ArticleScientific data2024
Metagenomics datasets of water and sediments from eutrophication-impacted artificial lakes in South Africa.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A metagenomic approach for microbial risk assessment and source attribution in high-risk ports of entry environments.Biosafety and health · 2025Article
- Analysis of metagenomic data.Nature reviews. Methods primers · 2025Article
- Metagenomics datasets of water and sediments from eutrophication-impacted artificial lakes in South Africa.Scientific data · 2024Article
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Authors and funding
5 authors.
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Abstract
We present metagenomes of 16 samples of water and sediment from two lakes, collected from eutrophic and non-eutrophic areas, including pooled samples enriched with phosphate and nitrate. Additionally, we assembled 167 bacterial metagenome-assembled genomes (MAGs). These MAGs were de-replicated into 83 unique genomes representing different species found in the lakes. All the MAGs exhibited >70% completeness and <10% contamination, with 79 MAGs being classified as 'nearly complete' (completeness >90%), while 54 falling within 80-90% range and 34 between 75-80% complete. The most abundant MAGs identified across all samples were Proteobacteria (n = 80), Firmicutes_A (n = 35), Firmicutes (n = 13), and Bacteriodota (n = 22). Other groups included Desulfobacteria_I (n = 2), Verrucomicrobiota (n = 4), Campylobacterota (n = 4) and Actinobacteriota (n = 6). Importantly, phylogenomic analysis identified that approximately 50.3% of the MAGs could not be classified to known species, suggesting the presence of potentially new and unknown bacteria in these lakes, warranting further in-depth investigation. This study provides valuable new dataset on the diverse and often unique microbial communities living in polluted lakes, useful in developing effective strategies to manage pollution.
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