Multiplexed barcoded CRISPR-Cas9 screening enabled by CombiGEM

• Main Authors: Wong, Siu Lun (Contributor), Cui, Cheryl (Contributor), Pregernig, Gabriela (Contributor), Milani, Pamela (Contributor), Choi, Gigi C. G. (Contributor), Adam, Miriam (Contributor), Perli, Samuel D. (Contributor), Kazer, Samuel Weisgurt (Contributor), Gaillard de Saint Germain, Alethe (Contributor), Hermann, Mario (Contributor), Shalek, Alexander K (Contributor), Fraenkel, Ernest (Contributor), Lu, Timothy K (Contributor)
• Other Authors: MIT Synthetic Biology Center (Contributor), Institute for Medical Engineering and Science (Contributor), Massachusetts Institute of Technology. Department of Biological Engineering (Contributor), Massachusetts Institute of Technology. Department of Chemistry (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Research Laboratory of Electronics (Contributor), Ragon Institute of MGH, MIT and Harvard (Contributor)
• Format: Article
• Language: English
• Published: National Academy of Sciences (U.S.), 2017-01-12T14:34:58Z.
• Subjects: Article
• Online Access: Get fulltext

 The orchestrated action of genes controls complex biological phenotypes, yet the systematic discovery of gene and drug combinations that modulate these phenotypes in human cells is labor intensive and challenging to scale. Here, we created a platform for the massively parallel screening of barcoded combinatorial gene perturbations in human cells and translated these hits into effective drug combinations. This technology leverages the simplicity of the CRISPR-Cas9 system for multiplexed targeting of specific genomic loci and the versatility of combinatorial genetics en masse (CombiGEM) to rapidly assemble barcoded combinatorial genetic libraries that can be tracked with high-throughput sequencing. We applied CombiGEM-CRISPR to create a library of 23,409 barcoded dual guide-RNA (gRNA) combinations and then perform a high-throughput pooled screen to identify gene pairs that inhibited ovarian cancer cell growth when they were targeted. We validated the growth-inhibiting effects of specific gene sets, including epigenetic regulators KDM4C/BRD4 and KDM6B/BRD4, via individual assays with CRISPR-Cas-based knockouts and RNA-interference-based knockdowns. We also tested small-molecule drug pairs directed against our pairwise hits and showed that they exerted synergistic antiproliferative effects against ovarian cancer cells. We envision that the CombiGEM-CRISPR platform will be applicable to a broad range of biological settings and will accelerate the systematic identification of genetic combinations and their translation into novel drug combinations that modulate complex human disease phenotypes.