Dataset Information

Microbiota and Metatranscriptome Changes Accompanying the Onset of Gingivitis.

ABSTRACT: Over half of adults experience gingivitis, a mild yet treatable form of periodontal disease caused by the overgrowth of oral microbes. Left untreated, gingivitis can progress to a more severe and irreversible disease, most commonly chronic periodontitis. While periodontal diseases are associated with a shift in the oral microbiota composition, it remains unclear how this shift impacts microbiota function early in disease progression. Here, we analyzed the transition from health to gingivitis through both 16S v4-v5 rRNA amplicon and metatranscriptome sequencing of subgingival plaque samples from individuals undergoing an experimental gingivitis treatment. Beta-diversity analysis of 16S rRNA reveals that samples cluster based on disease severity and patient but not by oral hygiene status. Significant shifts in the abundance of several genera occurred during disease transition, suggesting a dysbiosis due to development of gingivitis. Comparing taxonomic abundance with transcriptomic activity revealed concordance of bacterial diversity composition between the two quantification assays in samples originating from both healthy and diseased teeth. Metatranscriptome sequencing analysis indicates that during the early stages of transition to gingivitis, a number of virulence-related transcripts were significantly differentially expressed in individual and across pooled patient samples. Upregulated genes include those involved in proteolytic and nucleolytic processes, while expression levels of those involved in surface structure assembly and other general virulence functions leading to colonization or adaptation within the host are more dynamic. These findings help characterize the transition from health to periodontal disease and identify genes associated with early disease.IMPORTANCE Although more than 50% of adults have some form of periodontal disease, there remains a significant gap in our understanding of its underlying cause. We initiated this study in order to better characterize the progression from oral health to disease. We first analyzed changes in the abundances of specific microorganisms in dental plaque collected from teeth during health and gingivitis, the mildest form of periodontal disease. We found that the clinical score of disease and patient from whom the sample originated but not tooth brushing are significantly correlated with microbial community composition. While a number of virulence-related gene transcripts are differentially expressed in gingivitis samples relative to health, not all are increased, suggesting that the overall activity of the microbiota is dynamic during disease transition. Better understanding of which microbes are present and their function during early periodontal disease can potentially lead to more targeted prophylactic approaches to prevent disease progression.

SUBMITTER: Nowicki EM

PROVIDER: S-EPMC5904416 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Microbiota and Metatranscriptome Changes Accompanying the Onset of Gingivitis.

Nowicki Emily M EM Shroff Raghav R Singleton Jacqueline A JA Renaud Diane E DE Wallace Debra D Drury Julie J Zirnheld Jolene J Colleti Brock B Ellington Andrew D AD Lamont Richard J RJ Scott David A DA Whiteley Marvin M

mBio 20180417 2

Over half of adults experience gingivitis, a mild yet treatable form of periodontal disease caused by the overgrowth of oral microbes. Left untreated, gingivitis can progress to a more severe and irreversible disease, most commonly chronic periodontitis. While periodontal diseases are associated with a shift in the oral microbiota composition, it remains unclear how this shift impacts microbiota function early in disease progression. Here, we analyzed the transition from health to gingivitis thr ...[more]

PMID: 29666288

Similar Datasets

Project description:BACKGROUND: Microbial communities inhabiting human mouth are associated with oral health and disease. Previous studies have indicated the general prevalence of adult gingivitis in China to be high. The aim of this study was to characterize in depth the oral microbiota of Chinese adults with or without gingivitis, by defining the microbial phylogenetic diversity and community-structure using highly paralleled pyrosequencing. METHODS: Six non-smoking Chinese, three with and three without gingivitis (age range 21-39 years, 4 females and 2 males) were enrolled in the present cross-sectional study. Gingival parameters of inflammation and bleeding on probing were characterized by a clinician using the Mazza Gingival Index (MGI). Plaque (sampled separately from four different oral sites) and salivary samples were obtained from each subject. Sequences and relative abundance of the bacterial 16 S rDNA PCR-amplicons were determined via pyrosequencing that produced 400 bp-long reads. The sequence data were analyzed via a computational pipeline customized for human oral microbiome analyses. Furthermore, the relative abundances of selected microbial groups were validated using quantitative PCR. RESULTS: The oral microbiomes from gingivitis and healthy subjects could be distinguished based on the distinct community structures of plaque microbiomes, but not the salivary microbiomes. Contributions of community members to community structure divergence were statistically accessed at the phylum, genus and species-like levels. Eight predominant taxa were found associated with gingivitis: TM7, Leptotrichia, Selenomonas, Streptococcus, Veillonella, Prevotella, Lautropia, and Haemophilus. Furthermore, 98 species-level OTUs were identified to be gingivitis-associated, which provided microbial features of gingivitis at a species resolution. Finally, for the two selected genera Streptococcus and Fusobacterium, Real-Time PCR based quantification of relative bacterial abundance validated the pyrosequencing-based results. CONCLUSIONS: This methods study suggests that oral samples from this patient population of gingivitis can be characterized via plaque microbiome by pyrosequencing the 16 S rDNA genes. Further studies that characterize serial samples from subjects (longitudinal study design) with a larger population size may provide insight into the temporal and ecological features of oral microbial communities in clinically-defined states of gingivitis.

Project description:BACKGROUND: Next generation sequencing (NGS) technologies can be applied in complex microbial ecosystems for metatranscriptome analysis by employing direct cDNA sequencing, which is known as RNA sequencing (RNA-seq). RNA-seq generates large datasets of great complexity, the comprehensive interpretation of which requires a reliable bioinformatic pipeline. In this study, we focus on the development of such a metatranscriptome pipeline, which we validate using Illumina RNA-seq datasets derived from the small intestine microbiota of two individuals with an ileostomy. RESULTS: The metatranscriptome pipeline developed here enabled effective removal of rRNA derived sequences, followed by confident assignment of the predicted function and taxonomic origin of the mRNA reads. Phylogenetic analysis of the small intestine metatranscriptome datasets revealed a strong similarity with the community composition profiles obtained from 16S rDNA and rRNA pyrosequencing, indicating considerable congruency between community composition (rDNA), and the taxonomic distribution of overall (rRNA) and specific (mRNA) activity among its microbial members. Reproducibility of the metatranscriptome sequencing approach was established by independent duplicate experiments. In addition, comparison of metatranscriptome analysis employing single- or paired-end sequencing methods indicated that the latter approach does not provide improved functional or phylogenetic insights. Metatranscriptome functional-mapping allowed the analysis of global, and genus specific activity of the microbiota, and illustrated the potential of these approaches to unravel syntrophic interactions in microbial ecosystems. CONCLUSIONS: A reliable pipeline for metatransciptome data analysis was developed and evaluated using RNA-seq datasets obtained for the human small intestine microbiota. The set-up of the pipeline is very generic and can be applied for (bacterial) metatranscriptome analysis in any chosen niche.

Dataset Information

Microbiota and Metatranscriptome Changes Accompanying the Onset of Gingivitis.

Publications

Microbiota and Metatranscriptome Changes Accompanying the Onset of Gingivitis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets