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

多细胞生物是由各种类型和数量的细胞组成的，这些细胞必须在各种条件下协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，不同于培养皿中常见的2D环境。这个项目研究细胞如何在更自然的环境中协调它们的运动：像走钢丝的人一样沿着蛋白质涂层的纤维爬行。该项目将实验和理论结合起来，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。在二维表面上，细胞在相互接触后会逆转其迁移方向，这是20世纪50年代描述的一种现象。称为运动接触抑制（CIL），许多研究表明，CIL的结果取决于细胞类型。Camley-Nain最近的合作表明，在悬浮纤维上的CIL结果与在平面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理解的重要一步。这个项目的一种方法是通过测量将细胞分开所需的力来了解细胞彼此粘在一起的程度以及它们粘在纤维上的程度。另一个将是研究，当两个细胞碰撞，其中一个转身时，转身的细胞是否移动较慢，细胞是否较小，或者其他一些因素，比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向前伸出的方向（极性蛋白质），并观察细胞相互接触时这种极性是如何变化的。这项工作的广泛影响包括研究的内在优点，因为协调的细胞运动对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训练学生为广泛的读者写作。基于预测细胞-细胞碰撞结果的网络游戏将被建立起来，为更广泛的公众提供细胞生物学和物理学的不同寻常的视角。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相干运动。细胞间相互作用的一个典型例子是运动的接触抑制（CIL），在这种情况下，接触的细胞会重新极化，远离接触。长期以来，人们一直在平面基质上的细胞中研究CIL，但Nain-Camley合作团队最近发现，在悬浮纤维上的细胞中，CIL在质量上有所不同，而悬浮纤维更类似于细胞外基质。为什么仅仅从新的物理几何结构中产生巨大的CIL变化？什么物理因素最能预测细胞-细胞碰撞的结果？回答这些问题需要CIL的预测模型以及在严格控制和生物学相关的基质上进行的实验。这与Camley组（Rho GTPase极性、运动性和CIL的计算模型）和Nain组（精确定义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-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；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-基质粘附的测量参数化和扩展。粘附性将通过纳米力显微镜的拉力实验来量化。该项目将开发工具来预测当两个电池碰撞时哪个电池会转身（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，该合作将把数百次碰撞结果的观察结果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转化为再极化的决定的，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Rac活性测量来实验表征，并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质的不同，如果有，是如何不同的。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。

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.