ArticleEnvironmental science & technology2023
Identifying Eukaryotes and Factors Influencing Their Biogeography in Drinking Water Metagenomes.
Article in Environmental science & technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed, 23 citations in OpenAlex.
- Implementation and comparison of two concentration methods to detect and characterize bacteriophages and bacterial hosts from large drinking water samples.Environmental microbiome · 2025Article
- Tracing non-fungal eukaryotic diversity via shotgun metagenomes in the complex mudflat intertidal zones.mSystems · 2025Article
- Dynamics of drinking water biofilm formation associated with Legionella spp. colonization.NPJ biofilms and microbiomes · 2024Article
- New Drinking Water Genome Catalog Identifies a Globally Distributed Bacterial Genus Adapted to Disinfected Drinking Water Systems.Environmental science & technology · 2024Article
- Using grass inflorescence as source material for biomonitoring through environmental DNA metabarcoding.Molecular biology reports · 2024Article
- Benchmarking informatics approaches for virus discovery: caution is needed when combiningmSystems · 2024Article
- Responses of drinking water bulk and biofilm microbiota to elevated water age in bench-scale simulated distribution systems.NPJ biofilms and microbiomes · 2024Article
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Corrections and comments
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Authors and funding
7 authors at 6 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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
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Registered trials
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