UC San Diego

In mammalian systems, no cell acts in isolation, but rather coordinates to achieve higher-order function. Such cell behaviors are complex and influenced by context. To comprehensively understand them, we must understand how molecular interactions affect cell phenotypes, and analogously, how cell interactions affect higher-order phenotypes. I begin by examining the role of resource allocation in cellular decision-making processes. I underscore the significance of resource constraints and context in shaping cellular phenotypes and enabling population-level behaviors. My research then pivots to a detailed investigation into a rare systemic inflammatory disorder, Disabling Pansclerotic Morphea (DPM). I report on the discovery of novel variants in the STAT4 gene that are linked to DPM. Leveraging these insights, we propose a successful therapeutic approach using the JAK inhibitor, ruxolitinib, thereby demonstrating the importance of a context-informed genetic understanding in disease management. The JAK-STAT pathway is a key signaling pathway mediating immune cell communication. Thus, I shift the focus of my research to intercellular communication. My novel unsupervised method, Tensor-cell2cell, deciphers complex cell-cell communication patterns across multiple contexts (e.g., time points, disease severities, or spatial contexts). Given the generalizability of this approach to use other communication methods’ outputs as its input, I then introduce a protocol integrating two computational tools, LIANA and Tensor-cell2cell. LIANA is similarly generalizable in that it provides a centralized resource to run many methods, thus providing a natural preceding step to Tensor-cell2cell. The protocol enhances robustness and flexibility in identifying cell-cell communication programs across multiple samples. Finally, I present humanME, a computational tool for generating and analyzing human ME-Models from input metabolic models. This approach refines the prediction accuracy of growth rate and offers unique solutions, highlighting the importance of machinery resources in constraining intracellular activities. Collectively, this body of work leverages omics to provide mechanistic insights to how cellular context impacts interactions and functions in mammalian systems across molecular-, cell-, and tissue-scales. The new methods and tools proposed herein pave the way for more nuanced, context-driven research, underpinning future advancements in human health and disease.