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Comparative Analysis of Metagenomics and Metataxonomics for the Characterization of Vermicompost Microbiomes

The study of microbial communities or microbiotas in animals and environments is important because of their impact in a broad range of industrial applications, diseases and ecological roles. High throughput sequencing (HTS) is the best strategy to characterize microbial composition and function. Mic...

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Autores principales: Pérez-Losada, Marcos, Narayanan, Dhatri Badri, Kolbe, Allison R., Ramos-Tapia, Ignacio, Castro-Nallar, Eduardo, Crandall, Keith A., Domínguez, Jorge
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9127802/
https://www.ncbi.nlm.nih.gov/pubmed/35620097
http://dx.doi.org/10.3389/fmicb.2022.854423
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author Pérez-Losada, Marcos
Narayanan, Dhatri Badri
Kolbe, Allison R.
Ramos-Tapia, Ignacio
Castro-Nallar, Eduardo
Crandall, Keith A.
Domínguez, Jorge
author_facet Pérez-Losada, Marcos
Narayanan, Dhatri Badri
Kolbe, Allison R.
Ramos-Tapia, Ignacio
Castro-Nallar, Eduardo
Crandall, Keith A.
Domínguez, Jorge
author_sort Pérez-Losada, Marcos
collection PubMed
description The study of microbial communities or microbiotas in animals and environments is important because of their impact in a broad range of industrial applications, diseases and ecological roles. High throughput sequencing (HTS) is the best strategy to characterize microbial composition and function. Microbial profiles can be obtained either by shotgun sequencing of genomes, or through amplicon sequencing of target genes (e.g., 16S rRNA for bacteria and ITS for fungi). Here, we compared both HTS approaches at assessing taxonomic and functional diversity of bacterial and fungal communities during vermicomposting of white grape marc. We applied specific HTS workflows to the same 12 microcosms, with and without earthworms, sampled at two distinct phases of the vermicomposting process occurring at 21 and 63 days. Metataxonomic profiles were inferred in DADA2, with bacterial metabolic pathways predicted via PICRUSt2. Metagenomic taxonomic profiles were inferred in PathoScope, while bacterial functional profiles were inferred in Humann2. Microbial profiles inferred by metagenomics and metataxonomics showed similarities and differences in composition, structure, and metabolic function at different taxonomic levels. Microbial composition and abundance estimated by both HTS approaches agreed reasonably well at the phylum level, but larger discrepancies were observed at lower taxonomic ranks. Shotgun HTS identified ~1.8 times more bacterial genera than 16S rRNA HTS, while ITS HTS identified two times more fungal genera than shotgun HTS. This is mainly a consequence of the difference in resolution and reference richness between amplicon and genome sequencing approaches and databases, respectively. Our study also revealed great differences and even opposite trends in alpha- and beta-diversity between amplicon and shotgun HTS. Interestingly, amplicon PICRUSt2-imputed functional repertoires overlapped ~50% with shotgun Humann2 profiles. Finally, both approaches indicated that although bacteria and fungi are the main drivers of biochemical decomposition, earthworms also play a key role in plant vermicomposting. In summary, our study highlights the strengths and weaknesses of metagenomics and metataxonomics and provides new insights on the vermicomposting of white grape marc. Since both approaches may target different biological aspects of the communities, combining them will provide a better understanding of the microbiotas under study.
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spelling pubmed-91278022022-05-25 Comparative Analysis of Metagenomics and Metataxonomics for the Characterization of Vermicompost Microbiomes Pérez-Losada, Marcos Narayanan, Dhatri Badri Kolbe, Allison R. Ramos-Tapia, Ignacio Castro-Nallar, Eduardo Crandall, Keith A. Domínguez, Jorge Front Microbiol Microbiology The study of microbial communities or microbiotas in animals and environments is important because of their impact in a broad range of industrial applications, diseases and ecological roles. High throughput sequencing (HTS) is the best strategy to characterize microbial composition and function. Microbial profiles can be obtained either by shotgun sequencing of genomes, or through amplicon sequencing of target genes (e.g., 16S rRNA for bacteria and ITS for fungi). Here, we compared both HTS approaches at assessing taxonomic and functional diversity of bacterial and fungal communities during vermicomposting of white grape marc. We applied specific HTS workflows to the same 12 microcosms, with and without earthworms, sampled at two distinct phases of the vermicomposting process occurring at 21 and 63 days. Metataxonomic profiles were inferred in DADA2, with bacterial metabolic pathways predicted via PICRUSt2. Metagenomic taxonomic profiles were inferred in PathoScope, while bacterial functional profiles were inferred in Humann2. Microbial profiles inferred by metagenomics and metataxonomics showed similarities and differences in composition, structure, and metabolic function at different taxonomic levels. Microbial composition and abundance estimated by both HTS approaches agreed reasonably well at the phylum level, but larger discrepancies were observed at lower taxonomic ranks. Shotgun HTS identified ~1.8 times more bacterial genera than 16S rRNA HTS, while ITS HTS identified two times more fungal genera than shotgun HTS. This is mainly a consequence of the difference in resolution and reference richness between amplicon and genome sequencing approaches and databases, respectively. Our study also revealed great differences and even opposite trends in alpha- and beta-diversity between amplicon and shotgun HTS. Interestingly, amplicon PICRUSt2-imputed functional repertoires overlapped ~50% with shotgun Humann2 profiles. Finally, both approaches indicated that although bacteria and fungi are the main drivers of biochemical decomposition, earthworms also play a key role in plant vermicomposting. In summary, our study highlights the strengths and weaknesses of metagenomics and metataxonomics and provides new insights on the vermicomposting of white grape marc. Since both approaches may target different biological aspects of the communities, combining them will provide a better understanding of the microbiotas under study. Frontiers Media S.A. 2022-05-10 /pmc/articles/PMC9127802/ /pubmed/35620097 http://dx.doi.org/10.3389/fmicb.2022.854423 Text en Copyright © 2022 Pérez-Losada, Narayanan, Kolbe, Ramos-Tapia, Castro-Nallar, Crandall and Domínguez. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Pérez-Losada, Marcos
Narayanan, Dhatri Badri
Kolbe, Allison R.
Ramos-Tapia, Ignacio
Castro-Nallar, Eduardo
Crandall, Keith A.
Domínguez, Jorge
Comparative Analysis of Metagenomics and Metataxonomics for the Characterization of Vermicompost Microbiomes
title Comparative Analysis of Metagenomics and Metataxonomics for the Characterization of Vermicompost Microbiomes
title_full Comparative Analysis of Metagenomics and Metataxonomics for the Characterization of Vermicompost Microbiomes
title_fullStr Comparative Analysis of Metagenomics and Metataxonomics for the Characterization of Vermicompost Microbiomes
title_full_unstemmed Comparative Analysis of Metagenomics and Metataxonomics for the Characterization of Vermicompost Microbiomes
title_short Comparative Analysis of Metagenomics and Metataxonomics for the Characterization of Vermicompost Microbiomes
title_sort comparative analysis of metagenomics and metataxonomics for the characterization of vermicompost microbiomes
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9127802/
https://www.ncbi.nlm.nih.gov/pubmed/35620097
http://dx.doi.org/10.3389/fmicb.2022.854423
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