Automated generation of bacterial resource allocation models

Resource Balance Analysis (RBA) is a computational method based on resource allocation, which performs accurate quantitative predictions of whole-cell states (i.e. growth rate, meta-bolic fluxes, abundances of molecular machines including enzymes) across growth conditions. We present an integrated w...

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Bibliographic Details
Published in:arXiv.org 2019-06
Main Authors: Bulović, Ana, Fischer, Stephan, Dinh, Marc, Golib, Felipe, Liebermeister, Wolfram, Poirier, Christian, Tournier, Laurent, Klipp, Edda, Fromion, Vincent, Goelzer, Anne
Format: Article
Language:English
Subjects:
Bacteria
Computer simulation
E coli
Fluxes
Molecular machines
Resource allocation
Workflow
Online Access:Get full text
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Summary:Resource Balance Analysis (RBA) is a computational method based on resource allocation, which performs accurate quantitative predictions of whole-cell states (i.e. growth rate, meta-bolic fluxes, abundances of molecular machines including enzymes) across growth conditions. We present an integrated workflow of RBA together with the Python package RBApy. RBApy builds bacterial RBA models from annotated genome-scale metabolic models by add-ing descriptions of cellular processes relevant for growth and maintenance. The package in-cludes functions for model simulation and calibration and for interfacing to Escher maps and Proteomaps for visualization. We demonstrate that RBApy faithfully reproduces results ob-tained by a hand-curated and experimentally validated RBA model for Bacillus subtilis. We also present a calibrated RBA model of Escherichia coli generated from scratch, which ob-tained excellent fits to measured flux values and enzyme abundances. RBApy makes whole-cell modeling accessible for a wide range of bacterial wild-type and engineered strains, as il-lustrated with a CO2-fixing Escherichia coli strain.
ISSN:2331-8422
DOI:10.48550/arxiv.1906.04525