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High Sensitivity of Shotgun Metagenomic Sequencing in Colon Tissue Biopsy by Host DNA Depletion

Authors :
Wing Yin, Cheng
Wei-Xin, Liu
Yanqiang, Ding
Guoping, Wang
Yu, Shi
Eagle S H, Chu
Sunny, Wong
Joseph J Y, Sung
Jun, Yu
Source :
Genomics, Proteomics & Bioinformatics.
Publication Year :
2022
Publisher :
Elsevier BV, 2022.

Abstract

The high host genetic background of tissue biopsies hinders the application of shotgun metagenomic sequencing in characterizing the tissue microbiota. We proposed an optimized method that removed host DNA from colon biopsies and examined the effect on metagenomic analysis. Human or mouse colon biopsies were divided into two groups, with one group undergoing host DNA depletion while the other serving as the control. Host DNAs were removed through differential lysis of mammalian and bacterial cells before sequencing. The impact of host DNA depletion on microbiota was compared based on phylogenetic diversity analyses and regression analyses. Removing host DNA enhanced bacterial sequencing depth and improved species discovery, increasing bacterial reads by 2.46 ± 0.20 fold while reducing host reads by 6.80% ± 1.06%. Moreover, 3.40 times more of bacterial species were detected after host DNA depletion. This was confirmed from mouse colon tissues, increasing bacterial reads by 5.46 ± 0.42 fold while decreasing host reads by 10.2% ± 0.83%. Similarly, significantly more species were detected in mouse colon tissue upon host DNA depletion (P0.001). Furthermore, an increased microbial richness was evident in the host DNA-depleted samples compared to non-depleted controls in human colon biopsies and mouse colon tissues (P0.001). Our optimized method of host DNA depletion improved the sensitivity of shotgun metagenomic sequencing in bacterial detection in the biopsy, which may yield a more accurate taxonomic profile of the tissue microbiota and identify bacteria that are important for disease initiation or progression.

Details

ISSN :
16720229
Database :
OpenAIRE
Journal :
Genomics, Proteomics & Bioinformatics
Accession number :
edsair.doi.dedup.....68e37132cd58d19e5ecfc9807604fcc1