Research Project
10276814
Project Summary/Abstract Living cells possess the remarkable ability to adapt to changes in their environmental conditions. Adaptation involves changes in cellular properties in response to external cues in order to regulate vital physiological functions and processes. While much progress has been made in identifying the molecular components and biochemical pathways underlying cellular stress response, the role of cellular physical properties in adaptive stress response is mostly unknown. Our recent studies provide evidence that changes in cell shape and cellular physical properties promotes adaptive benefits in certain stressful conditions via mechanochemical feedback processes. The goal of the proposed research is to develop quantitative theory and data-driven computational models to uncover the biophysical feedback mechanisms underlying cellular adaptive response to environmental stresses. We will utilize an interdisciplinary approach that integrates tools from statistical physics, systems biology, and experimental data analysis to construct predictive models for cell behavior. We will specifically investigate adaptive response in two different biological systems: 1) adaptation to nutrient shifts and antibiotic stresses in proliferating bacterial cells, and 2) adaptation to energy deprivation and cell state transitions in nematode worm embryos. In each of these systems we will develop quantitative cell-level models based on known molecular circuits, intracellular biophysical interactions and dynamics observed in experimental data. The models will be calibrated and tested against quantitative single-cell data obtained from our experimental collaborators. The resultant models will help test different experimental hypotheses, isolate and test the relative roles of biochemical and physical pathways in cellular adaptive response, and pinpoint the main driving forces behind complex adaptive phenomena. In addition to developing quantitative models for cellular biophysical behaviors, our study will generate a variety of computational tools that will enable efficient whole-cell simulations of bacterial growth, morphogenesis, intracellular organization and single-cell development.
