A comparison of six DNA extraction protocols for 16S, ITS and shotgun metagenomic sequencing of microbial communities

BIOTECHNIQUES(2022)

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摘要
Microbial communities contain a broad phylogenetic diversity of organisms; however, the majority of methods center on describing bacteria and archaea. Fungi are important symbionts in many ecosystems and are potentially important members of the human microbiome, beyond those that can cause disease. To expand our analysis of microbial communities to include data from the fungal internal transcribed spacer (ITS) region, five candidate DNA extraction kits were compared against our standardized protocol for describing bacteria and archaea using 16S rRNA gene amplicon- and shotgun metagenomics sequencing. The results are presented considering a diverse panel of host-associated and environmental sample types and comparing the cost, processing time, well-to-well contamination, DNA yield, limit of detection and microbial community composition among protocols. Across all criteria, the MagMAX Microbiome kit was found to perform best. The PowerSoil Pro kit performed comparably but with increased cost per sample and overall processing time. The ZymoMagBead, NucleoMag Food and Norgen Stool kits were included. METHOD SUMMARY To allow for downstreamapplications involving fungi in addition to bacteria and archaea, five DNA extraction kits were compared with a previously established, standardized protocol for extracting DNA for microbial community analysis. Across 10 diverse sample types, one extraction kit was found to perform comparably to or better than the standardized protocol. This conclusion is based on per-sample comparisons of DNA yield, the number of quality-filtered sequences generated, the limit of detection of microbial cells, microbial community alpha-diversity, beta-diversity, taxonomic composition and the extent of well-to-well contamination.
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关键词
Earth Microbiome Project (EMP), high-throughput sequencing, Katharoseq, Macherey-Nagel, MagAttract PowerSoil, mock community, mycobiome, rRNA, whole genome sequencing
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