Metagenomic Shotgun Sequencing Provides Prevalence Data for Pathogens, and Source-Tracking Indices Useful in Public Health Risk Assessment of Environmental Waters

State-approved membrane filtration (MF) techniques for water quality assessments were contrasted with metagenomic shotgun sequencing (MSS) protocols to evaluate their efficacy in providing precise health-risk indices for surface waters. Samples from a freshwater receiving pond (ABI-1002) and two upstream storm water ditches (ABI-1003) and (ABI-1004) yielded alarmingly high Fecal coliform MF densities of 220, >2000 and >2000 CFU/100ml respectively. The indicator, Enterococcus bacteria exceeded allowable limits in all but the equipment control (ABI-1001). Using MSS, the relative numerical abundance of pathogenic bacteria, virulence and antibiotic resistance genes revealed the status and potential pollution sources of each ditch. High levels of Shigella sp. (0 (ABI-1001), 4945 (ABI-1002), 55,008 (ABI-1003), and 2221 (ABI-1004) genomic reads/100ml) correlated with virulence genes and antibiotic resistance genes found in fecal samples for ABI1003 and not ABI1004. Traditional culture methods (TCM) showed possible fecal contamination in two of the four samples, and no contamination in the others. MSS clearly distinguished between fecal and environmental bacteria contamination sources, and pinpointed actual risks from pathogens. Our data underscore the potential utility of MSS in precision risk assessment for public and biodiversity health and tracking of environmental microbiomes shifts by field managers and policy makers.

Increasing prediction performance of colorectal cancer disease status using random forests classification based on metagenomic shotgun sequencing data

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.

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

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.

Life History Recorded in the Vagino-cervical Microbiome Along with Multi-omes

The vagina contains at least a billion microbial cells,dominated by lactobacilli.Here we perform metagenomic shotgun sequencing on cervical and fecal samples from a cohort of 516 Chinese women of reproductive age,as well as cervical,fecal,and salivary samples from a second cohort of 632 women.Factors such as pregnancy history,delivery history,cesarean section,and breastfeeding were all more important than menstrual cycle in shaping the microbiome,and such information would be necessary before trying to interpret differences between vagino-cervical microbiome data.Greater proportion of Bifidobacterium breve was seen with older age at sexual debut.The relative abundance of lactobacilli especially Lactobacillus crispatus was negatively associated with pregnancy history.Potential markers for lack of menstrual regularity,heavy flow,dysmenorrhea,and contraceptives were also identified.Lactobacilli were rare during breastfeeding or post-menopause.Other features such as mood fluctuations and facial speckles could potentially be predicted from the vagino-cervical microbiome.Gut and salivary microbiomes,plasma vitamins,metals,amino acids,and hormones showed associations with the vagino-cervical microbiome.Our results offer an unprecedented glimpse into the microbiota of the female reproductive tract and call for international collaborations to better understand its long-term health impact other than in the settings of infection or pre-term birth.

Seasonal variations in the composition and functional profiles of gut microbiota reflect dietary changes in plateau pikas

Seasonal variations in gut microbiota of small mammals and how they are influenced by environmental variables are relatively poorly understood.We sampled 162 wild plateau pikas(Ochotona curzoniae)in 4 seasons over 2 and a half years and recorded the air temperature,precipitation,and nutrient content in edible vegetation at the sampling site.After conducting 16S rRNA and shotgun metagenomic sequencing,we found that the highest alpha diversity,the relative abundance of Firmicutes,and the simplest co-occurrence network occurred in winter,whereas the highest relative abundance of Proteobacteria and the most complex network structure were observed in spring.The highest relative abundance of Verrucomicrobiota and Spirochaetota was seen in summer and autumn,respectively.Air temperature,precipitation,and the contents of crude protein,crude fiber,and polysaccharide in vegetation had significant effects on the seasonal changes in gut microbiota.Diet contributed more to microbial variation than climatic factors.Metagenomic analysis revealed that the amino acid metabolism pathway and axillary activity enzymes were most abundant in summer,while abundance of carbohydrate-binding modules and carbohydrate esterases was highest in spring.These microbial variations were related to the changes in dietary nutrition,indicating that gut microbiota of plateau pika contribute to the efficient use of food resources.This study provides new evidence of how external environmental factors affect the intestinal environment of small mammals.