Heterogenity in Protein Copy Numbers induces Metabolic Variability in Modeled E. coli Populations

Abstract

Heterogeneity in isogenic population of bacteria arises due to inherent stochasticity in the process of gene expression as well as local environmental fluctuations. Advances in quantitative fluorescence imaging of Escherichia coli has enumerated such heterogeneity in terms of protein copy numbers at genome scale.In this study we use genome scale model of metabolism for Ecoli to investigate the effect of this variability on their growth rates and metabolic pathway usage. Results suggest wide variation in growth rate of single cells around the bulk measurement obtained via optical density measurements. This prediction is in agreement with the variation in growth rates measured experimentally at single cell level. We also predict variability in metabolic pathway usage among these cells owing to tradeoffs between energy efficiency and enzyme usage efficiency. All the variability in metabolism can be attributed to variability in expression of few genes. This integration of a metabolic model, which is a bottom up reconstruction from the genome, with single cell proteomics data gives us new insight into the effect of noise on the physiology of cell populations.