Hybrid sequence-based analysis reveals the distribution of bacterial species and genes in the oral microbiome at a high resolution

TL;DR

This study uses advanced sequencing techniques to identify new bacterial species and antibiotic resistance genes in the oral microbiome.

Contribution

The study identifies five potential novel bacterial species and reveals antibiotic resistance and virulence genes in a healthy oral microbiome.

Findings

Five single-cell-isolated bacteria were suggested as potential novel species.

Antibiotic resistance and virulence genes were detected in a healthy oral microbiome.

Metagenomic sequencing revealed non-bacterial DNA made up 80% of saliva samples.

Abstract

Bacteria in the oral microbiome are poorly identified owing to the lack of established culture methods for them. Thus, this study aimed to use culture-free analysis techniques, including bacterial single-cell genome sequencing, to identify bacterial species and investigate gene distribution in saliva. Saliva samples from the same individual were classified as inactivated or viable and then analyzed using 16S rRNA sequencing, metagenomic shotgun sequencing, and bacterial single-cell sequencing. The results of 16S rRNA sequencing revealed similar microbiota structures in both samples, with Streptococcus being the predominant genus. Metagenomic shotgun sequencing showed that approximately 80 % of the DNA in the samples was of non-bacterial origin, whereas single-cell sequencing showed an average contamination rate of 10.4 % per genome. Single-cell sequencing also yielded genome sequences for 43 out of 48 wells for the inactivated samples and 45 out of 48 wells for the viable samples. With respect to resistance genes, four out of 88 isolates carried cfxA, which encodes a β-lactamase, and four isolates carried erythromycin resistance genes. Tetracycline resistance genes were found in nine bacteria. Metagenomic shotgun sequencing provided complete sequences of cfxA, ermF, and ermX, whereas other resistance genes, such as tetQ and tetM, were detected as fragments. In addition, virulence factors from Streptococcus pneumoniae were the most common, with 13 genes detected. Our average nucleotide identity analysis also suggested five single-cell-isolated bacteria as potential novel species. These data would contribute to expanding the oral microbiome data resource.

•Bacterial single-cell seq of saliva suggested five potential novel species.•A healthy oral microbiome contained AMR and virulence factor genes.•Our data contribute to expanding oral microbiome data resource.

Bacterial single-cell seq of saliva suggested five potential novel species.

A healthy oral microbiome contained AMR and virulence factor genes.

Our data contribute to expanding oral microbiome data resource.

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