The Transcription Factor Tox2 Drives T Follicular Helper Cell Development via Regulating Chromatin Accessibility

Xu, Wei; Zhao, Xiaohong; Wang, Xiaoshuang; Feng, Hui; Gou, Mengting; Jin, Wei; Wang, Xiaohu; Liu, Xindong; Dong, Chen

doi:10.1016/j.immuni.2019.10.006

Cited by 131 publications

(133 citation statements)

References 37 publications

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“…Next, we examined the expression of TOX, a transcription factor involved in the adaptation of CD8 T cells to chronic infection (32)(33)(34)(35)(36). In response to acute infection, SMARTA Tfh cells expressed higher levels of TOX compared to Th1 cells, consistent with an earlier study highlighting the importance of TOX for Tfh cell development ( Figure S4C) (37). In contrast, TOX expression during rLCMV Clone-13 wt infection was most highly upregulated by Th1 effectors (Figure S4C).…”

Section: Smarta T Cells Co-expressing Both Pd1 and Lag3 Were Most Abusupporting

confidence: 83%

Opposing effects of T cell receptor signal strength on CD4 T cells responding to acute versus chronic viral infection

Künzli

Reuther

Pinschewer

et al. 2020

Preprint

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A hallmark of the adaptive immune response is the ability of CD4 T cells to differentiate into a variety of pathogen appropriate and specialized effector subsets. A long-standing question in CD4 T cell biology is whether the strength of TCR signals can instruct one Th cell fate over another. The contribution of TCR signal strength to the development of Th1 and T follicular helper (Tfh) cells has been particularly difficult to resolve, with conflicting results reported in a variety of models. Although cumulative TCR signal strength can be modulated by the infection specific environment, whether or not TCR signal strength plays a dominant role in Th1 versus Tfh cell fate decisions across distinct infectious contexts is not known. Here we characterized the differentiation of CD4 TCR transgenic T cells responding to a panel of recombinant wild type or altered peptide ligand lymphocytic choriomeningitis viruses (LCMV) derived from acute and chronic parental strains. We found that while TCR signal strength positively regulates T cell expansion in both infection settings, it exerts opposite and hierarchical effects on the balance of Th1 and Tfh cells generated in response to acute versus persistent infection. The observation that weakly activated T cells, which comprise up to fifty percent of an endogenous CD4 T cell response, support the development of Th1 effectors highlights the possibility that they may resist functional inactivation during chronic infection. We anticipate that the panel of variant ligands and recombinant viruses described herein will be a valuable tool for immunologists investigating a wide range of CD4 T cell responses.

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Section: Smarta T Cells Co-expressing Both Pd1 and Lag3 Were Most Abusupporting

confidence: 83%

Opposing effects of T cell receptor signal strength on CD4 T cells responding to acute versus chronic viral infection

Künzli

Reuther

Pinschewer

et al. 2020

Preprint

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“…In addition to CXCR5, CCR7, PSGL1, and S1P receptors that are involved in cell migration, SLAM family receptors and integrins are also involved in regulating Tfh cell functions [32]. In addition, other regulators, including ICOSL [222], Ascl2 [229], Itch [230], VHL [231], IL-37 [232], HIF-1α [233], COX-1 [234], Th-POK [235], and Tox2 [236] are also found to be important for Tfh cell differentiation and functions. Tfh cells provide help to GC B cells in two aspects: one is to promote GC B cell maturation, and the other is to promote antibody production.…”

Section: Tfh Cellsmentioning

confidence: 99%

CD4 T Helper Cell Subsets and Related Human Immunological Disorders

Zhu

2020

IJMS

222

138

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The immune system plays a critical role in protecting hosts from the invasion of organisms. CD4 T cells, as a key component of the immune system, are central in orchestrating adaptive immune responses. After decades of investigation, five major CD4 T helper cell (Th) subsets have been identified: Th1, Th2, Th17, Treg (T regulatory), and Tfh (follicular T helper) cells. Th1 cells, defined by the expression of lineage cytokine interferon (IFN)-γ and the master transcription factor T-bet, participate in type 1 immune responses to intracellular pathogens such as mycobacterial species and viruses; Th2 cells, defined by the expression of lineage cytokines interleukin (IL)-4/IL-5/IL-13 and the master transcription factor GAΤA3, participate in type 2 immune responses to larger extracellular pathogens such as helminths; Th17 cells, defined by the expression of lineage cytokines IL-17/IL-22 and the master transcription factor RORγt, participate in type 3 immune responses to extracellular pathogens including some bacteria and fungi; Tfh cells, by producing IL-21 and expressing Bcl6, help B cells produce corresponding antibodies; whereas Foxp3-expressing Treg cells, unlike Th1/Th2/Th17/Tfh exerting their effector functions, regulate immune responses to maintain immune cell homeostasis and prevent immunopathology. Interestingly, innate lymphoid cells (ILCs) have been found to mimic the functions of three major effector CD4 T helper subsets (Th1, Th2, and Th17) and thus can also be divided into three major subsets: ILC1s, ILC2s, and ILC3s. In this review, we will discuss the differentiation and functions of each CD4 T helper cell subset in the context of ILCs and human diseases associated with the dysregulation of these lymphocyte subsets particularly caused by monogenic mutations.

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“…In particular, we identified a cluster of Naive-like CD8 T cells and a smaller one of Naive-like CD4 T cells, co-expressing Tcf7 and Ccr7 while lacking any activation features; a cluster of Effector Memory-like CD8 T cells, co-expressing Tcf7 and granzymes (most prominently Gzmk), with low to intermediate expression of Pdcd1; an "Early activation" state of CD8 T cells, with an intermediate profile between the Naive-like and the EM-like CD8 types; a CD8 Terminally-Exhausted (Tex) effector cluster, characterized by high expression of granzymes, multiple inhibitory receptors (Pdcd1, Ctla4, Lag3, Tigit, Havcr2/TIM-3, etc.) and Tox 25,26 ; a CD8 Precursor-Exhausted (Tpex) cluster, with co-expression of Tcf7, Pdcd1, Ctla4, Tox but not Havcr2 or granzymes 25,27,28 ; a cluster of CD4 Th1 cells, expressing IFN-gamma receptor 1 (Ifngr1) and Fasl 29 ; a CD4 follicular-helper (Tfh) population 29,30 , with a pronounced expression level of Cxcr5, Tox and Slamf6; and a cluster of regulatory T cells (Treg), identified by Foxp3 ( Figure 1D…”

Section: A Cross-study Reference Atlas Of Tumor-infiltrating T Cell Smentioning

confidence: 99%

Projecting single-cell transcriptomics data onto a reference T cell atlas to interpret immune responses

Andreatta

Corría-Osorio

Müller³

et al. 2020

Preprint

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Single-cell transcriptomics is a transformative technology to explore heterogeneous cell populations such as T cells, one of the most potent weapons against cancer and viral infections. Recent advances in this technology and the computational tools developed in their wake provide unique opportunities to build reference atlases that can be used to systematically compare new single-cell RNA-seq (scRNA-seq) datasets derived from different models or therapeutic conditions. We have developed ProjecTILs (https://github.com/carmonalab/ProjecTILs), a novel computational tool to project new scRNA-seq data into a reference map of T cells, allowing their direct comparison in a stable, annotated system of coordinates. ProjecTILs enables the classification of query cells into curated, discrete states, but also over a continuous space of intermediate states. We illustrate the projection of several datasets from recent publications over two novel cross-study murine T cell reference atlases: the first describing tumor-infiltrating T lymphocytes (TILs), the second characterizing acute and chronic viral infection. ProjecTILs accurately predicted the effects of multiple perturbations, including the ablation of genes controlling T cell differentiation, such as Tox, Ptpn2, miR-155 and Regnase-1, and identified novel gene programs that were altered in these cells (such as a Lag3-Klrc1 inhibitory module), revealing mechanisms of action behind these immunotherapeutic targets and opening new opportunities for the identification of novel targets. By comparing multiple samples over the same reference map, and across alternative embeddings, our method allows exploring the effect of cellular perturbations (e.g. as the result of therapy or genetic engineering) in terms of transcriptional states and altered genetic programs. *

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The Transcription Factor Tox2 Drives T Follicular Helper Cell Development via Regulating Chromatin Accessibility

Abstract: Highlights d Tox2 is highly expressed in Tfh cells and regulated by Bcl6 and STAT3 d Forced expression of Tox2 drives Tfh development d Tox2 directly binds to Tfh-associated genes, promoting chromatin accessibility d Combined deletion of Tox2 and Tox abrogates Tfh development

Cited by 131 publications

References 37 publications

Opposing effects of T cell receptor signal strength on CD4 T cells responding to acute versus chronic viral infection

Opposing effects of T cell receptor signal strength on CD4 T cells responding to acute versus chronic viral infection

CD4 T Helper Cell Subsets and Related Human Immunological Disorders

Projecting single-cell transcriptomics data onto a reference T cell atlas to interpret immune responses

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