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Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data

Mining interspecies interactions remain a challenge due to the complex nature of microbial communities and the need for computational power to handle big data. Our meta-analysis indicates that genetic potential alone does not resolve all issues involving mining of microbial interactions. Nevertheles...

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Autores principales: Saraiva, Joao Pedro, Worrich, Anja, Karakoç, Canan, Kallies, Rene, Chatzinotas, Antonis, Centler, Florian, Nunes da Rocha, Ulisses
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8070991/
https://www.ncbi.nlm.nih.gov/pubmed/33920040
http://dx.doi.org/10.3390/microorganisms9040840
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author Saraiva, Joao Pedro
Worrich, Anja
Karakoç, Canan
Kallies, Rene
Chatzinotas, Antonis
Centler, Florian
Nunes da Rocha, Ulisses
author_facet Saraiva, Joao Pedro
Worrich, Anja
Karakoç, Canan
Kallies, Rene
Chatzinotas, Antonis
Centler, Florian
Nunes da Rocha, Ulisses
author_sort Saraiva, Joao Pedro
collection PubMed
description Mining interspecies interactions remain a challenge due to the complex nature of microbial communities and the need for computational power to handle big data. Our meta-analysis indicates that genetic potential alone does not resolve all issues involving mining of microbial interactions. Nevertheless, it can be used as the starting point to infer synergistic interspecies interactions and to limit the search space (i.e., number of species and metabolic reactions) to a manageable size. A reduced search space decreases the number of additional experiments necessary to validate the inferred putative interactions. As validation experiments, we examine how multi-omics and state of the art imaging techniques may further improve our understanding of species interactions’ role in ecosystem processes. Finally, we analyze pros and cons from the current methods to infer microbial interactions from genetic potential and propose a new theoretical framework based on: (i) genomic information of key members of a community; (ii) information of ecosystem processes involved with a specific hypothesis or research question; (iii) the ability to identify putative species’ contributions to ecosystem processes of interest; and, (iv) validation of putative microbial interactions through integration of other data sources.
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spelling pubmed-80709912021-04-26 Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data Saraiva, Joao Pedro Worrich, Anja Karakoç, Canan Kallies, Rene Chatzinotas, Antonis Centler, Florian Nunes da Rocha, Ulisses Microorganisms Review Mining interspecies interactions remain a challenge due to the complex nature of microbial communities and the need for computational power to handle big data. Our meta-analysis indicates that genetic potential alone does not resolve all issues involving mining of microbial interactions. Nevertheless, it can be used as the starting point to infer synergistic interspecies interactions and to limit the search space (i.e., number of species and metabolic reactions) to a manageable size. A reduced search space decreases the number of additional experiments necessary to validate the inferred putative interactions. As validation experiments, we examine how multi-omics and state of the art imaging techniques may further improve our understanding of species interactions’ role in ecosystem processes. Finally, we analyze pros and cons from the current methods to infer microbial interactions from genetic potential and propose a new theoretical framework based on: (i) genomic information of key members of a community; (ii) information of ecosystem processes involved with a specific hypothesis or research question; (iii) the ability to identify putative species’ contributions to ecosystem processes of interest; and, (iv) validation of putative microbial interactions through integration of other data sources. MDPI 2021-04-14 /pmc/articles/PMC8070991/ /pubmed/33920040 http://dx.doi.org/10.3390/microorganisms9040840 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Saraiva, Joao Pedro
Worrich, Anja
Karakoç, Canan
Kallies, Rene
Chatzinotas, Antonis
Centler, Florian
Nunes da Rocha, Ulisses
Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data
title Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data
title_full Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data
title_fullStr Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data
title_full_unstemmed Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data
title_short Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data
title_sort mining synergistic microbial interactions: a roadmap on how to integrate multi-omics data
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8070991/
https://www.ncbi.nlm.nih.gov/pubmed/33920040
http://dx.doi.org/10.3390/microorganisms9040840
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