Dataset Information

Oral Health: The Need for Both Conventional Microbial and Molecular Characterization.

ABSTRACT: This study aims to consider the microbial distribution in oral disease, as well as gene analysis and expression, in elucidating: 1, the fundamental underpinnings of oral disease, and 2, the potential relationship between oral diseases and systemic health. A key focus is identifying the microbiota associated with oral disease manifestations characterized by both conventional microbiological and molecular methods. Variations in the observed microbial populations characterized by conventional and molecular approaches have been identified for caries, periodontitis, peri-implantitis, and stomatitis. The discovery of therapeutic approaches for oral disease will require comprehensive microbial and genomic analysis. This study evaluated the current state of the relevant microbial and genomic information for several prevalent oral diseases.

SUBMITTER: Friedman E

PROVIDER: S-EPMC5734190 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Oral Health: The Need for Both Conventional Microbial and Molecular Characterization.

Friedman Elisheva E Alizadeh Negin N Loewy Zvi Z

High-throughput 20170801 3

This study aims to consider the microbial distribution in oral disease, as well as gene analysis and expression, in elucidating: 1, the fundamental underpinnings of oral disease, and 2, the potential relationship between oral diseases and systemic health. A key focus is identifying the microbiota associated with oral disease manifestations characterized by both conventional microbiological and molecular methods. Variations in the observed microbial populations characterized by conventional and m ...[more]

PMID: 29485609

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Project description:Metagenomic investigations have the potential to provide unprecedented insights into microbial ecologies, such as those relating to antimicrobial resistance (AMR). We characterized the microbial resistome in livestock operations raising cattle conventionally (CONV) or without antibiotic exposures (RWA) using shotgun metagenomics. Samples of feces, wastewater from catchment basins, and soil where wastewater was applied were collected from CONV and RWA feedlot and dairy farms. After DNA extraction and sequencing, shotgun metagenomic reads were aligned to reference databases for identification of bacteria (Kraken) and antibiotic resistance genes (ARGs) accessions (MEGARes). Differences in microbial resistomes were found across farms with different production practices (CONV vs. RWA), types of cattle (beef vs. dairy), and types of sample (feces vs. wastewater vs. soil). Feces had the greatest number of ARGs per sample (mean = 118 and 79 in CONV and RWA, respectively), with tetracycline efflux pumps, macrolide phosphotransferases, and aminoglycoside nucleotidyltransferases mechanisms of resistance more abundant in CONV than in RWA feces. Tetracycline and macrolide-lincosamide-streptogramin classes of resistance were more abundant in feedlot cattle than in dairy cow feces, whereas the β-lactam class was more abundant in dairy cow feces. Lack of congruence between ARGs and microbial communities (procrustes analysis) suggested that other factors (e.g., location of farms, cattle source, management practices, diet, horizontal ARGs transfer, and co-selection of resistance), in addition to antimicrobial use, could have impacted resistome profiles. For that reason, we could not establish a cause-effect relationship between antimicrobial use and AMR, although ARGs in feces and effluents were associated with drug classes used to treat animals according to farms' records (tetracyclines and macrolides in feedlots, β-lactams in dairies), whereas ARGs in soil were dominated by multidrug resistance. Characterization of the "resistance potential" of animal-derived and environmental samples is the first step toward incorporating metagenomic approaches into AMR surveillance in agricultural systems. Further research is needed to assess the public-health risk associated with different microbial resistomes.

Project description:Inter-individual variability in the microbial gene complement encoding for carbohydrate-active enzymes (CAZymes) can profoundly regulate how the host interacts with diverse carbohydrate sources thereby influencing host health. CAZy-typing, characterizing the microbiota-associated CAZyme-coding genes within a host individual, can be a useful tool to predict carbohydrate pools that the host can metabolize, or identify which CAZyme families are underrepresented requiring supplementation via microbiota transplantation or probiotics. CAZy-typing, moreover, provides a novel framework to search for disease biomarkers. As a proof of concept, we used publicly available metagenomes (935) representing 310 type strain bacterial genomes to establish the link between disease status and CAZymes in the oral and gut microbial ecosystem. The abundance and distribution of 220 recovered CAZyme families in saliva and stool samples from patients with colorectal cancer, rheumatoid arthritis, and type 1 diabetes were compared with healthy subjects. Based on the multivariate discriminant analysis, the disease phenotype did not alter the CAZyme profile suggesting a functional conservation in carbohydrate metabolism in a disease state. When disease and healthy CAZyme profiles were contrasted in differential analysis, CAZyme markers that were underrepresented in type 1 diabetes (15), colorectal cancer (12), and rheumatoid arthritis (5) were identified. Of interest, are the glycosyltransferase which can catalyze the synthesis of glycoconjugates including lipopolysaccharides with the potential to trigger inflammation, a common feature in many diseases. Our analysis has also confirmed the expansive carbohydrate metabolism in the gut as evidenced by the overrepresentation of CAZyme families in the gut compared to the oral site. Nevertheless, each site exhibited specific CAZyme markers. Taken together, our analysis provides an insight into the CAZyme landscape in health and disease and has demonstrated the diversity in carbohydrate metabolism in host-microbiota which can be a sound basis for optimizing the selection of pre, pro, and syn-biotic candidate products.

Dataset Information

Oral Health: The Need for Both Conventional Microbial and Molecular Characterization.

Publications

Oral Health: The Need for Both Conventional Microbial and Molecular Characterization.

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