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贝叶斯元模型对早期 T 细胞抗原受体信号进行建模,解释了其纳米级激活模式。

Bayesian metamodeling of early T-cell antigen receptor signaling accounts for its nanoscale activation patterns.

机构信息

Racah Institute of Physics, The Hebrew University, Jerusalem, Israel.

School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.

出版信息

Front Immunol. 2024 Oct 25;15:1412221. doi: 10.3389/fimmu.2024.1412221. eCollection 2024.

DOI:10.3389/fimmu.2024.1412221
PMID:39524449
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11543436/
Abstract

T cells respond swiftly, specifically, sensitively, and robustly to cognate antigens presented on the surface of antigen presenting cells. Existing microscopic models capture various aspects of early T-cell antigen receptor (TCR) signaling at the molecular level. However, none of these models account for the totality of the data, impeding our understanding of early T-cell activation. Here, we study early TCR signaling using Bayesian metamodeling, an approach for systematically integrating multiple partial models into a metamodel of a complex system. We inform the partial models using multiple published super-resolution microscopy datasets. Collectively, these datasets describe the spatiotemporal organization, activity, interactions, and dynamics of TCR, CD45 and Lck signaling molecules in the early-forming immune synapse, and the concurrent membrane alterations. The resulting metamodel accounts for a distinct nanoscale dynamic pattern that could not be accounted for by any of the partial models on their own: a ring of phosphorylated TCR molecules, enriched at the periphery of early T cell contacts and confined by a proximal ring of CD45 molecules. The metamodel suggests this pattern results from limited activity range for the Lck molecules, acting as signaling messengers between kinetically-segregated TCR and CD45 molecules. We assessed the potential effect of Lck activity range on TCR phosphorylation and robust T cell activation for various pMHC:TCR association strengths, in the specific setting of an initial contact. We also inspected the impact of localized Lck inhibition via Csk recruitment to pTCRs, and that of splicing isoforms of CD45 on kinetic segregation. Due to the inherent scalability and adaptability of integrating independent partial models Bayesian metamodeling, this approach can elucidate additional aspects of cell signaling and decision making.

摘要

T 细胞对呈递在抗原呈递细胞表面的同源抗原迅速、特异性、敏感且强有力地做出反应。现有的微观模型在分子水平上捕捉了早期 T 细胞抗原受体 (TCR) 信号的各个方面。然而,这些模型都没有考虑到所有的数据,从而阻碍了我们对早期 T 细胞激活的理解。在这里,我们使用贝叶斯元模型对早期 TCR 信号进行研究,这是一种系统地将多个部分模型集成到复杂系统元模型中的方法。我们使用多个已发表的超分辨率显微镜数据集来提供部分模型的信息。这些数据集共同描述了 TCR、CD45 和 Lck 信号分子在早期免疫突触中的时空组织、活性、相互作用和动力学,以及伴随的膜改变。所得的元模型解释了一个独特的纳米级动态模式,这是任何一个单独的部分模型都无法解释的:一个磷酸化 TCR 分子的环,在早期 T 细胞接触的外围富集,并被一个近端的 CD45 分子环限制。该元模型表明,这种模式是由于 Lck 分子的活性范围有限,它们在动力学上分离的 TCR 和 CD45 分子之间充当信号信使。我们评估了 Lck 活性范围对 TCR 磷酸化和各种 pMHC:TCR 结合强度下的 T 细胞激活的潜在影响,这是在初始接触的特定环境下进行的。我们还检查了通过 Csk 募集到 pTCR 来抑制局部 Lck 的影响,以及 CD45 剪接异构体对动力学分离的影响。由于贝叶斯元模型具有整合独立部分模型的固有可扩展性和适应性,因此这种方法可以阐明细胞信号转导和决策的其他方面。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/6b3c01ab7cd4/fimmu-15-1412221-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/3ee67c1cfe44/fimmu-15-1412221-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/c3834137aed5/fimmu-15-1412221-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/9ed8a099a9f2/fimmu-15-1412221-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/5af06200387b/fimmu-15-1412221-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/c0eb6547cc8e/fimmu-15-1412221-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/3201875cc7fe/fimmu-15-1412221-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/37e0665c2cf4/fimmu-15-1412221-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/2bcfb581f852/fimmu-15-1412221-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/6b3c01ab7cd4/fimmu-15-1412221-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/3ee67c1cfe44/fimmu-15-1412221-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/c3834137aed5/fimmu-15-1412221-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/9ed8a099a9f2/fimmu-15-1412221-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/5af06200387b/fimmu-15-1412221-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/c0eb6547cc8e/fimmu-15-1412221-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/3201875cc7fe/fimmu-15-1412221-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/37e0665c2cf4/fimmu-15-1412221-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/2bcfb581f852/fimmu-15-1412221-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c742/11543436/6b3c01ab7cd4/fimmu-15-1412221-g009.jpg

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