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Modelling microbial communities: Harnessing consortia for biotechnological applications
Microbes propagate and thrive in complex communities, and there are many benefits to studying and engineering microbial communities instead of single strains. Microbial communities are being increasingly leveraged in biotechnological applications, as they present significant advantages such as the d...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8441623/ https://www.ncbi.nlm.nih.gov/pubmed/34584635 http://dx.doi.org/10.1016/j.csbj.2021.06.048 |
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author | Ibrahim, Maziya Raajaraam, Lavanya Raman, Karthik |
author_facet | Ibrahim, Maziya Raajaraam, Lavanya Raman, Karthik |
author_sort | Ibrahim, Maziya |
collection | PubMed |
description | Microbes propagate and thrive in complex communities, and there are many benefits to studying and engineering microbial communities instead of single strains. Microbial communities are being increasingly leveraged in biotechnological applications, as they present significant advantages such as the division of labour and improved substrate utilisation. Nevertheless, they also present some interesting challenges to surmount for the design of efficient biotechnological processes. In this review, we discuss key principles of microbial interactions, followed by a deep dive into genome-scale metabolic models, focussing on a vast repertoire of constraint-based modelling methods that enable us to characterise and understand the metabolic capabilities of microbial communities. Complementary approaches to model microbial communities, such as those based on graph theory, are also briefly discussed. Taken together, these methods provide rich insights into the interactions between microbes and how they influence microbial community productivity. We finally overview approaches that allow us to generate and test numerous synthetic community compositions, followed by tools and methodologies that can predict effective genetic interventions to further improve the productivity of communities. With impending advancements in high-throughput omics of microbial communities, the stage is set for the rapid expansion of microbial community engineering, with a significant impact on biotechnological processes. |
format | Online Article Text |
id | pubmed-8441623 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-84416232021-09-27 Modelling microbial communities: Harnessing consortia for biotechnological applications Ibrahim, Maziya Raajaraam, Lavanya Raman, Karthik Comput Struct Biotechnol J Review Microbes propagate and thrive in complex communities, and there are many benefits to studying and engineering microbial communities instead of single strains. Microbial communities are being increasingly leveraged in biotechnological applications, as they present significant advantages such as the division of labour and improved substrate utilisation. Nevertheless, they also present some interesting challenges to surmount for the design of efficient biotechnological processes. In this review, we discuss key principles of microbial interactions, followed by a deep dive into genome-scale metabolic models, focussing on a vast repertoire of constraint-based modelling methods that enable us to characterise and understand the metabolic capabilities of microbial communities. Complementary approaches to model microbial communities, such as those based on graph theory, are also briefly discussed. Taken together, these methods provide rich insights into the interactions between microbes and how they influence microbial community productivity. We finally overview approaches that allow us to generate and test numerous synthetic community compositions, followed by tools and methodologies that can predict effective genetic interventions to further improve the productivity of communities. With impending advancements in high-throughput omics of microbial communities, the stage is set for the rapid expansion of microbial community engineering, with a significant impact on biotechnological processes. Research Network of Computational and Structural Biotechnology 2021-07-03 /pmc/articles/PMC8441623/ /pubmed/34584635 http://dx.doi.org/10.1016/j.csbj.2021.06.048 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Ibrahim, Maziya Raajaraam, Lavanya Raman, Karthik Modelling microbial communities: Harnessing consortia for biotechnological applications |
title | Modelling microbial communities: Harnessing consortia for biotechnological applications |
title_full | Modelling microbial communities: Harnessing consortia for biotechnological applications |
title_fullStr | Modelling microbial communities: Harnessing consortia for biotechnological applications |
title_full_unstemmed | Modelling microbial communities: Harnessing consortia for biotechnological applications |
title_short | Modelling microbial communities: Harnessing consortia for biotechnological applications |
title_sort | modelling microbial communities: harnessing consortia for biotechnological applications |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8441623/ https://www.ncbi.nlm.nih.gov/pubmed/34584635 http://dx.doi.org/10.1016/j.csbj.2021.06.048 |
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