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Sample GSM2538933

Query DataSets for GSM2538933

Status

Public on Jun 12, 2017

Title

TbetKO.CD4.ChIP_STAT2.IFNb_3d

Sample type

SRA

Source name

CD4+ T cells

Organism

Mus musculus

Characteristics

strain: C57BL/6
genotype: Tbx21-/-
culture condition: ChIP-seq in vitro culture protocol (IFN-β)
chip antibody: anti-STAT2, ab124283, AbCam

Treatment protocol

CD4+ T cells from spleens and lymph nodes of 6- to 8-week-old mice were purified by negative selection and magnetic separation (Miltenyi Biotec) followed by sorting of naïve CD4+CD62L+CD44-CD25- population using FACSAria III or FACSAria Fusion (BD).
RNA-seq in vitro culture protocol: All cells were cultured in RPMI medium with 10% (vol/vol) FCS, 2 mM glutamine, 100 IU/mL of penicillin, 0.1 mg/mL, of streptomycin and 20 mM HEPES buffer, pH 7.2-7.5 (all from Invitrogen), 1 mM sodium pyruvate, nonessential amino acids (gibco), and 2 μM β–mercaptoethanol (Sigma-Aldrich). Naïve CD4 T cells were activated by plate-bound anti- CD3 (10 μg/mL, Clone: 145-2C11) and anti-CD28 (10μg/mL, 37.51) in media for 6hr to 3 days either under neutral conditions or with IFN-γ (100 ng/mL, R&D Systems) or IFN-β (5000 U/mL, PBL interferon source)
ChIP-seq in vitro culture protocol: All cells were cultured in RPMI medium with 10% (vol/vol) FCS, 2 mM glutamine, 100 IU/mL of penicillin, 0.1 mg/mL, of streptomycin and 20 mM HEPES buffer, pH 7.2-7.5 (all from Invitrogen), 1 mM sodium pyruvate, nonessential amino acids (gibco), and 2 μM β–mercaptoethanol (Sigma-Aldrich). Naïve CD4 T cells were activated by plate-bound anti- CD3 (10 μg/mL, Clone: 145-2C11) and anti-CD28 (10μg/mL, 37.51) in media for 3 days either under neutral conditions (anti-IL-4 (10 μg/mL, 11B11) and anti-IFN-γ antibodies (10 μg/mL, XMG1.2)) or IFN-γ condition (IFN-γ (100 ng/mL, R&D Systems) and anti-IL-4 antibody (10 μg/mL)) or IFN-β condition (IFN-β (5000 U/mL, PBL interferon source), anti-IL-4 (10 μg/mL), and anti-IFN-γ antibodies (10 μg/mL))
Toxoplasma gondii infection protocol: We generated chimeric Rag2-/- mice, reconstituted with ~5 million WT (CD45.1) and ~5 million Tbx21-/- (CD45.2) naïve CD4+ T cells sorted from Age- and Sex- matched mice (Fig. 4A), and 5 days later i.p. infected them with approximately 20 cysts of the avirulent ME49 strain of T. gondii as described previously (Jankovic et al., 2007). Splenocytes and peritoneal exudate cells (PEC) were harvested at day 7 after the infection, and WT and Tbx21-/- CD4+ CD62Llo CD44hi NK1.1- GR-1- T cells were sorted based on congenic surface markers (CD45.1/CD45.2) by flow cytometer
LCMV infection protocol: WT and Tbx21-/- mice were infected either with 2 x 10^5 plaque-forming units (PFU) of LCMV Armstrong intraperitoneally or 2 x 10^6 PFU of LCMV Clone 13 intravenously. Eight and 7 days after inoculation, splenocytes were harvested and CD4+CD62Llo CD44hi memory T helper cell population was sorted by flow cytometer.

Extracted molecule

genomic DNA

Extraction protocol

RNA Sequencing (RNA-seq) was performed and analyzed as described previously. Total RNA was prepared from approximately 1 million cells by using TRIzol or mirVana miRNA Isolation Kit (Thermo Fisher Scientific Inc.). 200 ng of total RNA was subsequently used to prepare RNA-seq library by using TruSeq SR RNA sample prep kit (FC-122-1001, Illumina) by following manufacturer’s protocol.
RNA-seq: 200 ng of total RNA was subsequently used to prepare RNA-seq library by using TruSeq SR RNA sample prep kit (FC-122-1001, Illumina) by following manufacturer’s protocol.
RNA-seq: The libraries were sequenced for 50 cycles (single read) with a HiSeq 2000 or HiSeq 2500 (Illumina)
ChIP-seq: Cells cultured as indicated were cross-linked for 10 minutes with 1% formaldehyde and harvested. Cells were lysed by sonication and immunoprecipitated with anti-T-bet (sc-21003, Santa Cruz Biotechnology), anti- STAT1 (sc-592, Santa Cruz Biotechnology), anti-STAT2 (ab124283, AbCam), anti-H3K4m1 (ab8895, AbCam) and anti-H3K27ac (ab4729, AbCam)
ChIP-seq: Libraries were prepared according to Illumina's instructions. Briefly, DNA was end-repaired and the blunt-ended, then phosphorylated ends were treated with Taq polymerase and dATP to yield a protruding 3- 'A' base for ligation of NEBNext adapters which have a single 'T' base overhang at the 3’ end. After adapter ligation, DNA was PCR amplified with NEBNext index primers for 15 cycles and library fragments of ~250 bp (insert plus adaptor and PCR primer sequences) were band isolated from an agarose gel, and quantitated by Qubit (Invitrogen).
ChIP-Seq (size fractionation). The purified libraries were multiplexed and captured on an Illumina flow cell for cluster generation. Libraries were sequenced for 50 single read cycles on HiSeq 2000 or 2500 following the manufacturer's protocols.

Library strategy

ChIP-Seq

Library source

genomic

Library selection

ChIP

Instrument model

Illumina HiSeq 2000

Description

TbetKO.CD4.ChIP_STAT2.IFNb_3d_scaled10M.bw
TbetKO.CD4.ChIP_STAT2.IFNb_3d_peaks.bed

Data processing

abundance estimation, RNA-seq: Raw sequencing data were processed with CASAVA 1.8.2 to generate FastQ files. To quantify transcript abundance we pseudo-aligned RNA-seq reads to ENSEMBL transcripts, using kallisto (v0.42.4, options: -b 50 --single -l 200 -s 30) (Bray et al., 2016)
alignment, RNA-seq: We aligned sequence reads from each RNA-seq library to the mouse genome (build mm10) using STAR (v2.4.2a, options: --outFilterIntronMotifs RemoveNoncanonicalUnannotated --outFilterType BySJout)(Dobin et al., 2013), guided by annotated transcript structures (cDNA sequences from ENSEMBL release 82 GRCm38) (Yates et al., 2016). We visualized these alignments by counting positional coverage across the genome (BEDTOOLS v2.15: genomeCoverageBed -split -bg ) (Quinlan and Hall, 2010), scaling to 10M total read depth, converting to bigWig (wigToBigWig) (Kent et al., 2010), and viewing in IGV (Thorvaldsdottir et al., 2013)
alignment, ChIP-seq: We aligned ChIP-seq reads to the mouse genome (build mm10) with Bowtie (v1.1.2, options -m 1) (Langmead et al., 2009), allowing only uniquely aligning reads. We visualized each ChIP-seq dataset by counting positional coverage across the genome (BEDTOOLS v2.24; options: genomeCoverageBed -split -bg ) (Quinlan and Hall, 2010), scaling to 10M total read depth, converting to bigWig (wigToBigWig) (Kent et al., 2010), and viewing in IGV (Thorvaldsdottir et al., 2013)
peaks, ChIP-seq: We then identified peaks using MACS (v 1.4.3; default p-value threshold of 1E-5) (Y. Zhang et al., 2008) and GEM (v2.6; options: --k_min 6 --k_max 15) (Guo et al., 2012).
Genome_build: mm10
Supplementary_files_format_and_content: bigWig and MACS peak calls for ChIP-seq. bigWig track for selected RNA-seq samples, combined transcript abundance table including all RNA-seq samples.

Submission date

Mar 16, 2017

Last update date

May 15, 2019

Contact name

Fred P. Davis

E-mail(s)

[email protected]

Organization name

NIH

Department

NIAMS