MiStImm:一种基于代理的模拟工具,用于研究适应性免疫反应的自我非自我分辨能力。

Q1 Mathematics
Csaba Kerepesi, Tibor Bakács, Tamás Szabados
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引用次数: 0

摘要

背景:现在越来越需要复杂的计算模型来进行硅学实验,以辅助免疫学的体外和体内实验。我们介绍了微观随机免疫系统模拟器(MiStImm),这是一种基于代理的模拟工具,旨在研究适应性免疫系统的自我非自我分辨能力。MiStImm 可以模拟体液适应性免疫反应的一些组成部分,包括 T 细胞、B 细胞、抗体、危险信号、白细胞介素、自身细胞、外来抗原以及它们之间的相互作用。模拟从受孕后开始,在随机模拟事件的驱动下逐步(按时间)进行。我们还提供了可视化和分析模拟程序输出结果的工具:作为 MiStImm 的首次应用,我们模拟了两种不同的免疫模型,然后比较了它们在自我非我辨别方面的表现。第一个模型是所谓的传统免疫模型,第二个模型是基于我们早期的 T 细胞模型,即 "单信号模型"。我们的新 T 细胞模型假定,T 细胞与宿主细胞之间通过低亲和性互补 TCR-MHC 相互作用形成一个动态稳态耦合系统。新模型意味着,相当一部分天真多克隆 T 细胞会被招募到抗感染的第一道防线。使用 MiStImm 进行的模拟实验表明,新模型的计算实现显示了真实的模式。例如,尽管假设 T 细胞与自身细胞之间的 TCR-MHC 相互作用增强,但新模型仍能形成免疫记忆,而且不会产生自身免疫反应。模拟还表明,我们的新模型在克服关键的原发性感染方面取得了更好的结果,回答了 "人类基因组的一小部分如何能有效地与变异病原体 DNA 的巨大池竞争?免疫疗法领域的大量临床试验观察结果支持了我们在本文中介绍的硅学实验结果。我们希望我们的研究结果能鼓励人们进行体外和体内实验,以澄清适应性免疫系统的自我非自我分辨问题。我们也希望 MiStImm 或其中的某些概念能对其他希望实施或比较其他免疫模型的研究人员有所帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

MiStImm: an agent-based simulation tool to study the self-nonself discrimination of the adaptive immune response.

MiStImm: an agent-based simulation tool to study the self-nonself discrimination of the adaptive immune response.

MiStImm: an agent-based simulation tool to study the self-nonself discrimination of the adaptive immune response.

MiStImm: an agent-based simulation tool to study the self-nonself discrimination of the adaptive immune response.

Background: There is an increasing need for complex computational models to perform in silico experiments as an adjunct to in vitro and in vivo experiments in immunology. We introduce Microscopic Stochastic Immune System Simulator (MiStImm), an agent-based simulation tool, that is designed to study the self-nonself discrimination of the adaptive immune system. MiStImm can simulate some components of the humoral adaptive immune response, including T cells, B cells, antibodies, danger signals, interleukins, self cells, foreign antigens, and the interactions among them. The simulation starts after conception and progresses step by step (in time) driven by random simulation events. We also have provided tools to visualize and analyze the output of the simulation program.

Results: As the first application of MiStImm, we simulated two different immune models, and then we compared performances of them in the mean of self-nonself discrimination. The first model is a so-called conventional immune model, and the second model is based on our earlier T-cell model, called "one-signal model", which is developed to resolve three important paradoxes of immunology. Our new T-cell model postulates that a dynamic steady state coupled system is formed through low-affinity complementary TCR-MHC interactions between T cells and host cells. The new model implies that a significant fraction of the naive polyclonal T cells is recruited into the first line of defense against an infection. Simulation experiments using MiStImm have shown that the computational realization of the new model shows real patterns. For example, the new model develops immune memory and it does not develop autoimmune reaction despite the hypothesized, enhanced TCR-MHC interaction between T cells and self cells. Simulations also demonstrated that our new model gives better results to overcome a critical primary infection answering the paradox "how can a tiny fraction of human genome effectively compete with a vastly larger pool of mutating pathogen DNA?"

Conclusion: The outcomes of our in silico experiments, presented here, are supported by numerous clinical trial observations from the field of immunotherapy. We hope that our results will encourage investigations to make in vitro and in vivo experiments clarifying questions about self-nonself discrimination of the adaptive immune system. We also hope that MiStImm or some concept in it will be useful to other researchers who want to implement or compare other immune models.

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来源期刊
Theoretical Biology and Medical Modelling
Theoretical Biology and Medical Modelling MATHEMATICAL & COMPUTATIONAL BIOLOGY-
自引率
0.00%
发文量
0
审稿时长
6-12 weeks
期刊介绍: Theoretical Biology and Medical Modelling is an open access peer-reviewed journal adopting a broad definition of "biology" and focusing on theoretical ideas and models associated with developments in biology and medicine. Mathematicians, biologists and clinicians of various specialisms, philosophers and historians of science are all contributing to the emergence of novel concepts in an age of systems biology, bioinformatics and computer modelling. This is the field in which Theoretical Biology and Medical Modelling operates. We welcome submissions that are technically sound and offering either improved understanding in biology and medicine or progress in theory or method.
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