The relationship between structure and function is central to understanding how many biological and chemical processes operate, across length scales from small molecule chemicals to gross anatomy. Through an explosion in new technologies, including single-cell RNA sequencing (scRNAseq) and multiplexed tissue imaging (MTI), tissues can now be visualized with incredible molecular and cellular detail. However, such rich atlases of tissue structure are typically static snapshots from a fixed sample, and lack important information about how the tissue actually functions — how cells, fluids, and biomolecules dynamically interact to govern multicellular behaviors. Our project aims to overcome this limitation by building an integrated computational and experimental platform for quantitatively linking functional dynamics within tissue to a high-resolution spatial map of its molecular and cellular composition. As a result, the project aims to produce Molecular profiling of Tissue Dynamics (MOTID) as a generalizable method that links structure with function in multicellular communities, designed to be applicable across diverse models, tissue-types, and dynamic readouts. In this project, we aim for MOTID to be capable of simultaneously monitoring the dynamic morphology and migration of a substantial fraction all cells within a tissue region, combined with the fluid- phase movement of particular molecules moving from microvascular circulation through interstitium. Highly multiplexed imaging of the same tissue, guided by interactive statistical mining of complementary genomic data, will reveal immunologically-defined cell-type identities that correspond to the observed dynamic behavior. Thus, MOTID will provide a functional atlas that correlates cellular and fluid dynamics with molecular markers of cell state. As proof of principle applications upon which to validate the technology, we will examine dynamic behaviors in a mouse model of ischemia/reperfusion injury in the beating heart, and a genetically engineered model of malignant melanoma. To accomplish the successful development of MOTID, this project builds upon our team's expertise and extensive preliminary data in intravital microscopy, segmentation of single-cell dynamics within live tissues, interpretation of highly multiplexed data, and building integrated experimental/computational platforms for systems-level analysis.