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A Peptide-Based Method for (13)C Metabolic Flux Analysis in Microbial Communities

The study of intracellular metabolic fluxes and inter-species metabolite exchange for microbial communities is of crucial importance to understand and predict their behaviour. The most authoritative method of measuring intracellular fluxes, (13)C Metabolic Flux Analysis ((13)C MFA), uses the labelin...

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Autores principales: Ghosh, Amit, Nilmeier, Jerome, Weaver, Daniel, Adams, Paul D., Keasling, Jay D., Mukhopadhyay, Aindrila, Petzold, Christopher J., Martín, Héctor García
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4154649/
https://www.ncbi.nlm.nih.gov/pubmed/25188426
http://dx.doi.org/10.1371/journal.pcbi.1003827
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author Ghosh, Amit
Nilmeier, Jerome
Weaver, Daniel
Adams, Paul D.
Keasling, Jay D.
Mukhopadhyay, Aindrila
Petzold, Christopher J.
Martín, Héctor García
author_facet Ghosh, Amit
Nilmeier, Jerome
Weaver, Daniel
Adams, Paul D.
Keasling, Jay D.
Mukhopadhyay, Aindrila
Petzold, Christopher J.
Martín, Héctor García
author_sort Ghosh, Amit
collection PubMed
description The study of intracellular metabolic fluxes and inter-species metabolite exchange for microbial communities is of crucial importance to understand and predict their behaviour. The most authoritative method of measuring intracellular fluxes, (13)C Metabolic Flux Analysis ((13)C MFA), uses the labeling pattern obtained from metabolites (typically amino acids) during (13)C labeling experiments to derive intracellular fluxes. However, these metabolite labeling patterns cannot easily be obtained for each of the members of the community. Here we propose a new type of (13)C MFA that infers fluxes based on peptide labeling, instead of amino acid labeling. The advantage of this method resides in the fact that the peptide sequence can be used to identify the microbial species it originates from and, simultaneously, the peptide labeling can be used to infer intracellular metabolic fluxes. Peptide identity and labeling patterns can be obtained in a high-throughput manner from modern proteomics techniques. We show that, using this method, it is theoretically possible to recover intracellular metabolic fluxes in the same way as through the standard amino acid based (13)C MFA, and quantify the amount of information lost as a consequence of using peptides instead of amino acids. We show that by using a relatively small number of peptides we can counter this information loss. We computationally tested this method with a well-characterized simple microbial community consisting of two species.
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spelling pubmed-41546492014-09-08 A Peptide-Based Method for (13)C Metabolic Flux Analysis in Microbial Communities Ghosh, Amit Nilmeier, Jerome Weaver, Daniel Adams, Paul D. Keasling, Jay D. Mukhopadhyay, Aindrila Petzold, Christopher J. Martín, Héctor García PLoS Comput Biol Research Article The study of intracellular metabolic fluxes and inter-species metabolite exchange for microbial communities is of crucial importance to understand and predict their behaviour. The most authoritative method of measuring intracellular fluxes, (13)C Metabolic Flux Analysis ((13)C MFA), uses the labeling pattern obtained from metabolites (typically amino acids) during (13)C labeling experiments to derive intracellular fluxes. However, these metabolite labeling patterns cannot easily be obtained for each of the members of the community. Here we propose a new type of (13)C MFA that infers fluxes based on peptide labeling, instead of amino acid labeling. The advantage of this method resides in the fact that the peptide sequence can be used to identify the microbial species it originates from and, simultaneously, the peptide labeling can be used to infer intracellular metabolic fluxes. Peptide identity and labeling patterns can be obtained in a high-throughput manner from modern proteomics techniques. We show that, using this method, it is theoretically possible to recover intracellular metabolic fluxes in the same way as through the standard amino acid based (13)C MFA, and quantify the amount of information lost as a consequence of using peptides instead of amino acids. We show that by using a relatively small number of peptides we can counter this information loss. We computationally tested this method with a well-characterized simple microbial community consisting of two species. Public Library of Science 2014-09-04 /pmc/articles/PMC4154649/ /pubmed/25188426 http://dx.doi.org/10.1371/journal.pcbi.1003827 Text en © 2014 Ghosh et al 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
Ghosh, Amit
Nilmeier, Jerome
Weaver, Daniel
Adams, Paul D.
Keasling, Jay D.
Mukhopadhyay, Aindrila
Petzold, Christopher J.
Martín, Héctor García
A Peptide-Based Method for (13)C Metabolic Flux Analysis in Microbial Communities
title A Peptide-Based Method for (13)C Metabolic Flux Analysis in Microbial Communities
title_full A Peptide-Based Method for (13)C Metabolic Flux Analysis in Microbial Communities
title_fullStr A Peptide-Based Method for (13)C Metabolic Flux Analysis in Microbial Communities
title_full_unstemmed A Peptide-Based Method for (13)C Metabolic Flux Analysis in Microbial Communities
title_short A Peptide-Based Method for (13)C Metabolic Flux Analysis in Microbial Communities
title_sort peptide-based method for (13)c metabolic flux analysis in microbial communities
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4154649/
https://www.ncbi.nlm.nih.gov/pubmed/25188426
http://dx.doi.org/10.1371/journal.pcbi.1003827
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