The systematic functional analysis of combinatorial genetics has been limited by the throughput that can be achieved and the order of complexity that can be studied. To enable massively parallel characterization of genetic combinations in human cells, we developed a technology for rapid, scalable assembly of high-order barcoded combinatorial genetic libraries that can be quantified with high-throughput sequencing. We applied this technology, combinatorial genetics en masse (CombiGEM), to create high-coverage libraries of 1,521 two-wise and 51,770 three-wise barcoded combinations of 39 human microRNA (miRNA) precursors. We identified miRNA combinations that synergistically sensitize drug-resistant cancer cells to chemotherapy and/or inhibit cancer cell proliferation, providing insights into complex miRNA networks. More broadly, our method will enable high-throughput profiling of multifactorial genetic combinations that regulate phenotypes of relevance to biomedicine, biotechnology and basic science.
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We thank members of the Lu laboratory and H. Ding for helpful discussions. We thank S. Patnaik of the Roswell Park Cancer Institute for processing miRNA expression data from the ArrayExpress database of European Bioinformatics Institute, the Massachusetts Institute of Technology BioMicroCenter for technical support on Illumina HiSeq, J. Weis for assisting computational analysis of next-generation sequencing data and C. Cui for technical assistance on cell viability assays. This work was supported by the US National Institutes of Health (DP2 OD008435 and P50 GM098792), the Office of Naval Research (N00014-13-1-0424), the Ellison Foundation New Scholar in Aging Award, the Defense Advanced Research Projects Agency and the Defense Threat Reduction Agency (HDTRA1-15-1-0050). A.S.L.W. was supported by the Croucher Foundation. The pAWp6 vector backbone (pFUGW-UBCp-GFP) was a gift from L. Nissim of the T.K. Lu laboratory, MIT; miR-128 was a gift from M.F. Wilkinson, University of California San Diego, USA and miR-132 was a gift from R.H. Goodman, Oregon Health and Science University, USA; HOSE 11-12 and HOSE 17-1 cells were gifts from G.S.W. Tsao, University of Hong Kong, Hong Kong; OVCAR8 and OVCAR8-ADR cells were gifts from S.N. Bhatia, MIT, and T. Ochiya, Japanese National Cancer Center Research Institute, Japan, respectively.
T.K.L., A.W. and G.C. have filed a provisional patent application (U.S. Provisional Application No.: 62/102,255) on this work.
Integrated supplementary information
Supplementary Figure 1 Lentiviral Delivery of Combinatorial miRNA Expression Constructs Provides Efficient Target Gene Repression.
a, Design for lentiviral combinatorial miRNA expression and sensor constructs. Single or multiple miRNA precursor sequences arranged in tandem were placed downstream of a GFP gene to monitor expression driven by a CMV promoter in a lentiviral vector. Sensors harboring four repeats of the miRNA target sequence were cloned in the 3’UTR of a RFP gene expressed from an UBC promoter to report on miRNA activity. The constructs were delivered by lentiviruses to HEK293T cells and then analyzed for GFP and RFP expression using flow cytometry. b, Repression of RFP reporter activity by miRNA expression. Lentiviral constructs harboring a miRNA, the cognate sensor, or both were introduced into HEK293T cells. c, Combinatorial miRNA expression constructs effectively repressed RFP reporters containing the cognate miRNA sensors. Lentiviral constructs harboring two-wise or three-wise miRNA combinations, with or without the cognate sensors, were introduced into HEK293T cells. d, Limited cross-reactivity between miRNAs and non-cognate sensors. Lentiviral constructs harboring miRNAs paired with different sensors were delivered into HEK293T cells. The percentages of RFP-positive cells within GFP-positive cell populations were determined by flow cytometry. Data represent mean ± s.d. (n = 3).
Supplementary Figure 2 Efficient Lentiviral Delivery of a Dual-Fluorescent Protein Reporter Construct in Human Cells.
a, Strategy for testing lentiviral delivery of a dual-fluorescent protein reporter construct in human cells. Lentiviruses generated for vectors containing a GFP gene expressed from a CMV or UBC promoter, or a single vector encoding RFP and GFP genes under the UBC and CMV promoters, respectively, were delivered to HEK293T cells for analysis of GFP and RFP expression. b, c, Lentiviral delivery and expression of the dual-fluorescent protein reporter construct in human cells. (b) Fluorescent microscopy revealed that RFP and GFP were expressed in UBCp-RFP-CMVp-GFP virus-infected cells, whereas only GFP was expressed in cells infected with UBCp-GFP and CMVp-GFP lentiviruses. Scale bar denotes 400 μm. (c) Flow cytometry was used to measure cell populations positive for RFP and GFP fluorescence. Over 97 percent of UBCp-RFP-CMVp-GFP virus-infected HEK293T cells were positive for both RFP and GFP, and similar percentages of UBCp-GFP or CMVp-GFP virus-infected cells were GFP-positive.
Supplementary Figure 3 Identification of the Exponential Phase During PCR for CombiGEM Barcode Amplification.
a, b, Procedures for identifying the transition point from exponential to linear phase during PCR for CombiGEM barcode amplification. The one-wise miRNA vector library pooled-assembled in E. coli (a) and the genomic DNA isolated from human breast cancer cells (MCF7) infected with the two-wise library (b) were used as templates in replicate PCR reactions, and the barcodes representing each miRNA combinations were amplified using primers targeting the sequences located outside the barcode region. PCR products were collected from the reactions stopped at cycles between 10 to 20 (a) or 19 to 28 (b), and were then diluted as templates for quantitative PCR reactions. The mean difference of threshold cycle (Ct) between cycles was determined. Error bars indicate s.d. from triplicates. Primer efficiencies were estimated to be 102% (a) and 100% (b) respectively. PCR cycle numbers highlighted in magenta (a) and green (b) were used in unbiased barcode amplification for subsequent Illumina sequencing. c, d, Agarose gel analyses of the amplified PCR products with indicated cycle numbers from (a) and (b) are shown in (c) and (d), respectively.
Supplementary Figure 4 High Reproducibility of Barcode Quantitation in Biological Replicates for Combinatorial miRNA Screens.
a, b, Scatter plots showing high correlation between barcode representations (log2 number of normalized barcode counts) between two biological replicates for both docetaxel (25 nM)-treated or vehicle-treated OVCAR8-ADR cells infected with the two-wise (a) or three-wise (b) miRNA combinatorial libraries. R is Pearson correlation coefficient.
Supplementary Figure 5 Consistent Fold Changes of Barcodes among Same miRNA Combinations Arranged in Different Orders in the Expression Constructs.
a-c, The coefficient of variation (CV; defined as s.d./mean of the fold changes of normalized barcode counts for docetaxel (25 nM)-treated versus four-day vehicle-treated (a, b) and four-day versus one-day cultured cells (c)) was determined for the same two-wise (a) or three-wise (b, c) combination arranged in different orders (i.e., [A,B] vs. [B,A] for two-wise combinations; [A,B,C], [A,C,B], [B,A,C], [B,C,A], [C,A,B], and [C,B,A] for three-wise combinations). 92% of two-wise miRNA combinations had a CV of <0.2 in the drug-sensitivity screen (a), while 95% and 98% of three-wise combinations showed a CV of <0.2 in the drug-sensitivity (b) and cell-proliferation (c) screens respectively.
Supplementary Figure 6 Docetaxel Dose-Response Curves for the OVCAR8 Cell Line and the Docetaxel-Resistant OVCAR8-ADR Cell Line.
OVCAR8 cells and OVCAR8-ADR cells (OVCAR8’s docetaxel-resistant derivative) cells were treated with docetaxel at indicated doses for three days and subjected to the MTT assay. Cell viabilities were compared to their respective no drug controls. The OVCAR8-ADR cell line has a ~3-fold higher IC50 than the parental OVCAR8 cell line. Data represent mean ± s.d. (n = 3).
Supplementary Figure 7 Log2 Fold-Changes in Barcode Representation Between Biological Replicates for All Individual Combinations in the Pooled Screens.
a, b (upper panel), Log2 fold-changes in biological replicate 1 is plotted against replicate 2 for mean values of normalized barcode counts for docetaxel (25 nM)-treated versus vehicle-treated OVCAR8-ADR cells (a), and for relative cell viability at day 4 versus day 1 (b), for each three-wise combination. a, b (lower panel), Distributions of differences in the log2 fold change between two biological replicates at a bin size of 0.1 are shown. A majority of three-wise combinations (88-90%) had <0.3 log2 fold-change differences. R is the Pearson correlation coefficient.
Supplementary Figure 8 Three-dimensional Plots Depicting the Docetaxel-Sensitizing (a) and Proliferation-Modulating (b) Effects of Three-Wise miRNA Combinations.
The log2 ratios of the normalized barcode counts for docetaxel-treated versus four-day vehicle-treated OVCAR8-ADR cells (a) or four-day versus one-day cultured cells (b) were determined for all three-wise miRNA combinations, and were presented as colored bubbles. miRNA combinations with drug-resistance and drug-sensitization effects (a) have log2 ratios >0 and <0, respectively, and those with pro-proliferation and anti-proliferation effects (b) have log2 ratios >0 and <0, respectively. Each two-dimensional plane was arranged in the same hierarchically clustered order as in (Fig. 5a-c), and the additional third miRNA element is labeled. All log2 ratios shown were determined from the mean of two biological replicates.
Synergistic or buffering interactions have positive and negative GI scores, respectively, as described for case 1 to 7 in this figure. Positive and negative phenotypes have fold-changes of normalized barcode reads of >1 and <1 respectively, while no phenotype corresponds to a fold-change = 1. For miRNAs [A] and [B] with individual phenotypes “A” and “B”, the expected phenotype for the two-wise combination [A,B] is (“A” + “B” - 1) according to the additive model. Deviation was calculated by subtracting the expected phenotype from observed phenotype (i.e., Observed phenotype – Expected phenotype).
Supplementary Figure 10 GI Scores Between Biological Replicates for All Individual Combinations in the Pooled Screens.
a-c (upper panel), GI scores in biological replicate 1 are plotted against replicate 2 for docetaxel (25 nM)-treated versus vehicle-treated OVCAR8-ADR cells for each two-wise combination (a) and three-wise miRNA combination (b) respectively, and for relative cell viability at day 4 versus day 1 for each three-wise combination (c). a-c (lower panel), Distributions of differences in the GI scores between two biological replicates at a bin size of 0.1 are shown. A majority of combinations (80-93%) had GI score differences of <0.2.
Supplementary Figure 11 Synergistic Interactions between the miR-16-1/15a Cluster, miR-128b, and the let-7e/miR-99b Cluster Modulate Cell Proliferation Phenotypes.
a, GI scores for a given three-wise miRNA combination [A,B,C] are plotted and compared to other combinations that harbor two of the same miRNAs (in the first two positions) and every other miRNA member in our library (denoted as X in the third position). GI scores of each three-wise miRNA combination were calculated as described in Online Methods , and represent the interaction between the additional third miRNA and the two-wise miRNA combinations. GI scores were determined for the three possible permutations (i.e., [A,B,C], [B,C,A], and [A,C,B], see Online Methods ). In this example, A, B, and C represent the miR-16-1/15a cluster, miR-128b, and the let-7e/miR-99b cluster respectively, and X represents all 39 library members. b-d, GI maps based on cell-proliferation phenotypes for all three-wise miRNA combinations harboring the miR-16-1/15a cluster, miR-128b, and/or the let-7e/miR-99b cluster are displayed in the same order as for the GI map in Fig. 5a for easy comparison, with the additional third miRNA element in the three-wise combination being labeled above each GI map. The combinations for which no GIs were measured are indicated in gray. The combinations with GI at a Q-value of <0.003 are boxed.
Supplementary Figure 12 Three-Wise miRNA Combinations Display Distinct Docetaxel Sensitivity and Anti-Proliferation Phenotypes.
Fold changes of normalized barcode counts for docetaxel (25 nM)-treated versus vehicle-treated OVCAR8-ADR cells (y-axis) and also for four-day versus one-day cultured cells (x-axis) were plotted for all three-wise miRNA combinations. Each data point represents the mean of two biological replicates.
Supplementary Figure 13 Combinatorial Expression of the miR-16-1/15a Cluster, miR-128b, and the let-7e/miR-99b Cluster Inhibits Colony Formation by Viable OVCAR8-ADR Cells.
a, b, ~10,000 OVCAR8-ADR cells infected with each indicated miRNA combinations were treated with 25 nM of docetaxel for three days, and were cultured for another eleven days. Cells were stained with crystal violet to visualize colony formation for quantification. Representative images are shown in (a). The number of colonies for each sample was determined (b). The maximum number of discrete colonies that could be reliably counted was ~500 per well, and thus, samples with more than 500 colonies are presented as >500 colonies. Data represent mean ± s.d. (n = 3; *P < 0.05).
Supplementary Figure 14 High Consistency between Pooled Screens and Validation Data for Individual Hits.
For each two-wise and three-wise miRNA combination, the fold-change in the normalized barcode count for docetaxel (25 nM)-treated versus vehicle-treated OVCAR8-ADR cells, or four-day versus one-day cultured cells, obtained from the pooled screening data (‘Screen phenotype’) was plotted against its relative cell viability compared to vector control determined from the individual drug-sensitivity or cell-proliferation assays, respectively (‘Validation phenotype’) (R = 0.899). Data for the screening data are the mean of two biological replicates while the individual validation data represent the mean of three independent experiments. R is the Pearson correlation coefficient.
Supplementary Figure 15 Combinatorial Expression of the miR-16/15a Cluster, miR-128b, and/or the let-7e/miR-99b Cluster Reduce mRNA Levels of Targeted Genes in OVCAR8-ADR Cells.
a, qRT-PCR quantification of relative mRNA levels in OVCAR8-ADR cells expressing the miR-16/15a cluster or co-expressing the miR-16/15a cluster, miR-128b, and the let-7e/miR-99b cluster. Measured mRNA levels were normalized to GAPDH mRNA levels, and data represent mean ± s.d. (n = 3). mRNAs that were predicted or validated to contain conserved sites matching the seed region of the corresponding miRNAs using TargetScan and miRTarBase are shaded in orange in the table below the graph. Significant differences in the mRNA levels of CCND1, CCND3, CCNE1 and CHEK1 in cells expressing the miR-16/15a cluster (orange #; P < 0.05) or co-expressing the miR-16/15a cluster, miR-128b, and the let-7e/miR-99b cluster (purple #; P < 0.05) were determined by comparison with vector-control-infected cells. The asterisk (*P < 0.05) represents a significant difference in mRNA levels between cells expressing the miR-16/15a cluster versus co-expressing the miR-16/15a cluster, miR-128b, and the let-7e/miR-99b cluster. b, Relative mRNA levels of CDC14B in cells expressing various combinations of the miR-16/15a cluster, miR-128b, and/or the let-7e/miR-99b cluster. The mRNA level of CDC14B was significantly reduced in cells co-expressing the let-7e/miR-99b cluster and miR-128b, or the triple-combination expressing the miR-16/15a cluster, miR-128b, and the let-7e/miR-99b cluster. Data represent mean ± s.d. (n = 9; *P < 0.05). c, Summary diagram illustrating the potential roles of the miR-16/15a cluster, miR-128b, and the let-7e/miR-99b cluster in regulating the mRNA levels of multiple downstream targets. These genes may represent targets for future investigation into mechanisms that can modulate docetaxel resistance and/or proliferation phenotypes in OVCAR8-ADR cells.
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Wong, A., Choi, G., Cheng, A. et al. Massively parallel high-order combinatorial genetics in human cells. Nat Biotechnol 33, 952–961 (2015). https://doi.org/10.1038/nbt.3326
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