Modular design of multiscale models, with an application to the innate immune response to fungal respiratory pathogens

项目总结 跨空间和时间尺度的生物医学数据集的可用性增加使校准成为可能 捕捉从分子到整个生物体水平的综合过程的复杂模型。这 复杂性带来了与数学建模、软件设计、验证 可重复性和可扩展性。模型要素和动态的可视化是可用性的关键因素 由领域专家建立模型，如实验生物学家和临床医生。拟议的项目涉及 这些挑战涉及对呼吸道真菌感染的一种重要的免疫反应。它的目标是 为了开发一种新的模块化方法来建模体系结构，使用最近引入的技术 轻量级的虚拟机和我们用户友好的开源平台，用于构建和链接这些 所谓的“Docker Containers”，以透明方式创建复杂的模块化模型。的一个主要优势 软件容器是它们可以涵盖模型的整个计算环境，从而实现 史无前例的计算结果重复性。计算的首要目标是开发一个 多尺度模型模块化设计的新方法。虽然适用范围很广，但这种新型的计算 建模方法将侧重于开发一个多尺度模型，该模型捕获了 侵袭性曲霉病，一个重要的健康问题。 侵袭性曲霉病是免疫功能低下的宿主最常见的真菌感染之一 预后很差。致病微生物烟曲霉的孢子无处不在。 分布在环境中。健康的宿主清除吸入的孢子不会患上疾病，但 免疫力受损的人容易感染危及生命的呼吸道感染，然后 传播到其他器官。越来越多的免疫抑制疗法在移植和治疗中的使用 癌症极大地增加了这种感染造成的痛苦和死亡，预计这一趋势将 继续。目前的治疗方法主要集中在病原体上，但更好的治疗方法是 对这种感染中宿主防御成分的了解可能会导致新的 治疗。特别是，限制铁的可获得性是抗菌宿主防御的关键机制； 相反，成功的病原体进化出了从宿主中清除铁的有效机制。这些 这些机制有可能被用于治疗。拟议项目的生物学重点是 真菌和宿主之间对铁的争斗。生物医学的首要目标是开发一种 从生化和生物物理角度探讨铁在侵袭性曲霉病中作用的模拟工具 条件。

PROJECT SUMMARY Increased availability of biomedical data sets across spatial and temporal scales makes it possible to calibrate complex models that capture integrated processes from the molecular to the whole organism level. This complexity poses multiple challenges related to mathematical modeling, software design, validation, reproducibility, and extensibility. Visualization of model features and dynamics is a key factor in the usability of models by domain experts, such as experimental biologists and clinicians. The proposed project addresses these challenges in the context of the immune response to an important respiratory fungal infection. Its goal is to develop a novel modular approach to model architecture, using a recently introduced technology of lightweight virtual machines and our user-friendly open-source platform for the construction and linking of these so-called “Docker containers” to create complex modular models in a transparent fashion. A key benefit of software containers is that they can encompass the entire computational environment of a model, enabling unprecedented reproducibility of computational results. The overarching computational goal is to develop a novel approach to the modular design of multiscale models. While broadly applicable, this novel computational modeling approach will be focused on the development of a multiscale model capturing the early stages of invasive aspergillosis, an important health problem. Invasive aspergillosis is one of the most common fungal infections in immunocompromised hosts and carries a poor prognosis. The spores of the causative organism, Aspergillus fumigatus, are ubiquitously distributed in the environment. Healthy hosts clear the inhaled spores without developing disease, but individuals with impaired immunity are susceptible to a life-threatening respiratory infection that can then disseminate to other organs. The increasing use of immunosuppressive therapies in transplantation and cancer has dramatically increased suffering and death from this infection, and this trend is expected to continue. Current therapeutic approaches have been focused primarily on the pathogen, but a better understanding of the components of host defense in this infection may lead to the development of new treatments. In particular, restricting iron availability is a critical mechanism of antimicrobial host defense; conversely, successful pathogens have evolved potent mechanisms for scavenging iron from the host. These mechanisms have the potential to be harnessed therapeutically. The biological focus of the proposed project is the battle over iron between the fungus and the host. The overarching biomedical goal is to develop a simulation tool to explore the role of iron in invasive aspergillosis across biochemical and biophysical conditions.