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Identifying Eukaryotes and Factors Influencing Their Biogeography in Drinking Water Metagenomes
[Image: see text] The biogeography of eukaryotes in drinking water systems is poorly understood relative to that of prokaryotes or viruses, limiting the understanding of their role and management. A challenge with studying complex eukaryotic communities is that metagenomic analysis workflows are cur...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996835/ https://www.ncbi.nlm.nih.gov/pubmed/36827617 http://dx.doi.org/10.1021/acs.est.2c09010 |
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author | Gabrielli, Marco Dai, Zihan Delafont, Vincent Timmers, Peer H. A. van der Wielen, Paul W. J. J. Antonelli, Manuela Pinto, Ameet J. |
author_facet | Gabrielli, Marco Dai, Zihan Delafont, Vincent Timmers, Peer H. A. van der Wielen, Paul W. J. J. Antonelli, Manuela Pinto, Ameet J. |
author_sort | Gabrielli, Marco |
collection | PubMed |
description | [Image: see text] The biogeography of eukaryotes in drinking water systems is poorly understood relative to that of prokaryotes or viruses, limiting the understanding of their role and management. A challenge with studying complex eukaryotic communities is that metagenomic analysis workflows are currently not as mature as those that focus on prokaryotes or viruses. In this study, we benchmarked different strategies to recover eukaryotic sequences and genomes from metagenomic data and applied the best-performing workflow to explore the factors affecting the relative abundance and diversity of eukaryotic communities in drinking water distribution systems (DWDSs). We developed an ensemble approach exploiting k-mer- and reference-based strategies to improve eukaryotic sequence identification and identified MetaBAT2 as the best-performing binning approach for their clustering. Applying this workflow to the DWDS metagenomes showed that eukaryotic sequences typically constituted small proportions (i.e., <1%) of the overall metagenomic data with higher relative abundances in surface water-fed or chlorinated systems with high residuals. The α and β diversities of eukaryotes were correlated with those of prokaryotic and viral communities, highlighting the common role of environmental/management factors. Finally, a co-occurrence analysis highlighted clusters of eukaryotes whose members’ presence and abundance in DWDSs were affected by disinfection strategies, climate conditions, and source water types. |
format | Online Article Text |
id | pubmed-9996835 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-99968352023-03-10 Identifying Eukaryotes and Factors Influencing Their Biogeography in Drinking Water Metagenomes Gabrielli, Marco Dai, Zihan Delafont, Vincent Timmers, Peer H. A. van der Wielen, Paul W. J. J. Antonelli, Manuela Pinto, Ameet J. Environ Sci Technol [Image: see text] The biogeography of eukaryotes in drinking water systems is poorly understood relative to that of prokaryotes or viruses, limiting the understanding of their role and management. A challenge with studying complex eukaryotic communities is that metagenomic analysis workflows are currently not as mature as those that focus on prokaryotes or viruses. In this study, we benchmarked different strategies to recover eukaryotic sequences and genomes from metagenomic data and applied the best-performing workflow to explore the factors affecting the relative abundance and diversity of eukaryotic communities in drinking water distribution systems (DWDSs). We developed an ensemble approach exploiting k-mer- and reference-based strategies to improve eukaryotic sequence identification and identified MetaBAT2 as the best-performing binning approach for their clustering. Applying this workflow to the DWDS metagenomes showed that eukaryotic sequences typically constituted small proportions (i.e., <1%) of the overall metagenomic data with higher relative abundances in surface water-fed or chlorinated systems with high residuals. The α and β diversities of eukaryotes were correlated with those of prokaryotic and viral communities, highlighting the common role of environmental/management factors. Finally, a co-occurrence analysis highlighted clusters of eukaryotes whose members’ presence and abundance in DWDSs were affected by disinfection strategies, climate conditions, and source water types. American Chemical Society 2023-02-24 /pmc/articles/PMC9996835/ /pubmed/36827617 http://dx.doi.org/10.1021/acs.est.2c09010 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Gabrielli, Marco Dai, Zihan Delafont, Vincent Timmers, Peer H. A. van der Wielen, Paul W. J. J. Antonelli, Manuela Pinto, Ameet J. Identifying Eukaryotes and Factors Influencing Their Biogeography in Drinking Water Metagenomes |
title | Identifying Eukaryotes
and Factors Influencing Their
Biogeography in Drinking Water Metagenomes |
title_full | Identifying Eukaryotes
and Factors Influencing Their
Biogeography in Drinking Water Metagenomes |
title_fullStr | Identifying Eukaryotes
and Factors Influencing Their
Biogeography in Drinking Water Metagenomes |
title_full_unstemmed | Identifying Eukaryotes
and Factors Influencing Their
Biogeography in Drinking Water Metagenomes |
title_short | Identifying Eukaryotes
and Factors Influencing Their
Biogeography in Drinking Water Metagenomes |
title_sort | identifying eukaryotes
and factors influencing their
biogeography in drinking water metagenomes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996835/ https://www.ncbi.nlm.nih.gov/pubmed/36827617 http://dx.doi.org/10.1021/acs.est.2c09010 |
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