BackgroundPeriodontitis is a polymicrobial biofilm-induced inflammatory disease that affects 743 million people worldwide. The current model to explain periodontitis progression proposes that changes in the relative abundance of members of the oral microbiome lead to dysbiosis in the host-microbiome crosstalk and then to inflammation and bone loss. Using combined metagenome/metatranscriptome analysis of the subgingival microbiome in progressing and non-progressing sites, we have characterized the distinct molecular signatures of periodontitis progression.MethodsMetatranscriptome analysis was conducted on samples from subgingival biofilms from progressing and stable sites from periodontitis patients. Community-wide expression profiles were obtained using Next Generation Sequencing (Illumina). Sequences were aligned using ‘bowtie2’ against a constructed oral microbiome database. Differential expression analysis was performed using the non-parametric algorithm implemented on the R package ‘NOISeqBio’. We summarized global functional activities of the oral microbial community by set enrichment analysis based on the Gene Ontology (GO) orthology.ResultsGene ontology enrichment analysis showed an over-representation in the baseline of active sites of terms related to cell motility, lipid A and peptidoglycan biosynthesis, and transport of iron, potassium, and amino acids. Periodontal pathogens (Tannerella forsythia and Porphyromonas gingivalis) upregulated different TonB-dependent receptors, peptidases, proteases, aerotolerance genes, iron transport genes, hemolysins, and CRISPR-associated genes. Surprisingly, organisms that have not been usually associated with the disease (Streptococcus oralis, Streptococcus mutans, Streptococcus intermedius, Streptococcus mitis, Veillonella parvula, and Pseudomonas fluorenscens) were highly active transcribing putative virulence factors. We detected patterns of activities associated with progression of clinical traits. Among those we found that the profiles of expression of cobalamin biosynthesis, proteolysis, and potassium transport were associated with the evolution towards disease.ConclusionsWe identified metabolic changes in the microbial community associated with the initial stages of dysbiosis. Regardless of the overall composition of the community, certain metabolic signatures are consistent with disease progression. Our results suggest that the whole community, and not just a handful of oral pathogens, is responsible for an increase in virulence that leads to progression.Trial registrationNCT01489839, 6 December 2011.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-015-0153-3) contains supplementary material, which is available to authorized users.
Despite increasing knowledge on phylogenetic composition of the human microbiome, our understanding of the in situ activities of the organisms in the community and their interactions with each other and with the environment remains limited. Characterizing gene expression profiles of the human microbiome is essential for linking the role of different members of the bacterial communities in health and disease. The oral microbiome is one of the most complex microbial communities in the human body and under certain circumstances, not completely understood, the healthy microbial community undergoes a transformation toward a pathogenic state that gives rise to periodontitis, a polymicrobial inflammatory disease. We report here the in situ genome-wide transcriptome of the subgingival microbiome in six periodontally healthy individuals and seven individuals with periodontitis. The overall picture of metabolic activities showed that iron acquisition, lipopolysaccharide synthesis and flagellar synthesis were major activities defining disease. Unexpectedly, the vast majority of virulence factors upregulated in subjects with periodontitis came from organisms that are not considered major periodontal pathogens. One of the organisms whose gene expression profile was characterized was the uncultured candidate division TM7, showing an upregulation of putative virulence factors in the diseased community. These data enhance understanding of the core activities that are characteristic of periodontal disease as well as the role that individual organisms in the subgingival community play in periodontitis.
The oral microbiome plays a relevant role in the health status of the host and is a key element in a variety of oral and non-oral diseases. Despite advances in our knowledge of changes in microbial composition associated with different health conditions the functional aspects of the oral microbiome that lead to dysbiosis remain for the most part unknown. In this review, we discuss the progress made towards understanding the functional role of the oral microbiome in health and disease and how novel technologies are expanding our knowledge on this subject.
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).
Oral bacterial biofilms are highly complex microbial communities with up to 700 different bacterial taxa. We report here the use of metatranscriptomic analysis to study patterns of community gene expression in a multispecies biofilm model composed of species found in healthy oral biofilms (Actinomyces naeslundii, Lactobacillus casei, Streptococcus mitis, Veillonella parvula, and Fusobacterium nucleatum) and the same biofilm plus the periodontopathogens Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans. The presence of the periodontopathogens altered patterns in gene expression, and data indicate that transcription of protein-encoding genes and small noncoding RNAs is stimulated. In the healthy biofilm hypothetical proteins, transporters and transcriptional regulators were upregulated while chaperones and cell division proteins were downregulated. However, when the pathogens were present, chaperones were highly upregulated, probably due to increased levels of stress. We also observed a significant upregulation of ABC transport systems and putative transposases. Changes in Clusters of Orthologous Groups functional categories as well as gene set enrichment analysis based on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways showed that in the absence of pathogens, only sets of proteins related to transport and secondary metabolism were upregulated, while in the presence of pathogens, proteins related to growth and division as well as a large portion of transcription factors were upregulated. Finally, we identified several small noncoding RNAs whose predicted targets were genes differentially expressed in the open reading frame libraries. These results show the importance of pathogens controlling gene expression of a healthy oral community and the usefulness of metatranscriptomic techniques to study gene expression profiles in complex microbial community models.
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