Genome-wide CRISPR Screens in T Helper Cells Reveal Pervasive Crosstalk between Activation and Differentiation

Henriksson, Johan; Chen, Xi; Gomes, Tomás; Ullah, Ubaid; Meyer, Kerstin B.; Miragaia, Ricardo J.; Dy, Graham; Pramanik, Jhuma; Yusa, Kosuke; Lahesmaa, Riitta; Teichmann, Sarah A.

doi:10.1016/j.cell.2018.11.044

Cited by 163 publications

(123 citation statements)

References 103 publications

(122 reference statements)

Supporting

Mentioning

118

Contrasting

Order By: Relevance

“…The authors declare no competing interests Ra (Ranzani et al, 2015), Bl (this study), He (Hertweck et al, 2016), Lo (Locci et al, 2016), Re (Revu et al, 2018), Mi (Micossé et al, 2019, Hn (Henriksson et al, 2019), Ka (Kanduri et al, 2015), Tu (Tuomela et al, 2016). For further detail see Supplemental Table S1.…”

Section: Declaration Of Interestmentioning

confidence: 94%

Meta-Analysis of Transcriptomic Variation in T cell Populations Reveals Novel Signatures of Gene Expression and Splicing

Radens

Blake

Jewell

et al. 2019

Preprint

View full text Add to dashboard Cite

words)Distinct T cell subtypes are typically defined by the expression of distinct gene repertoires. However, there is variability between studies regarding the markers used to define each T cell subtype. Moreover, previous analysis of gene expression in T cell subsets has largely focused on gene expression rather than alternative splicing. Here we take a meta-analysis approach, comparing eleven independent RNA-Seq studies of human Th1, Th2, Th17 and/or Treg cells to identify transcriptomic features that correlate consistently with subtype. We find that known master-regulators are consistently enriched in the appropriate subtype, however, cytokines and other genes often used as markers are more variable. Importantly, we also identify previously unknown transcriptomic markers that consistently differentiate between subsets, including a few Treg-specific splicing patterns. Together this work highlights the heterogeneity in gene expression between isolates of the same subtype, but also suggests additional markers that can be used to define functional groupings.

show abstract

Section: Declaration Of Interestmentioning

confidence: 94%

Meta-Analysis of Transcriptomic Variation in T cell Populations Reveals Novel Signatures of Gene Expression and Splicing

Radens

Blake

Jewell

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…5a), in agreement with potent Th2 cell-inducing activities of IL-4. Indeed, transcripts including Batf , Bhlhe40 and Pparg encoding transcription factors resided in major regulatory nodes of T cell activation and Th2 cell differentiation 34 were as well induced in an IL-4-dependent manner in TGF RII-deficient T cells (Fig. 5a).…”

Section: Textmentioning

confidence: 99%

TGFβ Suppresses Type 2 Immunity to Cancer

Liu

Kuo

Capistrano

et al. 2020

Preprint

View full text Add to dashboard Cite

The immune system employs two distinct defense strategies against infections: pathogen elimination typified by type 1 immunity, and pathogen containment exemplified by type 2 immunity in association with tissue repair. Akin to infectious diseases, cancer progresses with cancer cell acquisition of microorganism-like behavior propagating at the expense of the host.While immunological mechanisms of cancer cell elimination are well defined, whether immunemediated cancer cell containment can be induced is poorly understood. Here we show that ablation of transforming growth factor-β receptor II (TGFβRII) in CD4 + T cells promotes tumor tissue healing and halts cancer progression. Notably, the restorative response is dependent on the T helper 2 cytokine IL-4 fortifying vasculature organization that spares only proximal layers of cancer cells from hypoxia, nutrient starvation and death. Thus, type 2 immunity represents an effective cancer defense mechanism, and TGFβ signaling in helper T cells may be targeted for novel cancer immunotherapy.3 TextIn response to invading pathogens, vertebrate immune system employs two discrete strategies of host defense: pathogen elimination typified by type 1 immunity following innate immune recognition of prokaryotic microorganisms 1 , and pathogen containment associated with tissue repair manifested by type 2 immunity following the invasion of metazoan parasites that inflict tissue damage 2 . Similar to infectious diseases, cancer imposes insults to the host with cancer cell acquisition of microorganism-like behavior of clonal expansion. Indeed, cancer cell-targeted type 1 immunity mediated by CD8 + cytotoxic T lymphocytes (CTLs), cytotoxic innate lymphocytes and innate-like T cells represent host protective mechanisms of cancer cell elimination 3-5 . Notwithstanding, the host impact of cancer cells is much more intimate than that of microbes, and cancer pathogenicity, in particular that of solid tumors, is dependent on cancer cell coercing a supportive environment that promotes tumor encroachments leading to the impairment of tissue function [6][7][8][9] . Notably, tumor tissues resemble active wounds, and are considered as "wounds that do not heal" 10 , implying that cancer microenvironment-targeted tissue repair responses could restrain tumor progression.Dissimilar from infectious diseases, cancer arises from malignant transformation of selfcells. Consequently, immunological self-tolerance can be maladapted to repress cancer-elicited immune responses. Indeed, multiple T cell self-tolerance regulators including Foxp3 + regulatory T (Treg) cells, co-inhibitory receptors PD-1 and CTLA-4, and the regulatory cytokine transforming growth factor-β (TGFβ) suppress immune control of tumor development [11][12][13][14][15] .Depletion of tumor-infiltrating Treg cells via genetic approaches or administration of anti-PD-1 and anti-CTLA-4 result in CTL-dependent cancer cell elimination in animal models and patients 16,17 . In transgenic mouse models of cancer, blockade of TGFβ signaling in T cells...

show abstract

“…The dynamic remodeling of enhancer landscapes and differential TF motif usage is a characteristic of distinct T-helper subsets (Bonelli et al 2014). The majority of data available to date has been performed on neonates (Henriksson et al 2019), adults (Yukawa et al 2020;Wolf et al 2020) or murine cells (Rawlings et al 2010;Chisolm et al 2017;Champhekar et al 2015;Ungerbäck et al 2018), and there is a paucity of data on infants and young children. Thus, our goal was to examine the utility of omni-ATAC for characterizing chromatin dynamics and inferring gene-regulatory networks in paediatric biobanked samples.…”

Section: Introductionmentioning

confidence: 99%

Mapping the landscape of chromatin dynamics during naïve CD4+ T-cell activation

Iqbal

Serralha

Kaur

et al. 2020

Preprint

View full text Add to dashboard Cite

T-cell activation induces context-specific gene expression programs that promote energy generation and biosynthesis, progression through the cell cycle and ultimately cell differentiation. The aim of this study was to apply the omni ATAC-seq method to characterize the landscape of chromatin changes induced by T-cell activation in mature naïve CD4+ T-cells. Using a well-established ex vivo protocol of canonical T-cell receptor signaling, we generated genome-wide chromatin maps of naïve T-cells from pediatric donors in quiescent or recently activated states. We identified thousands of individual chromatin accessibility peaks that are associated with T-cell activation. The majority of these were localized to intronic and intergenic enhancer regions, marked by active histone modifications whilst quiescence was maintained by repressive histone marks. Regions of activation-associated gains in chromatin accessibility were enriched for well-known pioneer transcription factor motifs, and super-enhancer regions associated with distinct gene regulatory networks. These cis-regulatory elements together brought about distinct transcriptional signatures in activated cells including TNFa-NFkB signaling, hormone-responsive genes, inflammatory response genes and IL2-STAT5 signaling. Our data provides novel insights into the chromatin dynamics and motif usage of T-cell receptor signaling events in early life. The characterized pathways demonstrate the utility of chromatin profiling techniques applied to bio-banked samples for characterizing gene regulatory elements.

show abstract

Genome-wide CRISPR Screens in T Helper Cells Reveal Pervasive Crosstalk between Activation and Differentiation

Cited by 163 publications

References 103 publications

Meta-Analysis of Transcriptomic Variation in T cell Populations Reveals Novel Signatures of Gene Expression and Splicing

Meta-Analysis of Transcriptomic Variation in T cell Populations Reveals Novel Signatures of Gene Expression and Splicing

TGFβ Suppresses Type 2 Immunity to Cancer

Mapping the landscape of chromatin dynamics during naïve CD4+ T-cell activation

Contact Info

Product

Resources

About