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

多细胞生物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协同工作并协调运动。此外，细胞必须在生物体内部完成此操作——这是一个复杂的 3D 环境，与培养皿中常见的 2D 环境不同。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，就像走钢丝的人一样。该项目结合了实验和理论，研究控制细胞在这些纤维上相互接触时发生的情况的物理和生物因素。在 2D 表面上，细胞在相互接触时会反转其迁移方向，这是 20 世纪 50 年代描述的现象。称为接触运动抑制 (CIL)，大量研究表明 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 上描述的结果有本质上的不同。因此，了解现实环境如何控制细胞相互作用是加深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细胞彼此粘附的程度以及细胞与纤维粘附的程度。另一项研究是研究当两个细胞碰撞且其中一个细胞转向时，转向的细胞是否是移动较慢的细胞、较小的细胞，还是其他一些因素，例如一个细胞是否具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），并观察当细胞彼此接触时极性如何变化。这项工作的更广泛影响包括该研究的内在优点，因为协调的细胞运动对于伤口愈合和正常发育等过程非常重要。 其他活动包括在线推广和培训学生为广大读者写作。将建立基于预测细胞与细胞碰撞结果的在线游戏，为更广泛的公众提供细胞生物学和物理学的不同寻常的观点。 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，细胞与细胞相互作用产生连贯运动。细胞与细胞相互作用的一个典型例子是运动的接触抑制（CIL），其中接触的细胞重新极化远离该接触。长期以来，人们一直在平面基质上的细胞中研究 CIL，但 Nain-Camley 合作最近发现，CIL 在悬浮纤维上的细胞中存在本质上的不同，后者更类似于细胞外基质。 CIL 的巨大变化如何仅由新的物理几何形状引起？哪些物理因素最能预测细胞间碰撞的结果？回答这些问题需要 CIL 的预测模型以及严格控制和生物学相关基质的实验。这与 Camley 小组（Rho GTPase 极性、运动性和 CIL 的计算模型）的经验与 Nain 小组（精确定义的悬浮纤维环境和机械生物学）的经验相匹配。该合作项目通过以下方式研究纤维环境中的 CIL：1) 研究机械力对细胞间相互作用的影响，2) 开发数据驱动的方法来预测细胞间碰撞的结果，3) 了解 Rho GTPase 极性、细胞形状和 CIL 之间的联系。现有的细胞-细胞相互作用的物理模型将根据细胞-细胞和细胞-基质粘附的测量进行参数化和扩展。粘附力将通过使用纳米力显微镜的拉伸实验来量化。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、极化程度最低的还是最小的？），并确定如何可靠地控制这种情况。为了预测这一结果，双方合作将对数百个碰撞结果的观察结果整合到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微小接触如何转化为重新极化的决定，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使用 FRET 报告基因测量 Rac 活性来进行实验表征，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。这将与了解 CIL 在不同细胞类型之间的差异相结合，以了解不同细胞类型之间的行为是否有本质上的差异，如果有，如何差异。该奖项反映了 NSF 的法定使命，并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，被认为值得支持。

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.