Document Type

Article

Publication Date

4-7-2021

Publication Title

mSphere

Keywords

JGM

JAX Source

mSphere 2020 Apr 7; 6(2):e01325-20

Volume

6

Issue

2

ISSN

2379-5042

PMID

33827913

DOI

https://doi.org/10.1128/msphere.01325-20

Abstract

Current 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.

Comments

We gratefully acknowledge the contribution of the Microbial Genomics Service and Genome Technologies Service at The Jackson Laboratory for expert assistance with the work described in this publication. We also gratefully acknowledge the Bioinformatics team at Tecan Genomics for their assistance in probe pool design and analysis development. We thank Julia Oh and John Graham for prepublication access to mWGS data from stool specimens of collaborative cross founder (CCF) mouse strains.

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

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