Collaborative Research: Theory and experiment of contact inhibition of locomotion in nanofiber geometries

多细胞生物体由各种类型和数量的细胞组成，这些细胞必须在各种条件下共同工作并协调它们的运动。此外，细胞必须在生物体内完成这一过程-这是一个复杂的3D环境，不同于普通的2D培养皿环境。该项目研究细胞如何在更自然的环境中协调运动：沿着蛋白质涂层的纤维爬行，就像走钢丝的步行者。该项目结合实验和理论来研究控制细胞在这些纤维上相互接触时发生的事情的物理和生物因素。在2D表面上，细胞在彼此接触时逆转其迁移方向，这是20世纪50年代描述的现象。被称为运动接触抑制（CIL），许多研究表明CIL结果取决于细胞类型。Camley-Nain合作最近表明，悬浮纤维上的CIL结果与平面2D上描述的结果有质的不同。因此，了解现实环境如何控制细胞相互作用是提高对这些生物过程的理解的重要一步。该项目的一种方法是通过测量将细胞拉开所需的力来了解有多少细胞相互粘附以及它们粘附在纤维上。另一个将是研究当两个细胞碰撞并且其中一个转向时，转向的细胞是否是移动较慢的细胞，较小的细胞，或者其他一些因素，例如一个细胞是否有长或不对称的卷须。该项目还将研究细胞内的蛋白质，这些蛋白质决定细胞将向哪个方向突出其前端（极性蛋白质），并观察当细胞相互接触时这种极性如何变化。这项工作的更广泛影响包括研究的内在价值，因为协调的细胞运动对于伤口愈合和正常发育等过程很重要。 其他活动包括在线推广和培训学生为广大读者写作。我们还将开发基于预测细胞间碰撞结果的网络游戏，为广大公众提供细胞生物学和物理学的独特视角。在许多生物学背景下，包括伤口愈合、发育和癌症转移，真核细胞集体迁移，细胞间相互作用产生连贯的运动。细胞-细胞相互作用的一个典型例子是运动的接触抑制（CIL），其中接触细胞从接触中恢复。CIL长期以来一直在平坦基底上的细胞中进行研究，但Nain-Camley合作最近发现，CIL在悬浮纤维上的细胞中有质的不同，其更类似于细胞外基质。CIL中的巨大变化如何仅由新的物理几何产生？哪些物理因素最能预测细胞间碰撞的结果？解决这些问题需要CIL的预测模型，再加上严格控制和生物相关基质的实验。这与Camley小组的经验（Rho GT3极性、运动性和CIL的计算模型）和Nain小组的经验（精确定义的悬浮纤维环境和机械生物学）相匹配。该合作项目通过以下方式研究纤维环境中的CIL：1）研究机械力对细胞-细胞相互作用的影响，2）开发一种数据驱动的方法来预测细胞-细胞碰撞的结果，以及3）了解Rho GT3极性，细胞形状和CIL之间的联系。现有的细胞间相互作用的物理模型将参数化和扩展的基础上测量细胞间和细胞基质的粘附。粘附将通过使用纳米网力显微镜的牵拉实验来量化。该项目将开发工具来预测当两个细胞碰撞时哪个细胞会转向（它是最慢的，极化最少的，还是最小的？）并确定如何可靠地控制这种情况。为了预测这一结果，该合作将把对数百次碰撞结果的观察整合到一个数据驱动的统计模型中，以确定关键的控制因素。为了了解细胞之间的小接触是如何被转换成恢复的决定的，该合作将研究细胞碰撞中的Rac极性。复极化的初始步骤将通过用FRET报告子进行Rac活性测量来实验性地表征，并且将在模型和实验之间测量和校准接触后的复极化程度。这将与理解CIL如何从细胞类型到细胞类型的差异相结合，以了解不同细胞类型之间的行为是否存在质的差异，如果是这样，如何。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

Multicellular organisms are composed of various types and numbers of cells that must work together and coordinate their movement under various conditions. Moreover, cells must do this inside an organism – a complex 3D environment unlike the common 2D environment of Petri dishes. This project studies how cells can coordinate their motion in a more natural environment: crawling along a protein-coated fiber, like a tightrope walker. The project combines experiments and theory to study the physical and biological factors that control what happens when cells contact each other on these fibers. On 2D surfaces cells reverse their migration direction upon contacting each other, a phenomenon described in the 1950s. Termed contact inhibition of locomotion (CIL), numerous studies have shown CIL outcomes to depend upon cell type. The Camley-Nain collaboration has recently shown CIL outcomes to be qualitatively different on suspended fibers than those described on flat 2D. Thus, understanding how realistic environments control cellular interactions is an essential step to improved understanding of these biological processes. One approach in this project will be to understand how much cells stick to each other and how much they stick to the fiber by measuring the force required to pull them apart. Another will be to study whether, when two cells collide and one turns around, the cell that turns around is the cell that is moving slower, the cell that is smaller, or some other factors like if one cell has long or asymmetric tendrils. The project will also study proteins inside a cell that determine which direction a cell will protrude its front (polarity proteins) and see how this polarity changes when cells contact each other. The Broader Impact of the work includes the intrinsic merit of the research as coordinated cellular movement is important for such processes as wound healing and normal development. Additional activities involve online outreach and training students to write for a broad audience. Online games based on predicting the outcome of cell-cell collisions will be built, to give an unusual view of cell biology and physics to the wider public.In many biological contexts, including wound healing, development, and cancer metastasis, eukaryotic cells migrate collectively, with coherent motion emerging from cell-cell interactions. A prototypical example of a cell-cell interaction is contact inhibition of locomotion (CIL), in which contacting cells repolarize away from that contact. CIL has been long studied in cells on flat substrates, but the Nain-Camley collaboration recently discovered that CIL is qualitatively different in cells on suspended fibers, which more closely resemble extracellular matrix. How do large changes in CIL arise only from new physical geometry? What physical factors are most predictive of the outcomes of cell-cell collisions? Answering these questions requires predictive models of CIL coupled with experiments on tightly-controlled and biologically relevant matrices. This matches the experience of the Camley group (computational models of Rho GTPase polarity, motility, and CIL) with that of the Nain group (precisely defined suspended fiber environments and mechanobiology). This collaborative project studies CIL in fibrous environments by: 1) Studying the effect of mechanical forces on cell-cell interactions, 2) Developing a data-driven method to predict the outcomes of cell-cell collisions, and 3) Understanding the link between Rho GTPase polarity, cell shape, and CIL. Existing physical models of cell-cell interactions will be parametrized and extended based on measurements of cell-cell and cell-substrate adhesion. Adhesion will be quantified by pulling experiments using nanonet force microscopy. The project will develop tools to predict which cell turns around when two cells collide (is it the slowest, the least polarized, the smallest?) and determine how can this be reliably controlled. To predict this outcome, the collaboration will integrate observations of hundreds of collision outcomes into a data-driven statistical model to determine the crucial controlling factors. To understand how a small contact between cells is transduced into a decision to repolarize, the collaboration will study Rac polarity in cell collisions. The initial steps of repolarization will be experimentally characterized by Rac activity measurements with FRET reporters, and the degree of repolarization post-contact will be measured and calibrated between model and experiment. This will be combined with understanding how CIL differs from cell type to cell type to understand if behaviors are qualitatively different between different cell types, and if so, how.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.