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A genome-wide CRISPR screen identifies a restricted set of HIV host dependency factors

Nature Genetics volume 49, pages 193–203 (2017)Cite this article

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Abstract

Host proteins are essential for HIV entry and replication and can be important nonviral therapeutic targets. Large-scale RNA interference (RNAi)-based screens have identified nearly a thousand candidate host factors, but there is little agreement among studies and few factors have been validated. Here we demonstrate that a genome-wide CRISPR-based screen identifies host factors in a physiologically relevant cell system. We identify five factors, including the HIV co-receptors CD4 and CCR5, that are required for HIV infection yet are dispensable for cellular proliferation and viability. Tyrosylprotein sulfotransferase 2 (TPST2) and solute carrier family 35 member B2 (SLC35B2) function in a common pathway to sulfate CCR5 on extracellular tyrosine residues, facilitating CCR5 recognition by the HIV envelope. Activated leukocyte cell adhesion molecule (ALCAM) mediates cell aggregation, which is required for cell-to-cell HIV transmission. We validated these pathways in primary human CD4+ T cells through Cas9-mediated knockout and antibody blockade. Our findings indicate that HIV infection and replication rely on a limited set of host-dispensable genes and suggest that these pathways can be studied for therapeutic intervention.

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Figure 1: A pooled, genome-wide CRISPR screen for HIV HDFs.
Figure 2: Loss of TPST2 or SLC35B2 confers strong protection against HIV infection and entry without compromising host cell viability.
Figure 3: SLC35B2 and TPST2 function in a common pathway for the sulfation of CCR5.
Figure 4: Homophilic ALCAM interactions are necessary for GXRCas9 cell aggregation.
Figure 5: Loss of ALCAM protects against cell-to-cell transmission of HIV through disruption of cell aggregation.
Figure 6: CRISPR-based approach for validation of HIV HDFs in primary human CD4+ T cells.

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Acknowledgements

We would like to thank the Ragon Institute Virology, Imaging, and Flow Cytometry cores, as well as the Center for Computational and Integrative Biology (CCIB) DNA Core Facility at Massachusetts General Hospital. We would like to thank A. McKeon, P. Jani, N.W. Hughes, and B.X. Liu for superb technical assistance, and A. Brass, G. Gaiha, and J.S. Park for helpful discussions. pMM310 was obtained through the AIDS Reagent Program, Division of AIDS, NIAID, NIH from M. Miller (Merck Research Laboratories). All plasmid reagents generated in this study have been deposited in Addgene. This work was supported by the Howard Hughes Medical Institute (D.M.S. and B.D.W.), the National Institutes of Health (grants CA103866 (D.M.S.), F31 CA189437 (T.W.), P50 GM082250 (A.M. and N.J.K.), U19 AI106754 (J.F.H. and N.J.K.), and P01 AI090935 (N.J.K.)), the National Human Genome Research Institute (grant 2U54HG003067-10; E.S.L.), the National Science Foundation (T.W.), the MIT Whitaker Health Sciences Fund (T.W.), the UCSF Sandler Fellowship (A.M.), a gift from J. Aronov (A.M.), the UCSF MPHD T32 Training Grant (J.F.H.), and the Deutsche Forschungsgemeinschaft (grant SCHU3020/2-1; K.S.). Support was also provided by NIH-funded Centers for AIDS Research (grant P30 AI027763, UCSF Center for AIDS Research (N.J.K.) and grant P30 AI060354, Harvard University Center for AIDS Research (B.D.W.)), which are supported by the following NIH co-funding and participating Institutes and Centers: NIAID, NCI, NICHD, NHLBI, NIDA, NIMH, NIA, FIC, and OAR. D.M.S. and B.D.W. are investigators of the Howard Hughes Medical Institute. R.J.P. is a Howard Hughes Medical Institute Research Fellow.

Author information

Author notes

  1. Ryan J Park and Tim Wang: These authors contributed equally to this work.

  2. bwalker@mgh.harvard.edu

Authors and Affiliations

  1. Ragon Institute of Massachusetts General Hospital (MGH), Massachusetts Institute of Technology (MIT), and Harvard University, Cambridge, Massachusetts, USA

    Ryan J Park, Dylan Koundakjian, Pedro Lamothe-Molina, Blandine Monel, Wilfredo Garcia-Beltran, Alicja Piechocka-Trocha & Bruce D Walker

  2. Harvard–MIT Health Sciences and Technology, Harvard Medical School, Boston, Massachusetts, USA

    Ryan J Park & Wilfredo Garcia-Beltran

  3. Broad Institute of MIT and Harvard University, Cambridge, Massachusetts, USA

    Ryan J Park, Tim Wang, Haiyan Yu, David M Sabatini, Eric S Lander, Nir Hacohen & Bruce D Walker

  4. Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Tim Wang, David M Sabatini & Eric S Lander

  5. Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, USA

    Tim Wang, Kevin M Krupzcak & David M Sabatini

  6. David H. Koch Institute for Integrative Cancer Research at MIT, Cambridge, Massachusetts, USA

    Tim Wang & David M Sabatini

  7. Department of Cellular and Molecular Pharmacology, California Institute for Quantitative Biosciences, QB3, University of California at San Francisco (UCSF), San Francisco, California, USA

    Judd F Hultquist & Nevan J Krogan

  8. Gladstone Institute of Virology and Immunology, J. David Gladstone Institutes, San Francisco, California, USA

    Judd F Hultquist & Nevan J Krogan

  9. Biological Sciences in Public Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA

    Pedro Lamothe-Molina

  10. Howard Hughes Medical Institute, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA

    Blandine Monel & Bruce D Walker

  11. Department of Microbiology and Immunology, University of California at San Francisco, San Francisco, California, USA

    Kathrin Schumann & Alexander Marson

  12. Diabetes Center, University of California at San Francisco, San Francisco, California, USA

    Alexander Marson

  13. Department of Medicine, University of California at San Francisco, San Francisco, California, USA

    Alexander Marson

  14. Innovative Genomics Initiative (IGI), University of California, Berkeley, Berkeley, California, USA

    Alexander Marson

  15. UCSF Helen Diller Family Comprehensive Cancer Center, University of California at San Francisco, San Francisco, California, USA

    Alexander Marson

  16. Department of Biology, Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    David M Sabatini

  17. Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA

    Eric S Lander

  18. Massachusetts General Hospital Cancer Center, Boston, Massachusetts, USA

    Nir Hacohen

  19. Institute of Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Bruce D Walker

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  1. Ryan J Park
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Contributions

R.J.P., T.W., A.M., N.J.K., D.M.S., E.S.L., N.H., and B.D.W. designed research. R.J.P., T.W., D.K., J.F.H., P.L.-M., B.M., K.S., H.Y., and K.M.K. conducted experiments. W.G.-B. and A.P.-T. contributed methods and reagents. R.J.P., T.W., D.K., and J.F.H. analyzed data. R.J.P., T.W., N.H., and B.D.W. wrote the manuscript.

Corresponding authors

Correspondence to David M Sabatini, Eric S Lander, Nir Hacohen or Bruce D Walker.

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Competing interests

T.W., D.M.S., and E.S.L. are inventors on a patent application for functional genomics using the CRISPR–Cas system (US 15/141,348), T.W. and D.M.S. are founders of KSQ Therapeutics, a CRISPR functional genomics company, and D.M.S. is a scientific advisor for KSQ Therapeutics. A patent has been filed on the use of Cas9–RNPs to edit the genome of human primary T cells (A.M. and K.S.). A.M. serves as an advisor to Juno Therapeutics, and the laboratory of A.M. has had sponsored research agreements with Juno Therapeutics and Epinomics.

Integrated supplementary information

Supplementary Figure 1 Alternative gene ranking method reveals an identical set of HIV HDFs.

Gene scores were calculated by using mean log2 fold change in the abundance of all sgRNAs for each gene.

Supplementary Figure 2 mRNA expression analysis of SLC35B2 and TPST2 in GXRCas9 cells subcloned following CRISPR-based knockout.

Wild-type SLC35B2 and TPST2 mRNA expression levels in WT GXRCas9 cells and TPST2- and SLC35B2-knockout clones as assessed by qRT-PCR, using primers that overlap the sgRNA target site to selectively amplify wild-type cDNA. Error bars, s.d. from triplicate reactions.

Supplementary Figure 3 ALCAM-null GXRCas9 cells are protected from a multi-round, spreading JR-CSF infection.

Low MOI (MOI = 0.1) virus challenge. Six days following JR-CSF infection, viable, GFP– cells were counted and cell number was normalized to that under a mock-infected condition. Error bars, s.d. from triplicate wells; *P < 0.0001, Welch’s t test.

Supplementary Figure 4 Validation of SLC35B2 as an HIV HDF in primary human CD4+ T cells.

Sulfation of surface CCR5 in primary CD4+ T cells following JR-CSF or Rejo.C challenge. Intracellular HIV Gag (p24) and total and sulfated surface CCR5 expression are shown as assessed by flow cytometry. Error bars, s.d. from triplicate wells; *P < 0.01, Welch’s t test. All P < 0.0001, except as follows: Donor 1 uninfected vs. Rejo.C p24+, P = 0.0005; Donor 2 uninfected vs. JRCSF p24–, P = 0.0003; uninfected vs. Rejo.C p24–, P = 0.0033; Rejo.C p24– vs. p24+, P = 0.0001.

Supplementary Figure 5 mRNA expression analysis of selected genes involved in T cell adhesion.

mRNA expression of ALCAM, LFA-1, and the ICAM family in primary CD4+ T cells and GXRCas9 cells as assessed by RNA sequencing.

Supplementary Figure 6 Antibody blockade of cell adhesion factors attenuates HIV spread in primary human CD4+ T cells.

(a) CRISPR-mediated knockout of the LFA-1 subunit (encoded by ITGAL) only blocks cell-to-cell transmission if donor and acceptor cells are both CD11a-null. (b,c) Cell-to-cell HIV transmission assay in primary CD4+ T cells following blockade with antibody to ICAM-1/LFA-1 (b) or CD45, as a control (c). The assay is set up as in Figure 5 except that donor cells are infected 36 h prior to co-culture and co-culture is for 2 d. Readout is by flow cytometry following intracellular staining for HIV Gag. Antibodies against ICAM-1, CD11a, and CD18 are added 15 min prior to co-culture. Error bars, s.d. from triplicate wells; *P < 0.01, Welch’s t test. P values were as follows: (a) n.s., P = 0.836; *P = 0.0036; (b) *P = 0.002; (c) n.s., P = 0.72.

Supplementary Figure 7 Loss of RELA, a candidate HDF identified by three previous RNAi screens, does not protect GXR cells from JR-CSF viral challenge.

Virus challenge assay (JR-CSF, MOI = 1) of GXRCas9 cells transduced with sgRELA (left) and immunoblot demonstrating depletion of RelA (right). RagC is a loading control. Error bars, s.d. from triplicate wells; n.s., P = 0.787, Welch’s t test.

Supplementary Figure 8 Essentiality analysis of screen hits and selected putative HIV HDFs.

Screen for essential genes in the Raji B cell line (Wang et al., 2015). For every gene in the human genome, the mean of the individual log2-transformed fold change values in the abundance of each of the sgRNAs targeting that gene is shown. Screen hits and selected putative HIV HDFs that are among the 10% most depleted (i.e., cell-essential) genes are highlighted.

Supplementary Figure 9 mRNA expression analysis of paralogous sulfation pathway genes.

(a,b) mRNA expression of TPST2, SLC35B2, PAPSS1, and select paralogs in GXRCas9 cells (a) and activated, primary CD4+ T cells and GXRCas9 cells (b) as assessed by RNA sequencing.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–9 and Supplementary Note. (PDF 1104 kb)

Supplementary Table 1

Genome-wide human sgRNA library annotation. (XLSX 10841 kb)

Supplementary Table 2

CRISPR gene scores. (XLSX 518 kb)

Supplementary Table 3

RNA sequencing analysis of GXRCas9 and activated, primary CD4+ T cells. (XLSX 1261 kb)

Supplementary Table 4

Nucleotide sequences. (XLSX 8 kb)

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Park, R., Wang, T., Koundakjian, D. et al. A genome-wide CRISPR screen identifies a restricted set of HIV host dependency factors. Nat Genet 49, 193–203 (2017). https://doi.org/10.1038/ng.3741

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