding wildtype or Opti-SpCas9. The editing efficiency of the gRNA scaffold variants was measured as the percentage of cells with depleted RFP fluorescence.
(D) Assessment of gRNA scaffold variants for efficient on-target editing with gRNAs targeting endogenous loci. The percentage of sites with indels was measured using a T7 endonuclease I (T7E1) assay. The ratio of the on-target activity of gRNA scaffold variants to the activity of scaffold was determined, and the median and interquartile range for the normalized percentage of indel formation are shown for the 5 loci tested. Each locus was measured three times.
(E) GUIDE-seq genome-wide specificity profiles for the panel of gRNA scaffold variants paired with the indicated gRNAs. Mismatched positions in off-target sites are colored, and GUIDE-seq read counts were used as a measure of the cleavage efficiency at a given site.
Combinatorial drug therapy targeting multiple pathways can limit the development of drug resistant phenotype in cancer cells since it is harder for the cells to activate multiple compensatory survival mechanisms.
This disclosure relates to systems and compositions that enables highly efficient, multiplexed genome editing and CRISPR screening. The engineered guide RNA scaffolds and promoters developed in this work enable three-way combinatorial CRISPR screens to be carried out based on a prior assembly method called CombiGEM-CRISPR, and can be used to improve genome editing efficiency in routine experiments and applications. High-throughput CRISPR screens from prior arts have only been able to study paired interactions between guide RNAs, and not those of greater complexity (such as interactions between three or more guide RNAs). The systematic screening of complex genetic interactions is enabled by the generation of engineered scaffolds and promoter sequences that can minimize possible lentiviral vector recombination due to long homologous sequences and permit use of the same pool of guide RNA oligos for building high-quality combinatorial guide RNA libraries.
Technically, the guide RNA scaffold sequences are engineered to minimize possible lentiviral vector recombination due to long homologous sequences, and the 3′ end of the promoter sequences of hH1 and mU6 are modified such that the same pool of gRNA oligos can be used for building the combinatorial guide RNA libraries. The engineered guide RNA scaffold and modified promoter sequences show higher or comparable activity for driving guide RNA expression when compared to their wild-type counterparts.
CombiGEM-CRISPR v2.0 toolkits include add-on designs on library vectors that enable only a single, reusable set of oligos to be synthesized for performing high-order combinatorial CRISPR screens. We and others have shown that CRISPR screens can be carried out via targeting two genes simultaneously using dual guide RNA (gRNA) expression cassettes (Chow et al., 2019; Du et al., 2017; Han et al., 2017; Najm et al., 2018; Shen et al., 2017; Wong et al., 2016a). Here we evaluated the extensibility of existing methods and other possible toolkits for assembling a three-way combinatorial gRNA library for screening (
Since previous CombiGEM toolkits were not directly adaptable for assembling three-way and even higher-order combinatorial gRNA libraries, here we further created a “one-set-fits-all” design such that building a n-way combinatorial CRISPR screening library of m guide RNAs using multiple gRNA expression cassettes always requires only m (instead of n×m) pairs of oligos to be synthesized. To ensure expression of three gRNAs in single cells, we assembled together the multiple gRNA expression cassettes in a single vector. Multiple promoters (including human U6, mouse U6, and human H1) (Adamson et al., 2016; Ma et al., 2014; Vidigal and Ventura, 2015) and modified gRNA scaffolds (Adamson et al., 2016; Briner et al., 2014; Dang et al., 2015; Grevet et al., 2018) were used in the expression cassettes (
In some embodiments, the promoters have sequences as shown below.
We constructed a lentiviral combinatorial gRNA expression vector containing multiple gRNA expression cassettes to efficiently and simultaneously knock out three target genes (
Combinatorial drug therapy targeting multiple pathways can limit the development of drug resistant phenotype in cancer cells since it is harder for the cells to activate multiple compensatory survival mechanisms (Bozic et al., 2013). We performed high-throughput studies to search for effective therapeutic combinations against high-grade serous ovarian cancer (HGSOC), the most prevalent subtype that contributes to two-third of all ovarian cancer deaths (Bowtell, 2010). With the CRISPR-based multi-gene knockout system described above, we applied CombiGEM-CRISPR v2.0 to assemble a high-coverage (99.8%) three-way combinatorial gRNA library (with 32×32×32 gRNAs=32,768 total combinations) (
We then conducted a pooled screen to isolate three-way gRNA combinations that modulate OVCAR8-ADR growth (
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MTOR
FGF2
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9308
A1_TOP1
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6726
TOP1
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459
OR_TUBA1A
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OP1_
GFB1
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4
038
5879
7
OR_POLA1_FGF2
834
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3
856
MAP2K1
TUBA1A
88
6263
264603
6
8
4
9653
59
792
1389
7225
1_HDAC1
922389
KBKB_POLA1_TUBA1A
_POLA1_FGF2
1_IGFB1
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311
05
7416
KBKB_FGF2_TGFB1
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2
7485
K3C3_
GFR_POLA1_FGF2
45
333
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3182
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4045
0635
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2
8028
R_POLA1_TGFB1
G
B1
YMS_TGFB1
485
1
4099
YMS
46
UBA1A_FGF2
30
2397
YMS_FGF2
2E−05
G
1
OR_POLA1
5009
213107
2
3838
DNM
1_TUBA1A
YMS_TGFB1
8462
G
B1
17462
2
3
647
_TUBA1A
05
IKBKB
TYMS
1
BA1A_TYMS
9785894
60810292
BA1A
BA1A
BA1A_
G
1
OR_PIK3C3
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OP1
RBB2_MAP2K1_TYMS
OR_POLA1_TUBA1A
FGF2
TGFB1
G
2
GFR_PIK3C3_TG
B1
934
GFR_M
OR_TYMS
YMS_PIK3C3
UBA1A_
YMS_FGF2
BB2_IKBKB
24
K4_DNMT1_MAP2K1
K4_MTOR_HDAC1
MAP2K1_PIK3C3
OP1_FGF2_
GHB1
OP1_MAP2K1
UBA1A_TYMS_TGFB1
GFB1
59
1_TYMS_PIK3C3
76
5834
G
2
41396711
MTOR
FGF2
12
68
51
97
A1_TOP1
YMS
FGF2
76
04
TOP1
TGFB1
16
MTOR
TYMS
831
26
7277692
3988
02
394
OR_TUBA1A
47627849
YMS_PIK3C3
4
76
OP1
OP
_POLA1
1645047
075
OP1_
GFB1
3
GFB1
02
indicates data missing or illegible when filed
Azacitidine (AZA), fludarabine (FLU), and erlotinib (ERL) were used to target DNMT1, POLA1, and EGFR, respectively. Lapatinib (LAP) was used to inhibit ERBB2, while it also acts on EGFR that belongs to the same Erb protein family. The three-drug treatment of AZA, FLU, and ERL/LAP showed significantly stronger growth-inhibitory effects than the single- and double-drug treatments (
Via one-pot reactions using CombiGEM-CRISPR v2.0 (
We then evaluated the growth inhibition effects brought by these two hit combinations by treating OVCAR8-ADR cells with drug pairs. Olaparib (OLA), azacitdine (AZA), seliciclib (SEL), and sirolimus (SIR) were used as the drugs to target PARP1, DNMT1, CDK2, and FKBP1A, respectively. These drug molecules have been reported to have potent effects on their targets (McClue et al., 2002; Muvarak et al., 2016; Sabers et al., 1995; Wishart et al., 2006; Yang et al., 2017). Our results indicated that OLA and AZA act synergistically to suppress the growth of OVCAR8-ADR cells (
Our screening approach can also be applied for searching effective therapeutic combinations that enhance protection against other disease phenotypes, such as Parkinson's disease (PD)-associated toxicity. We assembled another high-coverage (99.1%) pairwise gRNA library targeting 28 druggable genes, whose ablations or matching drug inhibitors were reported to suppress neuronal toxicity (
P
indicates data missing or illegible when filed
In summary, we have established a CRISPR-based multi-gene knockout screening platform to address the unmet need for rapid identification of effective three-way therapeutic combinations. Via pairing drug mechanisms of action to specific genes helps accelerating the identification of effective combinations for directing secondary screens and narrows a vast number of possible combinations down to few top-performing hits for further testing. We have demonstrated that systematic characterization of three-way combinations using CRISPR-based screening discovers the rare ones with synergistic interactions as most of them showed buffering interactions and were able to validate all three screen hits with strong growth inhibition effects and three-way interactions. Our CombiGEM-CRISPR v2.0 platform has broad utility as it can also be used for identifying new two-drug regimens that inhibit cancer cell growth (
As described in
This platform is also versatile to be used together with dCas9-based CRISPR interference systems (Qi et al., 2013) to partially lower the target gene expressions for mimicking drug inhibitor effects. This platform could be coupled with other technologies like single-cell RNA-seq to explore different cell signatures and contribute to the generation of druggable gene interaction network using existing knowledge (Adamson et al., 2016; Bassik et al., 2013; Chow et al., 2019; Du et al., 2017; Han et al., 2017; Shen et al., 2017). The platform presented in this study is easy-to-implement and will be valuable for perturbing the multi-layer genetic networks for understanding complex biological systems and designing new combination therapies.
HEK293T (female) and SK-N-MC (female) cells were obtained from American Type Culture Collection (ATCC). OVCAR8-ADR (female) cells were a gift from T. Ochiya (Japanese National Cancer Center Research Institute, Japan)(Honma et al., 2008). The identity of the OVCAR8-ADR cells was confirmed by a cell line authentication test (Genetica DNA Laboratories). KURAMOCHI (female) and OVSAHO (female) cells were obtained from Japanese Collection of Research Bioresources (JCRB) Cell Bank. iPSC-derived dopaminergic neurons were obtained from TGD Life Company Limited. OVCAR8-ADR-Cas9 and SK-N-MC-Cas9 cells were generated by transducing pAWp30 (Addgene, 73857) into the OVCAR8-ADR and SK-N-MC cells, respectively, followed by selection using zeocin (Life Technologies) for stable Cas9-integrated cells. The Streptococcus pyogenes Cas9 was used in this study. OVCAR8-ADR reporter cells that stably express RFP and GFP were generated by transducing the cells with pAWp9, followed by sorting based on GFP and RFP signals. The reporter cells were then infected with pAWp30 to stably integrate Cas9 after zeocin selection. HEK 293T and S-N-MC cells were cultured in DMEM supplemented with 10% FBS and 1× antibiotic-antimycotic (Life Technologies) at 37° C. with 5% CO2. KURAMOCHI, OVSAHO, and OVCAR8-ADR cells were cultured in RPMI 1640 supplemented with 10% FBS and 1× antibiotic-antimycotic at 37° C. with 5% CO2. Cells were checked for mycoplasma contamination every three or four months and were never tested positive.
The vectors used in this study (Table S5) were generated by standard molecular cloning strategies, including PCR, oligo annealing, restriction enzyme digestion, ligation, and Gibson assembly. Custom oligonucleotides were purchased from Genewiz. Vectors were transformed into E. coli strain DH5a competent cells and selected with ampicillin (100 μg/ml, USB) or carbenicillin (50 μg/ml, Teknova). DNA was extracted and purified by Plasmid Mini (Takara and Tiangen) or Midi preparation (Qiagen) kits. Sequences of the vectors were verified with Sanger sequencing.
2Csg-sgRNA scaffold-
2Csg-sgRNA scaffold-
indicates data missing or illegible when filed
To construct storage vectors with mouse U6 (mU6)- and human H1 (hH1) promoter-gRNA WT scaffold sequences, the promoter sequences were amplified from mouse and human genomic DNAs, respectively, and cloned into the vector backbone of pAWp28 (Addgene, 73850). pAWp28 is the storage vector with human U6 (hU6) promoter-gRNA WT scaffold sequence. Storage vectors with hU6-gRNA v1 scaffold and mU6-gRNA v2 scaffold were created by PCR-based mutagenesis. To drive gRNA expression to target the gene of interest, oligo pairs with gRNA target sequences were synthesized, annealed, and cloned into BbsI-digested storage vectors by T4 DNA ligase (New England Biolabs). To generate lentiviral vectors for expression of single gRNA targeting GFP, RFP, and BFP gene, the gRNA expression cassettes were released from the storage vectors by digestion with BglII and EcoRI enzymes (Thermo Fisher Scientific) and cloned into pAWp9 vector (Addgene, 73851) using ligation via the compatible stick ends generated by digestion of the vector with BamHI and EcoRI enzymes (Thermo Fisher Scientific). To build lentiviral vectors for expression of multiple gRNAs targeting the fluorescent proteins, the second gRNA expression cassette with hU6-gRNA-v1 (or WT) scaffold was released from the storage vector by digestion with BglII and EcoRI enzymes, and ligated into the BamHI- and EcoRI-digested storage vector containing the first gRNA expression cassette with hH1-gRNA-WT scaffold. Similarly, the third gRNA expression cassette with mU6-gRNA-v2 (or WT) scaffold was released from the storage vector by digestion and ligated into the storage vector harbouring the first and second gRNA expression cassettes. Lentiviral vectors were then generated by amplifying the pairwise or three-way gRNA expression cassettes from the storage vector by PCR, and cloned into the SbfI-digested pFUGW vector backbone (pAWp40) by Gibson assembly.
The gRNAs used in this study were designed based on GPP sgRNA Designer (Table S3). For the pairwise gRNA libraries, three gRNAs were selected per target gene based on the following criteria: 1) on-target efficacy scores are >0.6; 2) off-target ranks are <100; and 3) target sites are within 5-65% of the protein-coding sequence. gRNA sequences containing BamHI, EcoRI, BglII, and MfeI digestion sites were excluded to avoid incompatibility with CombiGEM. For the three-wise combinatorial gRNA library, two gRNAs were selected per target gene using the same criteria, except that their on-target efficacy scores are all >0.64. inDelphi and FORECasT were applied to predict the frameshift rate of gRNA. The gRNA sequences were inputted into BLAST to extract the 70-nucleotide context sequences of the gRNAs. The PAM sequence index were located in the 70-nt sequences and were inputted alongside with the context sequence into inDelphi and FORECasT, which were downloaded from GitHub. The K562 cell line was the prediction model used in inDelphi, and the output frameshift scores are extracted from the “Frameshift frequency” option. The output summary file from FORECasT was inputted into a Python code calculating the predicted frameshift frequency by summing up the percentage of the target frameshift categories that are not multiples of three then dividing the sum by 10.
To assemble the gRNA libraries (
The second-generation lentiviral vector system was used in this study. HEK293T cells were transfected by FuGene HD transfection reagent (Promega) according to manufacturer's instructions in 6-well plate, with 0.5 μg of pCMV-VSV-G, 1 μg of pCMV-dR8.2-dvpr, and 0.5 μg of the respective lentiviral vector per well. Lentivirus-containing supernatants were collected at 48 and 72 hrs post-transfection, which are then combined and filtered by 0.45 m polyethersulfone membrane (Pall). For routine transduction, we applied 300 μL of the filtered supernatant to one well of 12-well plate in the presence of 8 μg/ml polybrene (Sigma), with cell confluence at about 30%. For library transduction, Cas9-expressing cells were seeded onto 150-mm culture dishes at confluence about 50% with the cell number roughly equals 400-fold representation of the library size, and were transduced by the viruses at a multiplicity of infection (MOI) of ˜0.3, to ensure most cells were infected with just one virion.
To prepare samples for flow cytometry, cells were trypsinized and resuspended in FACS buffer (PBS with 2% FBS). BD LSR Fortessa analyser (Becton Dickinson) was used to detect the signal of TurboRFP, EGFP, and mTagBFP by 561 nm yellow-green laser (610/20 nm), 488 nm blue laser (530/30 nm), and 405 nm violet laser (450/50 nm), respectively. For cell cycle analysis, cells were fixed by ice-cold 70% ethanol at 4° C. for 1 hr, and then rehydrated by replacing the ethanol with PBS for 15 min at room temperature. To remove RNAs, RNase A (10 mg/ml) was added to the cells and incubated at 37° C. for 15 min. Genomic DNA contents were stained by propidium iodide (PI; Invitrogen) for 1 hr at room temperature in dark. Signal was detected by 561 nm yellow-green laser (586/15 nm) using a BD LSR Fortessa analyser. FlowJo software (v10.5.3, Becton Dickinson) was used for data analysis. For cell sorting, samples were prepared similarly as for FACS analysis, except that FACS buffer was supplemented with 2× antibiotic-antimycotic. BD Influx cell sorter (Becton Dickinson) equipped with 100-μm nozzle (24 psi with a frequency of 39.2 kHz) was used. GFP-positive cells were detected by 488 nm blue laser (530/40 nm) and sorted using 1.0 Drop Pure mode. For cells being infected with the screening libraries, the 1-2% cells that had the strongest GFP signals were not collected to minimize the chance of acquiring cells that were infected with more than a single virion. At least 100-fold more cells than the library size were collected.
For library-transduced cell pool, genomic DNA was extracted from cells with DNeasy Blood and Tissue kit (Qiagen) and quantified by Quant-iT PicoGreen dsDNA Assay kit (Life Technologies). To extract the 298-bp barcode-containing fragments, 0.5 ng of library plasmid DNA and 800 ng of genomic DNA per 50 μl of PCR reaction were used for PCR amplification using Kapa HiFi Hotstart Ready-mix (Kapa Biosystems). The forward and reverse primers used were 5′-GGATCCGCAACGGAATTC-3′ and 5′-GGTTGCGTCAGCAAACACAG-3′. The PCR amplification was kept at the exponential phase to minimize PCR bias. To ensure sufficient library coverage amplified from the genomic DNA, 20 and 10 PCR reactions were performed for the pairwise libraries used in studying ovarian cancer and Parkinson's disease, respectively, and 30 PCR reactions were performed for three-way combinatorial library. Illumina adapters and sequencing indices were then added to the amplicons by performing PCR using Kapa HiFi Hotstart Ready-mix. The forward and reverse primers used were 5′-CAAGCAGAAGACGGCATACGAGATGTGACTGGAGTTCAGACGTGTGCTCTTCCGAT CTGGTTGCGTCAGCAAACACAG-3′ and 5′-AATGATACGGCGACCACCGAGATCTACACTCTTTCCCTACACGACGCTCTTCCGATC TNNNNNNN(N1-4)GGATCCGCAACGGAATTC-3′, where NNNNNNNN denotes a specific indexing barcode assigned for each experimental sample and (N1-4) indicates the 1 to 4 nucleotides added to increase the diversity of the sequencing library. The final amplicons were purified by two rounds of size selection using a 1:0.5 and 1:0.95 ratio of Agencourt AMIPure XP beads (Beckman Coulter Genomics). Quantity and quality of samples were measured by real-time PCR using Kapa SYBR Fast qPCR Master Mix (Kapa Biosystems) with primer pair 5′-AATGATACGGCGACCACCGA-3′ and 5′-CAAGCAGAAGACGGCATACGA-3′, and analysed using a high-sensitivity DNA chip (Agilent) on an Agilent 2100 Bioanalyzer.
Barcode reads were processed from the sequencing data and normalized to count per million reads for comparison among samples. The normalized barcode counts for each gRNA combination in the cell pools were compared to the ones for dummy control gRNA combination within each sample to generate a log 2-transformed fold change. To improve data reliability, combinations that had a raw barcode read of <100 in the early time point samples from the ovarian cancer studies were excluded (
48934511
53098
8
16091369
299
.162501313
1951
24
2094143
723519
+ TGFB1sg2
7357516
2324
0024895
.309129902
523386
4184931
04024
217766
82705
+ TUBA1Asg2
+ TYMSsg3 + ERBB2sg1
32
148
87
Asg1 + TYMSsg3
5255
sg2
+ POLA1sg1 + TYMSsg1
062
12
45368
823198
36948008
24285225
3
311752
64
7167
7716349
+ TYMSsg1
5807
5
377961
+ TOP1sg1
+ HDAC1sg1 + PIK3C3sg1
+ TYMSsg3
94
36805
74718
356
915228
.664157524
908
393
+ HDAC1sg1
0
1
2488721
004
263
752
+ CDK4sg2 + ERBB2sg1
58
+ TOP1sg1 + TUBA1Asg1
+ TGFB1sg1
+ MTORsg2 + TGFB1sg2
+ MAP2K1sg2 + dummysg2
468873
+ EGFRsg2
677
indicates data missing or illegible when filed
A1sg3
AP1sg1
GFR1sg1
indicates data missing or illegible when filed
1,500 OVCAR8-ADR cells were seeded onto one well of a 96-well plate one day prior to drug treatment. 4,800 SK-N-MC cells were seeded onto one well of a 96-well plate and were pre-treated with the drug(s) for 72 hours, followed by adding rotenone (Abcam, ab143145) or MPP+ (Abcam, ab144783) to induce toxicity. Drugs were applied at indicated doses. Azacitidine (A-5959), olaparib (0-9201), sirolimus (R-5000), seliciclib (R-1234), lapatinib (L-4899), erlotinib (E4007), and vorinostat (V-8477) were purchased from LC Laboratories. Fludarabine (#14128) was purchased from Cayman Chemical Company. 17-DMAG (A2213) was purchased from ApexBio. 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay was performed, as described previously (Wong et al., 2015), to assess cell growth at different time points. Briefly, medium in the cell growing wells were replaced by 100 ul of 1×MTT solution in RPMI 1640 without phenol red and incubated at 37° C. with 5% CO2 for 3 hrs. Then 100 μl solubilization buffer (10% Triton X-100, 0.1N HCl in isopropanol) are applied to each well to dissolve the blue formazan crystals. The absorbance was measured at 570 nm and 650 nm by VARIOSKAN FLASH microplate reader (Thermo Scientific). Bliss independent (Bliss, 1939) and HSA (Borisy et al., 2003) models were adopted for evaluating interactions between drug pairs, and DiaMOND model (Cokol et al., 2017; Cokol-Cakmak et al., 2018) was used for measuring three-way drug interactions. The excess over Bliss independent model was calculated as, g12−(g1+g2−g1×g2/100), where g indicates the percentage of growth inhibition, the number indicates the drug component; the excess over HSA model was calculated by subtracting the highest growth inhibition effect of single agent from that of the combination; the DiaMOND model was used for calculating the frictional inhibitory concentration (FIC3), which equals (o1+o2+o3)/((e1+e2+e3)/3), where o indicates the observed concentration of each component in the combination, and e indicates the expected concentration of individual drugs at certain inhibitory level, which is determined by drug response curves. To generate the drug response curves, the three drugs were combined in a fixed ratio of 1:1:1 of their respective IC50 and scaled proportionally. If FIC3 is <1, the interaction is synergistic; if FIC3 is =1, the interaction is additive; and if FIC3 is >1, the interaction is antagonistic.
1,000 OVCAR8-ADR cells were seeded onto one well of a 6-well plate one day prior to drug treatment at indicated doses. Colonies were fixed by ice-cold methanol at −20° C. for 30 min and stained by crystal violet. Colony number and area were determined by ImageJ software.
Wild-type and transgenic Drosophila strains carrying gmr-GAL4 and UAS-α-syn(Auluck et al., 2002) were used. gmr-GAL4 female flies were crossed with w1118 (control) or UAS-α-syn male flies, and raised at 21.5° C. on cornmeal medium supplemented with drug(s) or vehicle control. Drug treatment was performed by adding vorinostat (LC Laboratories, V-8477) and/or 17-DMAG (InvivoGen, ant-dgl-25) into 2 ml of the medium at final concentrations of 0.5 μM and 96 μg/ml, respectively. After eclosion, progeny were transferred into a new vial with medium supplemented with fresh drug(s), and the drug(s) were changed every 3-4 days prior to the assay. Eyes of 7- to 11-day-old flies were examined under a light microscope (Olympus CX31) with a 60× oil objective as described previously (Wong et al., 2008). At least 100 ommatidia from 5-10 flies were examined and the number of rhabdomeres were recorded.
Total RNAs were isolated from drug-treated OVCAR8-ADR cells by MiniBEST universal RNA extraction kit (Takara). RNA samples were quantified and analysed using Qubit assay and high-sensitivity DNA chip (Agilent) on an Agilent 2100 Bioanalyzer, respectively. RNA-seq experiments were performed at the Centre for Genomic Sciences (LKS Faculty of Medicine, The University of Hong Kong). The Illumina adaptors of the paired-end raw sequence reads were trimmed by Trimmomatic 0.39. The STAR aligner version 2.7 was used to align the sequence reads to the human genome, where the genome index was built using the primary assembly of Gencode's version 30 release of the human genome. The raw count reads were extracted using the R package Rsubread. R packages EdgeR, limma, and HTSFilter were used for differential expression analysis comparing each of the pairwise and three-way drug combinations with the untreated samples. An FDR<0.05 filter was applied for the three-way combination versus untreated samples while an FDR<1 filter was applied for each of the two-way combinations versus untreated samples. The combinations and the genes were clustered by complete-linkage clustering, where the distance is defined as 1-Pearson correlation. The genes that were at least 20% up- or down-regulated in cells treated with the three-drug regimen when compared to the untreated control were inputted into DAVID web tools for pathway analysis, and the Reactome pathway database was used. The pathway mapping used a P=0.05 threshold.
Data analyses were performed using GraphPad Prism 7 software (GraphPad Software). Data expressed are mean±SD, biological replicates are specified for each experiment in figure legends. Statistical comparisons between two groups were carried out by Student t-test, whereas one-way ANOVA followed by Tukey's or Dunnett's post hoc tests were used for comparisons of groups more than two.
All sequencing data generated or analysed during this study are available.
The foregoing description of the specific embodiments will so fully reveal the general nature of the disclosure that others can, by applying knowledge within the skill of the relevant art(s) (including the contents of the documents cited and incorporated by reference herein), readily modify and/or adapt for various applications such specific embodiments, without undue experimentation, without departing from the general concept of the present disclosure. Such adaptations and modifications are therefore intended to be within the meaning and range of equivalents of the disclosed embodiments, based on the teaching and guidance presented herein. It is to be understood that the phraseology or terminology herein is for the purpose of description and not of limitation, such that the terminology or phraseology of the present specification is to be interpreted by the skilled artisan in light of the teachings and guidance presented herein, in combination with the knowledge of one skilled in the relevant art(s).
While various embodiments of the present disclosure have been described above, it should be understood that they have been presented by way of examples, and not limitation. It would be apparent to one skilled in the relevant art(s) that various changes in form and detail could be made therein without departing from the spirit and scope of the disclosure. Thus, the present disclosure should not be limited by any of the above-described exemplary embodiments but should be defined only in accordance with the following claims and their equivalents.
All references cited herein are incorporated herein by reference in their entirety and for all purposes to the same extent as if each individual publication or patent or patent application was specifically and individually indicated to be incorporated by reference in its entirety for all purposes.
This international patent application claims the benefit of U.S. Provisional Patent Application No.: 63/010,877 filed on Apr. 16, 2020, the entire content of which is incorporated by reference for all purpose.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/CN2021/087250 | 4/14/2021 | WO |
| Number | Date | Country | |
|---|---|---|---|
| 63010877 | Apr 2020 | US |
