Immunology Imaging and Modelling Network

免疫学成像和建模网络

基本信息

  • 批准号:
    BB/F003811/1
  • 负责人:
  • 金额:
    $ 10.77万
  • 依托单位:
  • 依托单位国家:
    英国
  • 项目类别:
    Research Grant
  • 财政年份:
    2008
  • 资助国家:
    英国
  • 起止时间:
    2008 至 无数据
  • 项目状态:
    已结题

项目摘要

The immune system is one of the most fascinating and complex multiscale systems imaginable. The adaptive immune system of a vertebrate is a vast army of cells and molecules that cooperate to seek out, mark, bind to and destroy pathogens. The system continuously processes information from a large variety of self and foreign antigens and marshalls the appropriate immune response. Stochastic modelling is ideally suited to immunology at many scales. For example: [1] Cells live in a Brownian world. Their motion is partly directed and partly random. The appropriate mathematical tools describing such motion are stochastic differential equations. [2] The battle between invading pathogens and the innate and adaptive immune systems is best described statistically. [3] The means by which the body selects and educates its T~cells and B~cells is probabilistic. For example: T~cells mature in the thymus, where they undergo testing and possible elimination based on their specificity for self or non-self antigen. [4] The immunoglobulin gene rearrangement that occurs during the development of B~cells, that generates diversity of the mature antibody repertoire, involves random recombination of gene segments. More than 5 million people are killed every year by infectious diseases. A better understanding of how the immune system responds to infection and of the factors that determine whether an infection results in protective immunity or disease could lead to medical advances resulting in a great reduction in human suffering. Immunology has traditionally been a qualitative science describing the cellular and molecular components of the immune system and their functions. Theoretical immunology is maturing into a discipline where modelling helps to interpret experimental data, to resolve controversies, and -- most importantly -- to suggest novel experiments allowing for more conclusive and more quantitative interpretations. The T~cell repertoire is comprised of at least 25 million receptors each with different antigen specificity. During the immune response, only a small fraction of the T~cells will recognize foreign antigen, activate and undergo proliferation. In the lymph nodes, these antigen-specific T~cells face the daunting task of first finding a dendritic cell presenting their cognate antigen. This seems specially difficult because the lymph nodes are densely packed with millions of competing T~cells having irrelevant specificity, dendritic cells presenting non-cognate peptide-MHC complexes, and many solid obstacles, such as the reticular network. Recently, it has become possible to visualize the in vivo motility of different immune cells. The resulting vivid movies and measurements of the events occurring in the lymph nodes suggest that T~cells achieve their aim by moving around at high velocities, greater than one cell diameter per minute. They walk in a consistent direction for several minutes but crawl along random trajectories in the long term. This ``stop-and-go'' fashion of walking has been suggested to be part of a program of intrinsic rhythmicity. However, these studies reveal neither the underlying mechanism of the observed behaviours nor the consequences of the densely packed lymph node environment on T~cell motility. The visualisation of dynamic processes in lymphoid tissues by confocal laser scanning microscopy and multi-photon excitation laser canning microscopy opens up possibilities for combined modelling and experimental efforts.
免疫系统是可以想象到的最迷人和最复杂的多尺度系统之一。脊椎动物的适应性免疫系统是一个庞大的细胞和分子军队,它们合作寻找,标记,结合和摧毁病原体。该系统不断处理来自各种自身和外来抗原的信息,并组织适当的免疫反应。随机建模非常适合许多尺度的免疫学。例如:[1]细胞生活在布朗世界中。它们的运动部分是定向的,部分是随机的。描述这种运动的适当数学工具是随机微分方程。[2]入侵的病原体与先天性和适应性免疫系统之间的战斗最好用统计学来描述。[3]机体选择和培养T~细胞和B~细胞的方法是概率性的。举例来说:T细胞在胸腺中成熟,在那里它们经历测试和基于它们对自身或非自身抗原的特异性的可能消除。[4]在B~细胞发育过程中发生的免疫球蛋白基因重排,产生成熟抗体库的多样性,涉及基因片段的随机重组。每年有500多万人死于传染病。更好地了解免疫系统如何对感染作出反应,以及确定感染是否导致保护性免疫或疾病的因素,可能会导致医学进步,从而大大减少人类的痛苦。免疫学传统上是描述免疫系统的细胞和分子组成及其功能的定性科学。理论免疫学正在成熟成为一门学科,在这门学科中,建模有助于解释实验数据,解决争议,最重要的是,提出新的实验,允许更有说服力和更定量的解释。T细胞库由至少2500万个受体组成,每个受体具有不同的抗原特异性。在免疫应答过程中,只有一小部分T细胞会识别外来抗原,激活并进行增殖。在淋巴结中,这些抗原特异性T细胞面临着首先找到呈递其同源抗原的树突状细胞的艰巨任务。这看起来特别困难,因为淋巴结密集地挤满了数百万个具有不相关特异性的竞争性T细胞、呈递非同源肽-MHC复合物的树突细胞和许多固体障碍物,如网状网络。最近,已经可以可视化不同免疫细胞的体内运动性。由此产生的生动电影和对淋巴结中发生的事件的测量表明,T细胞通过以每分钟大于一个细胞直径的高速移动来实现其目标。它们在几分钟内沿着一个一致的方向行走,但长期以来沿着沿着的轨迹爬行。这种“走走停停”的行走方式被认为是内在节奏性的一部分。然而,这些研究既没有揭示所观察到的行为的潜在机制,也没有揭示密集淋巴结环境对T细胞运动的后果。通过共聚焦激光扫描显微镜和多光子激发激光扫描显微镜在淋巴组织中的动态过程的可视化开辟了联合建模和实验努力的可能性。

项目成果

期刊论文数量(10)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
A mathematical perspective on CD4(+) T cell quorum-sensing.
CD4( ) T 细胞群体感应的数学视角。
  • DOI:
    10.1016/j.jtbi.2013.12.019
  • 发表时间:
    2014
  • 期刊:
  • 影响因子:
    2
  • 作者:
    Reynolds J
  • 通讯作者:
    Reynolds J
Quorum-Sensing in CD4(+) T Cell Homeostasis: A Hypothesis and a Model.
CD4(+)T细胞稳态中的Quorum-Sensing:一种假设和模型。
  • DOI:
    10.3389/fimmu.2012.00125
  • 发表时间:
    2012
  • 期刊:
  • 影响因子:
    7.3
  • 作者:
    Almeida AR;Amado IF;Reynolds J;Berges J;Lythe G;Molina-París C;Freitas AA
  • 通讯作者:
    Freitas AA
A stochastic T cell response criterion.
  • DOI:
    10.1098/rsif.2012.0205
  • 发表时间:
    2012-11-07
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Currie J;Castro M;Lythe G;Palmer E;Molina-París C
  • 通讯作者:
    Molina-París C
Receptor Pre-Clustering and T cell Responses: Insights into Molecular Mechanisms.
  • DOI:
    10.3389/fimmu.2014.00132
  • 发表时间:
    2014
  • 期刊:
  • 影响因子:
    7.3
  • 作者:
    Castro M;van Santen HM;Férez M;Alarcón B;Lythe G;Molina-París C
  • 通讯作者:
    Molina-París C
Asymmetric cell division during T cell development controls downstream fate.
  • DOI:
    10.1083/jcb.201502053
  • 发表时间:
    2015-09-14
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Pham K;Shimoni R;Charnley M;Ludford-Menting MJ;Hawkins ED;Ramsbottom K;Oliaro J;Izon D;Ting SB;Reynolds J;Lythe G;Molina-Paris C;Melichar H;Robey E;Humbert PO;Gu M;Russell SM
  • 通讯作者:
    Russell SM
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Carmen Molina-Paris其他文献

Carmen Molina-Paris的其他文献

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{{ truncateString('Carmen Molina-Paris', 18)}}的其他基金

Stochastic modelling of cellular immune responses: crossing the theoretical-experimental divide
细胞免疫反应的随机建模:跨越理论与实验的鸿沟
  • 批准号:
    BB/G023395/1
  • 财政年份:
    2009
  • 资助金额:
    $ 10.77万
  • 项目类别:
    Fellowship

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