Prevalence of Streptococci and Increased Polymicrobial Diversity Associated with Cystic Fibrosis Patient Stability

Diverse microbial communities chronically colonize the lungs of cystic fibrosis patients. Pyrosequencing of amplicons for hypervariable regions in the 16S rRNA gene generated taxonomic profiles of bacterial communities for sputum genomic DNA samples from 22 patients during a state of clinical stability (outpatients) and 13 patients during acute exacerbation (inpatients). We employed quantitative PCR (qPCR) to confirm the detection of Pseudomonas aeruginosa and Streptococcus by the pyrosequencing data and human oral microbe identification microarray (HOMIM) analysis to determine the species of the streptococci identified by pyrosequencing. We show that outpatient sputum samples have significantly higher bacterial diversity than inpatients, but maintenance treatment with tobramycin did not impact overall diversity. Contrary to the current dogma in the field that Pseudomonas aeruginosa is the dominant organism in the majority of cystic fibrosis patients, Pseudomonas constituted the predominant genera in only half the patient samples analyzed and reported here. The increased fractional representation of Streptococcus in the outpatient cohort relative to the inpatient cohort was the strongest predictor of clinically stable lung disease. The most prevalent streptococci included species typically associated with the oral cavity (Streptococcus salivarius and Streptococcus parasanguis) and the Streptococcus milleri group species. These species of Streptococcus may play an important role in increasing the diversity of the cystic fibrosis lung environment and promoting patient stability

Oral Microbiome Profiles: 16S rRNA Pyrosequencing and Microarray Assay Comparison

The human oral microbiome is potentially related to diverse health conditions and high-throughput technology provides the possibility of surveying microbial community structure at high resolution. We compared two oral microbiome survey methods: broad-based microbiome identification by 16S rRNA gene sequencing and targeted characterization of microbes by custom DNA microarray.Oral wash samples were collected from 20 individuals at Memorial Sloan-Kettering Cancer Center. 16S rRNA gene survey was performed by 454 pyrosequencing of the V3–V5 region (450 bp). Targeted identification by DNA microarray was carried out with the Human Oral Microbe Identification Microarray (HOMIM). Correlations and relative abundance were compared at phylum and genus level, between 16S rRNA sequence read ratio and HOMIM hybridization intensity.; Correlation = 0.70–0.84).Microbiome community profiles assessed by 16S rRNA pyrosequencing and HOMIM were highly correlated at the phylum level and, when comparing the more commonly detected taxa, also at the genus level. Both methods are currently suitable for high-throughput epidemiologic investigations relating identified and more common oral microbial taxa to disease risk; yet, pyrosequencing may provide a broader spectrum of taxa identification, a distinct sequence-read record, and greater detection sensitivity

Bacterial profiles of saliva in relation to diet, lifestyle factors, and socioeconomic status

Background and objective: The bacterial profile of saliva is composed of bacteria from different oral surfaces. The objective of this study was to determine whether different diet intake, lifestyle, or socioeconomic status is associated with characteristic bacterial saliva profiles. Design: Stimulated saliva samples from 292 participants with low levels of dental caries and periodontitis, enrolled in the Danish Health Examination Survey (DANHES), were analyzed for the presence of approximately 300 bacterial species by means of the Human Oral Microbe Identification Microarray (HOMIM). Using presence and levels (mean HOMIM-value) of bacterial probes as endpoints, the influence of diet intake, lifestyle, and socioeconomic status on the bacterial saliva profile was analyzed by Mann–Whitney tests with Benjamini–Hochberg’s correction for multiple comparisons and principal component analysis. Results: Targets for 131 different probes were identified in 292 samples, with Streptococcus and Veillonella being the most predominant genera identified. Two bacterial taxa (Streptococcus sobrinus and Eubacterium [11][G-3] brachy) were more associated with smokers than non-smokers (adjusted p-value\u3c0.01). Stratification of the group based on extreme ends of the parameters age, gender, alcohol consumption, body mass index (BMI), and diet intake had no statistical influence on the composition of the bacterial profile of saliva. Conversely, differences in socioeconomic status were reflected by the bacterial profiles of saliva. Conclusions: The bacterial profile of saliva seems independent of diet intake, but influenced by smoking and maybe socioeconomic status

T Cell Activation Results in Conformational Changes in the Src Family Kinase Lck to Induce Its Activation

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World Workshop on Oral Medicine VII: Targeting the oral microbiome Part 2: Current knowledge on malignant and potentially malignant oral disorders.

Objective: The World Workshop on Oral Medicine VII chose the oral microbiome as a focus area. Part 1 presents the methodological state of the science for oral microbiome studies. Part 2 was guided by the question: What is currently known about the microbiome associated with oral squamous cell carcinoma and potentially malignant disorders of the oral mucosa?. Materials and Methods: A scoping review methodology was followed to identify and analyse relevant studies on the composition and potential functions of the oral microbiota using high-throughput sequencing techniques. The authors performed searches in PubMed and EMBASE. After removal of duplicates, a total of 239 potentially studies were identified. Results: Twenty-three studies on oral squamous cell carcinoma, two on oral leukoplakia and four on oral lichen planus were included with substantial differences in diagnostic criteria, sample type, region sequenced and sequencing method utilised. The majority of studies focused on bacterial identification and recorded statistically significant differences in the oral microbiota associated with health and disease. However, even when comparing studies of similar methodology, the microbial differences between health and disease varied considerably. No consensus on the composition of the microbiomes associated with these conditions on genus and species level could be obtained. Six studies on oral squamous cell carcinoma had included in silico predicted microbial functions (genes and/or pathways) and found some similarities between the studies. Conclusions: Attempts to reveal the microbiome associated with oral mucosal diseases are still in its infancy, and the studies demonstrate significant clinical and methodological heterogeneity across disease categories. The immense richness and diversity of the microbiota clearly illustrate that there is a need for additional methodologically comparable studies utilising deep sequencing approaches in significant cohorts of subjects together with functional analyses. Our hope is that following the recipe as outlined in our preceding companion paper, that is Part 1, will enhance achieving this in the future and elucidate the role of the oral microbiome in oral squamous cell carcinoma and potentially malignant disorders of the oral mucosa

Use of 16S ribosomal RNA gene analyses to characterize the bacterial signature associated with poor oral health in West Virginia

<p>Abstract</p> <p>Background</p> <p>West Virginia has the worst oral health in the United States, but the reasons for this are unclear. This pilot study explored the etiology of this disparity using culture-independent analyses to identify bacterial species associated with oral disease.</p> <p>Methods</p> <p>Bacteria in subgingival plaque samples from twelve participants in two independent West Virginia dental-related studies were characterized using 16S rRNA gene sequencing and Human Oral Microbe Identification Microarray (HOMIM) analysis. Unifrac analysis was used to characterize phylogenetic differences between bacterial communities obtained from plaque of participants with low or high oral disease, which was further evaluated using clustering and Principal Coordinate Analysis.</p> <p>Results</p> <p>Statistically different bacterial signatures (<it>P </it>< 0.001) were identified in subgingival plaque of individuals with low or high oral disease in West Virginia based on 16S rRNA gene sequencing. Low disease contained a high frequency of <it>Veillonella </it>and <it>Streptococcus</it>, with a moderate number of <it>Capnocytophaga</it>. High disease exhibited substantially increased bacterial diversity and included a large proportion of Clostridiales cluster bacteria (<it>Selenomonas</it>, <it>Eubacterium, Dialister</it>). Phylogenetic trees constructed using 16S rRNA gene sequencing revealed that Clostridiales were repeated colonizers in plaque associated with high oral disease, providing evidence that the oral environment is somehow influencing the bacterial signature linked to disease.</p> <p>Conclusions</p> <p>Culture-independent analyses identified an atypical bacterial signature associated with high oral disease in West Virginians and provided evidence that the oral environment influenced this signature. Both findings provide insight into the etiology of the oral disparity in West Virginia.</p

Correlation Network Analysis Applied to Complex Biofilm Communities

The complexity of the human microbiome makes it difficult to reveal organizational principles of the community and even more challenging to generate testable hypotheses. It has been suggested that in the gut microbiome species such as Bacteroides thetaiotaomicron are keystone in maintaining the stability and functional adaptability of the microbial community. In this study, we investigate the interspecies associations in a complex microbial biofilm applying systems biology principles. Using correlation network analysis we identified bacterial modules that represent important microbial associations within the oral community. We used dental plaque as a model community because of its high diversity and the well known species-species interactions that are common in the oral biofilm. We analyzed samples from healthy individuals as well as from patients with periodontitis, a polymicrobial disease. Using results obtained by checkerboard hybridization on cultivable bacteria we identified modules that correlated well with microbial complexes previously described. Furthermore, we extended our analysis using the Human Oral Microbe Identification Microarray (HOMIM), which includes a large number of bacterial species, among them uncultivated organisms present in the mouth. Two distinct microbial communities appeared in healthy individuals while there was one major type in disease. Bacterial modules in all communities did not overlap, indicating that bacteria were able to effectively re-associate with new partners depending on the environmental conditions. We then identified hubs that could act as keystone species in the bacterial modules. Based on those results we then cultured a not-yet-cultivated microorganism, Tannerella sp. OT286 (clone BU063). After two rounds of enrichment by a selected helper (Prevotella oris OT311) we obtained colonies of Tannerella sp. OT286 growing on blood agar plates. This system-level approach would open the possibility of manipulating microbial communities in a targeted fashion as well as associating certain bacterial modules to clinical traits (e.g.: obesity, Crohn's disease, periodontal disease, etc)