DMS/NIGMS 1: An Experimental Mathematical Framework for understanding and Controlling Regulatory Delay in Self- Nonself Determination in the Immune System

DMS/NIGMS 1:理解和控制免疫系统自我非自我决定调节延迟的实验数学框架

基本信息

  • 批准号:
    10684080
  • 负责人:
  • 金额:
    $ 20万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-09-15 至 2024-08-31
  • 项目状态:
    已结题

项目摘要

How does the immune system differentiate self from nonself? Our hypothesis, based on circuit analogues, and supported by mathematical models, is that the delay between helper (Th) and regulatory T cell (Treg) response allows the immune system to respond to the rate of increase in Ag, and that it is this signal which triggers a broader immune response. The goal of this project, then, is to provide definitive experimental evidence verifying this hypothesis. Specifically, we propose an innovative in vivo experimental framework for isolating and controlling delay in immune response and use this framework to show that by changing this delay, we can alter the self-nonself determination. This project proposes a novel experimental framework for isolating and controlling the effect of delay in immune response. The obvious challenge is that, practically, it is not possible to eliminate delay in vivo. Our approach, then, is not to eliminate Treg delay, but rather to induce delay in the Th response. Unfortunately, this too is impractical, due to the myriad of pathways involved in Th response and inability to slow down these pathways without altering other parts of the Th response. To address this, we isolate the Th and Treg populations, and prove that introducing delay in the Vaccine Schedule (VS) presented to the Th circuit, but not to the Treg circuit, can be used to negate or even reverse the PD response - implying that immune decisions can be reversed. This presents the problem of how to delay the VS for the Th circuit, but not the Treg circuit. Our solution is to decouple these circuits in vivo (E2). Specifically, we use a donor mouse (M0) with a normal immune system. We then remove the immune system from M0 (similar to a bone-marrow transplant), use flow cytometry to separate Tregs from Ths, and then transplant the Th cells to Mouse H (MH) and the Treg cells to mouse R (MR), where neither MH nor MR have a pre-existing immune response to Ag. We then use microparticles developed by co-PI Acharya to apply the VSs to MR and MH, but delaying the VS for MH. Our circuit model then predicts that the effect of VS on response will be negated or reversed if Th delay is sufficiently large - verifying our hypothesis. A critical part of E2 is selecting markers by which to sort the M0 immune system. To identify these markers, we use E1, which replicates E2, but with a single mouse. We then use flow cytometry and feature selection algorithms developed by PI Peet to identify targets for sorting.
免疫系统如何区分自我和非自我?我们的假设,基于电路类似物,并得到数学模型的支持,是辅助(Th)和调节性T细胞(Treg)反应之间的延迟允许免疫系统对Ag的增加速率做出反应,并且正是这种信号引发了更广泛的免疫反应。这个项目的目标是提供明确的实验证据来验证这一假设。具体来说,我们提出了一个创新的体内实验框架,用于隔离和控制免疫反应的延迟,并使用这个框架来表明,通过改变这种延迟,我们可以改变自我非自我决定。 该项目提出了一种新的实验框架,用于隔离和控制免疫反应延迟的影响。明显的挑战是,实际上,不可能消除体内延迟。因此,我们的方法不是消除Treg延迟,而是诱导Th反应延迟。不幸的是,这也是不切实际的,因为Th应答中涉及无数的途径,并且不能在不改变Th应答的其他部分的情况下减慢这些途径。为了解决这个问题,我们分离Th和Treg群体,并证明在呈现给Th回路而不是Treg回路的疫苗时间表(VS)中引入延迟可以用于否定甚至逆转PD应答-这意味着免疫决定可以逆转。这提出了如何延迟Th电路而不是Treg电路的VS的问题。我们的解决方案是在体内(E2)解耦这些电路。具体来说,我们使用具有正常免疫系统的供体小鼠(M0)。然后,我们从M0中移除免疫系统(类似于骨髓移植),使用流式细胞术将Th细胞与Th细胞分离,然后将Th细胞移植到小鼠H(MH),将Treg细胞移植到小鼠R(MR),其中MH和MR都没有预先存在的对Ag的免疫应答。然后,我们使用共同PI Acharya开发的微粒将VS应用于MR和MH,但延迟MH的VS。然后,我们的电路模型预测,VS对响应的影响将被否定或逆转,如果Th延迟足够大-验证我们的假设。E2的一个关键部分是选择标记,通过这些标记对M0免疫系统进行分类。为了识别这些标记,我们使用E1,它复制E2,但使用一只小鼠。然后,我们使用PI Peet开发的流式细胞术和特征选择算法来识别分选目标。

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Matthew M Peet其他文献

Matthew M Peet的其他文献

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{{ truncateString('Matthew M Peet', 18)}}的其他基金

DMS/NIGMS 1: An Experimental Mathematical Framework for understanding and Controlling Regulatory Delay in Self- Nonself Determination in the Immune System
DMS/NIGMS 1:理解和控制免疫系统自我非自我决定调节延迟的实验数学框架
  • 批准号:
    10378783
  • 财政年份:
    2021
  • 资助金额:
    $ 20万
  • 项目类别:

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