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Orthologous CRISPR–Cas9 enzymes for combinatorial genetic screens

Nature Biotechnology volume 36, pages 179–189 (2018)Cite this article

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Abstract

Combinatorial genetic screening using CRISPR–Cas9 is a useful approach to uncover redundant genes and to explore complex gene networks. However, current methods suffer from interference between the single-guide RNAs (sgRNAs) and from limited gene targeting activity. To increase the efficiency of combinatorial screening, we employ orthogonal Cas9 enzymes from Staphylococcus aureus and Streptococcus pyogenes. We used machine learning to establish S. aureus Cas9 sgRNA design rules and paired S. aureus Cas9 with S. pyogenes Cas9 to achieve dual targeting in a high fraction of cells. We also developed a lentiviral vector and cloning strategy to generate high-complexity pooled dual-knockout libraries to identify synthetic lethal and buffering gene pairs across multiple cell types, including MAPK pathway genes and apoptotic genes. Our orthologous approach also enabled a screen combining gene knockouts with transcriptional activation, which revealed genetic interactions with TP53. The “Big Papi” (paired aureus and pyogenes for interactions) approach described here will be widely applicable for the study of combinatorial phenotypes.

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Figure 1: Development of a two Cas9 system for combinatorial screening.
Figure 2: Development of SaCas9 on-target rules.
Figure 3: Evaluation of synthetic lethal screens.
Figure 4: Synthetic lethal Big Papi screen.
Figure 5: Validation of synthetic lethal interactions.
Figure 6: Apoptosis Big Papi screen.
Figure 7: Big Papi screen with two Cas9 activities.

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References

  1. Roguev, A. et al. Quantitative genetic-interaction mapping in mammalian cells. Nat. Methods 10, 432–437 (2013).

    Article  CAS  Google Scholar 

  2. Horn, T. et al. Mapping of signaling networks through synthetic genetic interaction analysis by RNAi. Nat. Methods 8, 341–346 (2011).

    Article  CAS  Google Scholar 

  3. Tong, A.H.Y. et al. Global mapping of the yeast genetic interaction network. Science 303, 808–813 (2004).

    Article  CAS  Google Scholar 

  4. Costanzo, M. et al. A global genetic interaction network maps a wiring diagram of cellular function. Science 353, aaf1420 (2016).

    Article  Google Scholar 

  5. Bassik, M.C. et al. A systematic mammalian genetic interaction map reveals pathways underlying ricin susceptibility. Cell 152, 909–922 (2013).

    Article  CAS  Google Scholar 

  6. Wong, A.S.L. et al. Multiplexed barcoded CRISPR-Cas9 screening enabled by CombiGEM. Proc. Natl. Acad. Sci. USA 113, 2544–2549 (2016).

    Article  CAS  Google Scholar 

  7. Shen, J.P. et al. Combinatorial CRISPR-Cas9 screens for de novo mapping of genetic interactions. Nat. Methods 14, 573–576 (2017).

    Article  CAS  Google Scholar 

  8. Han, K. et al. Synergistic drug combinations for cancer identified in a CRISPR screen for pairwise genetic interactions. Nat. Biotechnol. 35, 463–474 (2017).

    Article  CAS  Google Scholar 

  9. ter Brake, O. et al. Lentiviral vector design for multiple shRNA expression and durable HIV-1 inhibition. Mol. Ther. 16, 557–564 (2008).

    Article  CAS  Google Scholar 

  10. Vidigal, J.A. & Ventura, A. Rapid and efficient one-step generation of paired gRNA CRISPR-Cas9 libraries. Nat. Commun. 6, 8083 (2015).

    Article  CAS  Google Scholar 

  11. Adamson, B. et al. A multiplexed single-cell CRISPR screening platform enables systematic dissection of the unfolded protein response. Cell 167, 1867–1882.e21 (2016).

    Article  CAS  Google Scholar 

  12. Zetsche, B. et al. Multiplex gene editing by CRISPR-Cpf1 using a single crRNA array. Nat. Biotechnol. 35, 31–34 (2017).

    Article  CAS  Google Scholar 

  13. McIntyre, G.J., Arndt, A.J., Gillespie, K.M., Mak, W.M. & Fanning, G.C. A comparison of multiple shRNA expression methods for combinatorial RNAi. Genet. Vaccines Ther. 9, 9 (2011).

    Article  CAS  Google Scholar 

  14. Stockman, V.B. et al. A high-throughput strategy for dissecting mammalian genetic interactions. PLoS One 11, e0167617–e13 (2016).

    Article  Google Scholar 

  15. Gilbert, L.A. et al. Genome-scale CRISPR-mediated control of gene repression and activation. Cell 159, 647–661 (2014).

    Article  CAS  Google Scholar 

  16. Doench, J.G. et al. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nat. Biotechnol. 34, 184–191 (2016).

    Article  CAS  Google Scholar 

  17. Zhu, S. et al. Genome-scale deletion screening of human long non-coding RNAs using a paired-guide RNA CRISPR-Cas9 library. Nat. Biotechnol. 34, 1279–1286 (2016).

    Article  CAS  Google Scholar 

  18. Doench, J.G. et al. Rational design of highly active sgRNAs for CRISPR-Cas9-mediated gene inactivation. Nat. Biotechnol. 32, 1262–1267 (2014).

    Article  CAS  Google Scholar 

  19. Ran, F.A. et al. In vivo genome editing using Staphylococcus aureus Cas9. Nature 520, 186–191 (2015).

    Article  CAS  Google Scholar 

  20. Friedland, A.E. et al. Characterization of Staphylococcus aureus Cas9: a smaller Cas9 for all-in-one adeno-associated virus delivery and paired nickase applications. Genome Biol. 16, 257 (2015).

    Article  Google Scholar 

  21. Hanzlikova, H., Gittens, W., Krejcikova, K., Zeng, Z. & Caldecott, K.W. Overlapping roles for PARP1 and PARP2 in the recruitment of endogenous XRCC1 and PNKP into oxidized chromatin. Nucleic Acids Res. 45, 2546–2557 (2017).

    CAS  PubMed  Google Scholar 

  22. Farmer, H. et al. Targeting the DNA repair defect in BRCA mutant cells as a therapeutic strategy. Nature 434, 917–921 (2005).

    Article  CAS  Google Scholar 

  23. van Delft, M.F. et al. The BH3 mimetic ABT-737 targets selective Bcl-2 proteins and efficiently induces apoptosis via Bak/Bax if Mcl-1 is neutralized. Cancer Cell 10, 389–399 (2006).

    Article  CAS  Google Scholar 

  24. Sun, C. & Bernards, R. Feedback and redundancy in receptor tyrosine kinase signaling: relevance to cancer therapies. Trends Biochem. Sci. 39, 465–474 (2014).

    Article  CAS  Google Scholar 

  25. Buscà, R., Pouysségur, J. & Lenormand, P. ERK1 and ERK2 Map Kinases: Specific Roles or Functional Redundancy? Front. Cell Dev. Biol. 4, 53 (2016).

    Article  Google Scholar 

  26. Uzgare, A.R. & Isaacs, J.T. Enhanced redundancy in Akt and mitogen-activated protein kinase-induced survival of malignant versus normal prostate epithelial cells. Cancer Res. 64, 6190–6199 (2004).

    Article  CAS  Google Scholar 

  27. Srivas, R. et al. A network of conserved synthetic lethal interactions for exploration of precision cancer therapy. Mol. Cell 63, 514–525 (2016).

    Article  CAS  Google Scholar 

  28. Hart, T. et al. High-resolution CRISPR screens reveal fitness genes and genotype-specific cancer liabilities. Cell 163, 1515–1526 (2015).

    Article  CAS  Google Scholar 

  29. Chaudhuri, L. et al. CHK1 and WEE1 inhibition combine synergistically to enhance therapeutic efficacy in acute myeloid leukemia ex vivo. Haematologica 99, 688–696 (2014).

    Article  CAS  Google Scholar 

  30. Souers, A.J. et al. ABT-199, a potent and selective BCL-2 inhibitor, achieves antitumor activity while sparing platelets. Nat. Med. 19, 202–208 (2013).

    Article  CAS  Google Scholar 

  31. Oltersdorf, T. et al. An inhibitor of Bcl-2 family proteins induces regression of solid tumours. Nature 435, 677–681 (2005).

    Article  CAS  Google Scholar 

  32. Leverson, J.D. et al. Exploiting selective BCL-2 family inhibitors to dissect cell survival dependencies and define improved strategies for cancer therapy. Sci. Transl. Med. 7, 279ra40 (2015).

    Article  Google Scholar 

  33. Lessene, G. et al. Structure-guided design of a selective BCL-X(L) inhibitor. Nat. Chem. Biol. 9, 390–397 (2013).

    Article  CAS  Google Scholar 

  34. Kotschy, A. et al. The MCL1 inhibitor S63845 is tolerable and effective in diverse cancer models. Nature 538, 477–482 (2016).

    Article  Google Scholar 

  35. Dummler, B. et al. Life with a single isoform of Akt: mice lacking Akt2 and Akt3 are viable but display impaired glucose homeostasis and growth deficiencies. Mol. Cell. Biol. 26, 8042–8051 (2006).

    Article  CAS  Google Scholar 

  36. Nitulescu, G.M. et al. Akt inhibitors in cancer treatment: The long journey from drug discovery to clinical use (Review). Int. J. Oncol. 48, 869–885 (2016).

    Article  CAS  Google Scholar 

  37. Stordal, B. et al. BRCA1/2 mutation analysis in 41 ovarian cell lines reveals only one functionally deleterious BRCA1 mutation. Mol. Oncol. 7, 567–579 (2013).

    Article  CAS  Google Scholar 

  38. Helleday, T. The underlying mechanism for the PARP and BRCA synthetic lethality: clearing up the misunderstandings. Mol. Oncol. 5, 387–393 (2011).

    Article  CAS  Google Scholar 

  39. Rooswinkel, R.W. et al. Antiapoptotic potency of Bcl-2 proteins primarily relies on their stability, not binding selectivity. Blood 123, 2806–2815 (2014).

    Article  CAS  Google Scholar 

  40. Cowling, V. & Downward, J. Caspase-6 is the direct activator of caspase-8 in the cytochrome c-induced apoptosis pathway: absolute requirement for removal of caspase-6 prodomain. Cell Death Differ. 9, 1046–1056 (2002).

    Article  CAS  Google Scholar 

  41. Kroemer, G., Galluzzi, L. & Brenner, C. Mitochondrial membrane permeabilization in cell death. Physiol. Rev. 87, 99–163 (2007).

    Article  CAS  Google Scholar 

  42. Li, P. et al. Cytochrome c and dATP-dependent formation of Apaf-1/caspase-9 complex initiates an apoptotic protease cascade. Cell 91, 479–489 (1997).

    Article  CAS  Google Scholar 

  43. Ma, S.B. et al. Bax targets mitochondria by distinct mechanisms before or during apoptotic cell death: a requirement for VDAC2 or Bak for efficient Bax apoptotic function. Cell Death Differ. 21, 1925–1935 (2014).

    Article  CAS  Google Scholar 

  44. Sarosiek, K.A. et al. BID preferentially activates BAK while BIM preferentially activates BAX, affecting chemotherapy response. Mol. Cell 51, 751–765 (2013).

    Article  CAS  Google Scholar 

  45. Chavez, A. et al. Highly efficient Cas9-mediated transcriptional programming. Nat. Methods 12, 326–328 (2015).

    Article  CAS  Google Scholar 

  46. Rotem, A. et al. Alternative to the soft-agar assay that permits high-throughput drug and genetic screens for cellular transformation. Proc. Natl. Acad. Sci. USA 112, 5708–5713 (2015).

    Article  CAS  Google Scholar 

  47. Miura, Y. et al. Susceptibility to killer T cells of gastric cancer cells enhanced by Mitomycin-C involves induction of ATBF1 and activation of p21 (Waf1/Cip1) promoter. Microbiol. Immunol. 48, 137–145 (2004).

    Article  CAS  Google Scholar 

  48. Wong, C.C. et al. Inactivating CUX1 mutations promote tumorigenesis. Nat. Genet. 46, 33–38 (2014).

    Article  CAS  Google Scholar 

  49. Faraonio, R. et al. p53 suppresses the Nrf2-dependent transcription of antioxidant response genes. J. Biol. Chem. 281, 39776–39784 (2006).

    Article  CAS  Google Scholar 

  50. Gao, Y. et al. Complex transcriptional modulation with orthogonal and inducible dCas9 regulators. Nat. Methods 13, 1043–1049 (2016).

    Article  CAS  Google Scholar 

  51. Kleinstiver, B.P. et al. Broadening the targeting range of Staphylococcus aureus CRISPR-Cas9 by modifying PAM recognition. Nat. Biotechnol. 33, 1293–1298 (2015).

    Article  CAS  Google Scholar 

  52. Lawrence, M.S. et al. Discovery and saturation analysis of cancer genes across 21 tumour types. Nature 505, 495–501 (2014).

    Article  CAS  Google Scholar 

  53. Forbes, S.A. et al. COSMIC: somatic cancer genetics at high-resolution. Nucleic Acids Res. 45, D1, D777–D783 (2017).

    Article  Google Scholar 

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Acknowledgements

We thank S. Elmore and G. Wei for helpful discussions; E. Sukharevsky, R. Hanna, and I. Sebenius for experimental assistance and comments on the manuscript; D. Ortiz for emotional uplift. We thank T. Hart and other anonymous referees for helpful comments during the review process. F.J.N. is supported by a cellular and developmental biology training grant (NIH T32GM007226-41). J.G.D. is supported by the Next Generation Fund at the Broad Institute of MIT and Harvard. This work was supported by the Functional Genomics Consortium (D.E.R.)., Starr Cancer Consortium (B.E.B.), and National Cancer Institute–NIH Common Fund (DP1CA216873) (B.E.B.).

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Author notes

  1. Fadi J Najm, Christine Strand, Katherine F Donovan, Mudra Hegde and Kendall R Sanson: These authors contributed equally to this work.

Authors and Affiliations

  1. Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA

    Fadi J Najm, Christine Strand, Katherine F Donovan, Mudra Hegde, Kendall R Sanson, Emma W Vaimberg, Meagan E Sullender, Ella Hartenian, Zohra Kalani, Scott T Younger, Bradley E Bernstein, David E Root & John G Doench

  2. Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA

    Fadi J Najm & Bradley E Bernstein

  3. Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA

    Fadi J Najm & Bradley E Bernstein

  4. Microsoft Research New England, Cambridge, Massachusetts, USA

    Nicolo Fusi & Jennifer Listgarten

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Contributions

F.J.N., C.S., K.F.D., K.R.S., Z.K., E.W.V., M.E.S., E.H., and J.G.D. designed and performed experiments. N.F. and J.L. performed the computational modeling of SaCas9 activity. M.H., S.T.Y., and J.G.D. analyzed screening data. B.E.B. and D.E.R. provided senior guidance. F.J.N., D.E.R., and J.G.D. wrote the manuscript with assistance from other authors.

Corresponding author

Correspondence to John G Doench.

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Competing interests

J.L. and N.F. are employed by Microsoft Research. J.G.D. consults for Tango Therapeutics.

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Najm, F., Strand, C., Donovan, K. et al. Orthologous CRISPR–Cas9 enzymes for combinatorial genetic screens. Nat Biotechnol 36, 179–189 (2018). https://doi.org/10.1038/nbt.4048

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