Effector/memory CD4 T cells making either Th1 or Th2 cytokines commonly co-express T-bet and GATA-3

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Abstract

Naïve CD4 T (NCD4T) cells post-activation undergo programming for inducible production of cytokines leading to generation of memory cells with various functions. Based on cytokine based polarization of NCD4T cells in vitro, programming for either ‘Th1’ (interferon-gamma [IFNg]) or ‘Th2’ (interleukin [IL]-4/5/13) cytokines is thought to occur via mutually exclusive expression and functioning of T-bet or GATA-3 transcription factors (TFs). However, we show that a high proportion of mouse and human memory-phenotype CD4 T (MCD4T) cells generated in vivo which expressed either Th1 or Th2 cytokines commonly co-expressed T-bet and GATA-3. While T-bet levels did not differ between IFNg-expressing and IL-4/5/13-expressing MCD4T cells, GATA-3 levels were higher in the latter. These observations were also confirmed in MCD4T cells from FVB/NJ or aged C57BL/6 or IFNg-deficient mice. While MCD4T cells from these strains showed greater Th2 commitment than those from young C57BL/6 mice, pattern of co-expression of TF was similar. Effector T cells generated in vivo following immunization also showed TF co-expression in Th1 or Th2 cytokine producing cells. We speculated that the difference in TF expression pattern of MCD4T cells generated in vivo and those generated in cytokine polarized cultures in vitro could be due to relative absence of polarizing conditions during activation in vivo. We tested this by NCD4T cell activation in non-polarizing conditions in vitro. Anti-CD3 and anti-CD28-mediated priming of polyclonal NCD4T cells in vitro without polarizing milieu generated cells that expressed either IFNg or IL-4/5/13 but not both, yet both IFNg- and IL-4/5/13-expressing cells showed upregulation of both TFs. We also tested monoclonal T cell populations activated in non-polarizing conditions. TCR-transgenic NCD4T cells primed in vitro by cognate peptide in non-polarizing conditions which expressed either IFNg or IL-4/5/13 also showed a high proportion of cells co-expressing TFs, and their cytokine commitment varied depending on genetic background or priming conditions, without altering pattern of TF co-expression. Thus, the model of mutually antagonistic differentiation programs driven by mutually exclusively expressed T-bet or GATA-3 does not completely explain natural CD4 T cell priming outcomes.

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T cell immunity. Functional heterogeneity of human memory CD4⁺ T cell clones primed by pathogens or vaccines.

Simone Becattini, Daniela Latorre, Federico Mele … (2015)

Distinct types of CD4(+) T cells protect the host against different classes of pathogens. However, it is unclear whether a given pathogen induces a single type of polarized T cell. By combining antigenic stimulation and T cell receptor deep sequencing, we found that human pathogen- and vaccine-specific T helper 1 (T(H)1), T(H)2, and T(H)17 memory cells have different frequencies but comparable diversity and comprise not only clones polarized toward a single fate, but also clones whose progeny have acquired multiple fates. Single naïve T cells primed by a pathogen in vitro could also give rise to multiple fates. Our results unravel an unexpected degree of interclonal and intraclonal functional heterogeneity of the human T cell response and suggest that polarized responses result from preferential expansion rather than priming.

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T-bet and GATA3 orchestrate Th1 and Th2 differentiation through lineage-specific targeting of distal regulatory elements

Aditi Kanhere, Arnulf Hertweck, Urvashi Bhatia … (2012)

CD4+ helper T cells respond to antigen and cytokine cues by differentiating into one of a number of specialized effector types, allowing the immune system to tailor its response to different pathogens. Failure to mount an appropriately polarized response increases the severity of infection and can induce autoimmune or allergic disorders1. Differentiation of CD4+ T cells into Th1 and Th2 effector cells is controlled by the transcription factors T-bet and GATA3, respectively. T-bet overexpression causes differentiation into the Th1 lineage whereas loss of T-bet induces default commitment to Th2 and Th17 lineages, resulting in impaired Th1 immunity and spontaneous asthma2 3 4 5. In contrast, deletion of Gata3 prevents differentiation into the Th2 lineage and overexpression in Th1 cells switches their polarity to a Th2 phenotype6 7. Our understanding of how T-bet and GATA3 function to regulate the Th1/Th2 cell fate decision mostly stems from the murine Ifng and Il4/Il5/Il13 loci, that encode the key Th1 and Th2 cytokines, respectively. Lineage-specific expression of these genes is dependent on a series of distal regulatory elements that act together to form domains segregated from surrounding chromatin8 9 10. These regulatory elements have been characterized by sequence conservation and DNaseI hypersensitivity and a number of them exhibit enhancer or insulator activity. During Th1 differentiation, T-bet directly binds to regulatory elements at the Ifng locus, leading to changes in histone modification and Ifng transcription10 11 12 13 14 15 16. T-bet also binds with the insulator/boundary element binding protein CTCF and the cohesin complex to conserved distal elements flanking the Ifng locus, forming intra-chromosomal loops between these elements and the Ifng gene17 18. GATA3 functions in a similar manner to activate expression of the Th2 cytokine locus, binding to multiple sites proximal and distal to Il4, Il5 and Il13 (11 19 20 21 22 23 24). As for the Ifng locus, these distal elements are brought into proximity with promoter regions by intra-chromosomal looping21 25. T-bet and Gata3 also act through distal elements to repress the expression of Ifng and Il4 in the alternate lineage. In Th1 cells, T-bet binds to the Il4 promoter and a silencer element downstream 8 11 12 26. In Th2 cells, Gata3 binding at the Ifng locus results in recruitment of polycomb repressive complex-2 (ref. 27). The antagonistic nature of T-bet and GATA3 is also reflected by their direct association and T-bet-mediated repression of GATA3 binding to Il5 promoter DNA28. Rather than being solely expressed in their specific lineage, T-bet and GATA3 are co-expressed in human Th1 cells polarized in vitro 11 29 30 31 and in mouse T cells after infection in vivo with lymphocytic choriomeningitis virus32. The co-expression of master regulator transcription factors may provide a mechanism for the functional plasticity that has been observed between T-cell effector sub-types31 33 34. Knowledge of the relationship between master regulator binding sites is therefore required to understand how CD4+ differentiation is controlled. However, although Th1 and Th2 cells exhibit a range of functional differences reflected by distinct programs of gene expression1, little is known about the relationship between T-bet and GATA3 binding outside of the Ifng and Il4/5/13 loci. To address this, and to maximize the utility of the data for our understanding human immunology, we sought to identify T-bet and GATA3 binding sites in primary human Th1 and Th2 cells by chromatin immunoprecipitation (ChIP) coupled with massively parallel sequencing (ChIP-Seq). Complemented by functional assays, this approach demonstrates how interplay between T-bet and GATA3 determines appropriate lineage differentiation. Results T-bet and GATA3 binding at IFNG and IL4/5/13 loci To identify T-bet and GATA3 binding sites across the human genome, we differentiated Th1 and Th2 cells in vitro from naive precursors11, performed ChIP for T-bet and GATA3, and generated libraries from ChIP and control input samples for Illumina sequencing. GATA3 ChIP-Seq was performed in both Th1 and Th2 cells because, unlike T-bet, it is expressed in both lineages in human (Supplementary Fig. S1)11 29 30 31. We first examined T-bet and GATA3 binding at the IFNG and IL4/5/13 loci. At IFNG, we found that T-bet bound to the promoter and at both known and novel distal sites (Fig. 1a). The T-bet binding sites at −4, −16.2, −30.3, −44/−41.5, +22/+23.4, +39.8/+41.8 and +78.9 kb are at positions orthologous to the murine enhancers CNS−6, CNS−22, CNS−34, CNS−55, CNS+18–20, CNS+29 and CNS+46, respectively. Consistent with this, these sites are often coincident with DNaseI hypersensitive sites (DHS) and histone H3 monomethylated at lysine 4 (H3K4me1), a marker of enhancers poised to be activated upon differentiation35. Similarly, the T-bet binding sites at −63.5 and +119 kb correspond to previously identified CTCF-bound insulator/boundary elements17 18 (Fig. 1a). Novel T-bet binding sites at −100, −81.4, −21.5, +147.6 and +170.2 kb overlap DHS sites and the −81.4 and −22 kb sites are also associated with H3K4me1, suggesting they also represent enhancer regions. In addition to T-bet binding, we found that in Th1 cells GATA3 was also bound to each of the sites, except for those at +22, +23.4, +117 and +119 kb (Fig. 1a). GATA3 also showed a similar binding pattern in Th2 cells, although somewhat reduced, with binding at the −100, −4, +78.9 and +147.8 kb sites no longer detectable. The peaks of T-bet and GATA3 binding at these elements were coincident, indicating that the two factors bind to the same or closely spaced sites. These binding characteristics were repeated at the IL4/5/13 locus (Fig. 1b). We identified known GATA3 binding sites at the Th2 LCR, CGRE upstream of IL13 and CNS2 and, in addition, sites upstream and downstream of IL5, elsewhere within RAD50 and at CNS1 between IL13 and IL4. In Th1 cells, a number of the GATA3 binding sites were lost and T-bet was bound to the IL5 upstream element, the LCR, CNS1, the IL4 promoter, CNS2 and the HSIV site at the IL4 silencer. As we found for IFNG, T-bet and GATA3 binding sites were coincident at IL4/5/13 and were also often positioned at DHS and sites of H3K4me1. These results show that ChIP-Seq detects both known and novel T-bet and GATA3 binding sites at the signature Th1 and Th2 cytokine loci. T-bet and GATA3 binding at immune regulator genes We next expanded our analysis to the rest of the human genome and identified T-bet and GATA3 binding sites from statistically significant clusters of sequence reads36. In total, we identified 15,175 T-bet binding sites and 14,569 GATA3 binding sites in Th1 cells and 13,303 GATA3 binding sites in Th2 cells. Analysis of overrepresented sequence motifs identified a T-box binding motif enriched at sites of T-bet binding in Th1 cells and a GATA motif enriched at GATA3 binding sites in Th2 cells (Fig. 2a). To further assess data quality, we performed ChIP-Seq for T-bet in Th1 cells cultured from wild-type or T-bet−/− mice. We found that only 0.6% of T-bet binding sites identified in the wild-type cells were also called in the T-bet−/− cells (Supplementary Fig. S2), providing further confidence in the data. We next assessed the location of T-bet and GATA3 binding sites across the human genome (Supplementary Dataset 1). In total, we found that 88% of T-bet and GATA3 binding sites were distal (>2 kb) to known gene promoters (Fig. 2b). Visual inspection revealed that a number of genes exhibited extensive domains of T-bet and GATA3 binding across the locus, similar to that pattern observed at IL4/5/13 and IFNG. Across the genome, we found that 316 genes were associated with five or more distinct T-bet binding sites in Th1 cells and 295 with five or more GATA3 binding sites in Th2 cells. We asked whether any specific classes of gene were associated with these extensive patterns of T-bet and GATA3 binding. Gene Ontology revealed that genes bound by T-bet or GATA3 at proximal and multiple distal sites exhibited a significant enrichment for functions in the immune response and in transcriptional regulation (Fig. 2c). Genes bound by T-bet and GATA3 only at the promoter did not exhibit enrichment of these functional categories. Immune regulatory genes exhibiting concentrations of distal T-bet and GATA3 binding sites included a number with known functions in Th1 or Th2 cells, such as BATF, BCL6, CXCR3, ETS1, GFI1, HOPX, IL4R, IL2RA, IRF1, IKZF1 (Ikaros), MAF, NFATC2, PRDM1 (Blimp1), RBPJ, RUNX1, RUNX3, STAT1, STAT4 and STAT5 (Fig. 2d and Supplementary Fig. S3). Furthermore, similar to the IL4/5/13 locus, we identified clusters of cytokine or receptor genes with extensive T-bet and GATA3 binding, for example, IL1R1/IL1RL2/IL1RL1(IL33R)/IL18R1/IL18RAP (Fig. 2f) and CCR9/CXCR6/XCR1/CCR1/CCR3/CCR2/CCR5/CCRL2 (Supplementary Fig. S3). These results reveal that a set of key immune regulatory genes exhibit broad domains of T-bet and GATA3 binding that may be important for specific patterns of expression during T-cell differentiation. Distal elements display markers of enhancer and insulators The distal sites bound by T-bet and GATA3 at IFNG and IL4/5/13 occur at the regions of high sequence conservation and display an open chromatin confirmation, characteristic of functional elements. We therefore asked whether T-bet and GATA3 binding sites surrounding other genes shared these features. We found that distal T-bet and GATA3 binding sites were frequently located at sequences with high conservation scores (30% and 25% were classified as most conserved, respectively, compared with an expected frequency of 9%) (Fig. 3a) and coincided with DHS, indicative of an open chromatin conformation (Fig. 3b). Next, comparing sites of T-bet and GATA3 binding with the enhancer mark H3K4me1 and the boundary element factor CTCF, we found enrichment for both H3K4me1 and CTCF at distal T-bet and GATA3 binding elements (Fig. 3c). The coincidence of T-bet and GATA3 binding sites with DHS, H3K4me1 and CTCF can also be observed at individual loci (Fig. 2 and Supplementary Fig. S3). We conclude that distal T-bet and GATA3 binding sites display markers of regulatory elements across the genome. We next sought to verify that distal T-bet binding sites that overlap regions of H3K4me1 function as enhancers. We cloned the distal binding sites at IL12RB (−2.7 kb), SETBP1 (−42 kb), SETBP1 (+78.6 kb), ANTXR2 (−37.6 kb), CD226 (−46.4 kb) and IGF2R (+13.8 kb), and inserted them upstream of the basal murine Ifng promoter driving a luciferase reporter. We then transfected these constructs into activated human CD4+ T cells and measured luciferase activity (Fig. 3e). We found that each of these elements enhanced luciferase expression compared with the Ifng promoter alone and conclude that distal T-bet and GATA3 binding sites identified by ChIP-Seq function as regulatory elements. Distal sites are associated with lineage-specific expression The association of distal binding sites with markers of enhancer or insulator function suggested that T-bet and GATA3 regulate their gene expression through these sites. To test this, we activated purified naive CD4+ T cells, cultured them in either Th1 or Th2 polarizing conditions and identified changes in expression using microarrays. We found that ~40% of genes with both proximal and distal T-bet and GATA3 binding sites exhibited changes in expression during T-cell activation, compared with only 20% of genes bound at proximal sites alone (Fig. 4a). Furthermore, genes bound by T-bet or GATA3 at both proximal and distal sites were more than twice as likely to show differential expression between Th1 and Th2 lineages in both human and mouse T cells (Fig. 4a). This was not a statistical effect of the increasing number of binding sites (Supplementary Fig. S4), and these results demonstrate that T-bet and GATA3 binding at promoter and distal sites correlate with changes in gene expression during T-cell differentiation. To confirm a functional role for T-bet and GATA3 binding to distal sites across the genome, we asked whether they were associated with a requirement for T-bet or GATA3 for gene regulation. We first compared gene expression in Th1 cells cultured from wild-type and T-bet-deficient mice (Fig. 4b). In total, around 4% of genes showed a requirement for T-bet for normal expression in Th1 cells. For genes bound by T-bet at proximal sites alone, we found that the frequency of gene expression changes was also ~4% showing that T-bet was not required for their regulation. In contrast, genes bound by T-bet at proximal and distal sites were four times more likely to be dependent on T-bet for their expression (P 4 kb from TSS) were assigned to the gene with the nearest TSS that was also bound proximally by T-bet or GATA3 (<2 kb from TSS). The significance of the association between transcription factor binding and change in gene expression was calculated using the hypergeometric distribution. Significant motifs were identified using MEME. Significantly enriched functional gene categories were identified using DAVID (http://david.abcc.ncifcrf.gov/). DNaseI hypersensitivity data are from the University of Washington ENCODE group18. H3K4me1 and CTCF ChIP-Seq data are from Barski et al.51 Gene expression microarrays Naive murine CD4+ T cells (CD4+CD25-CD62LhighCD44low) were activated and polarized in vitro for 7 days. Cells were reactivated with phorbol myristate acetate (PMA) (50 ng ml−1) and ionomycin (1 μg ml−1) for 4 h and then lysed in TRIzol (Invitrogen). Gene expression analysis was performed using Affymetrix GeneChip Mouse Gene 1.0 ST arrays (T-bet experiment) or Mouse Genome 430A 2.0 arrays (Gata3 experiment), according to the manufacturer’s instructions. Arrays images were analysed using Microarray Analysis Suite 5.0 with the default settings, and normalization was performed by robust multi-array average. For comparison to T-bet and GATA3 binding results, data for multiple transcripts were averaged for each gene. Gene expression data from human Th1 and Th2 cells were described previously11. Enhancer reporter assays Distal binding elements were amplified (primers in Supplementary Methods) and cloned upstream of the murine Ifng promoter (−591 to +42 bp) in the luciferase reporter vector pGL4.13 (Promega). For assaying enhancer activity (Fig. 3e), naive human CD4+ cells were activated for 72 h with anti-CD3/CD28 and cultured for an additional 72 h in the presence of IL2 only. Cells were then transfected with reporter plasmid and control Renilla plasmid pRL-TK (Promega) using nucleofection (Nuclofector 4D, Lonza) and reactivated with anti-CD3/CD28 for 6 h before assaying for luciferase activity. For lineage-specific measurement of Tbx21 enhancer activity, naive mouse or human cells were initially activated for 3 days under polarizing conditions, with IL2 (Th0) or IL4 and anti-IFNγ (Th2) (Th1 cells were not viable after transfection) and then cultured for additional 72 h (mouse) or 7 days (human). Cells were then transfected and reactivated in the presence of 20 ng ml−1 IL-12 (eBioscience). To measure the effect of T-bet on enhancer activity, we generated an EL4 cell line that stably expressed T-bet under blasticidin resistance and a control cell line only expressing the selectable marker. Luciferase activities were determined using the Dual Luciferase Reporter Assay System (Promega). Retroviral expression of T-bet HEK293T cells were transfected with pMIG-T-bet and pCL-Eco (Imgenex) using polyethyleneimine and viral supernatants collected 48 h later. Naive mouse T cells from Ifng−/− mice were sorted and maintained as before. After activation for 24 h with anti-CD3 and anti-CD28, cells were transduced in the presence of 8 μg ml−1 polybrene. Cells were activated for an additional 48 h and then cultured for 3 days with IL2. Total RNA was isolated, treated with Turbo-DNaseI (Ambion), reverse transcribed with oligo-dT primers and endogenous Tbx21 mRNA measured by quantitative PCR (Applied Biosystems). Expression values were normalized to Hprt. T-bet and Gata3 co-expression FLAG-tagged T-bet was fused to the blasticidin resistance gene using a 2A sequence to obtain co-translational expression and incorporated into the pMY-IRES-GFP retroviral vector (gift from Adrian Hayday). HA-tagged Gata3 was fused to the puromycin resistance gene and incorporated into pMY-IRES-mPlum. Stable EL4 cell lines were transduced and then selected to express either GFP and mPlum, FLAG-T-bet and mPlum, HA-Gata3 and GFP or FLAG-T-bet and HA-Gata3. ChIP was performed as above, except with sonication at 30 W for 13 × 30 s pulses and with antibodies against HA (3F10, Roche) and FLAG (M2, Sigma). Enrichment of T-bet and Gata3 binding sites relative to input DNA and a control region in Dleu2 were determined by quantitative PCR (primers in Supplementary Methods). Supplementary Information contains Supplementary Methods, two Supplemental Data files and eight Supplementary Figures. All raw and processed ChIP-Seq data are available at GEO under accession number GSE31320. Mouse array data can be accessed at ArrayExpress under accession number E-TABM-1187. Author contributions R.G.J. and G.M.L. conceived the study and are joint senior authors. A.K., A.H., G.M.L. and R.G.J. designed the experiments. A.K., A.H., U.B., M.R.G., E.P., I.J. and R.G.J. performed experiments. R.G.J. wrote the paper with input from A.K., A.H., M.R.G. and G.M.L. Additional information How to cite this article: Kanhere, A. et al. T-bet and GATA3 orchestrate Th1 and Th2 differentiation through lineage-specific targeting of distal regulatory elements. Nat. Commun. 3:1268 doi: 10.1038/ncomms2260 (2012). Supplementary Material Supplementary Figures and Methods Supplementary Figures S1-S8 and Supplementary Methods Supplementary Data 1 T-bet and GATA3 binding sites in the human genome. Supplementary Data 2 Coordinates of distal sites with different T-bet and GATA3 binding combinations.

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The polycomb protein Ezh2 regulates differentiation and plasticity of CD4(+) T helper type 1 and type 2 cells.

K Shinoda, Haruhiko Koseki, Atsushi Onodera … (2013)

After antigen encounter by CD4(+) T cells, polarizing cytokines induce the expression of master regulators that control differentiation. Inactivation of the histone methyltransferase Ezh2 was found to specifically enhance T helper 1 (Th1) and Th2 cell differentiation and plasticity. Ezh2 directly bound and facilitated correct expression of Tbx21 and Gata3 in differentiating Th1 and Th2 cells, accompanied by substantial trimethylation at lysine 27 of histone 3 (H3K27me3). In addition, Ezh2 deficiency resulted in spontaneous generation of discrete IFN-γ and Th2 cytokine-producing populations in nonpolarizing cultures, and under these conditions IFN-γ expression was largely dependent on enhanced expression of the transcription factor Eomesodermin. In vivo, loss of Ezh2 caused increased pathology in a model of allergic asthma and resulted in progressive accumulation of memory phenotype Th2 cells. This study establishes a functional link between Ezh2 and transcriptional regulation of lineage-specifying genes in terminally differentiated CD4(+) T cells. Copyright © 2013 Elsevier Inc. All rights reserved.

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Author and article information

Contributors

Arundhoti Das: Role: Data curationRole: MethodologyRole: Validation

Vidya Ranganathan: Role: Formal analysisRole: MethodologyRole: SupervisionRole: Writing – original draft

Danish Umar: Role: Methodology

Shipra Thukral: Role: Methodology

Anna George: Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing – review & editing

Satyajit Rath: Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing – review & editing

Vineeta Bal:

ORCID: http://orcid.org/0000-0002-8995-2045

Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing – review & editing

Hiroshi Shiku: Role: Editor

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Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS ONE

Journal ID (publisher-id): plos

Journal ID (pmc): plosone

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, CA USA )

ISSN (Electronic): 1932-6203

Publication date (Electronic): 31 October 2017

Publication date Collection: 2017

Volume: 12

Issue: 10

Electronic Location Identifier: e0185932

Affiliations

[001]National Institute of Immunology, New Delhi, India

Mie University Graduate School of Medicine, JAPAN

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Competing Interests: The authors have declared that no competing interests exist.

[¤]

Current address: BD Diagnostics, BD, India.

‡ These authors also contributed equally as senior authors on this work.

* E-mail: vineeta@ 123456nii.res.in

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Vineeta Bal http://orcid.org/0000-0002-8995-2045

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Publisher ID: PONE-D-17-06800

DOI: 10.1371/journal.pone.0185932

PMC ID: 5663332

PubMed ID: 29088218

SO-VID: 824040c7-aedc-4302-a469-597e858b3645

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This is an open access article 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.

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Date received : 20 February 2017

Date accepted : 21 September 2017

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Figures: 9, Tables: 0, Pages: 25

Funding

Funded by: Department of Biotechnology, Government of India

Award ID: BT/PR5138/BRB/10/1064/2012

Award Recipient : Anna George

Funded by: Department of Biotechnology, Government of India

Award ID: BT/PR14592/BRB/10/858/2010

Award Recipient : Satyajit Rath

Funded by: Department of Biotechnology, Government of India

Award ID: BT/PR7012/BRB/1159/2012

Award Recipient :

ORCID: http://orcid.org/0000-0002-8995-2045

Vineeta Bal

Funded by: Department of Science and Technology, Government of India

Award ID: SR/SO/BB-0035/2013

Award Recipient : Anna George

Funded by: Department of Science and Technology, Government of India

Award ID: SB/SO/HS/210/2013

Award Recipient : Satyajit Rath

Funded by: Department of Science and Technology, Government of India

Award ID: SR/SO/HS-0005/2011

Award Recipient :

ORCID: http://orcid.org/0000-0002-8995-2045

Vineeta Bal

Funded by: Department of Science and Technology, Government of India

Award ID: EMR/2015/001074

Award Recipient :

ORCID: http://orcid.org/0000-0002-8995-2045

Vineeta Bal

Funded by: Council for Scientific and Industrial Research, Government of India

Award Recipient : Arundhoti Das

Funded by: Council for Scientific and Industrial Research, Government of India

Award Recipient : Danish Umar

Funded by: Department of Biotechnology, Government of India

This work was supported in part by grants from the Department of Biotechnology, Government of India (to A.G. # BT/PR5138/BRB/10/1064/2012, to S.R. # BT/PR14592/BRB/10/858/2010, to V.B. # BT/PR7012/BRB/1159/2012); the Science and Engineering Research Board, Department of Science and Technology, Government of India (to A.G. # SR/SO/BB-0035/2013, S.R. # SB/SO/HS/210/2013, to V.B. #SR/SO/HS-0005/2011, EMR/2015/001074); and a fellowship from the Council for Scientific and Industrial Research, Government of India to A.D. and D.U. The National Institute of Immunology is supported by the Department of Biotechnology, Government of India. There were no sponsors for this work. Funding agencies had no role in either conceptualization or implementation of the work.

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Effector/memory CD4 T cells making either Th1 or Th2 cytokines commonly co-express T-bet and GATA-3

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T cell immunity. Functional heterogeneity of human memory CD4⁺ T cell clones primed by pathogens or vaccines.

T-bet and GATA3 orchestrate Th1 and Th2 differentiation through lineage-specific targeting of distal regulatory elements

The polycomb protein Ezh2 regulates differentiation and plasticity of CD4(+) T helper type 1 and type 2 cells.

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