Subgingival Microbiota Dysbiosis in Systemic Lupus Erythematosus: Association with Periodontal Status

Background Periodontitis results from the interaction between a subgingival biofilm and host immune response. Changes in biofilm composition are thought to disrupt homeostasis between the host and subgingival bacteria resulting in periodontal damage. Chronic systemic inflammatory disorders have been shown to affect the subgingival microbiota and clinical periodontal status. However, this relationship has not been examined in subjects with systemic lupus erythematosus (SLE). The objective of our study was to investigate the influence of SLE on the subgingival microbiota and its connection with periodontal disease and SLE activity. Methods We evaluated 52 patients with SLE compared to 52 subjects without SLE (control group). Subjects were classified as without periodontitis and with periodontitis. Oral microbiota composition was assessed by amplifying the V4 region of 16S rRNA gene from subgingival dental plaque DNA extracts. These amplicons were examined by Illumina MiSeq sequencing. Results SLE patients exhibited higher prevalence of periodontitis which occurred at a younger age compared to subjects of the control group. More severe forms of periodontitis were found in SLE subjects that had higher bacterial loads and decreased microbial diversity. Bacterial species frequently detected in periodontal disease were observed in higher proportions in SLE patients, even in periodontal healthy sites such as Fretibacterium, Prevotella nigrescens, and Selenomonas. Changes in the oral microbiota were linked to increased local inflammation, as demonstrated by higher concentrations of IL-6, IL-17, and IL-33 in SLE patients with periodontitis. Conclusions SLE is associated with differences in the composition of the microbiota, independently of periodontal status. Electronic supplementary material The online version of this article (doi:10.1186/s40168-017-0252-z) contains supplementary material, which is available to authorized users

CORE: A Phylogenetically-Curated 16S rDNA Database of the Core Oral Microbiome

Comparing bacterial 16S rDNA sequences to GenBank and other large public databases via BLAST often provides results of little use for identification and taxonomic assignment of the organisms of interest. The human microbiome, and in particular the oral microbiome, includes many taxa, and accurate identification of sequence data is essential for studies of these communities. For this purpose, a phylogenetically curated 16S rDNA database of the core oral microbiome, CORE, was developed. The goal was to include a comprehensive and minimally redundant representation of the bacteria that regularly reside in the human oral cavity with computationally robust classification at the level of species and genus. Clades of cultivated and uncultivated taxa were formed based on sequence analyses using multiple criteria, including maximum-likelihood-based topology and bootstrap support, genetic distance, and previous naming. A number of classification inconsistencies for previously named species, especially at the level of genus, were resolved. The performance of the CORE database for identifying clinical sequences was compared to that of three publicly available databases, GenBank nr/nt, RDP and HOMD, using a set of sequencing reads that had not been used in creation of the database. CORE offered improved performance compared to other public databases for identification of human oral bacterial 16S sequences by a number of criteria. In addition, the CORE database and phylogenetic tree provide a framework for measures of community divergence, and the focused size of the database offers advantages of efficiency for BLAST searching of large datasets. The CORE database is available as a searchable interface and for download at http://microbiome.osu.edu

The Drosophila melanogaster host model

The deleterious and sometimes fatal outcomes of bacterial infectious diseases are the net result of the interactions between the pathogen and the host, and the genetically tractable fruit fly, Drosophila melanogaster, has emerged as a valuable tool for modeling the pathogen–host interactions of a wide variety of bacteria. These studies have revealed that there is a remarkable conservation of bacterial pathogenesis and host defence mechanisms between higher host organisms and Drosophila. This review presents an in-depth discussion of the Drosophila immune response, the Drosophila killing model, and the use of the model to examine bacterial–host interactions. The recent introduction of the Drosophila model into the oral microbiology field is discussed, specifically the use of the model to examine Porphyromonas gingivalis–host interactions, and finally the potential uses of this powerful model system to further elucidate oral bacterial-host interactions are addressed

High-resolution ISR amplicon sequencing reveals personalized oral microbiome

Abstract Background Sequencing of the 16S rRNA gene has been the standard for studying the composition of microbial communities. While it allows identification of bacteria at the level of species, this method does not usually provide sufficient information to resolve communities at the sub-species level. Species-level resolution is not adequate for studies of transmission or stability or for exploring subspecies variation in disease association. Strain level analysis using whole metagenome shotgun sequencing has significant limitations that can make it unsuitable for large-scale studies. Achieving sufficient depth of sequencing can be cost-prohibitive, and even with adequate coverage, deconvoluting complex communities such as the oral microbiota is computationally very challenging. Thus, there is a need for high-resolution, yet cost-effective, high-throughput methods for characterizing microbial communities. Results Significant improvement in resolution for amplicon-based bacterial community analysis was achieved by combining amplicon sequencing of a high-diversity marker gene, the ribosomal 16-23S intergenic spacer region (ISR), with a probabilistic error modeling based denoising algorithm, DADA2. The resolving power of this new approach was compared to that of both standard and high-resolution 16S-based approaches using a set of longitudinal subgingival plaque samples. The ISR strategy resulted in a 5.2-fold increase in community resolution compared to reference-based 16S rRNA gene analysis and showed 100% accuracy in predicting the correct source of a clinical sample. Individuals’ microbial communities were highly personalized, and although they exhibited some drift in membership and levels over time, that difference was always smaller than the differences between any two subjects, even after 1 year. The construction of an ISR database from publicly available genomic sequences allowed us to explore genomic variation within species, resulting in the identification of multiple variants of the ISR for most species. Conclusions The ISR approach resulted in significantly improved resolution of communities and revealed a highly personalized human oral microbiota that was stable over 1 year. Multiple ISR types were observed for all species examined, demonstrating a high level of subspecies variation in the oral microbiota. The approach is high-throughput, high-resolution yet cost-effective, allowing subspecies-level community fingerprinting at a cost comparable to that of 16S rRNA gene amplicon sequencing. It will be useful for a range of applications that require high-resolution identification of organisms, including microbial tracking, community fingerprinting, and potentially for identification of virulence-associated strains

Porphyromonas gingivalis Strain Diversity▿ †

Porphyromonas gingivalis is implicated in the etiology of chronic periodontitis. Genotyping studies suggest that genetic variability exists among P. gingivalis strains; however, the extent of variability remains unclear and regions of variability remain largely unidentified. To assess P. gingivalis strain diversity, we previously used heteroduplex analysis of the ribosomal operon intergenic spacer region (ISR) to type strains in clinical samples and identified 22 heteroduplex types. Additionally, we used ISR sequence analysis to determine the relatedness of P. gingivalis strains to one another and demonstrated a link between ISR sequence phylogeny and the disease-associated phenotype of the strains. In the current study, heteroduplex analysis of the ISR was used to determine the worldwide genetic variability and distribution of P. gingivalis, and microarray-based comparative genomic hybridization (CGH) analysis was used to more comprehensively examine the variability of major heteroduplex type strains by using the entire genome. Heteroduplex analysis of clinical samples from geographically diverse populations identified 6 predominant geographically widespread heteroduplex types (prevalence, ≥5%) and 14 rare heterodpulex types (prevalence, <2%) which are found in one or a few locations. CGH analysis of the genomes of seven clinically prevalent heteroduplex type strains identified 133 genes from strain W83 that were divergent in at least one of the other strains. The relatedness of the strains to one another determined on the basis of genome content (microarray) analysis was highly similar to their relatedness determined on the basis of ISR sequence analysis, and a striking correlation between the genome contents and disease-associated phenotypes of the strains was observed