A comparison of DNA/RNA extraction protocols for high-throughput sequencing of microbial communities

One goal of microbial ecology researchers is to capture the maximum amount of information from all organisms in a sample. The recent COVID-19 pandemic, caused by the RNA virus SARS-CoV-2, has highlighted a gap in traditional DNA-based protocols, including the high-throughput methods the authors previously established as field standards. To enable simultaneous SARS-CoV-2 and microbial community profiling, the authors compared the relative performance of two total nucleic acid extraction protocols with the authors' previously benchmarked protocol. The authors included a diverse panel of environmental and host-associated sample types, including body sites commonly swabbed for COVID-19 testing. Here the authors present results comparing the cost, processing time, DNA and RNA yield, microbial community composition, limit of detection and well-to-well contamination between these protocols. ACCESSION NUMBERS Raw sequence data were deposited at the European Nucleotide Archive (accession number ERP124610), and raw and processed data are available at Qiita (study identifier 12201). Processing and analysis code is available on GitHub (https://github.com/justinshaffer/Extraction test MagMAX). METHOD SUMMARY To allow for downstream applications involving RNA-based organisms such as SARS-CoV-2, the authors compared the two extraction protocols designed to extract DNA and RNA with the authors' previously established protocol for extracting only DNA for microbial community analyses. Across ten diverse sample types, one of the two protocols was equivalent or better than the authors' established DNA-based protocol. The authors' conclusion is based on per-sample comparisons of DNA and RNA yield, number of quality sequences generated, microbial community alpha- and beta-diversity and taxonomic composition, limit of detection and extent of well-to-well contamination.

Automated summary

Researchers compared three nucleic acid extraction protocols, finding that one of the protocols performed equivalently or better than the authors' established DNA-based protocol across ten diverse sample types in terms of DNA and RNA yield, sequence quality, microbial community diversity, and other factors.