Generation of an atlas for commodity chemical production in Escherichia coli and a novel pathway prediction algorithm, GEM-Path

Miguel A. Campodonico, Barbara A. Andrews, Juan A. Asenjo, Bernhard Palsson, Adam Feist

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

The production of 75% of the current drug molecules and 35% of all chemicals could be achieved through bioprocessing (Arundel and Sawava, 2009). To accelerate the transition from a petroleum based chemical industry to a sustainable bio-based industry, systems metabolic engineering has emerged to computationally design metabolic pathways for chemical production. Although algorithms able to provide specific metabolic interventions and heterologous production pathways are available, a systematic analysis for all possible production routes to commodity chemicals in Escherichia call is lacking. Furthermore, a pathway prediction algorithm that combines direct integration of genome-scale models at each step of the search to reduce the search space does not exist. Previous work (Feist. el. al., 2010) performed a model driven evaluation of the growth coupled production potential for E. call to produce multiple native compounds from different feedstocks. In this study, we extended this analysis for non-native compounds by using an integrated approach through heterologous pathway integration and growth coupled metabolite production design. In addition to integration with genome-scale model integration, the GEM Path algorithm developed in this work also contains a novel approach to address reaction promiscuity. In total, 245 unique synthetic pathways for 20 large volume compounds were predicted. Host metabolism with these synthetic pathways was then analyzed for feasible growth-coupled production and designs could be identified for 1271 of the 6615 conditions evaluated. This study characterizes the potential for E coli to produce commodity chemicals, and outlines a generic strain design workflow to design production strains. (C) 2014 international Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.
Original languageEnglish
JournalMetabolic Engineering
Volume25
Pages (from-to)140-158
Number of pages19
ISSN1096-7176
DOIs
Publication statusPublished - 2014

Keywords

  • atlas
  • Facultatively Anaerobic Gram-Negative Rods Eubacteria Bacteria Microorganisms (Bacteria, Eubacteria, Microorganisms) - Enterobacteriaceae [06702] Escherichia coli species
  • 04500, Mathematical biology and statistical methods
  • 10515, Biophysics - Biocybernetics
  • 31000, Physiology and biochemistry of bacteria
  • 39008, Food microbiology - General and miscellaneous
  • Computational Biology
  • GEM-Path algorithm mathematical and computer techniques
  • metabolic engineering laboratory techniques
  • Bioprocess Engineering
  • Models and Simulations
  • BIOTECHNOLOGY
  • COMPLEX METABOLIC NETWORKS
  • CONSTRAINT-BASED MODELS
  • MICROBIAL-PRODUCTION
  • 2,3-BUTANEDIOL PRODUCTION
  • BIODIESEL PRODUCTION
  • BIOFUELS PRODUCTION
  • ADAPTIVE EVOLUTION
  • FLUX ANALYSIS
  • K-12 MG1655
  • SYSTEMS
  • Systems biology
  • Pathway predictions
  • Escherichia coli
  • Strain design

Cite this