Metagenomics and Metatranscriptomics Analysis Using ATCC Whole Cell Microbiome Standards

Metagenomic analyses have provided insight into the abundance and taxonomic profiles of microbiomes. As the clinical and biotechnological applications of microbiome research continue to expand, researchers are now leveraging metatranscriptomics to explore organism-level function in microbiome samples via RNA-Seq technology. To facilitate this research, we have developed whole cell mock community NGS standards representing complex mixtures of diverse bacterial species. In the following study, we used these mock community standards to create metagenomics and metatranscriptomic profiles to validate the bioinformatics analysis of whole-genome shotgun sequencing and RNA-Seq data. DNA and RNA were extracted from 100 μL aliquots of the whole cell NGS standards (ATCC MSA-2002 and ATCC MSA-2003), and shotgun sequencing of DNA and RNA was performed using the Illumina platform. Sequencing analysis was performed by the Kwan lab (University of Wisconsin-Madison) using the Autometa bioinformatics pipeline, which automated the taxonomic separation of genomic DNA contigs and profiled their RNA expression from metagenomes1. Results from de novo assembly and contig separation (“binning”) via the developed bioinformatics pipeline suggested taxonomic separation. There were high fractions of recovery and coverage for individual genomes assembled de novo from whole cell NGS standards. The mapping of RNA reads to genome bins showed detectable expression levels in all of the assembled genomes with detectable RNA read coverage for all strains. Functional annotation of biosynthetic gene clusters identified multiple pathways in different genomes. RNA expression profiles of NGS Standards showed different levels of gene expression and individual genome resolution. This proof-of-concept study, using integrated genome-resolved metagenomics and metatranscriptomics, demonstrates the utility, flexibility, and power of whole cell mock community standards to benchmark both the characterization and functional profiling of microbiomes.