Patterns of biological damage: managing subsystem failure in cellular systems

生物系统最终会失败、破裂、破裂或死亡。这些系统在自组织生长和发展过程中积极地避免、修复和管理子系统故障。我的小组将在从分子到有机体的不同组织水平上计算生物失败模型。我们想了解生命系统如何控制破坏和失败的时空模式，并从生命系统中学习如何设计和操纵有用的和有弹性的纳米级失败反应。我们将研究从子系统到系统的各个层面的故障。例如，分子失败如何影响大分子机制，或者细胞器失败如何影响细胞功能。我们将使用软材料、统计、计算和生物物理学的理论工具来关注失效的物理方面。我们将在不同的组织水平上追求三个方向：胶原组织，过氧化物酶体的数量和质量控制，以及宿主细胞的细菌入侵。i型胶原蛋白对结缔组织很重要。它是由胶原蛋白分子聚集成原纤维而形成的。我们将开发胶原原纤维的弹性模型，包括离散的原纤维损伤和加载的原纤维束破裂。我们还将探索胶原原纤维中对胶原排列的能量学，以便了解损伤何时变得能量有利。总之，我们将能够预测胶原蛋白材料的性质，从实验室测量单个原纤维。这将使我们能够有效地探索胶原蛋白损伤和失效的分子决定因素。过氧化物酶体是细胞内具有代谢活性的小细胞器。不需要的和受损的过氧化物酶体通过一个称为自噬的过程被细胞选择性地去除。关于过氧化物酶体损伤过程，特别是细胞在面对持续损伤时如何维持过氧化物酶体的功能，我们所知甚少。这将是我们建模的重点。我们工作的结果将是更好地理解细胞如何动态地管理大量的小细胞器。细菌对宿主真核细胞的入侵涉及多个层面：宿主组织、细胞和亚细胞区室和过程，但也包括通过自噬去除单个细菌。细胞感染过程包括细胞侵入、逃逸到细胞质、繁殖和向邻近细胞传播。我们将模拟这些系统中不同细菌之间以及不同感染阶段之间的相互作用。这些模型将被入侵不同阶段的更机械的模型所补充。随着我们在过氧化物酶体和细菌入侵方面的研究项目的成熟，它们将结合起来，进一步深入了解宿主细胞中小细胞器或细菌数量和功能的动态调节机制。每个方向的积极实验合作将加速进展。这将使我们把有趣的问题从生物学带入物理学。我们还将通过将定量建模与数据驱动实验联系起来，使物理技术对生物学家有用。通过结合生物学、生物物理学和建模方法，这些将有助于我们对这些生物系统有一个多层次的理解。这将突出这些系统中因果关系的物理机制。识别和理解定量现象学背后的机制将使我们能够将每种现象及其相关表型转化为工具，以更深入地了解生物系统在面对损害时是如何工作的。

Biological systems eventually fail, rupture, break, or die. These systems actively avoid, repair, and manage subsystem failure during self-organized growth and development. My group will computationally model biological failure at different levels of organization from the molecular to the organism. We want to understand how living systems control spatial and temporal patterns of damage and failure, and to learn from living systems how to design and manipulate useful and resilient response to failure at the nanoscale. We will study failure across scales, from subsystem to system. For example, how molecular failure affects macromolecular mechanisms, or how organelle failure affects cellular function. We will use the theoretical tools of soft-materials, statistical, computational, and biological physics to focus on physical aspects of failure. We will pursue three directions at distinct levels of organization: collagen tissue, peroxisome number and quality control, and bacterial invasion of host cells. Type-I collagen is important for connective tissue. It is built by tropo-collagen molecules assembling into fibrils. We will develop an elastic model of collagen fibrils with both discrete fibril damage and rupture of loaded bundles of fibrils. We will also explore the energetics of tropo-collagen alignment within collagen fibrils, in order to understand when damage becomes energetically favourable. Together, we will be able to predict collagen materials properties from laboratory measurements of individual fibrils. This would allow us to efficiently explore the molecular determinants of collagen damage and failure. Peroxisomes are small metabolically-active essential organelles within cells. Unneeded and damaged peroxisomes are selectively removed by the cell through a process called autophagy. Very little is known about peroxisome damage processes, and in particular how peroxisome function is maintained by the cell in the face of continual damage. This will be the focus of our modelling. The result of our work will be to better understand how cells dynamically manage large numbers of small organelles. The invasion of a host eukaryotic cell by a bacterium involves a variety of levels: the host tissue, cells, and subcellular compartments and processes but also the removal of individual bacteria by autophagy. Cellular infective process involve cellular invasion, escape into the cytoplasm, reproduction, and transmission to adjoining cells. We will model interactions between different bacteria, and between different stages of infection in these systems. These will be complemented by more mechanistic models of the different stages of invasion. As our programmes in peroxisomes and bacterial invasion mature, they will be combined to lead to additional insight into the mechanisms of dynamic regulation of number and function of small organelles or bacteria in host cells. Progress will be accelerated with active experimental collaborations in each direction. This will let us bring interesting problems from biology into physics. We will also make physics techniques useful for biologists by connecting quantitative modelling with data driven experiments. These will help us to develop a multi-level understanding of these biological systems, by combining biological, biophysical, and modelling approaches. This will highlight physical mechanisms of cause and effect in these systems. Identifying and understanding the mechanisms behind robustly quantitative phenomenology will allow us to turn each phenomenon, and its associated phenotypes, around into tools to look deeper into how biological systems work in the face of damage.