Biophysical models and mechanisms for cellular adaptation to environmental stress

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.

Grant Number: 5R35GM143042-06
NIH Institute/Center: NIH
Principal Investigator: Shiladitya Banerjee