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Systematic Cross-biospecimen Evaluation of DNA Extraction Kits for Long- and Short-read Multi-metagenomic Sequencing Studies

Authors :
Jacqueline Rehner
Georges Pierre Schmartz
Laura Groeger
Jan Dastbaz
Nicole Ludwig
Matthias Hannig
Stefan Rupf
Berthold Seitz
Elias Flockerzi
Tim Berger
Matthias Christian Reichert
Marcin Krawczyk
Eckart Meese
Christian Herr
Robert Bals
Sören L. Becker
Andreas Keller
Rolf Müller
Source :
Genomics, Proteomics & Bioinformatics, Vol 20, Iss 2, Pp 405-417 (2022)
Publication Year :
2022
Publisher :
Oxford University Press, 2022.

Abstract

High-quality DNA extraction is a crucial step in metagenomic studies. Bias by different isolation kits impairs the comparison across datasets. A trending topic is, however, the analysis of multiple metagenomes from the same patients to draw a holistic picture of microbiota associated with diseases. We thus collected bile, stool, saliva, plaque, sputum, and conjunctival swab samples and performed DNA extraction with three commercial kits. For each combination of the specimen type and DNA extraction kit, 20-gigabase (Gb) metagenomic data were generated using short-read sequencing. While profiles of the specimen types showed close proximity to each other, we observed notable differences in the alpha diversity and composition of the microbiota depending on the DNA extraction kits. No kit outperformed all selected kits on every specimen. We reached consistently good results using the Qiagen QiAamp DNA Microbiome Kit. Depending on the specimen, our data indicate that over 10 Gb of sequencing data are required to achieve sufficient resolution, but DNA-based identification is superior to identification by mass spectrometry. Finally, long-read nanopore sequencing confirmed the results (correlation coefficient > 0.98). Our results thus suggest using a strategy with only one kit for studies aiming for a direct comparison of multiple microbiotas from the same patients.

Details

Language :
English
ISSN :
16720229
Volume :
20
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Genomics, Proteomics & Bioinformatics
Publication Type :
Academic Journal
Accession number :
edsdoj.270244a887e14316a5f8c2f26c2794d9
Document Type :
article
Full Text :
https://doi.org/10.1016/j.gpb.2022.05.006