Shotgun metagenomes from productive lakes in an urban region of Sweden
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Abstract Urban lakes provide multiple benefits to society while influencing life quality. Moreover, lakes and their microbiomes are sentinels of anthropogenic impact and can be used for natural resource management and planning. Here, we release original metagenomic data from several well-characterized and anthropogenically impacted eutrophic lakes in the vicinity of Stockholm (Sweden). Our goal was to collect representative microbial community samples and use shotgun sequencing to provide a broad view on microbial diversity of productive urban lakes. Our dataset has an emphasis on Lake Mälaren as a major drinking water reservoir under anthropogenic impact. This dataset includes short-read sequence data and metagenome assemblies from each of 17 samples collected from eutrophic lakes near the greater Stockholm area. We used genome-resolved metagenomics and obtained 2378 metagenome assembled genomes that de-replicated into 514 species representative genomes. This dataset adds new datapoints to previously sequenced lakes and it includes the first sequenced set of metagenomes from Lake Mälaren. Our dataset serves as a baseline for future monitoring of drinking water reservoirs and urban lakes.Keywords:
Baseline (sea)
Abstract Shotgun metagenomic sequencing is a valuable tool for the taxonomic and functional profiling of microbial communities. However, this approach is challenging in samples, such as milk, where a low microbial abundance, combined with high levels of host DNA, result in inefficient and uneconomical sequencing. Here we evaluate approaches to deplete host DNA or enrich microbial DNA prior to sequencing using three commercially available kits. We compared the percentage of microbial reads obtained from each kit after shotgun metagenomic sequencing. Using bovine and human milk samples, we determined that host depletion with the MolYsis complete5 kit significantly improved microbial sequencing depth compared to other approaches tested. Importantly, no biases were introduced. Additionally, the increased microbial sequencing depth allowed for further characterization of the microbiome through the generation of metagenome-assembled genomes (MAGs). Furthermore, with the use of a mock community, we compared three common classifiers and determined that Kraken2 was the optimal classifier for these samples. This evaluation shows that microbiome analysis can be performed on both bovine and human milk samples at a much greater resolution without the need for more expensive deep-sequencing approaches.
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