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 and the other serving as the control.Host DNA was 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 folds while reducing host reads by 6.80%±1.06%.Moreover,2.40 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 folds while decreasing host reads by 10.2%±0.83%.Similarly,significantly more bacterial species were detected in the mouse colon tissue upon host DNA depletion(P<0.001).Furthermore,an increased microbial richness was evident in the host DNA-depleted samples compared with non-depleted controls in human colon biopsies and mouse colon tissues(P<0.001).Our optimized method of host DNA depletion improves the sensitivity of shotgun metagenomic sequencing in bacteria 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.
BACKGROUND Large abdominal wall defect(LAWD)caused by shotgun wound is rarely reported.CASE SUMMARY Herein,we describe a case of LAWD caused by a gunshot wound in which the abdominal wall was reconstructed in stages,including debridement,tensionreduced closure(TRC),and reconstruction with mesh and a free musculocutaneous flap.During a 3-year follow-up,the patient recovered well without hernia or other problems.CONCLUSION TRC is a practical approach for the temporary closure of LAWD,particularly in cases when one-stage abdominal wall restoration is unfeasible due to significant comorbidities.
Yan LiJia-Hua XingZheng YangYu-Jian XuXiang-Ye YinYuan ChiYi-Chi XuYu-Di HanYou-Bai ChenYan Han
Dysfunction of microbial communities in various human body sites has been shown to be associated with a variety of diseases raising the possibility of predicting diseases based on metagenomic samples.Although many studies have investigated this problem,there are no consensus on the optimal approaches for predicting disease status based on metagenomic samples.Using six human gut metagenomic datasets consisting of large numbers of colorectal cancer patients and healthy controls from different countries,we investigated different software packages for extracting relative abundances of known microbial genomes and for integrating mapping and as-sembly approaches to obtain the relative abundance profiles of both known and novel genomes.The random forests(RF)classification algorithm was then used to predict colorectal cancer status based on the microbial relative abundance profiles.Based on within data cross-validation and cross-dataset prediction,we show that the RF prediction performance using the microbial relative abundance profiles estimated by Centrifuge is generally higher than that using the microbial relative abundance profiles estimated by MetaPhlAn2 and Bracken.We also develop a novel method to integrate the relative abundance profiles of both known and novel microbial or-ganisms to further increase the prediction performance for colorectal cancer from metagenomes.
