Sequencing-based Metagenomics Research Articles

Comprehensive identification of pathogenic microbes and antimicrobial resistance genes in food products using nanopore sequencing-based metagenomics

Foodborne pathogens, particularly antimicrobial-resistant (AMR) bacteria, remain a significant threat to global health. Given the limitations of conventional culture-based approaches, which are limited in scope and time-consuming, metagenomic sequencing of food products emerges as a promising solution. This method provides a fast and comprehensive way to detect the presence of pathogenic microbes and antimicrobial resistance genes (ARGs). Notably, nanopore long-read sequencing provides more accurate bacterial taxonomic classification in comparison to short-read sequencing. Here, we revealed the impact of food types and attributes (origin, retail place, and food processing methods) on microbial communities and the AMR profile using nanopore metagenomic sequencing. We analyzed a total of 260 food products, including raw meat, sashimi, and ready-to-eat (RTE) vegetables. Clostridium botulinum, Acinetobacter baumannii, and Vibrio parahaemolyticus were identified as the top three foodborne pathogens in raw meat and sashimi. Importantly, even with low pathogen abundance, higher percentages of samples containing carbapenem and cephalosporin resistance genes were identified in chicken and RTE vegetables, respectively. In parallel, our results demonstrated that fresh, peeled, and minced foods exhibited higher levels of pathogenic bacteria. In conclusion, this comprehensive study offers invaluable data that can contribute to food safety assessments and serve as a basis for quality indicators.

A case series of co-infection in Mycobacterium tuberculosis and other pathogens: insights from nanopore sequencing

BackgroundTuberculosis (TB) continues to be a major global health burden, and co-infection with other pathogens further complicates the diagnosis and treatment of this infectious disease. The present retrospective study aimed to evaluate the clinical utility of nanopore sequencing in identifying co-infection caused by Mycobacterium tuberculosis (M.tb) and other pathogens.MethodsPatients with M.tb co-infection from December 2021 to March 2023 at the Jiangxi Provincial Chest Hospital were retrospectively studied. Data were collected including demographics, symptoms, imaging findings, pathogen diagnosis tests, and treatment history. Pathogen tests involved culture, AFB smear, Xpert MTB/RIF, and nanopore sequencing.ResultsThe enrolled patients included 20 M.tb cases and three nontuberculous mycobacteria (NTM) cases co-infected with other pathogens. Common clinical symptoms included cough (47.83%), expectoration (34.78%), and asthma (17.39%). Radiological examinations showed typical features of pulmonary tuberculosis, including nodules (73.91%), cord-like shadows (34.78%), cavities (34.78%), and destroyed lung manifestations (17.39%). Nanopore sequencing identified M.tb in a significant majority of the cases (86.96%), outperforming traditional culture tests (39.13%), acid-fast bacilli (AFB) tests (27.27%), and Xpert MTB/RIF (53.84%) tests. Notably, nanopore sequencing revealed that M.tb was frequently co-infected with Candida albicans, Klebsiella pneumoniae, and Mycobacterium abscessus. Three specific cases of co-infection with distinct diagnosis and treatment characteristics were presented in detail. They illustrated the complexity of TB co-infection management and the potential of nanopore sequencing for accurate diagnosis and informing the tailored therapeutic approaches.ConclusionNanopore sequencing-based metagenomics method can help clinicians to identify TB co-infection patterns and formulate a rational drug regimen in time.

Air monitoring by nanopore sequencing.

While the air microbiome and its diversity are essential for human health and ecosystem resilience, comprehensive air microbial diversity monitoring has remained rare, so that little is known about the air microbiome's composition, distribution, or functionality. Here we show that nanopore sequencing-based metagenomics can robustly assess the air microbiome in combination with active air sampling through liquid impingement and tailored computational analysis. We provide fast and portable laboratory and computational approaches for air microbiome profiling, which we leverage to robustly assess the taxonomic composition of the core air microbiome of a controlled greenhouse environment and of a natural outdoor environment. We show that long-read sequencing can resolve species-level annotations and specific ecosystem functions through de novo metagenomic assemblies despite the low amount of fragmented DNA used as an input for nanopore sequencing. We then apply our pipeline to assess the diversity and variability of an urban air microbiome, using Barcelona, Spain, as an example; this randomized experiment gives first insights into the presence of highly stable location-specific air microbiomes within the city's boundaries, and showcases the robust microbial assessments that can be achieved through automatable, fast, and portable nanopore sequencing technology.

322. Clinical-Grade Metagenomics in Urinary Tract Infections: Improving Performance of Next-Generation Sequencing Assays Using Internal Controls and Machine Learning

Abstract Background Shotgun sequencing-based metagenomics is a useful approach to profiling microbiomes in environmental and patient samples. In a clinical setting, metagenomic techniques have the advantage of identifying organisms, which cannot be readily cultured or confirmed by other techniques. We have developed a clinical-grade, streamlined metagenomics-based pipeline that includes regulatory compliant method considerations, such as an internal control followed by a machine-based learning (ML) process to identify pathogens in urine samples. Methods We built an optimized novel end-to-end NGS assay pipeline that harnesses pathogen-specific genome data to detect bacterial species. We processed de-identified clinical urine specimens, collected from patients symptomatic for urinary tract infection (UTI). This workflow includes an IPC, QIACube-MDx extraction, library preparation and Illumina NextSeq 550 sequencing and a novel interpretable ML based analytic approach, Biotia-DX. Clinical culture results and qPCR were used as a baseline for the assay to train the ML model and to establish accuracy relative to the clinical standard of care. Results We clinically validated over 40 key uropathogens and conducted clinical studies of specificity, intra/inter reproducibility, accuracy in urine specimens (n=300), and limit of detection in E. coli, K. pneumoniae, P. mirabilis, S. aureus, E. faecalis and Candida. Additionally, the implementation of an internal control coupled with our Biotia-DX software provides an accurate (F1 score 94.3%) and highly sensitive clinical grade diagnostic tool. Conclusion Urine has historically presented a challenge for diagnostics via culturing, with a high rate of culture-negative results (∼30% on average). We improved the clinical utility of an NGS urine assay by leveraging an IPC and ML software. This decreased the rate of false positive species called in a sample relative to other NGS techniques and allows for greater sensitivity and taxonomic specificity. This assay may be especially useful for low colony-count or negative-culture samples to diagnose and guide patient treatment. Disclosures Mara Couto-Rodriguez, MS, Biotia Inc.: Employee of Biotia Inc. a for-profit biotechnology company David C. Danko, PhD, Biotia Inc.: Employee of Biotia Inc. a for-profit biotechnology company Xavier O. Jirau Serrano, MS, Biotia Inc.: Employee of Biotia Inc. a for-profit biotechnology company Taylor Paisie, MS, Biotia Inc.: Employee of Biotia Inc. a for-profit biotechnology company John C. Papciak, BS, Biotia Inc.: Employee of Biotia Inc. a for-profit biotechnology company Eszter Szollosi, BS, Biotia Inc.: Employee of Biotia Inc. a for-profit biotechnology company Christopher E. Mason, PhD, Biotia Inc.: Advisor/Consultant|Biotia Inc.: Board Member|Biotia Inc.: Ownership Interest Caitlin Otto, PhD, D(ABMM), Biotia Inc.: Advisor/Consultant Niamh B. O'Hara, PhD, Biotia Inc.: Board Member|Biotia Inc.: Ownership Interest Dorottya Nagy-Szakal, MD PhD, Biotia Inc.: Employee of Biotia Inc. a for-profit biotechnology company|Biotia Inc.: Stocks/Bonds.

Permafrost thaw with warming reduces microbial metabolic capacities in subsurface soils.

Microorganisms are major constituents of the total biomass in permafrost regions, whose underlain soils are frozen for at least two consecutive years. To understand potential microbial responses to climate change, here we examined microbial community compositions and functional capacities across four soil depths in an Alaska tundra site. We showed that a 5-year warming treatment increased soil thaw depth by 25.7% (p = .011) within the deep organic layer (15-25cm). Concurrently, warming reduced 37% of bacterial abundance and 64% of fungal abundances in the deep organic layer, while it did not affect microbial abundance in other soil layers (i.e., 0-5, 5-15, and 45-55cm). Warming treatment altered fungal community composition and microbial functional structure (p < .050), but not bacterial community composition. Using a functional gene array, we found that the relative abundances of a variety of carbon (C)-decomposing, iron-reducing, and sulphate-reducing genes in the deep organic layer were decreased, which was not observed by the shotgun sequencing-based metagenomics analysis of those samples. To explain the reduced metabolic capacities, we found that warming treatment elicited higher deterministic environmental filtering, which could be linked to water-saturated time, soil moisture, and soil thaw duration. In contrast, plant factors showed little influence on microbial communities in subsurface soils below 15cm, despite a 25.2% higher (p < .05) aboveground plant biomass by warming treatment. Collectively, we demonstrate that microbial metabolic capacities in subsurface soils are reduced, probably arising from enhanced thaw by warming.

A novel enterovirus in lambs with poliomyelitis and brain stem encephalitis.

An Austrian organic dairy sheep farm experienced cases of recumbency and sudden deaths in 3‐ to 4‐week‐old lambs. Two animals were subjected to thorough clinical and pathological investigations. Pathohistological analysis identified severe nonsuppurative myelitis and mild nonsuppurative encephalitis. A reverse‐transcription quantitative PCR (RT‐qPCR) assay for the recently discovered ovine picornavirus causing comparable lesions scored negative. By next‐generation sequencing‐based metagenomics, a nearly complete genome of a novel enterovirus could be detected and assembled. In situ hybridization using a specifically designed probe revealed robust signals in affected motoneurons of the spinal cord suggesting a causative role of the novel virus.

Estuarine salinity gradient governs sedimentary bacterial community but not antibiotic resistance gene profile

Antibiotic resistance gene (ARG) pollution in estuarine environment has drawn great attention, and it is not clear if the physical and chemical parameters such as salinity, total organic carbon, total nitrogen, total phosphorus and antibiotics affects the distribution of ARGs. Herein, we deciphered the ARG profiles and microbial community compositions in sediments from Jiulong River Estuary (JRE) and Min River Estuary (MRE) of China using high-throughput sequencing-based metagenomics analysis. Furthermore, we explored the influence of salinity on bacterial community and ARG profiles. The results showed that Proteobacteria, Chloroflexi, and Acidobacteria were the dominant phyla in these two estuaries. The abundance of ARGs ranged from 1.05 × 10−1 to 2.93 × 10−1 copy of ARG per copy of 16S rRNA gene in all the sediment samples and the profiles of ARGs presented similar patterns in two estuaries. Multidrug resistance genes were the dominant ARG types in both estuaries, with an overall abundance of 2.39 × 10−2–1.07 × 10−1 copy of ARG per copy of 16S rRNA gene, followed by genes conferring resistance to bacitracin and macrolide-lincosamide-streptogramin. Salinity was an important influencing factor on the bacterial community but not on the ARG profiles. Instead, stochastic processes exerted the main influence on the distribution of ARGs. The comparison of ARG profiles among estuary sediments, marine sediments, and samples from anthropogenic pollution environments revealed remarkable similarity of ARG profiles between samples from estuary sediments and those from municipal wastewater treatment plants. These results suggested that the complex emission of anthropogenic pollution could cause the stochastic ecological pattern of ARGs.

Strategies for Natural Products Discovery from Uncultured Microorganisms

Microorganisms are highly regarded as a prominent source of natural products that have significant importance in many fields such as medicine, farming, environmental safety, and material production. Due to this, only tiny amounts of microorganisms can be cultivated under standard laboratory conditions, and the bulk of microorganisms in the ecosystems are still unidentified, which restricts our knowledge of uncultured microbial metabolism. However, they could hypothetically provide a large collection of innovative natural products. Culture-independent metagenomics study has the ability to address core questions in the potential of NP production by cloning and analysis of microbial DNA derived directly from environmental samples. Latest advancements in next generation sequencing and genetic engineering tools for genome assembly have broadened the scope of metagenomics to offer perspectives into the life of uncultured microorganisms. In this review, we cover the methods of metagenomic library construction, and heterologous expression for the exploration and development of the environmental metabolome and focus on the function-based metagenomics, sequencing-based metagenomics, and single-cell metagenomics of uncultured microorganisms.

Effects on microbiomes and resistomes and the source-specific ecological risks of heavy metals in the sediments of an urban river

This study aims to better understand the effects of heavy metal enrichment on microbiomes and resistomes and the source-specific ecological risks of metals in the sediments of an urban river. Geo-accumulation index and enrichment factor suggested the river sediments were contaminated by Cd, Cu, Pb, and Zn in varying degrees. High-throughput sequencing-based metagenomics analysis identified 430 types of antibiotic resistance genes (ARGs), dominated by the multidrug, MLS, bacitracin, quinolone, and aminoglycoside ARGs, and 52 metal resistance genes (MRGs) mainly conferring resistance to zinc, copper, cadmium, lead, mercury and multiple metals. Spearman correlation analysis and Mantel test showed the heavy metal enrichment exerted significant effects on the microbial community, ARGs and MRGs. Source apportionment using positive matrix factorization revealed that natural source (42.8%) was the largest contributor of metals in the river sediments, followed by urban activities (35.4%) and a mixed source (21.7%). However, when incorporating the apportionment results into a modified risk model to evaluate the source-specific ecological risks, results showed human activities dominated the risks of metals. Comparatively, the urban activities majorly caused moderate- and considerable- ecological risks, while the mixed source with respect to agricultural and industrial activities contributed higher percentages on high- and extremely high- ecological risks.

Microbial Diversity Analysis in the Oxygen Minimum Zones of the Arabian Sea using Metagenomics Approach

Large oxygen-depleted areas known as oxygen minimum zones (OMZs) have been reported from the Arabian Sea, and recent reports indicate that these areas are expanding at an alarming rate. In marine waters, oxygen depletion may also be related to global warming and temperature rise. The acidification and deoxygenation due to OMZs can lead to major consequences wherein the plants, fish and other biota will struggle to survive in the ecosystem. The present study has identified the microbial community structure using next generation sequencing-based metagenomics analysis in water sa mples collected at different depths from the OMZs and non-OMZs of the Arabian Sea. Environmental variables such as depth, site of collection and oxygen concentration might influence species richness and evenness among microbial communities in these locations. Our observations suggest that population dynamics of microbes consisting of nitrate reducers accompanied by sulphate reducers and sulphur oxidizers influences the interconnected geoche mical cycles of OMZs. In addition to providing baseline data related to the diversity and microbial community dynamics in waters in the OMZs; such analysis can provide insight into processes regulating productivity and ecological co mmunity structure of the ocean.

Near-Complete Genome Sequence of a Hepatitis A Subgenotype IB Virus Isolated from Frozen Raspberries

Hepatitis A virus is one of the most common causes of foodborne viral illness. Here, we report the nearly complete genome sequence of a hepatitis A virus (subgenotype IB) isolated from frozen raspberries using RNA sequencing-based metagenomics.

Characterization of antibiotic resistance genes in the sediments of an urban river revealed by comparative metagenomics analysis

The over-use of antibiotics causes growing concerns about human health risks induced by increasing rates of antimicrobial resistance. Riverine systems are considered generally as a natural reservoir of antibiotic resistance genes (ARGs). In this study, several methods including high-throughput sequencing-based metagenomics approach, statistical analysis and network analysis were applied jointly to characterize the wide-spectrum profile of ARGs in the sediments of an urban river in Beijing. Furthermore, contribution of human activities for the presence of ARGs was identified through comparative studies on the metagenomic profiling of ARGs between the river sediments and pristine niches (remote Antarctic soils and deep sea sediments). In total, 442 ARG subtypes belonging to 22 ARG types were detected in the human-impacted river sediments with an abundance range of 1.1 × 10−1–8.1 × 10−1 copy of ARG per copy of 16S-rRNA gene. The most abundant and diverse ARGs were commonly associated with antibiotics that have been extensively used in that area, likely indicating the spread of ARGs in river environments because of the selective pressure resulting from antibiotic use. As a whole, anthropogenic activities were the dominant contributor of major ARG types, for example, occupying 100% for sulfonamide-ARGs, 97% for beta-lactam-ARGs, 94% for aminoglycoside-ARGs and 64% for tetracycline-ARGs. This study provides insights into the role of human activities in accelerating the dissemination and proliferation of ARGs in urban river environment and draws attention to controlling the use and discharge of antibiotics for protection of public health.

Recovery of gut microbiota of healthy adults following antibiotic exposure.

To minimize the impact of antibiotics, gut microorganisms harbour and exchange antibiotics resistance genes, collectively called their resistome. Using shotgun sequencing-based metagenomics, we analysed the partial eradication and subsequent regrowth of the gut microbiota in 12 healthy men over a 6-month period following a 4-day intervention with a cocktail of 3 last-resort antibiotics: meropenem, gentamicin and vancomycin. Initial changes included blooms of enterobacteria and other pathobionts, such as Enterococcus faecalis and Fusobacterium nucleatum, and the depletion of Bifidobacterium species and butyrate producers. The gut microbiota of the subjects recovered to near-baseline composition within 1.5 months, although 9 common species, which were present in all subjects before the treatment, remained undetectable in most of the subjects after 180 days. Species that harbour β-lactam resistance genes were positively selected for during and after the intervention. Harbouring glycopeptide or aminoglycoside resistance genes increased the odds of de novo colonization, however, the former also decreased the odds of survival. Compositional changes under antibiotic intervention in vivo matched results from in vitro susceptibility tests. Despite a mild yet long-lasting imprint following antibiotics exposure, the gut microbiota of healthy young adults are resilient to a short-term broad-spectrum antibiotics intervention and their antibiotics resistance gene carriage modulates their recovery processes.

Changes of microbial community and metabolite in kimchi inoculated with different microbial community starters

Gas chromatography mass spectrometry-based metabolomics and next generation sequencing-based metagenomics were applied to investigate the effect of different microbial community starters (MCSs) on kimchi fermentation. Profiles of metabolites and microbial community in kimchi were remarkably different from those on the first day of fermentation according to MCS used. Kimchi inoculated with MCS5 or MCS10 had relatively higher levels of lactic acid, leucine, propanedioic acid, serine, glycerol, erythritol, and sorbitol but lower levels of butanedioic acid, glyceric acid, myo-inositol, xylose, fructose, and talose compared to control kimchi or kimchi inoculated with MCS1. Microbial communities of kimchi inoculated with MCS1, MCS5, and MCS10 were characterized by high ratios of Leuconostoc, Lactobacillus plantarum, and Lactobacillus brevis, respectively. The microbial community of kimchi formed on the first day of fermentation was stable for 50 days, suggesting that microbial communities containing multiple microorganisms can be used as starters to obtain desired quality of kimchi.

Metagenomics for the diagnosis of exotic infections

Next-generation sequencing-based metagenomics provides a powerful tool for hypothesis-free detection of unexpected and exotic pathogens. While proof-of-concept has been well established, the performance of metagenomics compared to traditional approaches is less well understood. We have demonstrated in retrospective studies that metagenomics can improve diagnostic yield compared to culture and PCR-based tests, especially in patients with complex healthcare needs. Results from metagenomics testing of patients with respiratory tract infections, fever of unknown origin, and encephalitis/meningitis will be discussed. Performing metagenomics in diagnostic laboratories with controlled and consistent quality remains challenging. While lessons can be learned from NGS testing in other disciplines, many challenges pertaining to specimen processing, data analysis, and reference sequence databases are unique to the field of microbiology. We have developed and validated a metagenomics-based test for detection of respiratory pathogens. This test makes extensive use of internal and external controls and was validated using both, real and virtual patient samples. Current challenges and potential solutions will be reviewed.

Microbial effects of part-stream low-frequency ultrasonic pretreatment on sludge anaerobic digestion as revealed by high-throughput sequencing-based metagenomics and metatranscriptomics

BackgroundPart-stream low-frequency ultrasound (LFUS) was one of the common practices for sludge disintegration in full-scale anaerobic digestion (AD) facilities. However, the effectiveness of part-stream LFUS treatment and its effect on AD microbiome have not been fully elucidated.MethodsHere we testified the effectiveness of part-stream LFUS pretreatment by treating only a fraction of feed sludge (23% and 33% total solid of the feed sludge) with 20 Hz LFUS for 70 s. State-of-the-art metagenomic and metatranscriptomic analysis was used to investigate the microbial process underpinning the enhanced AD performance by part-stream LFUS pretreatment.ResultsBy pretreating 33% total solid of the feed sludge, methane yield was increased by 36.5%, while the volatile solid reduction ratio remained unchanged. RNA-seq of the microbiome at stable stage showed that the continuous dosage of easy-degradable LFUS-pretreated feed sludge had gradually altered the microbial community by selecting Bacteroidales hydrolyzer with greater metabolic capability to hydrolyze cellulosic biomass without substrate attachment. Meanwhile, Thermotogales with excellent cell mobility for nutrient capturing was highly active within the community. Foremost proportion of the methanogenesis was contributed by the dominant Methanomicrobiales via carbon dioxide reduction. More interestingly, a perceivable proportion of the reverse electron flow of the community was input from Methanoculleus species other than syntrophic acetate-oxidizing bacteria. In addition, metagenomic binning retrieved several interesting novel metagenomic-assembled genomes (MAGs): MAG-bin6 of Alistipes shahii showed exceptional transcriptional activities towards protein degradation and MAG-bin11 of Candidatus Cloacimonetes with active cellulolytic GH74 gene detected.ConclusionsIn summary, despite the unchanged sludge digestibility, the applied part-stream LFUS pretreatment strategy was robust in adjusting the microbial pathways towards more effective substrate conversion enabled by free-living hydrolyser and beta-oxidation-capable methanogens.

Free-living bacteria and potential bacterial pathogens in sewage treatment plants.

To comprehensively understand the profile of free-living bacteria and potential bacterial pathogens in sewage treatment plants (STPs), this study applied high-throughput sequencing-based metagenomics approaches to investigate the effects of activated sludge (AS) treatment process and ultraviolet (UV) disinfection on the community of bacterial pathogens in two full-scale STPs. A total of 23 bacterial genera were identified as free-living bacteria, and 243 species/OTU97% were identified as potential bacterial pathogens, 6 of which were confidently detected in the STPs (with the total abundances ranging from 0.02 to 14.19%). Both diversity and relative abundance of the detected bacterial pathogens decreased obviously after AS treatment process (p < 0.05), and increased slightly after sedimentation (p < 0.05). UV disinfection shows no obvious effects on the total relative abundance of the free-living pathogenic bacteria in sewage. Although large amounts of the particle-bound pathogens were eliminated through the sewage treatment process, the STPs could not effectively remove the free-living bacterial pathogens, and some pathogenic bacteria (e.g., Pseudomonas aeruginosa) present in the effluent had higher relative abundance after UV disinfection. Overall, the results extend our knowledge regarding the community of potential pathogens (especially free-living pathogens) in STPs.

Effects of sample preservation and DNA extraction on enumeration of antibiotic resistance genes in wastewater.

With the growing application of high-throughput sequencing-based metagenomics for profiling antibiotic resistance genes (ARGs) in wastewater treatment plants (WWTPs), comparison of sample pretreatment and DNA extraction methods are needed to move toward standardized comparisons among laboratories. Three widely employed DNA extraction methods (FastDNA® Spin Kit for Soil, PowerSoil® DNA Isolation Kit and ZR Fecal DNA MiniPrep), with and without preservation in 50% ethanol and freezing, were applied to the influent, activated sludge and effluent of two WWTPs, in Hong Kong and in the USA. Annotated sequences obtained from the DNA extracted using the three kits shared similar taxonomy and ARG profiles. Overall, it was found that the DNA yield and purity, and diversity of ARGs captured were all highest when applying the FastDNA SPIN Kit for Soil for all three WWTP sample types investigated here (influent, activated sludge, effluent). Quantitative polymerase chain reaction of 16S rRNA genes confirmed the same trend as DNA extraction yields and similar recovery of a representative Gram-negative bacterium (Escherichia coli). Moreover, sample fixation in ethanol, deep-freezing and overseas shipment had no discernable effect on ARG profiles, as compared to fresh samples. This approach serves to inform future efforts toward global comparisons of ARG distributions in WWTPs.

Porphyromonas gingivalis is the most abundant species detected in coronary and femoral arteries

ABSTRACTAn association between oral bacteria and atherosclerosis has been postulated. A limited number of studies have used 16S RNA gene sequencing-based metagenomics approaches to identify bacteria at the species level from atherosclerotic plaques in arterial walls. The objective of this study was to establish detailed oral microbiome profiles, at both genus and species level, of clinically healthy coronary and femoral artery tissues from patients with atherosclerosis. Tissue specimens were taken from clinically non-atherosclerotic areas of coronary or femoral arteries used for attachment of bypass grafts in 42 patients with atherosclerotic cardiovascular disease. Bacterial DNA was sequenced using the MiSeq platform, and sequence reads were screened in silico for nearly 600 oral species using the HOMINGS ProbeSeq species identification program. The number of sequence reads matched to species or genera were used for statistical analyses. A total of 230 and 118 species were detected in coronary and femoral arteries, respectively. Unidentified species detected by genus-specific probes consisted of 45 and 30 genera in coronary and in femoral artery tissues, respectively. Overall, 245 species belonging to 95 genera were detected in coronary and femoral arteries combined. The most abundant species were Porphyromonas gingivalis, Enterococcus faecalis, and Finegoldia magna based on species probes. Porphyromonas, Escherichia, Staphylococcus, Pseudomonas, and Streptococcus genera represented 88.5% mean relative abundance based on combined species and genus probe detections. Porphyromonas was significantly more abundant than Escherichia (i.e. 46.8% vs. 19.3%; p = 0.0005). This study provides insight into the presence and types of oral microbiome bacterial species found in clinically non-atherosclerotic arteries.

MetaDP: a comprehensive web server for disease prediction of 16S rRNA metagenomic datasets.

High-throughput sequencing-based metagenomics has garnered considerable interest in recent years. Numerous methods and tools have been developed for the analysis of metagenomic data. However, it is still a daunting task to install a large number of tools and complete a complicated analysis, especially for researchers with minimal bioinformatics backgrounds. To address this problem, we constructed an automated software named MetaDP for 16S rRNA sequencing data analysis, including data quality control, operational taxonomic unit clustering, diversity analysis, and disease risk prediction modeling. Furthermore, a support vector machine-based prediction model for intestinal bowel syndrome (IBS) was built by applying MetaDP to microbial 16S sequencing data from 108 children. The success of the IBS prediction model suggests that the platform may also be applied to other diseases related to gut microbes, such as obesity, metabolic syndrome, or intestinal cancer, among others (http://metadp.cn:7001/).