Multi-cellular and multi-scale systems modeling to understand the dynamics of the human immune system in interdisciplinary applications

多细胞和多尺度系统建模，以了解跨学科应用中人体免疫系统的动态

• 批准号: 10543785
• 负责人: Tomas Helikar
• 金额: $ 37.13万
• 依托单位: UNIVERSITY OF NEBRASKA LINCOLN
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2026-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10543785
• 关键词: Behavior; Biochemical; Biological; Biological Markers; Biological Models; Brain; CD4 Positive T Lymphocytes; COVID-19; Cells; Collaborations; Communication; Communities; Complex; Computer software; Decision Making; Dimensions; Disease; Education; Etiology; Funding; Gene Expression Regulation; Human; Immune; Immune response; Immune system; Immunological Models; Immunologist; Interdisciplinary Study; International; Laboratories; Mediator; Metabolism; Methods; Modeling; Multiomic Data; Nature; Pathology; Pharmacotherapy; Property; Reproducibility; Research; Research Personnel; Software Engineering; Stimulus; System; Technology; Time; Visualization; Work; cell type; computer framework; cost; cytokine; data-driven model; design; drug discovery; effective therapy; human model; multi-scale modeling; pathogen; predictive modeling; programs; response; simulation; translational scientist; virtual

PROJECT SUMMARY/ABSTRACT The immune system is arguably the second most complex human system after the brain. Its proper response to foreign stimuli is governed by network-like interactions among various types of cells and cytokines as their communication mediators. The complexity at the inter-cellular level of the immune system is further exacerbated by the similarly complex biological and biochemical networks within each cell (metabolism, gene regulation, etc.) responsible for the dynamics and decision-making at the single-cell level. Such multiscale complexity makes it incredibly challenging to understand the complete etiology and pathology of immune-system-related diseases. My research program aims to identify how the immune system can be rewired en masse to elicit higher-order decision-making while still enabling the system to remain otherwise “healthy.” To this end, my research program is leveraging a highly interdisciplinary research team (computational and experimental immunologists, software engineers, and education researchers) and collaborators to build a Virtual Immune System -- a multi-scale, multi-approach computational framework to understand better the complex dynamical nature of the immune system, identify more accurate multi-dimensional biomarkers, and identify safe and effective treatments within a reasonable time and cost. In the next five years, in addition to expanding the Virtual Immune system, my program will continue to develop methods and technologies for data-driven model construction, visualization, computation, real-time simulations, and reproducibility to advance multi-scale modeling of the immune system and beyond. We will continue to decipher the dynamics of the immune system under various pathologies and the re-programmability of CD4+ T cells under the milieu of their microenvironments. My laboratory will continue to iteratively predict, validate, and refine predictions generated using the systems approaches and technologies. To do this, we will generate our multi-omics data to more precisely validate immune system behaviors and apply our findings to refine the computational approaches directly. My team will continue to build collaborations and deepen our existing relationships, including with translational partners to advance the impact of our systems work on drug discovery, the international team modeling COVID-19, and with virologists and immunologists to further validate our computational predictions experimentally.

项目概要/摘要 免疫系统可以说是仅次于大脑的第二复杂的人体系统。它是 对外来刺激的正确反应是由各种类型之间的网络式相互作用控制的 细胞和细胞因子作为它们的通讯介质。细胞间的复杂性 同样复杂的生物和免疫系统水平进一步加剧了免疫系统的水平。 每个细胞内的生化网络（代谢、基因调控等）负责 单细胞水平的动力学和决策。如此多尺度的复杂性使得 了解完整的病因和病理学非常具有挑战性 免疫系统相关疾病。我的研究计划旨在确定免疫如何 系统可以整体重新布线，以引发更高阶的决策，同时仍然使 系统保持“健康”。为此，我的研究计划利用了高度 跨学科研究团队（计算和实验免疫学家、软件 工程师和教育研究人员）和合作者构建虚拟免疫系统—— 多尺度、多方法计算框架，以更好地理解复杂的 免疫系统的动态性质，识别更准确的多维生物标志物， 并在合理的时间和成本内确定安全有效的治疗方法。在接下来的五年里 多年来，除了扩展虚拟免疫系统之外，我的程序还将继续发展 数据驱动模型构建、可视化、计算的方法和技术， 实时模拟和可重复性，以推进免疫系统的多尺度建模 以及更远的地方。我们将继续破译免疫系统在各种情况下的动态变化 CD4+ T 细胞在其环境下的病理学和重编程性 微环境。我的实验室将继续迭代预测、验证和完善 使用系统方法和技术生成的预测。为此，我们将 生成我们的多组学数据，以更精确地验证免疫系统行为并应用 我们的研究结果直接改进了计算方法。我的团队将继续建设 合作并深化我们现有的关系，包括与翻译合作伙伴的关系 推进我们的系统工作对药物发现、国际团队建模的影响 COVID-19，并与病毒学家和免疫学家一起进一步验证我们的计算 通过实验进行预测。