Amplicon Sequencing of Single-Copy Protein-Coding Genes Reveals Accurate Diversity for Sequence-Discrete Microbiome Populations.

An in-depth understanding of microbial function and the division of ecological niches requires accurate delineation and identification of microbes at a fine taxonomic resolution. Microbial phylotypes are typically defined using a 97% small subunit (16S) rRNA threshold. However, increasing evidence has demonstrated the ubiquitous presence of taxonomic units of distinct functions within phylotypes. These so-called sequence-discrete populations (SDPs) have used to be mainly delineated by disjunct sequence similarity at the whole-genome level. However, gene markers that could accurately identify and quantify SDPs are lacking in microbial community studies. Here, we developed a pipeline to screen single-copy protein-coding genes that could accurately characterize SDP diversity via amplicon sequencing of microbial communities. Fifteen candidate marker genes were evaluated using three criteria (extent of sequence divergence, phylogenetic accuracy, and conservation of primer regions) and the selected genes were subject to test the efficiency in differentiating SDPs within Gilliamella, a core honeybee gut microbial phylotype, as a proof-of-concept. The results showed that the 16S V4 region failed to report accurate SDP diversities due to low taxonomic resolution and changing copy numbers. In contrast, the single-copy genes recommended by our pipeline were able to successfully quantify Gilliamella SDPs for both mock samples and honeybee guts, with results highly consistent with those of metagenomics. The pipeline developed in this study is expected to identify single-copy protein coding genes capable of accurately quantifying diverse bacterial communities at the SDP level. IMPORTANCE Microbial communities can be distinguished by discrete genetic and ecological characteristics. These sequence-discrete populations are foundational for investigating the composition and functional structures of microbial communities at high resolution. In this study, we screened for reliable single-copy protein-coding marker genes to identify sequence-discrete populations through our pipeline. Using marker gene amplicon sequencing, we could accurately and efficiently delineate the population diversity in microbial communities. These results suggest that single copy protein-coding genes can be an accurate, quantitative, and economical alternative for characterizing population diversity. Moreover, the feasibility of a gene as marker for any bacterial population identification can be quickly evaluated by the pipeline proposed here.