Ex vivo and in vivo CRISPR/Cas9 screenings identify the roles of protein N-glycosylation in regulating T-cell activation and functions
- Chinese Institute for Cancer Research, Chinese Institutes for Medical Research, China
- National Institute of Biological Sciences, China
- Chinese Academy of Medical Sciences & Peking Union Medical College, China
- School of Basic Medical Sciences, Capital Medical University, China
Figures
Figure 1 with 2 supplements
Ex vivo CRISPR/Cas9 screenings identify genes and pathways that regulate PD-1 expression of CD8+ T-cells.
(a) Schematic view of ex vivo CRISPR/Cas9 screening in mouse primary CD8+ T-cells. (b) Volcano plot showing results of ex vivo CRISPR/Cas9 genome-wide screenings. The screenings were repeated independently once. The p-values were calculated using the α-robust rank aggregation (α-RRA) algorithm in MAGeCK. (c) Verification of candidate genes by individual single gRNAs. The relative expression levels of surface PD-1 protein and PD-1 mRNA were measured by FACS as mean fluorescent intensity (MFI) and RT-qPCR, respectively. The verification assays were biologically replicated twice. (d) GSEA of significantly enriched KEGG pathways in genome-wide screening. The enrichment score (ES) and statistical significance were calculated using the clusterProfiler (version 3.12.0) R package.
Figure 1—figure supplement 1
Multiple components in N-glycan biosynthesis pathway were identified in genome-wide screenings for PD-1 regulators in CD8+ T-cells.
(a) Flow cytometry gating strategy for FACS sorting of ex vivo genome-wide screenings. (b) Schematic views of the N-glycan biosynthesis pathway. The genes identified in current genome-wide screenings are labeled. (c) Distribution of N-glycan biosynthesis-related genes in current screenings. The blue curve represents all target genes; the red curve represents all genes involved in the N-glycan biosynthesis pathway; and the gray curve represents control gRNAs. (d) Representative PD-1 FACS plots for gRNAs targeting B4galt1 (sg1 and sg2), Mgat2 (sg1 and sg2), and Dpm3 (sg1 and sg2) genes. The verification assays were biologically replicated twice.
Figure 1—figure supplement 2
Gene knockout efficiency detected by T7E1 assay.
T7E1 assay showed gene knockout efficiencies of single sgRNAs validated in Figure 1c and sgRNAs targeting B4galt1. * indicates the cleaved products.
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Figure 1—figure supplement 2—source data 1
Original files for PAGE gel images for Figure 1—figure supplement 2.
- https://cdn.elifesciences.org/articles/108724/elife-108724-fig1-figsupp2-data1-v1.zip
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Figure 1—figure supplement 2—source data 2
PDF file containing original PAGE gel for Figure 1—figure supplement 2, indicating the genes, gRNAs, and relevant bands.
- https://cdn.elifesciences.org/articles/108724/elife-108724-fig1-figsupp2-data2-v1.zip
Figure 2
In vivo CRISPR/Cas9 screenings with a custom gRNA library identify genes that regulate functions of CD8+ T-cells in tumor microenvironment.
(a) Schematic view of in vivo CRISPR/Cas9 screening in mouse primary CD8+ T-cells. (b) Volcano plot showing results of ex vivo CRISPR/Cas9 screening. The screenings were repeated independently once. The p-values were calculated using the α-RRA algorithm in MAGeCK. (c) Volcano plot showing results of in vivo CRISPR/Cas9 screenings. The screenings were repeated independently once. The p-values were calculated using the α-RRA algorithm in MAGeCK.
Figure 3 with 2 supplements
B4GALT1 suppression in CD8+ T-cells activates TCR signaling and enhances T-cell functions.
(a) CRISPR/Cas9 knockout of B4galt1 (sgB4galt1) (sg2) in CD8+ T-cells increases expression of PD-1 before and after co-culture with B16F10-OVA cells. The MFIs of PD-1 were measured by FACS (n=6). The relative mRNA levels of PD-1 were measured by quantitative RT-qPCR (n=6). The p-values were calculated using a two-tailed Student’s t-test. (b) The effect of B4galt1 knockout on PD-1 surface expression could be rescued by overexpression of either long- or short-isoform B4galt1 (n=3). The p-values were calculated using a two-tailed Student’s t-test. (c) CRISPR/Cas9 knockout of B4galt1 in CD8+ T-cells increases expression of TNFα and IFNγ after co-culture with B16F10-OVA cells. The relative mRNA levels were measured by quantitative RT-qPCR (n=3). The secreted TNFα and IFNγ in medium were measured by ELISA (n=6). The p-values were calculated using a two-tailed Student’s t-test. (d) CRISPR/Cas9 knockout of B4galt1 in OT-I CD8+ T-cells increases in vitro specific killing activities on B16F10-OVA cells (n=3). The p-values were calculated using a two-tailed Student’s t-test. (e) Schematic view of B4GALT1 knockdown in human NY-ESO-1 TCR-T-cells. (f) Knockdown of B4GALT1 in human NY-ESO-1 TCR-T-cells by shRNA increases in vitro killing activities on A375 cells (n=5). The p-values were calculated using a two-tailed Student’s t-test. (g) Knockdown of B4GALT1 in human NY-ESO-1 TCR-T-cells increases expression of TNFα and IFNγ after co-culture with A375 cells. The secreted TNFα and IFNγ in medium were measured by ELISA (n=3). The p-values were calculated using a two-tailed Student’s t-test. (h) Heatmap demonstrating differentially expressed genes (DEGs) between B4galt1 knockout and control mouse OT-I CD8+ T-cells after co-culture. The genes in TCR signaling pathway are labeled on the left side. (i) Volcano plot showing upregulated and downregulated genes (p-value <0.01) in B4galt1 knockout mouse OT-I CD8+ T-cells after co-culture. The genes in TCR signaling pathway are labeled with dark blue and dark red. Top genes and some genes in TCR signaling pathway are annotated. The p-value was calculated using the Wald test, and p.adjust was calculated using Benjamini–Hochberg with the R package DESeq2 (version 1.22.2). (j) Bar graph showing KEGG pathways significantly changed in B4galt1 knockout mouse OT-I CD8+ T-cells after co-culture. The p-value was calculated using the clusterProfiler (version 3.12.0) R package. All of these functional effects were biologically replicated at least twice. Data are shown as the mean ± SEM. *p<0.05; **p<0.01; ***p<0.001.
Figure 3—figure supplement 1
Effect of B4GALT1 knockout on functions of hCD19-CAR-T-cells and anti-CD3/28 stimulated T-cells.
CRISPR/Cas9 knockout of B4GALT1 in hCD19-CAR-T-cells does not affect in vitro killing of Nalm6 target cells (n=3). The killing assays were biologically replicated three times. Data are shown as the mean ± SEM. NS, not significant.
Figure 3—figure supplement 2
Effect of B4GALT1 knockout on functions of anti-CD3/28 stimulated T-cells.
B4GALT1 knockout and control OT-I T-cells (1 × 105 cells/ml) were stimulated with anti-CD3 (1 mg/ml) and anti-CD28 (0.5 mg/ml) for 8 hours. The mRNA expression levels of Tnfα (n=17) and Ifnγ (n=16 for control, n=17 for sgB4galt1) were measured by quantitative RT-qPCR. The assay was biologically replicated twice. The p-value was calculated using a two-tailed Student’s t-test. Data are shown as the mean ± SEM. **p<0.01. NS, not significant.
Figure 4 with 2 supplements
Knockout of B4galt1 in CD8+ T-cells enhances T-cell-mediated tumor immunotherapy.
(a) Schematic view of B4galt1 functional test in tumor microenvironment. (b) CRISPR/Cas9 knockout of B4galt1 in OT-I T-cells enhances growth control of B16F10-OVA tumors in vivo. The p-value was calculated using two-way ANOVA. (c) Compared with control OT-I T-cells, the tumors were significantly smaller when B4galt1 knockout OT-I T-cells were transplanted (n=5 for control, n=7 for sgB4galt1). The p-value was calculated using a two-tailed Student’s t-test. (d) CRISPR/Cas9 knockout of B4galt1 increases numbers of OT-I T-cells in B16F10-OVA tumors (n=5 for control, n=7 for sgB4galt1). The p-value was calculated using a two-tailed Student’s t-test. The in vivo functional effects were biologically replicated at least twice. Data are shown as the mean ± SEM. *p<0.05; **p<0.01.
Figure 4—figure supplement 1
Flow cytometry gating strategy for analysis of tumor-infiltrated OT-I T-cells.
Figure 4—figure supplement 2
Effect of B4GALT1 knockout on functions of tumor-infiltrated OT-I T-cells.
(a) Tumor infiltration of CFSE-labeled OT-I CD8+ T-cells 24 hours after transplantation (n=9 for control, n=10 for sgB4galt1). The p-value was calculated using a two-tailed Student’s t-test. (b) Enhanced proliferation of CFSE-labeled B4GALT1 knockout (sgB4galt1) OT-I T-cells in tumors (n=6). Data are shown as the mean ± SEM. NS, not significant.
Figure 5 with 2 supplements
Systematic identification of direct substrates of B4GALT1 on T-cell surface.
(a) Schematic view of recombinant Gal-1 pulldown and LC-MS experiments. (b) Volcano plot showing identified Gal-1 binding proteins in control and B4galt1 knockout OT-I cells. Proteins among the top list were annotated and labeled with red (decreased in B4galt1 knockout) and green (increased in B4galt1 knockout). Proteins in the TCR signaling pathway are underlined. The p-values were calculated using Limma in DEqMS (V1.8.0). (c) Bar graph showing KEGG pathways significantly changed in B4galt1 knockout OT-I T-cells. The p-value was calculated using the clusterProfiler (version 3.12.0) R package. (d) Western blot verification of pulldown hits in top list. (e) N-glycome analysis with PNGase F suggests that CD8β is a direct substrate of B4GALT1. (f) Compared with wild-type control, B4GALT1 knockout OT-1 T-cells showed significantly stronger TCR-CD8 FRET signals (n=6). The FRET assays were biologically replicated three times. (g) Schematic view of the CD8β-CD3ε fusion construct. (h) Overexpression of a CD8β-CD3ε fusion protein bypassed the effect of B4GALT1 on T-cell in vitro killing activities (n=3). The killing assays were biologically replicated three times. All of the p-values were calculated by a two-tailed Student’s t-test. Data are shown as the mean ± SEM. *p<0.05; **p<0.01; ***p<0.001; NS, not significant.
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Figure 5—source data 1
Original files for western blot result displayed in Figure 5.
- https://cdn.elifesciences.org/articles/108724/elife-108724-fig5-data1-v1.zip
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Figure 5—source data 2
PDF file containing original western blots for Figure 5, indicating the relevant bands and treatments.
- https://cdn.elifesciences.org/articles/108724/elife-108724-fig5-data2-v1.zip
Figure 5—figure supplement 1
CRISPR/Cas9 knockout of B4GALT1 in OT-I T-cells alters surface-binding of lectins and galectin-1.
(a) Scheme for FACS analysis of N-glycome by lectins and galectin-1. (b–d) Cells were stained with biotin-ECL (b), biotin-sWGA (c), biotin-rGal-1 (d) and streptavidin-PE. Blue and red curves indicate control sgRNA- and sgB4galt1-infected OT-I cells, respectively. Gray dotted curves indicate cells stained with streptavidin-PE only. The MFIs of each sample were measured by FACS (n=3). The p-value was calculated using a two-tailed Student’s t-test. The FACS stainings were biologically replicated three times. Data are shown as the mean ± SEM. *p<0.05; **p<0.01.
Figure 5—figure supplement 2
Flow cytometry gating strategy for TCR-CD8 FRET assay.
Figure 6 with 1 supplement
The expression levels of B4GALT1 and tumor-infiltrated CD8+ T-cells in the tumor microenvironment are associated with prognosis of human patients.
(a) The association between B4GALT1 expression levels and overall survival for patients with different CD8A levels in TCGA-ACC, -LAML, -LUAD, and -READ cohorts. (b) The association between CD8A expression levels and overall survival for patients with different B4GALT1 levels in TCGA-ACC, -LAML, -LUAD, and -READ cohorts. The p-values for all survival curves were calculated using two-sided Log-rank test.
Figure 6—figure supplement 1
Expression levels of B4GALT1 and tumor-infiltrated CD8+ T-cells in tumor microenvironment are associated with prognosis of human patients.
(a) Kaplan-Meier survival curves of B4GALT1 expression levels for all primary tumor samples in TCGA cohort. (b) Kaplan–Meier survival curves of CD8A normalized B4GALT1 expression levels for all primary tumor samples in TCGA cohort. (c) The p-value heatmap showing associations between B4GALT1 expression levels and overall survival of patients with different tumor CD8A levels (CD8Ahigh and CD8Alow) in indicated TCGA cohorts (three columns on the left), as well as associations between CD8A expression levels and overall survival of patients with different tumor B4GALT1 levels (B4GALT1high and B4GATL1low) in indicated TCGA cohorts (three columns on the right). Hazard ratio (HR) values are listed in boxes. Samples with p-value >0.05 were all filled with white background. The p-values for all survival curves were calculated using two-sided Log-rank test.
Additional files
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Supplementary file 1
List of sequences of gRNAs and primers used in current study.
- https://cdn.elifesciences.org/articles/108724/elife-108724-supp1-v1.xlsx
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Supplementary file 2
List of plasmids used in current study.
- https://cdn.elifesciences.org/articles/108724/elife-108724-supp2-v1.xlsx
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Supplementary file 3
Information of custom library used in current study.
- https://cdn.elifesciences.org/articles/108724/elife-108724-supp3-v1.xlsx
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Supplementary file 4
Results of ex vivo CRISPR/Cas9 genome-wide screenings in Figure 1b.
- https://cdn.elifesciences.org/articles/108724/elife-108724-supp4-v1.xlsx
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Supplementary file 5
Results of in vivo CRISPR/Cas9 screenings with custom library in Figure 2c.
- https://cdn.elifesciences.org/articles/108724/elife-108724-supp5-v1.xlsx
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MDAR checklist
- https://cdn.elifesciences.org/articles/108724/elife-108724-mdarchecklist1-v1.docx
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Ex vivo and in vivo CRISPR/Cas9 screenings identify the roles of protein N-glycosylation in regulating T-cell activation and functions
eLife 14:RP108724.
https://doi.org/10.7554/eLife.108724.3
