Dr. Ross P. Carlson (Dept. of Chemical and Biological Engineering, Center for Biofilm Engineering, MSU)

9/26/2024  3:10pm

Abstract: 

Systems biology techniques, such as flux balance analysis (FBA), are powerful tools for predicting principles of metabolism and cell design. These tools analyze in silico representations of cellular metabolism inferred from genome sequences, omics data sets, and culturing studies. Mass and energy balances are at the core of these metabolic models. The balances are formalized as sets of linear equations which define possible biochemical fluxes essential for life including cellular energy production and cell growth. The metabolic models are typically underdetermined so solutions of interest are identified using experiment-informed flux constraints and ecology-informed optimization criteria. A metabolic theory is presented here for predicting bacterial maximum growth rate, overflow metabolism, respiration efficiency, and maintenance energy flux based on the intersection of cell geometry, membrane protein crowding, and metabolism. The presented theory uses biophysical properties and metabolic systems analysis to successfully predict the phenotypes of E. coli K-12 strains, MG1655 and NCM3722, which are genetically similar but have surface area to volume ratios that differ up to 30%, maximum growth rates on glucose media that differ by 40%, and overflow phenotypes that start at growth rates that differ by 80%. Cell geometry and membrane protein crowding are significant biophysical constraints on phenotype and provide a theoretical framework for improved understanding and control of cell biology.