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

1
Department of Environmental Microbiology, Helmholtz Centre for Environmental Research-UFZ, 04318 Leipzig, Germany
2
German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig, Germany
3
Institute of Biology, Leipzig University, 04103 Leipzig, Germany
*
Author to whom correspondence should be addressed.
Academic Editor: Jean Armengaud
Microorganisms 2021, 9(4), 840; https://doi.org/10.3390/microorganisms9040840
Received: 9 February 2021 / Revised: 13 March 2021 / Accepted: 8 April 2021 / Published: 14 April 2021
(This article belongs to the Section Systems Microbiology)
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. View Full-Text
Keywords: microbial communities; synergistic interactions; ecosystem processes; multi-omics microbial communities; synergistic interactions; ecosystem processes; multi-omics
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MDPI and ACS Style

Saraiva, J.P.; Worrich, A.; Karakoç, C.; Kallies, R.; Chatzinotas, A.; Centler, F.; Nunes da Rocha, U. Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data. Microorganisms 2021, 9, 840. https://doi.org/10.3390/microorganisms9040840

AMA Style

Saraiva JP, Worrich A, Karakoç C, Kallies R, Chatzinotas A, Centler F, Nunes da Rocha U. Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data. Microorganisms. 2021; 9(4):840. https://doi.org/10.3390/microorganisms9040840

Chicago/Turabian Style

Saraiva, Joao P., Anja Worrich, Canan Karakoç, Rene Kallies, Antonis Chatzinotas, Florian Centler, and Ulisses Nunes da Rocha. 2021. "Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data" Microorganisms 9, no. 4: 840. https://doi.org/10.3390/microorganisms9040840

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