ArticleFrontiers in microbiology2023
Identification of microbial community in the urban environment: The concordance between conventional culture and nanopore 16S rRNA sequencing.
Article in Frontiers in microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Naked-Eye and On-Site Detection ofFoods (Basel, Switzerland) · 2026Article
- Exploring colostrum microbiota and its influence on early calf gut microbiota development using full-length 16S rRNA gene metabarcoding.Scientific reports · 2025Article
- Impact of Chemotherapy Alone and in Combination with Immunotherapy on Oral Microbiota in Cancer Patients-A Pilot Study.Microorganisms · 2025Article
- EnsembleSeq: a workflow towards real-time, rapid, and simultaneous multi-kingdom-amplicon sequencing for holistic and resource-effective microbiome research at scale.Microbiology spectrum · 2024Article
- Who inhabits the built environment? A microbiological point of view on the principal bacteria colonizing our urban areas.Frontiers in microbiology · 2024Review
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Authors and funding
12 authors.
Funding
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Abstract
Introduction: Microbes in the built environment have been implicated as a source of infectious diseases. Bacterial culture is the standard method for assessing the risk of exposure to pathogens in urban environments, but this method only accounts for <1% of the diversity of bacteria. Recently, full-length 16S rRNA gene analysis using nanopore sequencing has been applied for microbial evaluations, resulting in a rise in the development of long-read taxonomic tools for species-level classification. Regarding their comparative performance, there is, however, a lack of information. Methods: Here, we aim to analyze the concordance of the microbial community in the urban environment inferred by multiple taxonomic classifiers, including ARGpore2, Emu, Kraken2/Bracken and NanoCLUST, using our 16S-nanopore dataset generated by MegaBLAST, as well as assess their abilities to identify culturable species based on the conventional culture results. Results: According to our results, NanoCLUST was preferred for 16S microbial profiling because it had a high concordance of dominant species and a similar microbial profile to MegaBLAST, whereas Kraken2/Bracken, which had similar clustering results as NanoCLUST, was also desirable. Second, for culturable species identification, Emu with the highest accuracy (81.2%) and F1 score (29%) for the detection of culturable species was suggested. Discussion: In addition to generating datasets in complex communities for future benchmarking studies, our comprehensive evaluation of the taxonomic classifiers offers recommendations for ongoing microbial community research, particularly for complex communities using nanopore 16S rRNA sequencing.
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