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An experimentally-refined, dynamic gene regulatory network model of T-cell memory

An experimentally-refined, dynamic gene regulatory network model of T-cell memory
经过实验改进的 T 细胞记忆动态基因调控网络模型
批准号:
10576265
负责人:
Artem Barski
金额:
$68.76万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-03-08 至 2026-02-28

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英文摘要
An experimentally-refined, dynamic gene regulatory network model of T-cell memory Summary T cell memory induced by prior exposure to a pathogen or vaccination provides enhanced protection against a subsequent infection with the same pathogen. Enhanced protection is partially driven by clonal expansion, which leads to an increased number of T cells capable of recognizing the antigen. Additionally, memory T cells possess a “rapid recall ability” that allows them to fight pathogens by producing cytokines and other effector molecules within minutes of re-exposure (as opposed to days, upon initial exposure). We recently showed that rapid recall correlates with the epigenetic poising of enhancers and promoters of the “rapid-recall genes” in memory T cells. Importantly, the sites of epigenetic change significantly overlap with the risk loci for autoimmune and atopic disease, suggesting that this mechanism is important for human health. However, it is still unclear if and how the epigenetic poising causes enhanced expression of rapid recall genes. Furthermore, memory T cells persist for a lifetime; yet the mechanisms that maintain the memory epigenome – for decades– are not known. Our preliminary data suggest that rapid recall is coordinated by several families of transcription factors (TFs) and thousands of putative DNA regulatory elements. This complexity requires a systems-level, engineering approach. Thus, this proposal is a collaboration between the groups of Artem Barski, a T cell biologist, and Emily Miraldi, a mathematical modeler, to create experimentally validated, genome-scale models of memory immune responses across heterogeneous T cell populations. Aim 1. Using single-cell genomics, we will characterize the gene expression and chromatin dynamics of T cell activation in naïve and memory cells and build mathematical models that integrate these data (along with relevant existing genomics resources) into a dynamic gene regulatory network (GRN). Our GRN model will predict the molecular drivers (TFs) and regulatory elements that orchestrate rapid recall. Aim 2. Although T-cell activation in naïve and memory cells similarly promotes nuclear translocation of inducible TFs, our data lead us to hypothesize that chromatin remodeling upon initial pathogen exposure alters the occupancy of inducible TFs in memory T cells and that this is the basis of rapid recall. We will combine dynamic TF perturbation and occupancy experiments to establish the molecular interactions driving rapid recall. Aim 3. We will identify the mechanisms by which memory T cells maintain the epigenome conducive for rapid recall – over the human lifespan. We hypothesize that constitutive TFs maintain the epigenome poised for rapid recall. We propose dynamic TF perturbation experiments to uncover the identities of these regulators. This study will help uncover basic mechanisms of T cell memory and identify potential targets for manipulating immunologic memory responses. Because rapid recall is the basis for vaccination and central to allergy, asthma, and cancer immunity, this study will have a broad impact on human health.
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  • 批准号:
    10338010
  • 项目类别:
  • 资助金额:
    $5.2万
  • 财政年份:
    2021
  • 负责人:
    Artem Barski
  • 依托单位:
An experimentally-refined, dynamic gene regulatory network model of T-cell memory
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