CRISPR screen in regulatory T cells reveals modulators of Foxp3

Abstract

Regulatory T (Treg) cells are required to control immune responses and maintain homeostasis, but are a significant barrier to antitumour immunity1. Conversely, Treg instability, characterized by loss of the master transcription factor Foxp3 and acquisition of proinflammatory properties2, can promote autoimmunity and/or facilitate more effective tumour immunity3,4. A comprehensive understanding of the pathways that regulate Foxp3 could lead to more effective Treg therapies for autoimmune disease and cancer. The availability of new functional genetic tools has enabled the possibility of systematic dissection of the gene regulatory programs that modulate Foxp3 expression. Here we developed a CRISPR-based pooled screening platform for phenotypes in primary mouse Treg cells and applied this technology to perform a targeted loss-of-function screen of around 500 nuclear factors to identify gene regulatory programs that promote or disrupt Foxp3 expression. We identified several modulators of Foxp3 expression, including ubiquitin-specific peptidase 22 (Usp22) and ring finger protein 20 (Rnf20). Usp22, a member of the deubiquitination module of the SAGA chromatin-modifying complex, was revealed to be a positive regulator that stabilized Foxp3 expression; whereas the screen suggested that Rnf20, an E3 ubiquitin ligase, can serve as a negative regulator of Foxp3. Treg-specific ablation of Usp22 in mice reduced Foxp3 protein levels and caused defects in their suppressive function that led to spontaneous autoimmunity but protected against tumour growth in multiple cancer models. Foxp3 destabilization in Usp22-deficient Treg cells could be rescued by ablation of Rnf20, revealing a reciprocal ubiquitin switch in Treg cells. These results reveal previously unknown modulators of Foxp3 and demonstrate a screening method that can be broadly applied to discover new targets for Treg immunotherapies for cancer and autoimmune disease.

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Fig. 1: Discovery and validation of Foxp3 regulators in primary mouse Treg cells using a targeted pooled CRISPR screen.
Fig. 2: Usp22 is required for Foxp3 maintenance and Treg suppressive function.
Fig. 3: Treg-specific ablation of Usp22 results in autoimmunity and enhances antitumour immunity.

Data availability

Data from the screen (Fig. 1) and RNA sequencing (Fig. 2, Extended Data Fig. 5) are provided here in Supplementary Tables 1 and 5. ChIP–seq data that support the findings of this study have been deposited in the Gene Expression Omnibus under the accession code GSE140102. Foxp3 ChIP–seq results are in the Gene Expression Omnibus under accession code GSE40684; ATAC–seq and ChIP–seq for H3K4me, H3K27ac, H3K4me3 are in the Sequence Read Archive under accession number DRP003376. Source data for Figs. 13 and Extended Data Figs. 28 are provided with the paper. All other data are available from the corresponding author upon reasonable request.

Code availability

All code used for data visualization in this manuscript will be made available on request.

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Acknowledgements

We thank all members of the Marson lab as well as M. S. Anderson, K. M. Ansel, C. J. Ye, K. Schumann and L. Gilbert for helpful suggestions and technical advice; J. Freimer, S. Raju and E. Guo for helpful advice and assistance with the RNA-seq analysis pipeline; V. Nguyen, V. Tobin, R. Apathy, M. Nguyen, the UCSF Flow Cytometry Core, and N. Hah and G. Chou in the Salk NGS Core Facility for technical assistance; S. Pyle for assistance with graphics; and D. Nguyen for critical reading of the manuscript. D.F. is supported by NIH R01 grants (AI079056, AI108634 and CA232347). E.M. is supported by NIH F31 CA220801-03. J.T.C. is supported by the National Science Foundation Graduate Research Fellowship Program grant 1650113. J.G. was supported by the Salk Institute T32 Cancer Training Grant T32CA009370 and the NIGMS NRSA F32 GM128377-01. D.C.H. is supported by the National Institutes of Health (NIH) (GM128943-01, CA184043-03), the V Foundation for Cancer Research V2016-006, the Pew-Stewart Foundation for Cancer Research and the Leona M. and Harry B. Helmsley Charitable Trust. The Marson lab has received gifts from J. Aronov, G. Hoskin, K. Jordan, B. Bakar, the Caufield family and funds from the Innovative Genomics Institute (IGI), the Northern California JDRF Center of Excellence and the Parker Institute for Cancer Immunotherapy (PICI). A.M. holds a Career Award for Medical Scientists from the Burroughs Wellcome Fund, is an investigator at the Chan–Zuckerberg Biohub and is a recipient of a The Cancer Research Institute (CRI) Lloyd J. Old STAR grant. This work used the Vincent J. Coates Genomics Sequencing Laboratory at UC Berkeley, supported by NIH S10 OD018174 Instrumentation Grant, the UCSF Flow Cytometry Core, supported by the Diabetes Research Center grants NIH P30 DK063720 and NIH S10 1S10OD021822-01, and the Salk NGS Core Facility, supported by the NIH-NCI CCSG: P30 014195, the Chapman Foundation and the Helmsley Charitable Trust.

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Affiliations

Authors

Contributions

Conceptualization: J.T.C., E.M., E.S., Yusi .Z., Z.S., F.V.G., J.A.B., A.M. and D.F. Methodology: J.T.C., E.S. and T.L.R. Investigation: J.T.C., E.M., E.S., J.G., Yusi Z., O.S., Y.X., T.L.R., D.R.S., Yana Z., S.C., Z.L., J.M.W., J.H., I.A.V., G.Y.P., Y.L. and I.I. Resources: D.C.H., J.A.B., A.M. and D.F. Formal analysis: J.T.C., E.S. and J.G. Software: E.S. Data curation: J.T.C., E.S. and J.G. Supervision: B.Z., Y.L., F.V.G., D.C.H., J.A.B., A.M. and D.F. Funding acquisition: J.T.C., E.M., D.C.H., A.M. and D.F. Writing, original draft preparation: J.T.C., E.M., J.G., Yusi Z., A.M. and D.F. Writing, review and editing: J.T.C., E.M., J.G., Z.S., F.V.G., D.C.H., J.A.B., A.M. and D.F.

Corresponding authors

Correspondence to Alexander Marson or Deyu Fang.

Ethics declarations

Competing interests

T.L.R. is a cofounder of Arsenal Biosciences. A.M. is a cofounder, member of the Boards of Directors and a member of the Scientific Advisory Boards of Spotlight Therapeutics and Arsenal Biosciences. A.M. has served as an advisor to Juno Therapeutics, is a member of the scientific advisory board at PACT Pharma, and is an advisor to Trizell. A.M. owns stock in Arsenal Biosciences, Spotlight Therapeutics and PACT Pharma. The Marson lab has received sponsored research support from Juno Therapeutics, Epinomics and Sanofi, and gifts from Gilead and Anthem. J.A.B. is a cofounder of Sonoma BioTherapeutics; a stock holder and member of the Board of Directors on Rheos Medicines; and a stock holder and member of the Scientific Advisory Boards of Vir Therapeutics, Arcus Biotherapeutics, Solid Biosciences, and Celsius Therapeutics. J.A.B. owns stock in MacroGenics and Kadmon Holdings. A patent application has been filed based on the screen data described here.

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Peer review information Nature thanks John Doench, William P. Tansey and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Design and quality control of targeted pooled CRISPR screen in primary mouse Treg cells.

a, Design strategy for selection of genes for unbiased targeted library of 492 targets, including 489 nuclear factors and 3 control targets (non-targeting (NT), GFP and RFP). Genes were selected on the basis of gene ontology (GO) annotation and then subselected on the basis of highest expression across any CD4 T cell subset for a total of 2,000 sgRNAs. b, Diagram of MSCV expression vector with Thy1.1 reporter used for retroviral transduction of the sgRNA library. c, Detailed time line schematic of the 12-day targeted screen pipeline. Arrows indicate when the cells were split and medium was replenished. d, Retroviral transduction efficiency of the targeted library in primary mouse Treg cells shown by Thy1.1 surface expression measured by flow cytometry. The infection was scaled to achieve a high efficiency multiplicity of infection. e, Foxp3 expression from screen input, output and control cells measured by flow cytometry. Top, Foxp3 expression from input Foxp3+ purified Treg cells as measured by GFP expression on day 0. Middle, Foxp3 expression as measured by endogenous intracellular staining from control Treg cells (not transduced with library) on day 12. Bottom, Foxp3 expression as measured by endogenous intracellular staining from screen Treg cells (transduced with library) on day 12. f, Targeted screen (2,000 guides) shows that sgRNAs targeting Foxp3 and Usp22 were enriched in Foxp3low cells (blue). Non-targeting control (NT ctrl) sgRNAs were evenly distributed across the cell populations (black). g, Distribution of read counts after next-generation sequencing of sgRNAs of sorted cell populations, Foxp3high and Foxp3low. h, Schematic of experimentally determined and predicted protein–protein interactions between top hits, 16 negative regulators (red) and 25 positive regulators (red), generated by STRING-db59. Black lines connect interacting proteins and dotted lines outline selected known protein complexes. All data are presented as mean ± s.e.m. ns, no significant difference. Sample sizes (n), P values, statistical tests and number of times experiments were replicated are listed in Methods, ‘Statistics and reproducibility’.

Extended Data Fig. 2 Validation of Foxp3 modulators in primary mouse and human Treg cells with Cas9 RNP electroporation.

a, Overview of orthogonal validation strategy using arrayed electroporation of Cas9 RNPs in Treg cells. b, Foxp3 expression 4 days after electroporation of Cas9 RNPs in mouse Treg cells as measured by flow cytometry of top screen hits. Each row shows three histograms layered on top of one another (1–2 for controls) with each representing effects of independent gRNAs for each target gene. Percentages shown on the right depict the average frequency of Foxp3+ cells across gRNAs targeting each gene. c, Percentage of Foxp3 cells of live, CD4+ cells 4 days after electroporation of Cas9 RNPs in mouse Treg cells as measured by flow cytometry of top screen hits. Each data point represents an independent sgRNA for each target gene. d, Foxp3 MFI of Foxp3+ mouse Treg cells for 3-4 distinct gRNAs targeting each gene paired with the mean KO efficiency (top) for each guide as determined by TIDE analysis. e, Representative flow plots depicting FOXP3 and CD25 expression 7 days after electroporation of Cas9 RNPs targeting USP22 or NT ctrl in human Treg cells. The subpopulation of cells with the highest expression of FOXP3 and CD25 (FOXP3highCD25high) is highlighted with a red gate. f, Percentage of FOXP3+ cells from human Treg cells electroporated with Cas9 RNPs targeting USP22 or NT ctrl in ten biological replicates. Lines connect paired samples. g, Percentage of FOXP3highCD25high cells from human Treg cells electroporated with Cas9 RNPs targeting USP22 or NT ctrl in 10 biological replicates. h, FOXP3 MFI of human Treg cells for 3–4 distinct gRNAs targeting each gene paired with the mean KO efficiency (top) for each guide as determined by TIDE analysis. i, Simple linear regression of FOXP3 MFI (y axis) by percentage of editing efficiency determined by TIDE analysis (x axis) for 4 gRNAs targeting USP22 in 2–4 biological donors. j, FOXP3 MFI of human Treg cells electroporated with Cas9 RNPs with 2–3 distinct sgRNAs each in 2–4 biological donors; corresponding to h. Data points with less than 60% editing efficiency KO by TIDE analysis were excluded from the graph. All data are presented as mean ± s.e.m. Sample sizes (n), P values, statistical tests and number of times experiments were replicated are listed in Methods, ‘Statistics and reproducibility’Source Data.

Extended Data Fig. 3 Design and validation of Treg-specific Usp22-knockout mice.

a, Schematic of the mouse Usp22 locus. Targeting vector contains IRES-lacZ and a neo cassette inserted into exon 2. b, Genotyping by PCR showed a 600-bp band for the WT allele and a 400-bp band for mutant allele, simultaneously in the homozygous floxed (fl/fl) mice. c, Western blot analysis of Usp22 in CD4+CD25 conventional T cells (Tconv) and CD4+CD25+ Treg cells isolated from Usp22+/+Foxp3YFP-cre WT and Usp22fl/flFoxp3YFP-cre KO mice. GAPDH was used as a loading control. d, Statistical analysis of CD4+Foxp3+ Treg frequencies, corresponding to Fig. 2c. e, Western blot analysis of Foxp3 protein from Treg cells isolated from spleen and lymph nodes of Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice. GAPDH was used as a loading control. f, iTreg differentiation of naive CD4+ T cells from Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice with titration of TGF-β (as indicated). g, Summary of iTreg differentiation of naive CD4+ T cells from Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice with titration of TGF-β (as indicated). h, In vitro suppressive activity of Treg cells assessed by the division of naive CD4+CD25 T cells. Naive T cells were labelled with cytosolic cell proliferation dye and activated by anti-CD3 and antigen-presenting cells (irradiated splenocytes from WT mice, depleted of CD3+ T cells), then cocultured at various ratios (as indicated above) with YFP+ Treg cells sorted from eight-week-old Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice. Numbers indicate the percentage of non-dividing cells for each ratio. i, In vitro suppressive activity of control (pMIG-Control) or Foxp3+ (pMIG-Foxp3) transduced YFP+ Treg cells sorted from Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice. Naive T cells were labelled with cytosolic cell proliferation dye and activated then cocultured at 1:4 transduced YFP+ Treg cells to naive T effectors (Teff). Numbers indicate the percentage of non-dividing cells for each ratio. j, Summary of in vitro suppression experiments, corresponding to i. Lines connect paired samples. Ratios indicate the proportion of Treg cells to naive T effectors (Teff). Data are presented as the frequency of non-dividing cells relative to the corresponding WT 0:1 Treg:Teff control. Data are mean ± s.e.m. Sample sizes (n), P values, statistical tests and number of times experiments were replicated are listed in Methods, ‘Statistics and reproducibility’. Source data for gels and blots can be found in Supplementary Fig. 1Source Data.

Extended Data Fig. 4 Usp22 acts as a deubiquitinase to control post-translational Foxp3 expression.

a, Endogenous interaction of Usp22 and Foxp3 in mouse iTreg cells from WT mice. Rabbit Usp22 antibody was used to perform the immunoprecipitation and mouse Foxp3 antibody was used to detect the bound Foxp3. Normal rabbit IgG was used as control. Whole-cell lysates (WCL) were used as sample processing controls. b, Ubiquitination assay of Foxp3. HEK293 cells were cotransfected with Flag–Foxp3 and HA–ubiquitin (HA–ub) and either Myc-empty vector, Myc–Usp22, or the catalytically inactive mutant Myc–Usp22(C185A) (C>A), and then immunoprecipitated with anti-Flag and immunoblotted for HA-ubiquitin (Foxp3-ub). Whole-cell lysates were used as sample processing controls. c, Splenocytes isolated from Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice were treated with 200 μg ml−1 cycloheximide for the indicated times. Inset numbers for each histogram indicate the MFI of Foxp3 in Treg cells (black, WT; blue, KO). d, Foxp3 MFI from splenic CD4+CD25+Foxp3+ Treg population treated with 200 μg ml−1 cycloheximide for the indicated time course (n = 3), corresponding to c. Data are mean ± s.e.m. Sample sizes (n), P values, statistical tests and number of times experiments were replicated are listed in Methods, ‘Statistics and reproducibility’. Source data for blots can be found in Supplementary Fig. 1. Source Data

Extended Data Fig. 5 Usp22 regulates Foxp3 through transcriptional mechanisms.

a, Representative flow cytometry analysis of the YFP+ Treg population (gated on CD4+ cells) from the spleen and lymph nodes of Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice. b, Statistical analysis of YFP MFI in CD4+YFP+ Treg cells from the thymus (Thy), peripheral lymph nodes (pLN) and spleen (Spl) of Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice. c, Statistical analysis of CD4+YFP+ Treg frequencies in Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice, corresponding to b. d, Volcano plot for RNA sequencing of Usp22 RNP KO Treg cells vs Rnf20 RNP KO Treg cells. The x axis shows LFC; the y axis shows −log10 of the P value as calculated by DESeq2. Genes downregulated in the Usp22 RNP KO compared with Rnf20 RNP KO are shown in red and upregulated genes are shown in blue, defined by P < 5 × 10−3 and LFC > 0.8. Foxp3 (shown in green) trended down but did not reach significance. e, qPCR analysis of FOXP3 mRNA in human Treg cells from 2 donors 8 days post-electroporation with Cas9 RNPs targeting NTC, FOXP3, USP22, RNF20 or both USP22 and RNF20; normalized to the expression of ACTB transcripts. Data are mean ± s.e.m. and are representative of at least two independent experiments. f, qPCR analysis of Foxp3 mRNA levels in mouse Treg cells 4 and 8 days post-electroporation with Cas9 RNPs targeting NTC, Foxp3, Usp22, Rnf20 or both Usp22 and Rnf20; normalized to the expression of Actb transcripts. g, Western blot analysis of ubiquitinated histone 2A (H2AK119Ub; H2A-ub) and ubiquitinated histone 2B (H2BK120Ub; H2B-ub) from iTreg cells from Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice. GAPDH was used as a loading control. Source data can be found in Supplementary Fig. 1. h, Schematic of Foxp3 locus depicting PCR products used for ChIP–qPCR in i and j. i, ChIP–qPCR analysis of H2AK119Ub (H2A-ub), where primers amplified across the TSS and the CNS1 enhancer region of the Foxp3 locus. Data are normalized to the input and are presented as mean ± s.d. j, ChIP–qPCR data analysis for H2BK120Ub (H2B-ub) for PCR across the TSS and across the CNS1 enhancer region of the Foxp3 locus. Data are normalized to the input and are presented as mean ± s.d. k, Heat map of ChIP–seq read density for Foxp3, Usp22 and Rnf20 at sites bound by Foxp3 (using previously published Foxp3 ChIP data51), ranked by highest to lowest Foxp3-binding signal. The corresponding LFC for either H2BK120Ub or H2AK119Ub upon Usp22 or Rnf20 deletion at these sites are plotted on the right, with each biological replicate shown as an individual column. l, Average ChIP–seq read density of H2BK120Ub at Treg superenhancers in control versus Usp22-deficient Treg cells. m, Co-occurrence analysis showing the natural log of the ratio of the observed number of overlapping regions over the expected values for sites that either gain or lose H2BK120Ub in Usp22-deficient Treg cells against publicly available histone modification data for H3K4me, H3K4me3 and H3K27ac as well as enhancer classes, as described in Methods. n, Analysis of reciprocal regulation of Foxp3 by deubiquitinase Usp22 and E3 ubiquitin ligase Rnf20. YFP MFI of Treg cells sorted from Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice and then electroporated with either NTC or Rnf20 RNP, corresponding with Fig. 2j, where Foxp3 MFI from the same experiment is shown. All data are presented as mean ± s.e.m., unless otherwise stated. Sample sizes (n), P values, statistical tests and number of times experiments were replicated are listed in Methods, ‘Statistics and reproducibility’. Source data for blots can be found in Supplementary Fig. 1. Source Data

Extended Data Fig. 6 Autoimmune inflammation in Treg-specific Usp22 knockout mice.

a, Body weight differences between 8-week-old, sex-matched C57BL/6 WT (BL6), Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice. b, Representative flow cytometry analysis of CD44 and CD62L expression in splenic CD4+ and CD8+ T cells from aged seven-month-old Usp22+/+Foxp3YFP-cre WT and Usp22fl/flFoxp3YFP-cre KO mice. Numbers in quadrants indicate percentage of each cell population. c, The frequency of splenic CD4+ and CD8+ effector T cells (CD44highCD62Llow) and naive T cells (CD44lowCD62Lhigh) of aged seven-month-old Usp22+/+Foxp3YFP-cre WT and Usp22fl/flFoxp3YFP-cre KO mice summarized, corresponding to b. All data are presented as mean ± s.e.m. Sample sizes (n), P values, statistical tests and number of times experiments were replicated are listed in Methods, ‘Statistics and reproducibility’. Source Data

Extended Data Fig. 7 T cell-specific ablation of Usp22 results in decreased Foxp3 and increased T cell activation.

a, Western blot analysis of Usp22 in CD4+ T cells isolated from spleens of Usp22fl/flLckcre KO and Usp22+/+Lckcre WT mice. GAPDH was used as a loading control. Source data can be found in Supplementary Fig. 1. b, Representative macroscopic images of spleens and peripheral lymph nodes (pLN) from ten-month-old Usp22fl/flLckcre KO and Usp22+/+Lckcre WT mice. c, Representative flow cytometry plots showing CD44 and CD62L expression in CD4+ and CD8+ T cells from spleens of ten-month-old Usp22fl/flLckcre KO and Usp22+/+Lckcre WT mice. d, Frequency of effector memory T cells (CD44highCD62Llow) in peripheral lymph nodes (pLN) and spleens from ten-month-old Usp22fl/flLckcre KO and Usp22+/+Lckcre WT mice. e, Representative flow cytometry plots showing the splenic CD4+Foxp3+ Treg population from ten-month-old Usp22fl/flLckcre KO and Usp22+/+Lckcre WT mice. f, Foxp3 MFI of the CD4+Foxp3+ Treg population in the spleen and pLN from ten-month-old Usp22fl/flLckcre KO and Usp22+/+Lckcre WT mice. g, IL-2 production by CD4+CD25 T cells under various stimulation conditions (as indicated) for three days was assessed by flow cytometry in Usp22fl/flLckcre KO and Usp22+/+Lckcre WT mice. Although the dominant effect of Usp22-deficiency in T cells was increased T cell activation and lymphoproliferation, we found some evidence of impaired IL-2 production in conventional T cells. h, Usp22-deficiency in T cells led to a selective defect in iTreg differentiation. In vitro differentiation of CD4+ naive T cells cultured under TH1, TH2, TH17 or sub-optimal TGF-β (1 ng ml−1) iTreg conditions from Usp22fl/flLckcre KO and Usp22+/+Lckcre WT mice was assessed by flow cytometry. i, Summary of in vitro differentiation experiments showing percent differentiation, corresponding to h. Data are mean ± s.e.m. Sample sizes (n), P values, statistical tests and number of times experiments were replicated are listed in Methods, ‘Statistics and reproducibility’Source Data.

Extended Data Fig. 8 Tumour growth is inhibited in Treg-specific Usp22 knockout mice in multiple cancer models.

a, Left, representative flow cytometric analysis of splenic IFN-γ in CD8+ T cells from EG7 tumour-bearing Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice. Right, statistical analysis of IFN-γ production by splenic CD8+ T cells from EG7 tumour-bearing Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO. b, Left, representative flow cytometric analysis of splenic granzyme B (GrzB) in CD8+ T cells from EG7 tumour-bearing Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice. Right, statistical analysis of granzyme B production by splenic CD8+ T cells from EG7 tumour-bearing Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice. c, The MFI of various Treg markers (as indicated) from splenic CD4+Foxp3+ Treg cells from Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO EG7 tumour-bearing mice, assessed by flow cytometry. d, qPCR analysis of Ifng, Gzmb and Cd8a mRNA levels in the tumour tissue of Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO EG7 tumour-bearing mice. e, Tumour volumes from Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice subcutaneously inoculated with 5 × 104 B16 melanoma cells. For e, h, k, tumour volumes were measured every 2–3 days by scaling along 3 orthogonal axes (x, y and z) and calculated as (xyz)/2. f, The MFI of various Treg markers (as indicated) from splenic CD4+Foxp3+ Treg cells in Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO B16 tumour-bearing mice, assessed by flow cytometry. g, Foxp3 MFI of Foxp3+ cells from tumour-infiltrating Treg cells in Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO B16 tumour-bearing mice. h, Tumour volumes from Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice subcutaneously inoculated with 1 × 106 LLC1 Lewis lung carcinoma cells. i, The MFI of various Treg markers (as indicated) from splenic CD4+Foxp3+ Treg cells in Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO LLC1 tumour-bearing mice, assessed by flow cytometry. j, Foxp3 MFI of Foxp3+ cells from tumour-infiltrating Treg cells in Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO LLC1 tumour-bearing mice. k, Tumour volumes from Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO mice subcutaneously inoculated with 1 × 106 MC38 colon adenocarcinoma cells. l, The MFI of various Treg markers (as indicated) from splenic CD4+Foxp3+ Treg cells in Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO MC38 tumour-bearing mice, assessed by flow cytometry. m, Foxp3 MFI of Foxp3+ cells from tumour-infiltrating Treg cells in Usp22+/+Foxp3YFP-cre WT or Usp22fl/flFoxp3YFP-cre KO MC38 tumour-bearing mice. Data are mean ± s.e.m. Sample sizes (n), P values, statistical tests and number of times experiments were replicated are listed in Methods, ‘Statistics and reproducibility’Source Data.

Supplementary information

Supplementary Figure 1

Uncropped gel source data.

Reporting Summary

Supplementary Data

Statistics and Reproducibility. The exact sample sizes (n), p-values, statistical tests and number of times the experiment was replicated.

Supplementary Table 1

Screen data. This file includes results from MAGeCK analysis for sgRNA and gene level enrichment and normalized and raw count files.

Supplementary Table 2

Tracking of Indels by DEcomposition (TIDE) analysis. This file includes primer sequences used to amply targeted DNA regions and editing efficiency data for RNP electroporations determined by using Sanger sequencing traces to quantify insertions and deletions in the DNA of a targeted cell pool.

Supplementary Table 3

Synthetic oligos used in this study - sgRNA library, primers and crRNA for RNP arrays.

Supplementary Table 4

A list of antibodies used in this study.

Supplementary Table 5

Differentially expressed genes and raw counts from RNA sequencing.

Source data

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Cortez, J.T., Montauti, E., Shifrut, E. et al. CRISPR screen in regulatory T cells reveals modulators of Foxp3. Nature (2020). https://doi.org/10.1038/s41586-020-2246-4

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