Central control of dynamic gene circuits governs T cell rest and activation

Primary human T cell isolation and expansion

CD4⁺ regulatory and effector T cells were isolated from fresh peripheral blood Leukopaks (70500, STEMCELL Technologies) from healthy human donors with institutional review board-approved informed written consent (STEMCELL Technologies). The contents of the Leukopaks were washed twice with a 1X volume of EasySep buffer (DPBS, 2% FBS and 1 mM EDTA (pH 8.0)) using centrifugation. The washed cells were resuspended at 200 × 10⁶ cells per millilitre in EasySep buffer and isolated with the EasySep Human CD4⁺CD127^lowCD25⁺ Regulatory T Cell Isolation Kit (18063, STEMCELL Technologies), according to the manufacturer’s protocol. Following isolation with the kit, T_reg cells were stained Alexa Fluor 647 anti-human IL-2Rα antibody (302618, BioLegend; diluted 1:25), phycoerythrin anti-human CD127 (557938, Beckon Dickinson; diluted 1:50) and Pacific Blue anti-human CD4 antibody (344620, BioLegend; diluted 1:50) and isolated with FACS performed on a BD FACS ARIA Fusion 1 (656700) to ensure a pure population without contaminating effector cells. After sorting pure CD4⁺CD127^lowCD25⁺ T_reg cells, the cells were seeded at 1 × 10⁶ cells per millilitre in XVIVO-15 (02-053Q, Lonza) supplemented with 5% FCS, 55 µM 2-mercaptoethanol, 4 mM N-acetyl l-cysteine and 200 U ml^−1 IL-2 (10101641, Amerisource Bergen). T_eff cells were seeded at 1 × 10⁶ cells per millilitre in RPMI-1640 supplemented with 10% FCS, 2 mM l-glutamine (25030081, Fisher Scientific), 10 mM HEPES (H0887-100ML, Sigma), 1X MEM non-essential amino acids (11140050, Fisher), 1 mM sodium pyruvate (11360070, Fisher Scientific), 100 U ml^−1 penicillin–streptomycin (P4333-100ML, Sigma) and 50 U ml^−1 IL-2 (10101641, Amerisource Bergen). Both cell subsets were then stimulated with ImmunoCult human CD3/CD28/CD2 T cell activator (10990, STEMCELL Technologies) at 25 µl ml^−1 for T_reg cells and 6.25 µl ml^−1 for T_eff cells. Cells were cultured at 37 °C with 5% CO₂. Following activation and electroporation, cells were split 1:2 every 48 h to maintain an approximate density of 1 × 10⁶ cells per millilitre and supplemented with respective doses of IL-2.

Pooled CRISPR knockout screen trans-regulator editing

Pooled screens were performed following the protocol described previously¹⁹. In brief, 24 h after stimulating and plating the T cells, the trans-regulator lentiviral library¹⁹ was added to each culture (Supplementary Table 6). The cells were counted before transduction, and virus was added at a multiplicity of infection of 0.8, using gentle mixing to disperse the viral media without disrupting cell bundling. The cells were then incubated at 37 °C for an additional 24 h, pelleted by centrifugation, and viral media were replaced with fresh media supplemented with IL-2.

Twenty-four hours after washing, the cells were pelleted by centrifugation at 150g for 10 min, resuspended at 1.5 × 10⁶ cells per 17.8 µl supplemented with P3 Primary Cell Nucleofector Buffer (component of V4SP-3960, Lonza) and combined with 7.2 µl ribonucleoprotein particle (RNP)/1.5 × 10⁶ cells in a sterile 10-ml reservoir. After mixing the cells and RNPs, 25 µl of the mixture was distributed to the wells of a 96-well Nucleocuvette Plate (component of V4SP-3960, Lonza). Cells were nucleofected using code EO-115 for T_reg cells and EH-115 for T_eff cells on the Lonza 4D-Nucleofector System with the 96-well Shuttle. Immediately after nucleofection, 90 µl pre-warmed cell-appropriate medium was added to each well, and the cells were incubated at 37 °C for 15 min. Following incubation, cells were seeded at 1 × 10⁶ cells per millilitre in media supplemented with IL-2.

IL-2Rα screen sorting and library preparation

Transduced and electroporated cells were expanded for a minimum of 6 days following editing before sorting. Cell sorting was performed 10 days following isolation for the resting screens. For the stimulated T_eff screen, cells were restimulated with ImmunoCult human CD3/CD28/CD2 T cell activator (10990, STEMCELL Technologies) 9 days following initial isolation, and sorting was performed 72 h after restimulation, at the time of peak IL-2Rα expression. Before sorting, cells were counted, washed once with EasySep buffer and stained with Alexa Fluor 647 anti-human IL-2Rα antibody (302618, BioLegend; diluted 1:25). Cells were then washed and resuspended in EasySep buffer. During sorting, cells were gated on the GFP⁺ population (lentiviral sgRNA library marker) and the top and bottom 20% of IL-2Rα-expressing cells were sorted into 15-ml conical tubes coated with FCS. Isolated cells were pelleted, counted and lysed. Genomic DNA extraction was performed using phenol-chloroform extractions, and sgRNA libraries were amplified and prepared for sequencing using custom primers. Libraries were sequenced on an Illumina HiSeq 4000 at the UCSF CAT.

Screen analysis

All pooled screens were analysed with MAGeCK⁴² (v0.5.9.5). MAGeCK count was performed on all donors using –norm-method none followed by MAGeCK test –sort-criteria pos to identify genes that resulted in a statistically significant change in IL-2Rα expression. Results are calculated as the IL-2Rα^low bin/IL-2Rα^high bin. Screen visualization is represented as the IL-2Rα^high bin/IL-2Rα^low bin by flipping the sign for the fold change. All genes with an FDR-adjusted P < 0.05 were considered significant.

Arrayed CRISPR knockout of select regulators

Guide-loaded Cas9 RNPs were assembled with custom CRISPR RNAs (crRNAs) (Dharmacon), which were resuspended in IDT duplex buffer (11-01-03-01, IDT) at 160 µM. Sequences are provided in Supplementary Table 6. Dharmacon Edit-R CRISPR–Cas9 synthetic tracrRNA (U-002005-20, Dharmacon) also resuspended in nuclease-free duplex buffer at 160 µM was combined at a 1:1 molar ratio in a 96-well plate and incubated at 37 °C for 30 min. Single-stranded donor oligonucleotides (sequence: TTAGCTCTGTTTACGTCCCAGCGGGCATGAGAGTAACAAGAGGGTGTGGTAATATTACGGTACCGAGCACTATCGATACAATATGTGTCATACGGACACG; 100 µM stock) was added to the complex at a 1:1 molar ratio and incubated at 37 °C for 5 min. Finally, Cas9 protein (MacroLab; 40 µM stock) was added at a 1:2 molar ratio and incubated at 37 °C for 15 min. The resulting RNPs were frozen at −80 °C until the day of electroporation and were thawed to room temperature before use. Forty-eight hours following T cell activation, the cells were pelleted at 100g for 10 min and resuspended in room temperature P3 Primary Cell Nucleofector Buffer (V4XP-3032, Lonza) at 1.5 × 10⁶ cells per 17.8 µl. Cells (1.5 × 10⁶) were transferred to each RNP-containing well and mixed gently. Of the combined RNP cell solution, 25 µl was transferred to a 96-well electroporation cuvette plate (VVPA-1002, Lonza) and nucleofected with pulse code DS-137. Immediately following electroporation, the cells were gently resuspended in 90 µl warmed media and incubated at 37 °C for 15 min. After recovery, the cells were cultured in 96-well round-bottom plates at 1 × 10⁶ cells per millilitre for the duration of the experiment. To prevent edge effects, the sgRNAs were randomly distributed across each plate, and the first and last columns and rows of each plate were filled with PBS to prevent evaporation. Unless otherwise specified, CRISPR–Cas9-edited cells were restimulated on day 8 following isolation for stimulation response arrayed assays with ImmunoCult human CD3/CD28/CD2 T cell activator (10990, STEMCELL Technologies).

Genotyping of arrayed knockouts

On the final day of the respective assay, genomic DNA was isolated using DNA QuickExtract (QE09050, Lucigen) according to the manufacturer’s protocol. Primers were designed to flank each sgRNA target site. Amplicons of the region were generated by adding 1.25 µl each of forwards and reverse primer at 10 µM to 5 µl of sample in QuickExtract, 12.5 µl of NEBNext Ultra II Q5 master mix (M0544L, NEB) and H₂O to a total 25 µl reaction volume. Touchdown PCR was used with the following cycling conditions: 98 °C for 3 min, 15 cycles of 94 °C for 20 s followed by 65 °C to 57.5 °C for 20 s (0.5 °C incremental decreases per cycle) and 72 °C for 1 min, and a subsequent 20 cycles at 94 °C for 20 s, 58 °C for 20 s and 72 °C for 1 min, and a final 10-min extension at 72 °C. Amplicons were diluted 1:200 and Illumina sequencing adapters were then added in a second PCR. Indexing reactions included 1 µl of the diluted PCR1 sample, 2.5 µl of each the forwards and the reverse Illumina TruSeq indexing primers at 10 µM each, 12.5 µl of NEB Q5 master mix and H₂O to a total 25 µl reaction volume. The following PCR cycling conditions were used: 98 °C for 30 s, followed by 98 °C for 10 s, 60 °C for 30 s and 72 °C for 30 s for 12 cycles, and a final extension period at 72 °C for 2 min. Samples were pooled at an equivolume ratio and SPRI purified before sequencing on an Illumina MiSeq with PE 150 reads. Analysis was performed with CRISPResso2 (v2.2.7)⁴³ CRISPRessoBatch –skip_failed –n_processes 4 –exclude_bp_from_left 5 –exclude_bp_from_right 5 –plot_window_size 10.

Flow cytometry analysis of arrayed knockouts

The BioLegend FoxP3 Fix/Perm kit (421403, BioLegend) was used for staining according to the manufacturer’s protocol. Cells were washed in EasySep buffer before extracellular staining. Cells were stained with Alexa Fluor 647 anti-human IL-2Rα (CD25) antibody diluted 1:25 (302618, BioLegend), Ghost Dye Red 780 diluted 1:1,000 (13-0865-T500, Tonbo) and BV711 anti-human CD4 diluted 1:50 (344648, BioLegend) for 20 min at 4 °C and then washed once with EasySep buffer. After fixing and permeabilizing according to the kit, intracellular staining was performed with phycoerythrin anti-mouse/human Helios antibody (137216, BioLegend), KIRAVIA Blue 520 anti-human CD152 (also known as CTLA-4) antibody (349938, BioLegend) and Pacific Blue anti-human FOXP3 antibody (320116, BioLegend) each diluted 1:50 in permeabilization buffer for 30 min at room temperature. Cells were subsequently washed in permeabilization buffer and resuspended in EasySep buffer before running on the Thermo Fisher Attune NxT flow cytometer (A29004). Analysis of flow data was performed in FlowJo (v10.8.1). Gating was performed to select for lymphocytes, singlets, live cells (Ghost Dye negative) and CD4⁺ cells in the specified order. This population was then used to calculate the median fluorescence intensity for IL-2Rα or CTLA4. Visualization was performed in R using ggplot2 (v3.4.1).

Cloning and lentivirus preparation

CRISPRi sgRNAs for Perturb-seq were selected from the Dolcetto library⁴⁴ and cloned into the LGR2.1 plasmid backbone (Addgene #108098). A lenti EF1a-Zim-3-dCas9-P2A-BSD was generated using Gibson assembly as previously described⁴⁵. Lentivirus was prepared according to the a previous protocol²⁵.

Perturb-seq

Twenty-four hours after stimulation of isolated human T_reg cells and T_eff cells from two donors, the cells were transduced with Zim3–dCas9 lentivirus at 3% v/v. The following day, Perturb-seq sgRNA library lentivirus was added at 0.75% v/v (multiplicity of infection of 0.3). Forty-eight hours after transduction with Zim3–dCas9, 10 mg ml^−1 blasticidin (A1113903, Gibco) was added to each sample to select for dCas9⁺ cells. Blasticidin was replenished every 48 h until the cells were processed for sequencing. Eight days after initial isolation and stimulation of cells, half of the T_reg and T_eff cell culture was restimulated with ImmunoCult human CD3/CD28/CD2 T cell activator (10990, STEMCELL Technologies). On the tenth day after initial isolation, the resting and 48-h restimulated samples were collected for 10X single-cell sequencing. First, cells from each donor within the same stimulation and cell-type condition were pooled at equal concentrations. Sorting was performed to isolate live GFP⁺ cells from each condition. Sorted cells were processed according to the Chromium Next GEM Single Cell 5′ HT Reagent Kits v2 (Dual Index) with Feature Barcode technology for CRISPR Screening and Cell Surface Protein guide User Guide, CG000513. In brief, sorted cells were pelleted and washed once with cell staining buffer (420201, BioLegend). Next, the samples were blocked with Human TruStain FcX Fc Blocking reagent (422302, BioLegend). Meanwhile, TotalSeq-C Human Universal Cocktail V1.0 (399905, BioLegend) was prepared using cell staining buffer (420201, BioLegend), and TotalSeq-C0251 anti-human hashtag antibodies 1–4 (394661, BioLegend) were added to aliquots of the cocktail. After blocking, cells were stained with TotalSeq-C cocktail including one hashtag per cell and stimulation condition. After staining, the cells were washed three times in cell staining buffer. The samples were then resuspended in PBS with 1% BSA (Gibco) for final counting. The resulting samples were pooled across conditions and approximately 65,000 cells per well were loaded into eight wells of a Chromium Next GEM Chip N Single Cell Kit (1000375, 10X Genomics) for GEM generation. The samples were prepared for sequencing using the Chromium Next GEM (Gel Bead-in-emulsion) Single Cell 5′ HT Kit v2 (1000374), 5′ Feature Barcode Kit (1000256) and 5′ CRISPR Kit (1000451) according to the manufacturer’s protocol. GEM generation and library preparation were performed by the Gladstone Genomics Core. The resulting libraries were sequenced using a NovaSeqX Series 10B flowcell (20085595, Illumina) at the UCSF CAT.

Perturb-seq analysis

Fastqs for each 10X well were concatenated across lanes and flow cells. Alignment of Perturb-seq data and count aggregation for the gene expression, CRISPR sgRNA and antibody-derived tag (ADT) libraries was performed with cellranger⁴⁶ count (v7.1.0) using the default settings and –expect-cells=45000 –chemistry=SC5P-R2. Gene expression fastqs were aligned to ‘refdata-gex-GRCh38- 2020-A’ human transcriptome reference acquired from 10X Genomics. SgRNA sequences were aligned to a custom reference file using the pattern TAGCTCTTAAAC(BC), whereas ADTs were aligned to the TotalSeq-C-Human-Universal-Cocktail-399905-Antibody-reference-UMI-counting.csv provided by BioLegend, also including the hashtag oligo (HTO) sequences, which were used to distinguish each cell-type and stimulation condition. Counts for each respective library were aggregated across wells with cellranger aggr using the default settings. Cells were assigned to a donor using genetic demultiplexing with Souporcell⁴⁷ (https://github.com/wheaton5/souporcell). For each well, souporcell_pipeline.py was run using the bam file and cellranger count output barcodes.tsv as input in addition to the reference fasta. Donor calls shared across wells were identified using shared_samples.py using the vcf file outputs from Souporcell.

Perturb-seq analysis was performed in R (v4.3.1) using Seurat⁴⁸ (v4.3.0.1) based on code previously published⁴⁹. Count matrices were imported into R using the Seurat Read10X function. After creating a Seurat object with CreateSeuratObject, quality filtering was performed to retain cells with more than 1,000 RNA features identified and less than 7.5% mitochondrial RNA. Cells without a singular donor assignment were also excluded from the object as well as cells with more than one HTO assignment as determined after running HTODemux. Low abundance transcripts were filtered using the threshold of ten cells per feature and TCR genes were removed from the primary RNA assay as they were found to be a major source of variance in the dataset. No sgRNA targets were removed as the number of cells in each condition exceeded the threshold set of 150 cells. After filtering, gene expression counts were normalized and transformed using the Seurat SCTransform function with regression of both S phase score and G2/M phase score, as described on Satija (https://satijalab.org/seurat/articles/cell_cycle_vignette.html). ADT counts were normalized using the centred log-ratio (CLR) normalization method of NormalizeData. After generating principal component analysis of both normalized and transformed RNA and ADT data, Harmony⁵⁰ (v0.1.1) was used to correct for donor-associated variability in the dataset. The resulting normalized and transformed counts were used for downstream analysis unless otherwise specified. Uniform manifold approximation and projections (UMAPs) were generated using the transformed and corrected RNA and ADT counts with Seurat function FindMultiModalNeighbors followed by RunUMAP using weighted.nn. Before cell-type-specific analysis, T_reg cells were manually filtered to include only cells belonging to clusters with FOXP3 and IKZF2 expression to maximize cell purity (clusters 1, 7, 8, 15, 6, 4, 19, 20, 17 and 23).

Activation scoring was performed according to Schmidt et al.^25,49. In brief, Seurat FindMarkers was used to identify differentially expressed genes between stimulated and resting non-targeting control cells within the T_eff cells and T_reg cells individually. Genes that had a log₂-transformed fold change of more than 0.25 and were detected in 10% of restimulated or resting cells were used to generate gene weights for the score calculated as sum(GE × GW/GM), where GE is the normalized/transformed expression count of a gene, GW is the weight of the gene, and GM is the mean expression of the gene in non-target control cells of the respective cell type. Wilcoxon tests were performed to determine significance compared with non-targeting control cells with Bonferroni correction for multiple hypothesis testing (Supplementary Table 7). To observe the effect of each sgRNA within independent cell and stimulation conditions, the cells were subset by HTO. RNA and ADT normalization, transformation and donor variability correction were repeated for each subset as described above for the combined dataset. UMAPs were generated using the transformed and corrected RNA and ADT counts with Seurat function FindMultiModalNeighbors followed by RunUMAP using weighted.nn. Cell cycle quantification for each subset was performed using cycle assignments generated using the Satija cell cycle vignette referenced above.

Pseudobulking of resting and stimulated T_reg and T_eff cell samples was performed using Seurat AggregateExpression grouped by HTO, target gene and donor pulling from the counts slot (sgRNAs targeting the same gene were collapsed within the same donor). Differential expression analysis was performed with the resulting pseudobulked raw counts for both RNA and ADTs. DESeq2 (v1.32.0)⁵¹ was used to identify differentially expressed genes and proteins between each sgRNA and non-targeting control sample within each cell-type and stimulation condition, using donor information as a covariate. Network plots of differentially expressed gene connections were visualized in R using influential⁵² (v2.2.7) and ggraph⁵³ (v2.1.0), including only genes with an adjusted P < 0.05. Other visualization of differentially expressed genes and surface proteins was performed using ggplot2 (v3.4.1).

Bulk RNA-seq

At their respective timepoints, resting and 48-h restimulated cells were pelleted and resuspended at 1 × 10⁶ cells per 300 µl of RNA lysis buffer (R1060-1-100, Zymo). Cells were pipette mixed and vortexed to lyse and frozen at −80 °C until RNA isolation was performed. RNA was isolated using the Zymo-Quick RNA micro prep kit (R1051) according to the manufacturer’s protocol with the following modifications: after thawing the samples, each sample was vortexed vigorously to ensure total lysis before loading into the extraction columns. The optional kit provided DNAse step was skipped, and instead RNA was eluted from the isolation column after the recommended washes and digested with Turbo-DNAse (AM2238, Fisher Scientific) at 37 °C for 20 min. Following digestion, RNA was purified using the RNA Clean & Concentrator-5 kit (R1016, Zymo) according to the manufacturer’s protocol. The purified RNA was submitted to the UC Davis DNA Technologies and Expression Analysis Core to generate 3′ Tag-seq libraries with unique molecular indices (UMIs). Barcoded sequencing libraries were prepared using the QuantSeq FWD kit (Lexogen) for multiplexed sequencing on a NextSeq 500 (Illumina).

Bulk RNA-seq analysis

RNA-seq data were processed using the pipeline previously described¹⁹. In brief, fastq adapter trimming was performed with cutadapt (v2.10). Low-quality bases were trimmed with seqtk (v0.5.0). Reads were then aligned with STAR⁵⁴ (v2.7.10a) and mapped to GRCh38. UMI counting and deduplication was performed with umi_tools⁵⁵ (v1.0.1) and gene counts were generated from the deduplicated reads using featureCounts (subread v2.0.1) using Gencode v41 basic transcriptome annotation. Quality control metrics were generated for each sample with Fastqc⁵⁶ (v0.11.9), rseqc⁵⁷ (v3.0.1) and Multiqc⁵⁸ (v1.9). Differentially expressed genes between Mediator knockouts and AAVS1-knockout samples as well as stimulated and resting AAVS1-knockout samples (Supplementary Table 8) were identified from the deduplicated count matrix using DESeq2 (v1.32.0)⁵¹ in R (v4.1.0). Comparisons were made within each cell-type and stimulation condition across three donors, using donor ID as a covariate in the model. Normalized counts were generated using a DESeqDataSet containing all samples, followed by estimateSizeFactors and counts(normalized=TRUE). AAVS1-knockout normalized sample counts were then subset and averaged across donors for visualization.

Differentially expressed genes for MED12-knockout versus AAVS1-knockout samples were defined by a cut-off of adjusted P < 0.05 (Supplementary Table 3). Comparison of the effects of MED12-knockout differentially expressed genes across stimulation-responsive categories was performed by grouping MED12-knockout versus AAVS1-knockout differentially expressed genes according to their stimulation-responsive behaviour in control cells (stimulation response = adjusted P < 0.05 and abs(log₂ fold change) > 1). The Bonferroni-adjusted P value resulting from a two-tailed t-test is displayed (Fig. 4a), comparing each stimulation-responsive group to the non-stimulation-responsive group. The boxplot centre line denotes the median; the box limits indicate the upper and lower quartiles; the whiskers denote the 1.5-times interquartile range (genes per group (downregulated, not stimulation responsive and upregulated) = resting T_eff cells: 272, 954 and 218; stimulated T_eff cells: 242, 1,432 and 467; resting T_reg cells: 269, 1,491 and 241; and stimulated T_reg cells: 245, 1,945 and 426).

A one-sided Fisher’s exact test for regulators of IL-2Rα within the differentially expressed genes downstream of MED12 was determined using screen results from the matched cell-type and stimulation conditions (Fig. 4b). Genes were subset to those targeted in the screen library and detected in CD4⁺ T cell bulk RNA-seq (genes per group: regulators, non-regulators = resting T_eff cells: 62 and 807; stimulated T_eff cells: 41 and 824; and resting T_reg cells: 82 and 787). Pathway analysis was performed using PathfindR⁵⁹ (v1.6.4) including KEGG, Reactome and GO-BP gene sets and the lowest P value is displayed. Visualization was performed after removing KEGG disease pathways. Apoptosis pathway visualization was performed using Cytoscape⁶⁰ (v3.8.2). Gene set enrichment analysis was performed with clusterProfiler⁶¹ (v4.10.1) using msigdbr (v7.5.1) on all human gene sets.

SEL120-34A treatment

SEL120-34A (S8840, Selleckchem) was reconstituted in ultrapure H₂O according to the manufacturer’s recommendations. Cells were treated every 48 h with a 1 µM dose, and treatment was started 48 h following cell isolation to align with the time at which cells are edited in CRISPR-based experiments. Restimulation of cells for flow cytometry and CUT&RUN was performed 10 days after initial isolation.

Endogenous immunoprecipitation of MED12

Immunoprecipitation base buffer (0.05 M Tris-HCl pH 7.5, 0.15 M NaCl, 0.001 M EDTA and AP MS water) was prepared the day of the experiment. Of resting and 48-hour restimulated cells, 20 × 10⁶ cells per sample and immunoprecipitation were washed twice with PBS. Samples were then lysed in 500 µl lysis buffer per 10 × 10⁶ cells (Base buffer, 1X PhosphoStop (04906837001, Roche), 1X Complete mini-EDTA protease inhibitor cocktail tablets (11836170001, Sigma-Aldrich), 0.50% NP-40 Surfact-Amps Detergent Solution (85124, Thermo Scientific) and incubated on nutator for 30 min at 4 °C. To digest chromatin, tip sonication was performed in round with incubation on ice between each step: 7 s 12%, 7 s 12%, 7 s 12% and 7 s 15% with four rounds of sonication total. Cell lysate was clarified by centrifugation at 3,500g for 10 min at 4 °C. A bicinchoninic acid (BCA) assay was performed for each sample, and protein concentrations were normalized across conditions. Of whole-cell lysate, 10% was reserved for input, and samples were split into MED12 (14360, Cell Signaling Technologies) immunoprecipitation and rabbit IgG isotype control (3900, Cell Signaling Technologies) immunoprecipitation conditions. In each case, 10 µg antibody was added to a 1.5 ml protein lo bind tube containing clarified protein and samples were incubated overnight at 4 °C, with rotation on a nutator. In the morning, Pierce protein A + G magnetic beads (88802, Thermo Fisher) were washed four times using 1 ml of lysis buffer per 1 ml of bead slurry, allowing the beads to bind to a magnet between each wash before removing the buffer. After the final wash, beads were resuspended in lysis buffer at the original bead slurry volume, and 50 µl was added to each sample. The lysate–antibody–bead mixture was then incubated at 4 °C for 2 h with rotation on a nutator. After incubation, beads were bound to a magnetic tube rack and washed one time with immunoprecipitation buffer + NP-40 (immunoprecipitation buffer + 0.05% NP-40) followed by three washes with a 900 µl immunoprecipitation buffer. The resulting purified proteins were processed for mass spectrometry or western blot.

Mass spectrometry

After immunoprecipitation, bound proteins were lysed in 8 M urea + 25 mM ammonium bicarbonate followed by reduction (5 mM dithiothreitol for 1 h at 37 °C), alkylation (10 mM iodoacetamide for 45 min at room temperature in the dark) and digestion overnight with 1 µg of trypsin (Promega). Peptide samples were applied to activated columns, and the columns were washed three times with 200 µl of 0.1% trifluoroacetic acid. Peptides were eluted with 140 µl of 50% acetonitrile and 0.1% trifluoroacetic acid and dried down by speedvac.

Samples were resuspended in 0.1% formic acid and separated by reversed-phase chromatography using an EASY-nLC instrument (Thermo Fisher Scientific) with a 15-cm PepSep column (inner diameter of 150 µm; Bruker). Samples were acquired by data-dependent acquisition. Mobile phase A consisted of 0.1% formic acid in water, and mobile phase B consisted of 80% acetonitrile and 0.1% formic acid. Peptides were separated at a flow rate of 500 nl min^−1 over the following 60 min gradient: 4–35% B in 44 min, 35–45% B in 5 min and 10 min at 88% B. Peptides were analysed by an Orbitrap Lumos MS instrument (Thermo Fisher Scientific). Data were collected in positive ion mode with MS1 resolution of 240,000, 350–1,350 m/z scan range, maximum injection time of 50 ms, radiofrequency lens of 30%. For data-dependent acquisition, MS2 fragmentation was performed on charge states 2–5 with a 20-s dynamic exclusion after a single selection and 10 ppm ± mass tolerance. All raw mass spectrometry data were searched using MaxQuant (v2.4.7) against the human proteome (UniProt canonical protein sequences, downloaded in September 2022) using default settings and with a match-between-runs enabled⁶².

Mass spectrometry analysis

Protein spectral counts as determined by MaxQuant search results were used for protein–protein interaction (PPI) confidence scoring by SAINTexpress⁶³ (v3.6.1). Rabbit IgG pulldown samples were used as control. The total list of candidate PPIs was filtered to those that met the criteria of SAINTexpress Bayesian FDR ≤ 0.05. To quantify changes in interactions between resting and stimulated T cell states, we used a label-free quantification approach in which statistical analysis was performed using MSstats (v4.8.7)⁶⁴ from the artMS (v1.18.0) R package. Visualization was performed in Cytoscape with additional connections included from the STRING database⁶⁵.

Western blots

After affinity purification of proteins, beads were resuspended in 100 µl 2X sample buffer (4× Laemmli Sample Buffer; 1610747, Bio-Rad) with 1:10 β-mercaptoethanol (63689-25ML-F, Sigma) diluted 1:1 with 500 µl lysis buffer. Samples were boiled for 5 min at 95 °C and stored at −20 °C until further processing. Western blots were performed as previously published⁶⁶. In brief, cell lysates were subjected to SDS–PAGE on 4–15% acrylamide gels and electroblotted to polyvinylidene difluoride membranes. Blocking and primary (diluted 1:1,000) and secondary antibody incubations of immunoblots were performed in Tris-buffered saline + 0.1% Tween-20 supplemented with 5% (w/v) BSA (antibodies are provided in Supplementary Table 9). Horseradish peroxidase-conjugated goat anti-rabbit and IgG (Southern Biotech) were used at a dilution of 1:30,000, and immunoreactive bands were detected using Pierce ECL Western Blotting Substrate (32106) according to the manufacturer’s instructions.

CUT&RUN

CUT&RUN was performed on resting and 48-h restimulated cells according to the manufacturer’s protocol with the EpiCypher CUTANA ChIC/CUT&RUN Kit and provided reagents. Samples for H3K27ac CUT&RUN were lightly crosslinked before isolation using 0.1% formaldehyde (252549, Sigma) for 1 min and quenched with 125 mM glycine (50046, Sigma). In brief, 5 × 10⁵ T cells per reaction were washed with PBS before nuclear isolation using the EpiCypher recommended lysis buffer consisting of 20 mM HEPES pH 7.9 (Sigma-Aldrich), 10 mM KCl (Sigma-Aldrich), 0.1% Triton X-100 (Sigma-Aldrich), 20% glycerol (Sigma-Aldrich), 1 mM MnCl₂ (Sigma-Aldrich), 1X cOmplete Mini-Tablet (11873580001, Roche) and 0.5 mM spermidine (Sigma-Aldrich). The cells were resuspended in 100 µl per reaction cold nuclear extraction buffer and incubated on ice for 10 min. Following lysis, nuclei were pelleted and resuspended in 100 µl per reaction of nuclear extraction buffer. The isolated nuclei were then frozen at −80 °C in extraction buffer until DNA isolation. After thawing the samples at 37 °C, the nuclei were bound to activated conA beads. After adsorption of nuclei to beads, permeabilization was performed with 0.01% digitonin-containing buffer. Antibodies for H3K27ac (13-0045, EpiCypher), H3K4me1 (13-0057, EpiCypher), H3K4me2 (13-0027, EpiCypher), H3K4me3 (13-0041, EpiCypher) and IgG (13-0042, EpiCypher) were added at 500 ng per reaction. Following overnight antibody binding, pAG-MNase addition and chromatin cleavage, 0.5 ng of the provided Escherichia coli DNA was added to each sample following chromatin cleavage by MNase. Before DNA isolation, crosslinked samples were digested overnight with proteinase K (AM2546, Invitrogen) as recommended. The provided spin columns and buffers were used for DNA isolation and purification. The resulting DNA was prepared for sequencing using the CUTANA CUT&RUN Library Prep Kit (14-1002) according to the manufacturer’s protocol.

CUT&RUN analysis

Pooled libraries were sequenced on a NextSeq 500 (H3K27ac) and NextSeq 2000 with 2 × 75 or 2 × 50 paired-end reads, respectively. Bcl2fastq (v2.19) with the settings –minimum-trimmed-read-length 8 was used to generate fastqs. CUT&RUN data analysis was performed according Zheng et al. with the recommended settings unless otherwise specified below⁶⁷. In brief, the fastqs were trimmed with cutadapt (v1.18). Bowtie2 (v2.2.5)⁶⁸ was used to align the trimmed fastqs to GRCh38 using settings –local –very-sensitive –no-mixed –no-discordant –phred33 –dovetail -I 10 -X 700 -p 8 -q and E. coli (EMBL accession U00096.2) with settings –local –very-sensitive –no-overlap –no-dovetail –no-mixed –no-discordant –phred33 -I 10 -X 700 -p 8 -q. Bam files were generated with SAMtools^69,70 (v1.9) view -bS -F 0 × 04 and bam-to-bed conversion performed with bedtools (v2.30.0) bamtobed -bedpe. Bedfiles were filtered to include only paired reads of less than 1,000 bp with the command awk ‘$1==$4 & & $6-$2 < 1000 {print $0}’ samplename.bed before generating bedgraph files using bedtools (v2.30.0) genomecov -bg. Peak calling was performed using the bedgraph files as input with SEACR⁷¹ (v1.3). Each target bedgraph file was compared to the respective donor and knockout condition IgG file to identify peaks above the background using the norm and stringent options for H3K27ac samples. Spike-in scaling was performed before methylation peak calling with SEACR using the IgG file as background without normalization (non option) and with the stringent option.

Before generating a peak by sample matrix for each target, ChIP–seq blacklist regions were removed from the data. The sample matrix was reduced across all peaks within the dataset, and H3K27ac peaks were segmented into regions of 5,000 bp maximum length. Regions of differential acetylation or methylation between the regulator knockouts and AAVS1-knockout samples were identified for the peaks called across any of the samples from bam files using DESeq2 (v1.32.0)⁵¹ in R (v4.1.0; Supplementary Table 10). Comparisons were made within each cell-type and stimulation condition using AAVS1s prepared in the same batch of samples. Gene annotation was performed using the gene with the nearest TSS to each region with the GenomicRanges⁷² (v1.44.0) nearest function. Final bedgraph scaling was performed based on peak coverage across all samples and conditions using DESeq2 (v1.32.0) sizefactors. SEL120-34A and H₂O treatment samples were compared as described for MED12-knockout and AAVS1-knockout samples, using the peak matrix from MED12-knockout and AAVS1-knockout samples to maximize detection of overlapping regions across datasets.

ChIP–seq

A portion of edited T_eff cells were restimulated with ImmunoCult human CD3/CD28/CD2 T cell activator (10990, STEMCELL Technologies) 10 days following isolation and collected 48 h later. Up to 1–2 × 10⁶ T_eff cells were crosslinked in PBS with 1% methanol-free formaldehyde (28908, Thermo) for 10 min at 18–22 °C followed by quenching in glycine at 125 mM final concentration. Crosslinked cell pellets were snap-frozen in liquid nitrogen and stored at –80 °C. Nuclei were isolated from thawed, crosslinked cells via sequential lysis in LB1 (50 mM HEPES-KOH pH 7.5, 140 mM NaCl, 1 mM EDTA, 10% glycerol, 0.5% IGEPAL CA-360 and 0.25% Triton X-100), LB2 (10 mM Tris-HCl pH 8, 200 mM NaCl, 1 mM EDTA and 0.5 mM EGTA) and LB3 (10 mM Tris-HCl pH 8, 100 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 1% sodium deoxycholate (NaDOC) and 0.5% N-laurylsarcosine) supplemented with 0.5 mM phenylmethylsulfonyl fluoride (PMSF; P7626, Sigma) and 0.5X protease inhibitor cocktail (PIC; P8340, Sigma). Chromatin was sheared on a Covaris E220-focused ultrasonicator using 1-ml milliTubes (520128, Covaris) with 140 W peak incident power, 5% duty factor, 200 cycles per burst, 6 °C temperature setpoint (minimum of 3 °C and maximum of 9 °C), fill level 10, and time 12–14 min to obtain a target size of 200–700 bp. Formaldehyde crosslinked, sheared mouse CD8⁺ T cell chromatin was spiked in at 2.5% of human T_eff chromatin based on fluorometric (Qubit, Q33238, Thermo) or OD260 (Nanodrop, 912A1099, Thermo) quantification. Triton X-100 was added to a final concentration of 1% before immunoprecipitation for 16 h at 4 °C with 2–8 µg of indicated antibodies (Supplementary Table 9) bound to a 1:1 mixture of protein A and protein G magnetic beads (10001D and 10003D, Thermo). Bead-bound antibody–chromatin complexes were sequentially washed three times with wash buffer 1 (20 mM Tris pH 8, 150 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 1% Triton X-100, 0.1% SDS and 0.1% NaDOC), twice with wash buffer 2 (20 mM Tris-HCl pH 8, 500 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 1% Triton X-100, 0.1% SDS and 0.1% NaDOC), twice with wash buffer 3 (20 mM Tris-HCl pH 8, 250 mM LiCl, 1 mM EDTA, 0.5% IGEPAL CA-360 and 0.5% NaDOC), twice with TET (10 mM Tris-HCl pH 8, 1 mM EDTA and 0.2% Tween-20) and once with TE0.1 (10 mM Tris-HCl pH 8, 0.1 mM EDTA, 0.5 mM PMSF and 0.5X PIC) supplemented with 0.5 mM PMSF and 0.5X PIC. Beads were resuspended in TT (10 mM Tris-HCl pH 8 and 0.05% Tween-20) before on-bead library preparation using the NEBNext Ultra II DNA Library Prep Kit (E7370L, NEB) as previously described⁷³. ChIP–seq libraries were multiplexed for paired-end (2 × 50 bp) sequencing on an Illumina NextSeq 2000 instrument.

ChIP–seq analysis

Reads were trimmed to remove adapters and low-quality sequences and aligned to the hg38 and mm10 reference genome assemblies with bwa⁷⁴ (v0.7.17-r1188) before filtering to remove duplicates and low-quality alignments including problematic genomic regions⁷⁵ using the nf-core/ChIP–seq pipeline⁷⁶ (v2.0.0; https://doi.org/10.5281/zenodo.3240506) with default parameters. Normalization to mouse spike-in chromatin was performed by scaling counts to the quotient of the ratios of human:mouse ChIP reads and human:mouse input reads as previously described⁷⁷. CXXC1 peaks for visualization were identified using bam files from all AAVS1-knockout donors for MACS2 (v2.2.6)⁷⁸ callpeak -q 0.05 with input samples used to define the background. High-confidence MED12 peaks were identified using bam files from all AAVS1-knockout donors for MACS2 callpeak -q 0.05 with MED12-knockout samples used to define the background (Supplementary Table 11). Utilization of high-confidence peaks generated from knockout controls reduced potential false-positive signals from the ChIP samples, providing a more rigorous assessment of MED12 binding^79,80. ChIP–seq blacklist regions were removed from CXXC1 and MED12 peaks before analysis.

Polymerase pausing analysis

The polymerase pausing index was calculated as previously described³³ as (TSS coverage/TSS length)/(gene body coverage/gene body length). Gencode v43 gene structures were selected for APRIS genes and filtered to include only genes expressed in T_eff bulk RNA-seq data (defined from AAVS1 T_eff RNA-seq base mean > 10). The TSS region of each gene was defined as 200 bp upstream and downstream of the TSS. The gene body was defined as the region 400 bp downstream from the TSS plus 400 bp past the final exon of the gene. Rtracklayer⁸¹ (v1.62.0) was used to import spike-in scaled RNA Pol II CTD bigwigs, and GenomicAlignments (v1.38.2) summarizeOverlaps() was used to determine the coverage within the defined gene regions.

CUT&RUN and ChIP–seq visualization

Visualization of scaled tracks was performed with rtracklayer (v1.62.0) and ggplot2 (v3.5.1) with smoothing. APRIS gene structure was used for gene annotation with gggenes (v0.5.0). CD4⁺ T_reg STAT5A ChIP–seq data were accessed from ChIP Atlas⁸², SRX212432 and GSM1056923, and generated by Hoffmann et al.³¹. Deeptools (v3.5.5)⁸³ was used to generate profile plots of ChIP–seq data using computeMatrix scale-regions -b 3000 –regionBodyLength 5000 -a 3000 –skipZeros with scaled bigwigs, and a bed file of all expressed genes (defined from AAVS1 T_eff RNA-seq base mean > 10) as input, followed by plotProfile –perGroup.

MED12 CAR activation scoring

MED12 CAR RNA-seq data from Freitas et al. was accessed from the Gene Expression Omnibus, using the downloader to retrieve the raw counts file (GSE174279_raw_counts_GRCh38.p13_NCBI.tsv.gz). First, DESeq2 (v1.32.0) was used to identify differentially expressed genes between AAVS1-knockout stimulated and resting samples. The top upregulated genes were defined using the following criteria: adjusted P < 0.01, log₂ fold change > 2 and base mean > 10. The resulting 797 genes were used to generate a gene signature of activation. Normalized counts for the MED12-knockout and AAVS1-knockout resting and stimulated samples were generated with DESeq2 vst and converted to a summarized experiment with SummarizedExperiment⁸⁴ (v1.22.0). The normalized count matrix and activation score were used as input for GSVA⁸⁵ (v1.40.1) using the gsva function with min.sz=10, max.sz=6000, kcdf = ‘Poisson’. Visualization of the resulting gene scores was performed with ggplot2(v3.4.1) and adjusted P values were generated using rstatix (v0.7.2).

Activation-induced cell death assays

Activation-induced cell death assays were performed using titrated amounts of ImmunoCult human CD3/CD28/CD2 T cell activator (10990, STEMCELL Technologies) in addition to 50 U ml^−1 of IL-2. Active caspase-3/7 staining was performed 72 h following addition of stimulus using the CellEvent Caspase-3/7 Green Flow Cytometry Assay Kit (C10427, Invitrogen) according to the manufacturer’s protocol. Gating of the apoptotic population was performed on the lymphocyte gate and defined as active caspase-3/7 positive and SYTOX nucleic acid stain negative. FAS staining was performed using phycoerythrin anti-human CD95 (Fas) antibody (305608, BioLegend; diluted 1:50).

Luminex assays

On day 12 following isolation for T_eff cells and day 8 following isolation for T_reg cells, cells were plated in 96-well plates in cytokine-free medium at a density of 2 × 10⁵ cells per well. Cells were restimulated with ImmunoCult human CD3/CD28/CD2 T cell activator (10990, STEMCELLl Technologies) and supernatant was collected after 24 h. The supernatant was stored at −80 °C until processing by EVE Technologies with the Luminex xMAP technology on the Luminex 200 system. After a serial titration to determine appropriate dilutions, samples were run in technical duplicate, and Luminex 48 plex human panel A was run for T_eff cells (diluted 1:20) and T_reg cells (diluted 1:5). The multi-species TGF 3 plex panel was also run for T_reg cells (undiluted). Technical replicates were averaged by EVE for each sgRNA and donor combination to determine protein concentration. Cytokines with more than one sample out of range were removed from the analysis to exclude low abundance proteins (Supplementary Table 12).

Suppression assays

Donor-matched T_eff cells were isolated and frozen at −80 °C without activation until 24 h before the assay. T_eff cells were thawed and cultured overnight at 2 × 10⁶ cells per millilitre with 10 U ml^−1 IL-2. On the day of the assay, T_eff cells were counted and stained with CellTrace Violet (C34557, Invitrogen) according to the manufacturer’s protocol using a 1:2,000 dilution of dye. Assay plates were assembled with 1 × 10⁵ T_eff cells per well in 96-well round bottom plates with titrated amounts of T_reg cells ranging from 1:1 to 8:1 T_eff cells:T_reg cells. One well per condition was also included of 1 × 10⁵ T_reg cells and 5 × 10⁴ T_eff cells (1:2 T_eff cells:T_reg cells), as well as resting and stimulated T_reg cells and T_eff cells individually as controls. T_reg Suppression Inspector (130-092-909, Miltenyi Biotec) iMACS particles were prepared and added to the appropriate wells according to the manufacturer’s recommendations. Assays were performed in technical triplicate for four donors, and plates were incubated for 96 h at 37 °C. At the time of readout, cells were stained with Alexa Fluor 647 anti-human IL-2Rα (302618, BioLegend), BV711 anti-human CD4 (344648, BioLegend) and Ghost Dye Red 780 (13-0865-T500, Tonbo), and analysed on the Attune NxT flow cytometer (A29004).

Analysis of flow data was performed in FlowJo (v10.8.1) with gating to select for lymphocytes, singlets, live cells (Ghost Dye negative), CD4⁺ T cells and T_eff cells (CellTrace Violet+CD25^low). A gate was then set for each donor using the non-stimulated T_eff-only control (CellTrace Violet high peak) to establish a proliferative T_eff count. A gate was also set for iMACS beads by selecting non-lymphocytes, beads using forward scatter area (FSC-A) and Ghost Dye. An absolute proliferating T_eff cell count was then established using the formula (proliferative T_eff cell count × input bead count)/(beads), which adjusts for variations in stimulation and collection abnormalities. Percentage suppression was calculated as (100 – (absolute proliferating T_eff cell count/absolute proliferating T_eff cell count of stimulated responder only condition)) × 100. The median of the technical replicate collection plates was used to calculate percent suppression and absolute proliferating T_eff cell count per donor for visualization.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.