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Title: High‐quality genome‐scale metabolic modelling of Pseudomonas putida highlights its broad metabolic capabilities

Abstract

Summary 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, i JN1462 (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 .

Authors:
ORCiD logo [1];  [2];  [3];  [4];  [5];  [6];  [6]; ORCiD logo [5];  [7];  [6]
  1. Department of Systems Biology Centro Nacional de Biotecnología (CNB‐CSIC) Madrid Spain, Department of Bioengineering University of California, San Diego La Jolla CA USA
  2. Department of Bioengineering University of California, San Diego La Jolla CA USA, Department of Chemical and Biomolecular Engineering University of Nebraska‐Lincoln Lincoln NE USA
  3. Center for Systems Biology, University of Iceland Reykjavík Iceland
  4. Department of Systems Biology Centro Nacional de Biotecnología (CNB‐CSIC) Madrid Spain
  5. Department of Environmental Protection Estación Experimental del Zaidín (CSIC) Granada Spain
  6. Department of Bioengineering University of California, San Diego La Jolla CA USA
  7. Department of Chemical and Biomolecular Engineering University of Nebraska‐Lincoln Lincoln NE USA
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1574030
Alternate Identifier(s):
OSTI ID: 1574031; OSTI ID: 1625852
Grant/Contract Number:  
DE‐AC02‐05CH11231; AC02-05CH11231
Resource Type:
Journal Article: Published Article
Journal Name:
Environmental Microbiology
Additional Journal Information:
Journal Name: Environmental Microbiology Journal Volume: 22 Journal Issue: 1; Journal ID: ISSN 1462-2912
Publisher:
Wiley-Blackwell
Country of Publication:
United Kingdom
Language:
English
Subject:
Microbiology

Citation Formats

Nogales, Juan, Mueller, Joshua, Gudmundsson, Steinn, Canalejo, Francisco J., Duque, Estrella, Monk, Jonathan, Feist, Adam M., Ramos, Juan Luis, Niu, Wei, and Palsson, Bernhard O. High‐quality genome‐scale metabolic modelling of Pseudomonas putida highlights its broad metabolic capabilities. United Kingdom: N. p., 2019. Web. doi:10.1111/1462-2920.14843.
Nogales, Juan, Mueller, Joshua, Gudmundsson, Steinn, Canalejo, Francisco J., Duque, Estrella, Monk, Jonathan, Feist, Adam M., Ramos, Juan Luis, Niu, Wei, & Palsson, Bernhard O. High‐quality genome‐scale metabolic modelling of Pseudomonas putida highlights its broad metabolic capabilities. United Kingdom. https://doi.org/10.1111/1462-2920.14843
Nogales, Juan, Mueller, Joshua, Gudmundsson, Steinn, Canalejo, Francisco J., Duque, Estrella, Monk, Jonathan, Feist, Adam M., Ramos, Juan Luis, Niu, Wei, and Palsson, Bernhard O. 2019. "High‐quality genome‐scale metabolic modelling of Pseudomonas putida highlights its broad metabolic capabilities". United Kingdom. https://doi.org/10.1111/1462-2920.14843.
@article{osti_1574030,
title = {High‐quality genome‐scale metabolic modelling of Pseudomonas putida highlights its broad metabolic capabilities},
author = {Nogales, Juan and Mueller, Joshua and Gudmundsson, Steinn and Canalejo, Francisco J. and Duque, Estrella and Monk, Jonathan and Feist, Adam M. and Ramos, Juan Luis and Niu, Wei and Palsson, Bernhard O.},
abstractNote = {Summary 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, i JN1462 (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 .},
doi = {10.1111/1462-2920.14843},
url = {https://www.osti.gov/biblio/1574030}, journal = {Environmental Microbiology},
issn = {1462-2912},
number = 1,
volume = 22,
place = {United Kingdom},
year = {Mon Nov 11 00:00:00 EST 2019},
month = {Mon Nov 11 00:00:00 EST 2019}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record at https://doi.org/10.1111/1462-2920.14843

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Cited by: 71 works
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