Nov 30, 2023

ATAC-seq, primary human T cells overexpressing BATF3

  • 1Duke University
  • Andrea Daniel: This protocol was adapted form Sean McCutcheon's work in the Gersbach lab at Duke University.
  • Gersbach Lab
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Protocol CitationSean R. McCutcheon, Adam M. Swartz, Michael C. Brown, Alejandro Barrera, Christian McRoberts Amador, Keith Siklenka, Lucas Humayun, Maria A. ter Weele, James M. Isaacs, Andrea Daniel, Timothy E. Reddy, Andrew Allen, Smita K. Nair, Scott J. Antonia, Charles A. Gersbach 2023. ATAC-seq, primary human T cells overexpressing BATF3. protocols.io https://dx.doi.org/10.17504/protocols.io.4r3l22pmql1y/v1
Manuscript citation:
McCutcheon, S.R., Swartz, A.M., Brown, M.C. et al. Transcriptional and epigenetic regulators of human CD8+ T cell function identified through orthogonal CRISPR screens.Nat Genet (2023). https://doi.org/10.1038/s41588-023-01554-0
License: This is an open access  protocol  distributed under the terms of the  Creative Commons Attribution License,  which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: November 29, 2023
Last Modified: November 30, 2023
Protocol  Integer ID: 91591
Keywords: ATACseq, T cells, CAR T cells, BATF3, HER2 CAR T cells, SKBR3, chromatin remodeling, atac, batf3 this protocol, cell, overexpressing batf3, stimulated cell, human her2
Funders Acknowledgements:
NIH
Grant ID: HG012053
Abstract
This protocol describes methods for performing ATACseq on human HER2 targeted CAR T cells overexpressing BATF3 or GFP. Chromatin remodeling was assessed in acutely and chronically stimulated cells.
Transfections for high-titer lentiviral production
Plate 1.2 x 106 or 7 x 106 HEK293T cells in a 6 well plate or 10 cm dish in the afternoon with 2 mL or 12 mL of complete opti-MEM (Opti-MEM‱ I Reduced Serum Medium supplemented with 1x Glutamax, 5% FBS, 1 mM Sodium Pyruvate, and 1x MEM Non-Essential Amino Acids).
The next morning, transfect HEK293T cells with 0.5 μg pMD2.G, 1.5 μg psPAX2, and 0.5 μg transgene for 6 well plates or 3.25 μg pMD2.G, 9.75 μg psPAX2, and 4.3 μg transgene for 10 cm dishes using Lipofectamine 3000.
Exchanged media 6 hours after transfection and collect and pool lentiviral supernatant at 24 hours and 48 hours after transfection.
Primary human CD8+ T cell cultures
Isolated CD8+ T cells from individual donors were obtianed directly from vials purchased from StemCell Technologies.
Culture T cells in PRIME-XV T cell Expansion XSFM (FujiFilm) supplemented with 5% human platelet lysate (Compass Biomed), 100 U/ml penicillin and 100 μg/ml streptomycin. All media were supplemented with 100 U/ml human IL-2 (Peprotech).
Transduction of primary human CD8+ T cells
Centrifuged lentiviral supernatant at 600g for 10 min to remove cellular debris.
Concentrate lentivirus to 50–100× the initial concentration using Lenti-X Concentrator (Takara Bio).
Transduce T cells at 5–10% v/v of concentrated lentivirus at 24 h post-activation. For dual transduction experiments, T cells were serially transduced at 24 h and 48 h.
T cell stimulation with HER2+ tumor cells
HER2+ SKBR3 breast cancer cells were maintained in Dulbecco's modified Eagle medium (DMEM) GlutaMAX supplemented with 10% fetal bovine serum (FBS), 1mM sodium pyruvate, 1x MEM nonessential amino acids, 10mM HEPES, 100U/ml penicillin and 100ug/ml streptomycin.
Transfer 1 x 105 HER2 CAR T cells (with or without BATF3 overexpression) to a new 24-well plate with 2 x105 SKBR3 cells (1:2 E:T ratio) every 3 days (T cells are stimulated on days 3, 6, and 9).
T cells are removed from antigen stimulation for 2 days to recover after the final round of tumor cell stimulation before ATAC-seq on day 14 after transduction.
ATAC-seq
Sort a total of 5 × 104 transduced CD8+ T cells for Omni ATAC-seq as previously described75. See the published Omni ATAC-seq reference protocol:
https://doi.org/10.1038/protex.2017.096

Libraries were sequenced on an Illumina NextSeq 2000 with paired-end 50-bp reads. Read quality was assessed with FastQC and adapters were trimmed with Trimmomatic72.
Trimmed reads were aligned to the Hg38 reference genome using Bowtie76(v1.0.0) using parameters -v 2–best–strata -m 1.
Reads mapping to the ENCODE hg38 blacklisted regions were removed using bedtools2 (ref. 77) intersect (v2.25.0). Duplicate reads were excluded using Picard MarkDuplicates (v1.130 (ref. 78)). 
Count-per-million-normalized bigWig files were generated for visualization using deeptools bamCoverage79 (v3.0.1).
Peak calling was performed using MACS2 narrowPeak80 and filtered for Padj ≤ 0.001. Peak calls were merged across samples to make a union-peak set.
A count matrix containing the number of reads in peaks for each sample was generated using featureCounts73 (subread v1.4.6) and used for differential analysis in DESeq2 (ref. 68) (v.1.36). 
ChIPSeeker81 was used to annotate the genomic regions and retrieve the nearest gene around each peak.
HOMER (v4.11) package82 was used to find transcription factor binding motifs that contributed to changes in chromatin accessibility with BATF3 OE compared to control cells.
We defined the set of target differentially accessible peaks using DESeq2 (Padj < 0.05) and a background set of nondynamic regions (p value > 0.2 and |log2(fold change)| < 0.2) with all sets having a sufficiently large number of sequences.
Next, for each set we extracted FASTA sequences from the human reference genome (GRCh38) and ran findMotif.pl to discover motifs and compute the enrichment over background. By default, this function uses a hypergeometric distribution to score motifs to calculate enrichment p-values, controlling for differences in GC-content across target and background sets.
Protocol references
Omni-ATAC-seq: Improved ATAC-seq protocol
https://doi.org/10.1038/protex.2017.096
Corces, MA et al.
68. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014). 72. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic—a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014). 75. Corces, M. R. et al. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat. Methods 14, 959–962 (2017). 76. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009). 77. Quinlan, A. R. & Hall, I. M. BEDTools—a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010). 78. Picard. Broad Institute http://broadinstitute.github.io/picard/ (2017). 79. Ramırez, F., Dundar, F., Diehl, S., Gruning, B. A. & Manke, T. deepTools—a flexible platform for exploring deep-sequencing data. Nucleic Acids Res. 42, W187–W191 (2014). 80. Zhang, Y. et al. Model-based analysis of ChIP–seq (MACS). Genome Biol. 9, R137 (2008). 81. Yu, G., Wang, L.-G. & He, Q.-Y. ChIPseeker—an R:Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics 31, 2382–2383 (2015). 82. Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).