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Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™
Ultra-high performance liquid chromatography–high-resolution mass spectrometry (UPHLC–HRMS) is used to discover and monitor single or sets of biomarkers informing about metabolic processes of interest. The technique can detect 1000’s of molecules (i.e., metabolites) in a single instrument run and pr...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9641191/ https://www.ncbi.nlm.nih.gov/pubmed/36386687 http://dx.doi.org/10.3389/fmicb.2022.981994 |
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author | May, Amanda L. Xie, Yongchao Kara Murdoch, Fadime Michalsen, Mandy M. Löffler, Frank E. Campagna, Shawn R. |
author_facet | May, Amanda L. Xie, Yongchao Kara Murdoch, Fadime Michalsen, Mandy M. Löffler, Frank E. Campagna, Shawn R. |
author_sort | May, Amanda L. |
collection | PubMed |
description | Ultra-high performance liquid chromatography–high-resolution mass spectrometry (UPHLC–HRMS) is used to discover and monitor single or sets of biomarkers informing about metabolic processes of interest. The technique can detect 1000’s of molecules (i.e., metabolites) in a single instrument run and provide a measurement of the global metabolome, which could be a fingerprint of activity. Despite the power of this approach, technical challenges have hindered the effective use of metabolomics to interrogate microbial communities implicated in the removal of priority contaminants. Herein, our efforts to circumvent these challenges and apply this emerging systems biology technique to microbiomes relevant for contaminant biodegradation will be discussed. Chlorinated ethenes impact many contaminated sites, and detoxification can be achieved by organohalide-respiring bacteria, a process currently assessed by quantitative gene-centric tools (e.g., quantitative PCR). This laboratory study monitored the metabolome of the SDC-9™ bioaugmentation consortium during cis-1,2-dichloroethene (cDCE) conversion to vinyl chloride (VC) and nontoxic ethene. Untargeted metabolomics using an UHPLC-Orbitrap mass spectrometer and performed on SDC-9™ cultures at different stages of the reductive dechlorination process detected ~10,000 spectral features per sample arising from water-soluble molecules with both known and unknown structures. Multivariate statistical techniques including partial least squares-discriminate analysis (PLSDA) identified patterns of measurable spectral features (peak patterns) that correlated with dechlorination (in)activity, and ANOVA analyses identified 18 potential biomarkers for this process. Statistical clustering of samples with these 18 features identified dechlorination activity more reliably than clustering of samples based only on chlorinated ethene concentration and Dhc 16S rRNA gene abundance data, highlighting the potential value of metabolomic workflows as an innovative site assessment and bioremediation monitoring tool. |
format | Online Article Text |
id | pubmed-9641191 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96411912022-11-15 Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™ May, Amanda L. Xie, Yongchao Kara Murdoch, Fadime Michalsen, Mandy M. Löffler, Frank E. Campagna, Shawn R. Front Microbiol Microbiology Ultra-high performance liquid chromatography–high-resolution mass spectrometry (UPHLC–HRMS) is used to discover and monitor single or sets of biomarkers informing about metabolic processes of interest. The technique can detect 1000’s of molecules (i.e., metabolites) in a single instrument run and provide a measurement of the global metabolome, which could be a fingerprint of activity. Despite the power of this approach, technical challenges have hindered the effective use of metabolomics to interrogate microbial communities implicated in the removal of priority contaminants. Herein, our efforts to circumvent these challenges and apply this emerging systems biology technique to microbiomes relevant for contaminant biodegradation will be discussed. Chlorinated ethenes impact many contaminated sites, and detoxification can be achieved by organohalide-respiring bacteria, a process currently assessed by quantitative gene-centric tools (e.g., quantitative PCR). This laboratory study monitored the metabolome of the SDC-9™ bioaugmentation consortium during cis-1,2-dichloroethene (cDCE) conversion to vinyl chloride (VC) and nontoxic ethene. Untargeted metabolomics using an UHPLC-Orbitrap mass spectrometer and performed on SDC-9™ cultures at different stages of the reductive dechlorination process detected ~10,000 spectral features per sample arising from water-soluble molecules with both known and unknown structures. Multivariate statistical techniques including partial least squares-discriminate analysis (PLSDA) identified patterns of measurable spectral features (peak patterns) that correlated with dechlorination (in)activity, and ANOVA analyses identified 18 potential biomarkers for this process. Statistical clustering of samples with these 18 features identified dechlorination activity more reliably than clustering of samples based only on chlorinated ethene concentration and Dhc 16S rRNA gene abundance data, highlighting the potential value of metabolomic workflows as an innovative site assessment and bioremediation monitoring tool. Frontiers Media S.A. 2022-10-25 /pmc/articles/PMC9641191/ /pubmed/36386687 http://dx.doi.org/10.3389/fmicb.2022.981994 Text en Copyright © 2022 May, Xie, Kara Murdoch, Michalsen, Löffler and Campagna. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Microbiology May, Amanda L. Xie, Yongchao Kara Murdoch, Fadime Michalsen, Mandy M. Löffler, Frank E. Campagna, Shawn R. Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™ |
title | Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™ |
title_full | Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™ |
title_fullStr | Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™ |
title_full_unstemmed | Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™ |
title_short | Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™ |
title_sort | metabolome patterns identify active dechlorination in bioaugmentation consortium sdc-9™ |
topic | Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9641191/ https://www.ncbi.nlm.nih.gov/pubmed/36386687 http://dx.doi.org/10.3389/fmicb.2022.981994 |
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