De novo species identification using 16S rRNA gene nanopore sequencing

Abstract

Nanopore sequencing is rapidly becoming more popular for use in various microbiota-based applications. Major limitations of current approaches are that they do not enable de novo species identification and that they cannot be used to verify species assignments. This severely limits applicability of the nanopore sequencing technology in taxonomic applications. Here, we demonstrate the possibility of de novo species identification and verification using hexamer frequencies in combination with k-means clustering for nanopore sequencing data. The approach was tested on the human infant gut microbiota of 3-month-old infants. Using the hexamer k-means approach we identified two new low abundant species associated with vaginal delivery. In addition, we confirmed both the vaginal delivery association for two previously identified species and the overall high levels of bifidobacteria. Taxonomic assignments were further verified by mock community analyses. Therefore, we believe our de novo species identification approach will have widespread application in analyzing microbial communities in the future.

MetaSquare: an integrated metadatabase of 16S rRNA gene amplicon for microbiome taxonomic classification

“…Two analyses were conducted for database performance: QIIME 2 on a classical short-read/16S rRNA gene amplicon with the V3–V4 amplicon dataset published by NCBI BioProject PRJNA715083 ( Kameoka et al , 2021 ) and Kraken 2 on long-read/16S rRNA gene near-full length amplicon with datasets from PRJDB9744, V1–V9 amplicon ( Matsuo et al , 2021 ) and PRJNA637202, V3–V9 amplicon ( Angell et al , 2020 ). We compared the taxonomic classification output of QIIME 2 with MetaSquare (this study), SILVA, Greengenes and 16-UDb.…”

Nanopore Electrochemistry for Pathogen Detection

“…Moreover, Angell et al . utilized hexamer frequencies in combination with k ‐ means clustering to analyze MinION sequencing data [75] . This approach enabled de novo identification of low abundant species related to vaginal delivery, like Bacteroides xylanisolvens , C. aerofaciens .…”

“…[74] Moreover, Angell et al utilized hexamer frequencies in combination with k-means clustering to analyze MinION sequencing data. [75] This approach enabled de novo identification of low abundant species related to vaginal delivery, like Bacteroides xylanisolvens, C. aerofaciens. To date, several publications have evaluated the capability of MinION sequencer for the identification of bacterial pathogens via WGS.…”