Literature DB >> 24777662

Identification of potential drug targets in Salmonella enterica sv. Typhimurium using metabolic modelling and experimental validation.

Hassan B Hartman1, David A Fell1, Sergio Rossell2, Peter Ruhdal Jensen2, Martin J Woodward3, Lotte Thorndahl4, Lotte Jelsbak4, John Elmerdahl Olsen4, Anu Raghunathan5, Simon Daefler5, Mark G Poolman1.   

Abstract

Salmonella enterica sv. Typhimurium is an established model organism for Gram-negative, intracellular pathogens. Owing to the rapid spread of resistance to antibiotics among this group of pathogens, new approaches to identify suitable target proteins are required. Based on the genome sequence of S. Typhimurium and associated databases, a genome-scale metabolic model was constructed. Output was based on an experimental determination of the biomass of Salmonella when growing in glucose minimal medium. Linear programming was used to simulate variations in the energy demand while growing in glucose minimal medium. By grouping reactions with similar flux responses, a subnetwork of 34 reactions responding to this variation was identified (the catabolic core). This network was used to identify sets of one and two reactions that when removed from the genome-scale model interfered with energy and biomass generation. Eleven such sets were found to be essential for the production of biomass precursors. Experimental investigation of seven of these showed that knockouts of the associated genes resulted in attenuated growth for four pairs of reactions, whilst three single reactions were shown to be essential for growth.
© 2014 The Authors.

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Year:  2014        PMID: 24777662     DOI: 10.1099/mic.0.076091-0

Source DB:  PubMed          Journal:  Microbiology        ISSN: 1350-0872            Impact factor:   2.777


  12 in total

1.  Identification of common highly expressed genes of Salmonella Enteritidis by in silico prediction of gene expression and in vitro transcriptomic analysis.

Authors:  Kim Lam R Chiok; Devendra H Shah
Journal:  Poult Sci       Date:  2019-07-01       Impact factor: 3.352

2.  A genome-scale metabolic model of Cupriavidus necator H16 integrated with TraDIS and transcriptomic data reveals metabolic insights for biotechnological applications.

Authors:  Nicole Pearcy; Marco Garavaglia; Thomas Millat; James P Gilbert; Yoseb Song; Hassan Hartman; Craig Woods; Claudio Tomi-Andrino; Rajesh Reddy Bommareddy; Byung-Kwan Cho; David A Fell; Mark Poolman; John R King; Klaus Winzer; Jamie Twycross; Nigel P Minton
Journal:  PLoS Comput Biol       Date:  2022-05-23       Impact factor: 4.779

3.  The In Vitro Redundant Enzymes PurN and PurT Are Both Essential for Systemic Infection of Mice in Salmonella enterica Serovar Typhimurium.

Authors:  Lotte Jelsbak; Mie I B Mortensen; Mogens Kilstrup; John E Olsen
Journal:  Infect Immun       Date:  2016-06-23       Impact factor: 3.441

4.  Characterization and prediction of the mechanism of action of antibiotics through NMR metabolomics.

Authors:  Verena Hoerr; Gavin E Duggan; Lori Zbytnuik; Karen K H Poon; Christina Große; Ute Neugebauer; Karen Methling; Bettina Löffler; Hans J Vogel
Journal:  BMC Microbiol       Date:  2016-05-10       Impact factor: 3.605

5.  MCS2: minimal coordinated supports for fast enumeration of minimal cut sets in metabolic networks.

Authors:  Reza Miraskarshahi; Hooman Zabeti; Tamon Stephen; Leonid Chindelevitch
Journal:  Bioinformatics       Date:  2019-07-15       Impact factor: 6.937

6.  Thymol tolerance in Escherichia coli induces morphological, metabolic and genetic changes.

Authors:  Fatemah Al-Kandari; Rabeah Al-Temaimi; Arnoud H M van Vliet; Martin J Woodward
Journal:  BMC Microbiol       Date:  2019-12-16       Impact factor: 3.605

7.  Genome-Scale Metabolic Modelling Approach to Understand the Metabolism of the Opportunistic Human Pathogen Staphylococcus epidermidis RP62A.

Authors:  Teresa Díaz Calvo; Noemi Tejera; Iain McNamara; Gemma C Langridge; John Wain; Mark Poolman; Dipali Singh
Journal:  Metabolites       Date:  2022-02-02

8.  Genome-wide characterization of Phytophthora infestans metabolism: a systems biology approach.

Authors:  Sander Y A Rodenburg; Michael F Seidl; Dick de Ridder; Francine Govers
Journal:  Mol Plant Pathol       Date:  2018-01-30       Impact factor: 5.663

9.  A Genome-Scale Metabolic Model of Thalassiosira pseudonana CCMP 1335 for a Systems-Level Understanding of Its Metabolism and Biotechnological Potential.

Authors:  Ahmad Ahmad; Archana Tiwari; Shireesh Srivastava
Journal:  Microorganisms       Date:  2020-09-11

Review 10.  Antibiotic resistance: Time of synthesis in a post-genomic age.

Authors:  Teresa Gil-Gil; Luz Edith Ochoa-Sánchez; Fernando Baquero; José Luis Martínez
Journal:  Comput Struct Biotechnol J       Date:  2021-05-21       Impact factor: 7.271

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