Emergent Subpopulation Behavior Uncovered with a Community Dynamic Metabolic Model of Escherichia coli Diauxic Growth

Abstract

Escherichia coli diauxie is a fundamental example of metabolic adaptation, a phenomenon that is not yet completely understood. Further insight into this process can be achieved by integrating experimental and computational modeling methods. We present a dynamic metabolic modeling approach that captures diauxie as an emergent property of subpopulation dynamics in E. coli monocultures. Without fine-tuning the parameters of the E. coli core metabolic model, we achieved good agreement with published data. Our results suggest that single-organism metabolic models can only approximate the average metabolic state of a population, therefore offering a new perspective on the use of such modeling approaches. The open source modeling framework that we provide can be applied to model general subpopulation systems in more-complex environments and can be extended to include single-cell-level stochasticity.

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 26, 2019
Source ID
10.1128/msystems.00230-18

Entities

People

  • Antonella Succurro
  • Daniel Segrè
  • Oliver Ebenhöh

Organizations

  • Boston University
  • Cluster of Excellence on Plant Sciences
  • European Commission
  • German Research Foundation
  • Human Frontier Science Program
  • National Institutes of Health
  • National Science Foundation
  • United States Department of Defense
  • United States Department of Energy
  • University of Cologne
  • University of Düsseldorf

Tags

Fields of Study

  • Biology

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Modeling and Simulation
  • Microbial Pathology