NetMet: A Network-Based Tool for Predicting Metabolic Capacities of Microbial Species and their Interactions.
Metabolic networks
environment
expansion algorithm
genomics
microbial interactions
network modeling
simulation
Journal
Microorganisms
ISSN: 2076-2607
Titre abrégé: Microorganisms
Pays: Switzerland
ID NLM: 101625893
Informations de publication
Date de publication:
03 Jun 2020
03 Jun 2020
Historique:
received:
11
05
2020
revised:
01
06
2020
accepted:
02
06
2020
entrez:
7
6
2020
pubmed:
7
6
2020
medline:
7
6
2020
Statut:
epublish
Résumé
Metabolic conversions allow organisms to produce a set of essential metabolites from the available nutrients in an environment, frequently requiring metabolic exchanges among co-inhabiting organisms. Genomic-based metabolic simulations are being increasingly applied for exploring metabolic capacities, considering different environments and different combinations of microorganisms. NetMet is a web-based tool and a software package for predicting the metabolic performances of microorganisms and their corresponding combinations in user-defined environments. The algorithm takes, as input, lists of (i) species-specific enzymatic reactions (EC numbers), and (ii) relevant metabolic environments. The algorithm generates, as output, lists of (i) compounds that individual species can produce in each given environment, and (ii) compounds that are predicted to be produced through complementary interactions. The tool is demonstrated in two case studies. First, we compared the metabolic capacities of different haplotypes of the obligatory fruit and vegetable pathogen
Identifiants
pubmed: 32503277
pii: microorganisms8060840
doi: 10.3390/microorganisms8060840
pmc: PMC7356744
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : Israel Science Foundation
ID : 484/17
Organisme : Centre National pour la Recherche Scientifique et Technique
ID : N/A
Déclaration de conflit d'intérêts
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
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