Linking GPCR organization states with functional heterogeneity in the pancreatic islet

目前对组织复杂性的看法主要基于单细胞筛选技术，该技术根据共同的特征（如成熟度、增殖能力和突变潜力）对细胞进行分类。通常，关于细胞功能的推断是基于在组织背景之外进行的测量，以及细胞所属状态的特征。因此，未成熟的细胞往往被认为是增殖的，但功能差，而更成熟的细胞是长寿和高功能的。虽然单细胞筛选方法是高维的，但它们不具有光学显微镜固有的时空分辨率。本提案将利用基因组编辑，蛋白质标记，超分辨率成像和空间转录组学的最新进展，在组织水平上提供细胞异质性的高阶原位组织，对我们理解组织（dys）功能产生影响。使用胰岛作为示例性微器官，和GPCR作为候选细胞表面信号蛋白，我们将：1）在细胞群体水平绘制GPCR组织/动力学图，并在重新分类细胞状态之前将该信息与潜在的转录组学特征整合; 2）理解在细胞刺激、代谢应激和其他组织扰动状态期间高阶GPCR组织/动力学如何变化; 3）使用新的活性整合子和细胞特异性转录因子再表达功能性地询问由GPCR组织/动力学定义的细胞状态;以及4）检查跨物种的高阶细胞异质性。这项工作将首次展示单个信号蛋白的组织和动态如何与整个细胞群的细胞状态和细胞活性相关。更广泛地说，这些研究将建立细胞异质性的高分辨率视图，从而使我们对复杂组织的功能组织的理解发生重大变化。

The current view of tissue complexity is mainly based upon single-cell screening technologies, which classify cells according to shared traits, such as maturity, proliferative capacity and mutational potential. Often, inferences about cell function are based upon measurements made outside of the tissue context, as well as the characteristics of the state to which the cell belongs. Thus, immature cells tend to be considered as proliferative, but poorly functional, whereas more mature cells are long-lived and highly functional. While single-cell screening approaches are high-dimensional, they do not have the spatiotemporal resolution inherent to light microscopy. The present proposal will leverage recent advances in genome editing, protein labelling, super-resolution imaging and spatial transcriptomics to provide a higher-order in situ organization of cell heterogeneity at the tissue level, with repercussions for our understanding of tissue (dys)function. Using pancreatic islets as an exemplar micro-organ, and GPCRs as candidate cell surface signalling proteins, we will: 1) map GPCR organization/dynamics at the cell population level and integrate this information with underlying transcriptomic features, before re-classifying cell states; 2) understand how higher-order GPCR organization/dynamics change during cell stimulation, metabolic stress and other states of tissue perturbation; 3) functionally interrogate cell states defined by GPCR organization/dynamics using novel activity integrators and cell-specific transcription factor re-expression; and 4) examine higher-order cell heterogeneity across species. The proposed work will show for the first time how the organization and dynamics of individual signalling proteins relate to cell state and cell activity across the cell population. More broadly, these studies will establish a high-resolution view of cell heterogeneity, leading to a step-change in our understanding of the functional organisation of complex tissues.