Comparison of a long-read amplicon sequencing approach to short-read amplicons for microbiome analysis

Abstract

Most microbiome studies to date rely on sequencing short amplicons of the 16S rRNA gene on Illuminas platforms. Because of the short read length, sequences often can be identified reliably only to the family or genus levels. Long read sequencing with whole-length 16S rRNA sequencing can improve taxonomic resolution, but often only to the species level. StrainID is an alternative approach that amplifies a large segment of the ribosomal operon, including the entire 16S rRNA gene, internal transcribed spacer, and a portion of the 23S rRNA gene. This longer amplicon is designed to allow ribotype-level classification. Although studies have demonstrated the utility of StrainID for several sample types, it has not yet been validated for saliva. Here, we compared the performance of StrainID to short read amplicons with saliva samples as well as a synthetic mock DNA community and human and mouse fecal samples. Short reads were amplified with primer pairs appropriate for the corresponding sample type, and were classified with two different taxonomic databases. For both saliva and fecal samples, we found that StrainID performed similarly to short reads overall and demonstrated a key benefit with phylogenetic-based beta diversity tests and taxonomic classification. Our results further build on establishing StrainID as a valid method and specifically validate its use with saliva samples. ImportanceThe interpretation of microbiome composition studies is highly dependent on the methodologies chosen during experimental design, which affects factors such as resolution, throughput, cost, and accuracy. StrainID is an approach that can improve resolution while maintaining high-throughput and similar costs to short-read sequencing. The salivary microbiome represents a diverse community of microbes with links to a variety of health conditions and disease states. Closely related strains of bacteria can have drastically different effects on their host. Establishing StrainID as a valid approach for studying the salivary microbiome opens avenues for research that improve upon alternative methods by increasing sensitivity and accuracy compared to traditional short read approaches.