The RAVEN Toolbox and Its Use for Generating a Genome-scale Metabolic Model for Penicillium chrysogenum
Journal article, 2013

We present the RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox: a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology. The RAVEN Toolbox workflow was applied in order to reconstruct a genome-scale metabolic model for the important microbial cell factory Penicillium chrysogenum Wisconsin54-1255. The model was validated in a bibliomic study of in total 440 references, and it comprises 1471 unique biochemical reactions and 1006 ORFs. It was then used to study the roles of ATP and NADPH in the biosynthesis of penicillin, and to identify potential metabolic engineering targets for maximization of penicillin production.

Author

Rasmus Ågren

Chalmers, Chemical and Biological Engineering, Life Sciences

Liming Liu

Chalmers, Chemical and Biological Engineering, Life Sciences

Saeed Shoaie

Chalmers, Chemical and Biological Engineering, Life Sciences

Wanwipa Vongsangnak

Chalmers, Chemical and Biological Engineering, Life Sciences

Intawat Nookaew

Chalmers, Chemical and Biological Engineering, Life Sciences

Jens B Nielsen

Chalmers, Chemical and Biological Engineering, Life Sciences

PLoS Computational Biology

1553-734X (ISSN) 1553-7358 (eISSN)

Vol. 9 3 e1002980- e1002980

Industrial Systems Biology of Yeast and A. oryzae (INSYSBIO)

European Commission (EC) (EC/FP7/247013), 2010-01-01 -- 2014-12-31.

Areas of Advance

Information and Communication Technology

Life Science Engineering (2010-2018)

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

Subject Categories

Bioinformatics and Systems Biology

DOI

10.1371/journal.pcbi.1002980

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4/5/2022 6