Comparison of 16S rRNA gene amplicon and whole-genome shotgun metagenomic sequencing for subgingival oral microbiome profiling

Background Periodontitis is a chronic inflammatory disease driven by a dysbiotic subgingival microbiome. While 16S rRNA gene amplicon sequencing is widely used, whole-genome shotgun (WGS) metagenomics is increasingly applied for higher taxonomic and functional resolution.Objective The aim of this study was to directly compare 16S rRNA gene amplicon (V1–V2) sequencing and WGS metagenomic sequencing using matched subgingival plaque samples from patients with periodontitis.Methods Subgingival plaque samples from 28 patients with periodontitis were analyzed using both 16S rRNA gene amplicon (V1–V2) sequencing and WGS metagenomics. Taxonomic composition, microbial diversity, differential abundance and functional analysis were compared across platforms.Results WGS generated markedly higher read counts than 16S rRNA gene amplicon but showed wide variability in non-human reads, whereas 16S rRNA gene amplicon yielded a consistent proportion of non-chimeric reads. High taxonomic overlap was observed at the phylum level but declined at higher taxonomic ranks. WGS preferentially detected taxa such as Actinomyces, Corynebacterium and Olsenella, while the 16S rRNA gene amplicon more frequently captured Saccharibacteria (TM7) and low-abundance taxa. Core genera, including Rothia, Neisseria and Cardiobacterium showed comparable abundance patterns across platforms. When patients were grouped depending on probing pocket depth (PPD), LEfSe analysis resulted in platform-specific enrichment patterns. Functional analyses revealed shared central pathways, such as pyruvate metabolism, while 16S-based PICRUSt2 emphasized reductive and degradative pathways and WGS-based HUMAnN highlighted oxidative and biosynthetic pathways. Notably, WGS-based functional profiles were strongly influenced by microbial read depth.Conclusions This comparative analysis demonstrates that 16S rRNA gene amplicon (V1–V2) sequencing and WGS both robustly capture core subgingival microbial signatures. While WGS provides higher species-level and functional resolution, the resolution was strongly constrained by microbial read depth in host-rich subgingival samples. These findings provide practical guidance for selecting appropriate sequencing strategies and optimizing sample preparation when designing WGS-based periodontal microbiome studies.