Spatio-temporal cellular dynamics regulating differential healing outcomes

Project Summary / Abstract: Healthy individuals have a tremendous intrinsic ability to heal after injury. Wound repair involves complex and coordinated actions of various cell types acting across three sequential healing phases: Inflammatory, Proliferative and Resolution. Efficient wound repair requires a timely progression from one phase of healing to the next, with the ultimate goal of returning the injured tissue to homeostasis. Wounds of the oral cavity heal faster than skin wounds, and their phases of healing are optimized to result in a more regenerative outcome. In contrast, the phases of healing become corrupted by chronic diseases, leading to, on one extreme, pathological tissue under-healing (as in diabetic and chronic wounds) and on the other extreme, pathological tissue over-healing (as in carcinogenesis). However, studies that directly compare models of reparative skin healing with optimized oral healing, or with disease models of pathological under- or over-healing, are lacking. The overall goal of this MIRA research proposal is to understand the progression of healing phases across differential healing outcomes at the spatio-temporal single cell level. We aim to discover critical junctions along the healing continuum where healing becomes optimized (as in oral wounds) or pathological (as in chronic wounds and tumors). Our approaches are innovative because we will use state-of-the-art single cell and spatial sequencing technologies combined within a new spatio-temporal analytical framework to systematically compare cell type dynamics, cell-cell interactions and cell-specific gene regulatory networks across mouse models of successful and pathological healing. In the first project, we will generate a new spatial single cell dataset of oral wound healing and use our network-based analytical framework to identify cell-specific spatio-temporal gene signatures that distinguish optimized oral healing from reparative skin healing. In the second project, we will apply this analytical framework to identify healing-associated bottlenecks in datasets of pathological under-healing (diabetic skin injury model) and over-healing (oral and skin carcinogenesis models). We will validate our findings using existing datasets of human pathology, including those from diabetic chronic wounds and skin/oral cancers, and then experimentally using orthogonal methods in cell and animal models of wound healing and carcinogenesis. Overall, this proposal will increase our understanding of the complex cell population dynamics that result in reparative, optimized or pathological healing outcomes. The projects will result in novel phase-resolved and cell-specific gene expression signatures that describe healing-related stages of disease progression in under-healing diabetic wounds and over-healing tumors. These signatures will have diagnostic, prognostic and therapeutic value for targeting of specific cells and pathways, with the ultimate goal of promoting the healing of surgical, traumatic and chronic wounds as well as inhibiting cancer progression.