Abstract
ABSTRACTCurrent sequencing-based methods for profiling microbial communities rely on marker gene (e.g., 16S rRNA) or metagenome shotgun sequencing (mWGS) analysis. We present an approach based on a single-primer extension reaction using a highly multiplexed oligonucleotide probe pool. This approach, termed MA-GenTA (microbial abundances from genome tagged analysis), enables quantitative, straightforward, cost-effective microbiome profiling that combines desirable features of both 16S rRNA and mWGS strategies. The use of multiple probes per target genome and rigorous probe design criteria enabled robust determination of relative abundance. To test the utility of the MA-GenTA assay, probes were designed for 830 genome sequences representing bacteria present in mouse stool specimens. Comparison of the MA-GenTA data with mWGS data demonstrated excellent correlation down to 0.01% relative abundance and a similar number of organisms detected per sample. Despite the incompleteness of the reference database, nonmetric multidimensional scaling (NMDS) clustering based on the Bray-Curtis dissimilarity metric of sample groups was consistent between MA-GenTA, mWGS, and 16S rRNA data sets. MA-GenTA represents a potentially useful new method for microbiome community profiling based on reference genomes.IMPORTANCE New methods for profiling the microbial communities can create new approaches to understanding the composition and function of those communities. In this study, we combined bacterial genome-specific probe design with a highly multiplexed single primer extension reaction as a new method to profile microbial communities, using stool from various mouse strains as a test case. This method, termed MA-GenTA, was benchmarked against 16S rRNA gene sequencing and metagenome sequencing methods and delivered similar relative abundance and clustering data. Since the probes were generated from reference genomes, MA-GenTA was also able to provide functional pathway data for the stool microbiome in the assayed samples. The method is more informative than 16S rRNA analysis while being less costly than metagenome shotgun sequencing.
Highlights
The primary molecular methods for determining microbial composition are based on marker gene sequencing or whole-metagenome shotgun sequencing
Combining 1.3 Tbp of data from 298 mouse metagenomic libraries, Lesker et al [15] assembled 1.2 million contigs; a subset of these could be grouped into 830 high-quality metagenome-assembled genomes (MAGs) that are predicted to be .90% complete and,5% contaminated based on the representation of single-copy genes [16]
The MA-GenTA assay is based on approximating the relative abundance of hundreds of microbial species using sets of probes designed to be unique to each genome
Summary
The primary molecular methods for determining microbial composition are based on marker gene sequencing or whole-metagenome shotgun sequencing (mWGS). The 16S rRNA marker gene has been widely used for bacterial profiling for decades across diverse ecosystems [1, 2] Using this method, taxonomic classification of the bacterial community can be obtained at modest cost and a resolution that ranges from subspecies to family level, depending on the 16S rRNA segment that is sequenced [4,5,6]. One approach to overcome the limited availability of reference genome sequences is construction of in silico genomes based on computational sequence assembly of large mWGS data sets to create metagenome-assembled genomes (MAGs) [12,13,14]. We adapted the Allegro Targeted Genotyping assay’s single primer extension reaction that is widely used for genotyping [17, 18] and implemented it as a quantitative, straightforward, and cost-effective method for profiling mouse microbial communities based on the iMGMC hqMAGs
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