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Determining the Metabolic Footprints of Hydrocarbon Degradation Using Multivariate Analysis

The functional dynamics of microbial communities are largely responsible for the clean-up of hydrocarbons in the environment. However, knowledge of the distinguishing functional genes, known as the metabolic footprint, present in hydrocarbon-impacted sites is still scarcely understood. Here, we cond...

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Autores principales: Smith, Renee. J., Jeffries, Thomas C., Adetutu, Eric M., Fairweather, Peter G., Mitchell, James G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3839897/
https://www.ncbi.nlm.nih.gov/pubmed/24282619
http://dx.doi.org/10.1371/journal.pone.0081910
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author Smith, Renee. J.
Jeffries, Thomas C.
Adetutu, Eric M.
Fairweather, Peter G.
Mitchell, James G.
author_facet Smith, Renee. J.
Jeffries, Thomas C.
Adetutu, Eric M.
Fairweather, Peter G.
Mitchell, James G.
author_sort Smith, Renee. J.
collection PubMed
description The functional dynamics of microbial communities are largely responsible for the clean-up of hydrocarbons in the environment. However, knowledge of the distinguishing functional genes, known as the metabolic footprint, present in hydrocarbon-impacted sites is still scarcely understood. Here, we conducted several multivariate analyses to characterise the metabolic footprints present in a variety of hydrocarbon-impacted and non-impacted sediments. Non-metric multi-dimensional scaling (NMDS) and canonical analysis of principal coordinates (CAP) showed a clear distinction between the two groups. A high relative abundance of genes associated with cofactors, virulence, phages and fatty acids were present in the non-impacted sediments, accounting for 45.7 % of the overall dissimilarity. In the hydrocarbon-impacted sites, a high relative abundance of genes associated with iron acquisition and metabolism, dormancy and sporulation, motility, metabolism of aromatic compounds and cell signalling were observed, accounting for 22.3 % of the overall dissimilarity. These results suggest a major shift in functionality has occurred with pathways essential to the degradation of hydrocarbons becoming overrepresented at the expense of other, less essential metabolisms.
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spelling pubmed-38398972013-11-26 Determining the Metabolic Footprints of Hydrocarbon Degradation Using Multivariate Analysis Smith, Renee. J. Jeffries, Thomas C. Adetutu, Eric M. Fairweather, Peter G. Mitchell, James G. PLoS One Research Article The functional dynamics of microbial communities are largely responsible for the clean-up of hydrocarbons in the environment. However, knowledge of the distinguishing functional genes, known as the metabolic footprint, present in hydrocarbon-impacted sites is still scarcely understood. Here, we conducted several multivariate analyses to characterise the metabolic footprints present in a variety of hydrocarbon-impacted and non-impacted sediments. Non-metric multi-dimensional scaling (NMDS) and canonical analysis of principal coordinates (CAP) showed a clear distinction between the two groups. A high relative abundance of genes associated with cofactors, virulence, phages and fatty acids were present in the non-impacted sediments, accounting for 45.7 % of the overall dissimilarity. In the hydrocarbon-impacted sites, a high relative abundance of genes associated with iron acquisition and metabolism, dormancy and sporulation, motility, metabolism of aromatic compounds and cell signalling were observed, accounting for 22.3 % of the overall dissimilarity. These results suggest a major shift in functionality has occurred with pathways essential to the degradation of hydrocarbons becoming overrepresented at the expense of other, less essential metabolisms. Public Library of Science 2013-11-25 /pmc/articles/PMC3839897/ /pubmed/24282619 http://dx.doi.org/10.1371/journal.pone.0081910 Text en © 2013 Renee Smith http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Smith, Renee. J.
Jeffries, Thomas C.
Adetutu, Eric M.
Fairweather, Peter G.
Mitchell, James G.
Determining the Metabolic Footprints of Hydrocarbon Degradation Using Multivariate Analysis
title Determining the Metabolic Footprints of Hydrocarbon Degradation Using Multivariate Analysis
title_full Determining the Metabolic Footprints of Hydrocarbon Degradation Using Multivariate Analysis
title_fullStr Determining the Metabolic Footprints of Hydrocarbon Degradation Using Multivariate Analysis
title_full_unstemmed Determining the Metabolic Footprints of Hydrocarbon Degradation Using Multivariate Analysis
title_short Determining the Metabolic Footprints of Hydrocarbon Degradation Using Multivariate Analysis
title_sort determining the metabolic footprints of hydrocarbon degradation using multivariate analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3839897/
https://www.ncbi.nlm.nih.gov/pubmed/24282619
http://dx.doi.org/10.1371/journal.pone.0081910
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