Assessment of metagenomic workflows using a newly constructed human gut microbiome mock community

Abstract

To quantify the biases introduced during human gut microbiome studies, analyzing an artificial mock community as the reference microbiome is indispensable. However, there are still limited resources for a mock community which well represents the human gut microbiome. Here, we constructed a novel mock community comprising the type strains of 18 major bacterial species in the human gut and assessed the influence of experimental and bioinformatics procedures on the 16S rRNA gene and shotgun metagenomic sequencing. We found that DNA extraction methods greatly affected the DNA yields and taxonomic composition of sequenced reads, and that some of the commonly used primers for 16S rRNA genes were prone to underestimate the abundance of some gut commensal taxa such as Erysipelotrichia, Verrucomicrobiota and Methanobacteriota. Binning of the assembled contigs of shotgun metagenomic sequences by MetaBAT2 produced phylogenetically consistent, less-contaminated bins with varied completeness. The ensemble approach of multiple binning tools by MetaWRAP can improve completeness but sometimes increases the contamination rate. Our benchmark study provides an important foundation for the interpretation of human gut microbiome data by providing means for standardization among gut microbiome data obtained with different methodologies and will facilitate further development of analytical methods.