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Streamlined identification of strain engineering targets for bioprocess improvement using metabolic pathway enrichment analysis

Metabolomics is a powerful tool for the identification of genetic targets for bioprocess optimisation. However, in most cases, only the biosynthetic pathway directed to product formation is analysed, limiting the identification of these targets. Some studies have used untargeted metabolomics, allowi...

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Autores principales: Cortada-Garcia, Joan, Daly, Rónán, Arnold, S. Alison, Burgess, Karl
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415327/
https://www.ncbi.nlm.nih.gov/pubmed/37563133
http://dx.doi.org/10.1038/s41598-023-39661-x
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author Cortada-Garcia, Joan
Daly, Rónán
Arnold, S. Alison
Burgess, Karl
author_facet Cortada-Garcia, Joan
Daly, Rónán
Arnold, S. Alison
Burgess, Karl
author_sort Cortada-Garcia, Joan
collection PubMed
description Metabolomics is a powerful tool for the identification of genetic targets for bioprocess optimisation. However, in most cases, only the biosynthetic pathway directed to product formation is analysed, limiting the identification of these targets. Some studies have used untargeted metabolomics, allowing a more unbiased approach, but data interpretation using multivariate analysis is usually not straightforward and requires time and effort. Here we show, for the first time, the application of metabolic pathway enrichment analysis using untargeted and targeted metabolomics data to identify genetic targets for bioprocess improvement in a more streamlined way. The analysis of an Escherichia coli succinate production bioprocess with this methodology revealed three significantly modulated pathways during the product formation phase: the pentose phosphate pathway, pantothenate and CoA biosynthesis and ascorbate and aldarate metabolism. From these, the two former pathways are consistent with previous efforts to improve succinate production in Escherichia coli. Furthermore, to the best of our knowledge, ascorbate and aldarate metabolism is a newly identified target that has so far never been explored for improving succinate production in this microorganism. This methodology therefore represents a powerful tool for the streamlined identification of strain engineering targets that can accelerate bioprocess optimisation.
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spelling pubmed-104153272023-08-12 Streamlined identification of strain engineering targets for bioprocess improvement using metabolic pathway enrichment analysis Cortada-Garcia, Joan Daly, Rónán Arnold, S. Alison Burgess, Karl Sci Rep Article Metabolomics is a powerful tool for the identification of genetic targets for bioprocess optimisation. However, in most cases, only the biosynthetic pathway directed to product formation is analysed, limiting the identification of these targets. Some studies have used untargeted metabolomics, allowing a more unbiased approach, but data interpretation using multivariate analysis is usually not straightforward and requires time and effort. Here we show, for the first time, the application of metabolic pathway enrichment analysis using untargeted and targeted metabolomics data to identify genetic targets for bioprocess improvement in a more streamlined way. The analysis of an Escherichia coli succinate production bioprocess with this methodology revealed three significantly modulated pathways during the product formation phase: the pentose phosphate pathway, pantothenate and CoA biosynthesis and ascorbate and aldarate metabolism. From these, the two former pathways are consistent with previous efforts to improve succinate production in Escherichia coli. Furthermore, to the best of our knowledge, ascorbate and aldarate metabolism is a newly identified target that has so far never been explored for improving succinate production in this microorganism. This methodology therefore represents a powerful tool for the streamlined identification of strain engineering targets that can accelerate bioprocess optimisation. Nature Publishing Group UK 2023-08-10 /pmc/articles/PMC10415327/ /pubmed/37563133 http://dx.doi.org/10.1038/s41598-023-39661-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Cortada-Garcia, Joan
Daly, Rónán
Arnold, S. Alison
Burgess, Karl
Streamlined identification of strain engineering targets for bioprocess improvement using metabolic pathway enrichment analysis
title Streamlined identification of strain engineering targets for bioprocess improvement using metabolic pathway enrichment analysis
title_full Streamlined identification of strain engineering targets for bioprocess improvement using metabolic pathway enrichment analysis
title_fullStr Streamlined identification of strain engineering targets for bioprocess improvement using metabolic pathway enrichment analysis
title_full_unstemmed Streamlined identification of strain engineering targets for bioprocess improvement using metabolic pathway enrichment analysis
title_short Streamlined identification of strain engineering targets for bioprocess improvement using metabolic pathway enrichment analysis
title_sort streamlined identification of strain engineering targets for bioprocess improvement using metabolic pathway enrichment analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10415327/
https://www.ncbi.nlm.nih.gov/pubmed/37563133
http://dx.doi.org/10.1038/s41598-023-39661-x
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