AUTHOR=Zhang Lei , Chen Ting , Wang Ye , Zhang Shengwei , Lv Qingyu , Kong Decong , Jiang Hua , Zheng Yuling , Ren Yuhao , Huang Wenhua , Liu Peng , Jiang Yongqiang TITLE=Comparison Analysis of Different DNA Extraction Methods on Suitability for Long-Read Metagenomic Nanopore Sequencing JOURNAL=Frontiers in Cellular and Infection Microbiology VOLUME=12 YEAR=2022 URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2022.919903 DOI=10.3389/fcimb.2022.919903 ISSN=2235-2988 ABSTRACT=

Metagenomic next-generation sequencing (mNGS) is a novel useful strategy that is increasingly used for pathogens detection in clinic. Some emerging mNGS technologies with long-read ability are useful to decrease sequencing time and increase diagnosed accuracy, which is of great significance in rapid pathogen diagnosis. Reliable DNA extraction is considered critical for the success of sequencing; hence, there is thus an urgent need of gentle DNA extraction method to get unbiased and more integrate DNA from all kinds of pathogens. In this study, we systematically compared three DNA extraction methods (enzymatic cell lysis based on MetaPolyzyme, mechanical cell lysis based on bead beating, and the control method without pre–cell lysis, respectively) by assessing DNA yield, integrity, and the microbial diversity based on long-read nanopore sequencing of urine samples with microbial infections. Compared with the control method, the enzymatic-based method increased the average length of microbial reads by a median of 2.1-fold [Inter Quartile Range (IQR), 1.7–2.5; maximum, 4.8) in 18 of the 20 samples and the mapped reads proportion of specific species by a median of 11.8-fold (Inter Quartile Range (IQR), 6.9–32.2; maximum, 79.27]. Moreover, it provided fully (20 of 20) consistent diagnosed results to the clinical culture and more representative microbial profiles (P < 0.05), which all strongly proves the excellent performance of enzymatic-based method in long-read mNGS–based pathogen identification and potential diseases diagnosis of microbiome related.