Journal
ENVIRONMENTAL MICROBIOLOGY
Volume 22, Issue 1, Pages 255-269Publisher
WILEY
DOI: 10.1111/1462-2920.14843
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Funding
- European Union's Horizon 2020 Research and Innovation Programme [635536, 686585, 814650]
- Spanish Ministry of Economy and Competitiveness [BIO2014-59528-JIN, RTI-2018-094370-B-I00]
- National Science Foundation [1610400]
- Novo Nordisk Fonden [NNF10CC1016517]
- U.S. Department of Energy, Office of Science [DE-AC02-05CH11231]
- Division Of Graduate Education
- Direct For Education and Human Resources [1610400] Funding Source: National Science Foundation
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Genome-scale reconstructions of metabolism are computational species-specific knowledge bases able to compute systemic metabolic properties. We present a comprehensive and validated reconstruction of the biotechnologically relevant bacterium Pseudomonas putida KT2440 that greatly expands computable predictions of its metabolic states. The reconstruction represents a significant reactome expansion over available reconstructed bacterial metabolic networks. Specifically, iJN1462 (i) incorporates several hundred additional genes and associated reactions resulting in new predictive capabilities, including new nutrients supporting growth; (ii) was validated by in vivo growth screens that included previously untested carbon (48) and nitrogen (41) sources; (iii) yielded gene essentiality predictions showing large accuracy when compared with a knock-out library and Bar-seq data; and (iv) allowed mapping of its network to 82 P. putida sequenced strains revealing functional core that reflect the large metabolic versatility of this species, including aromatic compounds derived from lignin. Thus, this study provides a thoroughly updated metabolic reconstruction and new computable phenotypes for P. putida, which can be leveraged as a first step toward understanding the pan metabolic capabilities of Pseudomonas.
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