PT - JOURNAL ARTICLE AU - Megan Sarah Beaudry AU - Jincheng Wang AU - Troy Kieran AU - Jesse Thomas AU - Natalia Juliana Bayona-Vasquez AU - Bei Gao AU - Alison Devault AU - Brian Brunelle AU - Kun Lu AU - Jia-Sheng Wang AU - Olin E. Rhodes AU - Travis C. Glenn TI - Improved microbial community characterization of 16S rRNA via metagenome hybridization capture enrichment AID - 10.1101/2020.12.18.423101 DP - 2020 Jan 01 TA - bioRxiv PG - 2020.12.18.423101 4099 - http://biorxiv.org/content/early/2020/12/19/2020.12.18.423101.short 4100 - http://biorxiv.org/content/early/2020/12/19/2020.12.18.423101.full AB - Environmental microbial diversity is often investigated from a molecular perspective using 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics. While amplicon methods are fast, low-cost, and have curated reference databases, they can suffer from amplification bias and are limited in genomic scope. In contrast, shotgun metagenomic methods sample more genomic regions with fewer sequence acquisition biases. However, shotgun metagenomic sequencing is much more expensive (even with moderate sequencing depth) and computationally challenging. Here, we develop a set of 16S rRNA sequence capture baits that offer a potential middle ground with the advantages from both approaches for investigating microbial communities. These baits cover the diversity of all 16S rRNA sequences available in the Greengenes (v. 13.5) database, with no sequence having < 80% sequence similarity to at least one bait for all segments of 16S. The use of our baits provide comparable results to 16S amplicon libraries and shotgun metagenomic libraries when assigning taxonomic units from 16S sequences within the metagenomic reads. We demonstrate that 16S rRNA capture baits can be used on a range of microbial samples (i.e., mock communities and rodent fecal samples) to increase the proportion of 16S rRNA sequences (average >400-fold) and decrease analysis time to obtain consistent community assessments. Furthermore, our study reveals that bioinformatic methods used to analyze sequencing data may have a greater influence on estimates of community composition than library preparation method used, likely in part to the extent and curation of the reference databases considered.Competing Interest StatementThe EHS DNA lab provides oligonucleotide aliquots and library preparation services at cost, including some oligonucleotides and services used in this manuscript (baddna.uga.edu). Brian Brunelle and Alison Devault are employed by, and thereby have financial interest in, Daicel Arbor Biosciences, who provided the in-solution capture reagents used in this work.