Identification of microbial community in the urban environment: The concordance between conventional culture and nanopore 16S rRNA sequencing

• DOI: 10.3389/fmicb.2023.1164632
• Publication Date: 2023-04-14T07:46:00Z
• Authors: Annie Wing-Tung Lee; Chloe Toi-Mei Chan; Lily Lok-Yee Wong; Cheuk-Yi Yip; Wing-Tung Lui; Kai-Chun Cheng; Jake Siu-Lun Leung; Lam-Kwong Lee; Ivan Tak-Fai Wong; Timothy Ting-Leun...; Hiu-Yin Lao; Gilman Kit-Hang Siu
• Keywords: Concordance; Identification; Bacterial taxonomy; Biological classification; Taxonomic rank

Microbes in the built environment have been implicated as a source of infectious diseases. Bacterial culture is standard method for assessing risk exposure to pathogens urban environments, but this only accounts <1% diversity bacteria. Recently, full-length 16S rRNA gene analysis using nanopore sequencing has applied microbial evaluations, resulting rise development long-read taxonomic tools species-level classification. Regarding their comparative performance, there is, however, lack information.Here, we aim analyze concordance community inferred by multiple classifiers, including ARGpore2, Emu, Kraken2/Bracken and NanoCLUST, our 16S-nanopore dataset generated MegaBLAST, well assess abilities identify culturable species based on conventional results.According results, NanoCLUST was preferred profiling because it had high dominant similar profile whereas Kraken2/Bracken, which clustering results also desirable. Second, identification, Emu with highest accuracy (81.2%) F1 score (29%) detection suggested.In addition generating datasets complex communities future benchmarking studies, comprehensive evaluation classifiers offers recommendations ongoing research, particularly sequencing.