Design strategies for programming and quantitatively interrogating cellular competition in heterogeneous tissues

挑战：管理细胞群体如何组装成功能组织的规则是一个长期存在的谜题。我的研究计划的长期目标是了解这些规则，使功能组织能够在培养皿中组装。我之前的DG培训了30名HQP，并探索了不同细胞群体的属性如何影响整体组织行为。这项建议侧重于了解组织中细胞群体的异质性。具体地说，我们将探索支配细胞竞争的规则，这是一个发生在发育中和成年组织中的基本过程，在这个过程中，更适合的“赢家”细胞会杀死更适合的“输家”细胞。我们将通过以下目标探索这些规则： 目的1：在体外和电子计算机中建立哺乳动物细胞竞争的二维模型，以量化失败者细胞杀伤和获胜者细胞生长的空间和时间动力学 我们将设计包含赢家和输家细胞结构域的单层。使用荧光细胞死亡和生长记者，结合自动图像跟踪算法，我们将量化失败者的细胞杀伤率，以及哪些细胞和组织属性影响这一比率。利用我们的实验数据，我们将开发一个计算模型来预测失败者的杀伤率。 目的2：探讨竞争动力学与组织异质性的关系 我们将A)量化具有特定赢家/输家结构域几何形状的单层中的杀伤率，或生长在微槽上，以诱导细胞的形态极化，无论是平行于或垂直于赢家-输家结构域界面，以测试组织结构影响竞争的假设；以及B)监测单层中的赢家扩张，该单层设计有荧光标记，以使赢家细胞能够区分赢家-输家细胞界面的近端和远端，以检验竞争与成本相关的假说。 目的3：探讨代谢梯度对三维竞争动力学和异质性的影响 我们将使用我们独特的3D示踪系统来测试这一假设，即营养和废物因素的梯度将影响获胜者和失败者群体的代谢信号，从而影响他们的相对适合度和竞争能力。 新颖性/影响：通过应用独特的工程工具，拟议的研究将以一种全新的方式询问控制细胞竞争的关键参数，这将改变这一爆炸性领域。了解竞争和组织异质性之间的关系将为设计具有可预测结构的自组织组织以及理解竞争如何导致组织在衰老和疾病中分解提供基础。此外，该计划将聘用18名HQP，他们将获得有效过渡到现代劳动力并影响加拿大在未来几十年将面临的复杂跨学科问题所必需的批判性思维、量化分析和专业技能。

CHALLENGE:The rules that govern how populations of cells assemble into functional tissues are a long-standing puzzle. The long-term objective of my research program is to understand these rules to enable the assembly of functional tissues in a dish. My previous DG trained 30 HQP and explored how the properties of different cell populations impact overall tissue behaviour. This proposal focuses on understanding cell population heterogeneity in a tissue. Specifically, we will explore the rules that dictate cell competition, a fundamental process that occurs in both developing and adult tissue, in which more fit “winner” cells kill less fit “loser” cells in the population. We will explore these rules via the follow aims: Aim 1: Create 2-dimensional in vitro and in silico models of mammalian cell competition to quantify the spatial and temporal dynamics of loser cell killing and winner cell growth We will engineer monolayers containing domains of winner and loser cells. Using fluorescent cell death and growth reporters, combined with automated image tracking algorithms we will quantify loser cell killing rate and which cell and tissue properties affect this rate. Using our experimental data, we will develop a computational model to predict loser killing rate. Aim 2: Explore the relationship between competition dynamics and tissue heterogeneity We will A)Quantify kill rates in monolayers with specific winner/loser domain geometries or grown on microgrooves oriented to induce morphological polarization of the cells either parallel or perpendicular to the winner-loser domain interface to test the hypothesis that tissue structure impacts competition and B)Monitor winner expansion in monolayers engineered with fluorescence markers to enable winner cells proximal and distant to the winner-loser cell interface to be distinguished to test the hypothesis that competition is associated with a cost. Aim 3: Explore the impact of metabolic gradients on competition dynamics and heterogeneity in 3-dimensions (3D) We will use our unique 3D TRACER system to test the hypothesis that gradients of nutrient and waste factors will impact metabolic signalling in winner and loser populations impacting their relative fitness and ability to compete. NOVELTY/IMPACT: By applying unique engineering tools, the proposed research will interrogate the critical parameters that control cell competition in an entirely new way that will transform this exploding field. Understanding the relationship between competition and tissue heterogeneity will provide a basis for engineering self-organizing tissues with predictable structures and for understanding how competition drives tissue break down in aging and disease. In addition, the program will engage 18 HQP who will gain the critical thinking, quantitative analysis and professional skills essential to effectively transition into a modern workforce and impact the complex inter-disciplinary problems Canada will face in the coming decades.