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Deciphering the metabolic capabilities of Bifidobacteria using genome-scale metabolic models
Bifidobacteria, the initial colonisers of breastfed infant guts, are considered as the key commensals that promote a healthy gastrointestinal tract. However, little is known about the key metabolic differences between different strains of these bifidobacteria, and consequently, their suitability for...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6890778/ https://www.ncbi.nlm.nih.gov/pubmed/31796826 http://dx.doi.org/10.1038/s41598-019-54696-9 |
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author | Devika, N. T. Raman, Karthik |
author_facet | Devika, N. T. Raman, Karthik |
author_sort | Devika, N. T. |
collection | PubMed |
description | Bifidobacteria, the initial colonisers of breastfed infant guts, are considered as the key commensals that promote a healthy gastrointestinal tract. However, little is known about the key metabolic differences between different strains of these bifidobacteria, and consequently, their suitability for their varied commercial applications. In this context, the present study applies a constraint-based modelling approach to differentiate between 36 important bifidobacterial strains, enhancing their genome-scale metabolic models obtained from the AGORA (Assembly of Gut Organisms through Reconstruction and Analysis) resource. By studying various growth and metabolic capabilities in these enhanced genome-scale models across 30 different nutrient environments, we classified the bifidobacteria into three specific groups. We also studied the ability of the different strains to produce short-chain fatty acids, finding that acetate production is niche- and strain-specific, unlike lactate. Further, we captured the role of critical enzymes from the bifid shunt pathway, which was found to be essential for a subset of bifidobacterial strains. Our findings underline the significance of analysing metabolic capabilities as a powerful approach to explore distinct properties of the gut microbiome. Overall, our study presents several insights into the nutritional lifestyles of bifidobacteria and could potentially be leveraged to design species/strain-specific probiotics or prebiotics. |
format | Online Article Text |
id | pubmed-6890778 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-68907782019-12-10 Deciphering the metabolic capabilities of Bifidobacteria using genome-scale metabolic models Devika, N. T. Raman, Karthik Sci Rep Article Bifidobacteria, the initial colonisers of breastfed infant guts, are considered as the key commensals that promote a healthy gastrointestinal tract. However, little is known about the key metabolic differences between different strains of these bifidobacteria, and consequently, their suitability for their varied commercial applications. In this context, the present study applies a constraint-based modelling approach to differentiate between 36 important bifidobacterial strains, enhancing their genome-scale metabolic models obtained from the AGORA (Assembly of Gut Organisms through Reconstruction and Analysis) resource. By studying various growth and metabolic capabilities in these enhanced genome-scale models across 30 different nutrient environments, we classified the bifidobacteria into three specific groups. We also studied the ability of the different strains to produce short-chain fatty acids, finding that acetate production is niche- and strain-specific, unlike lactate. Further, we captured the role of critical enzymes from the bifid shunt pathway, which was found to be essential for a subset of bifidobacterial strains. Our findings underline the significance of analysing metabolic capabilities as a powerful approach to explore distinct properties of the gut microbiome. Overall, our study presents several insights into the nutritional lifestyles of bifidobacteria and could potentially be leveraged to design species/strain-specific probiotics or prebiotics. Nature Publishing Group UK 2019-12-03 /pmc/articles/PMC6890778/ /pubmed/31796826 http://dx.doi.org/10.1038/s41598-019-54696-9 Text en © The Author(s) 2019 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Devika, N. T. Raman, Karthik Deciphering the metabolic capabilities of Bifidobacteria using genome-scale metabolic models |
title | Deciphering the metabolic capabilities of Bifidobacteria using genome-scale metabolic models |
title_full | Deciphering the metabolic capabilities of Bifidobacteria using genome-scale metabolic models |
title_fullStr | Deciphering the metabolic capabilities of Bifidobacteria using genome-scale metabolic models |
title_full_unstemmed | Deciphering the metabolic capabilities of Bifidobacteria using genome-scale metabolic models |
title_short | Deciphering the metabolic capabilities of Bifidobacteria using genome-scale metabolic models |
title_sort | deciphering the metabolic capabilities of bifidobacteria using genome-scale metabolic models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6890778/ https://www.ncbi.nlm.nih.gov/pubmed/31796826 http://dx.doi.org/10.1038/s41598-019-54696-9 |
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