Collaborative Research: Multiscale and Multiphasic Modeling of Single and Collective Migration in Fibrous Extracellular Matrices

合作研究：纤维细胞外基质中单一和集体迁移的多尺度和多相建模

• 批准号: 1953572
• 负责人: Vivek Shenoy
• 金额: $ 30万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1953572&HistoricalAwards=false
• 关键词: Collaborative; Research; Multiscale; Multiphasic; Modeling

Biological cells sense and respond to physical forces, which can shape and guide their behavior. Cells can also actively generate forces, to probe and deform materials in their surrounding environment. These dynamic interactions between clusters of cells and their environment are critical to an immense range of activities including early development and cancer progression. In recent years there has been a growing interest to uncover what drives cells to escape from growing clusters, either independently or in collective streams. However, a thorough understanding of the biophysics governing such activity is lacking. To address these issues, a novel computational and experimental framework will be developed to investigate how the interplay between cellular forces, adhesion, and environmental physics drive cells to proliferate, escape, and invade distant regions of the body. The new tools proposed will impact many areas in biology, including normal and abnormal tissue development, wound healing, and tissue regeneration. The innovative mathematical models and methods will advance computing in biology as well as other fields of science such as bioengineering and biotechnology.Current mathematical models cannot predict why cells invade from a proliferative cluster and migrate either independently or as collective strands, which determines the metastatic risk of invading cells during cancer progression. This problem will be addressed through a novel multi-scale framework that integrates computational models of highly non- linear matrix mechanics, force-mediated cell signaling, and active cell contractility. Such an approach will provide a new understanding of the mechanisms by which matrix properties promote or discourage cell invasion, and why cells tend to either move collectively or act alone. In particular, the critical role of cell-mediated matrix remodeling, long range force transmission, and epithelial-to-mesenchymal transitions (EMT) will be uncovered. The kinetics of cell invasion requires the formation of protrusions, assembly and dissolution of adhesions, and remodeling of contractile actomyosin fibers. These stochastic processes will be modelled using Kinetic Monte Carlo methods, that will explicitly account for fluctuations in the cell’s response to its environment. Additionally, a novel multi-scale bio-chemo-mechanical model of tissue growth will be developed to predict formation of arbitrarily shaped cell clusters and to quantify how complex patterns of cells emerge from such clusters. This research will lead to a paradigm shift in the mathematical modelling of cell invasion by explicitly including signalling, non-linear matrix mechanics and the two-way recursive dialog between cells and the matrix.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

生物细胞感知并响应物理力量，这些力量可以塑造和指导它们的行为。细胞也可以主动产生力，探测和变形周围环境中的物质。细胞群与其环境之间的动态相互作用对包括早期发育和癌症进展在内的一系列活动至关重要。近年来，人们越来越有兴趣揭示是什么驱使细胞从生长的集群中逃逸，无论是独立的还是集体的。然而，缺乏对控制这种活动的生物物理学的透彻理解。为了解决这些问题，将开发一个新的计算和实验框架来研究细胞力，粘附和环境物理之间的相互作用如何驱动细胞增殖，逃逸和入侵身体的遥远区域。提出的新工具将影响生物学的许多领域，包括正常和异常组织发育，伤口愈合和组织再生。创新的数学模型和方法将推动生物学以及其他科学领域的计算，如生物工程和生物技术。目前的数学模型无法预测为什么细胞会从增殖集群侵入，并独立或集体迁移，这决定了癌症进展过程中入侵细胞的转移风险。这个问题将通过一个新的多尺度框架来解决，该框架集成了高度非线性矩阵力学、力介导的细胞信号传导和活性细胞收缩的计算模型。这种方法将对基质特性促进或阻碍细胞入侵的机制，以及为什么细胞倾向于集体移动或单独行动提供新的理解。特别是，细胞介导的基质重塑、远程力传递和上皮-间质转化（EMT）的关键作用将被揭示。细胞侵袭的动力学需要突起的形成，粘连的组装和溶解，以及收缩肌动球蛋白纤维的重塑。这些随机过程将使用动力学蒙特卡罗方法进行建模，这将明确地解释细胞对其环境反应的波动。此外，将开发一种新的多尺度生物化学-机械组织生长模型，以预测任意形状细胞团的形成，并量化细胞如何从这些细胞团中出现复杂的模式。这项研究将通过明确地包括信号、非线性矩阵力学和细胞与矩阵之间的双向递归对话，导致细胞入侵数学模型的范式转变。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Dynamic self-reinforcement of gene expression determines acquisition of cellular mechanical memory

• DOI: 10.1016/j.bpj.2021.10.006
• 发表时间: 2021-11-16
• 期刊: BIOPHYSICAL JOURNAL
• 影响因子: 3.4
• 作者: Price, Christopher C.;Mathur, Jairaj;Shenoy, Vivek B.
• 通讯作者: Shenoy, Vivek B.

Recursive feedback between matrix dissipation and chemo-mechanical signaling drives oscillatory growth of cancer cell invadopodia.

• DOI: 10.1016/j.celrep.2021.109047
• 发表时间: 2021-04-27
• 期刊: Cell reports
• 影响因子: 8.8
• 作者: Gong Z;Wisdom KM;McEvoy E;Chang J;Adebowale K;Price CC;Chaudhuri O;Shenoy VB
• 通讯作者: Shenoy VB

Enhanced substrate stress relaxation promotes filopodia-mediated cell migration.

• DOI: 10.1038/s41563-021-00981-w
• 发表时间: 2021-09
• 期刊: Nature materials
• 影响因子: 41.2
• 作者: Adebowale K;Gong Z;Hou JC;Wisdom KM;Garbett D;Lee HP;Nam S;Meyer T;Odde DJ;Shenoy VB;Chaudhuri O
• 通讯作者: Chaudhuri O