Community-wide transcriptome of the oral microbiome in subjects with and without periodontitis

Abstract

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.

Figure 1

Principal coordinate analysis (PCoA) of phylogenetic profiles from metagenomes and metatranscriptomes. Ordination graph for the first two axes of a PCoA of the phylogenetic profiles obtained from the metagenome and metatranscriptome of the oral microbial communities in healthy sites and sites with severe periodontitis. The % on the axes represents the variance explained by each of the coordinates.

Figure 2

Rank distribution of statistically significant relative increase in number of hits for the metagenome and metatranscriptome results. The ratio of counts in disease vs health was log2 transformed and plotted according to ranks. The statistical significance was calculated using the non-parametric test implemented in the program NOISeq as described in the Materials and methods section. Only species with significant differences, according to NOISeq, either in metagenomic or metatranscriptomic counts, are presented. In green, species with statistical differences in both metagenome and metatranscriptome. In blue, species with statistical differences in metagenomic counts. In red, species with statistical differences in metatranscriptome counts. Red star indicates major periodontal pathogens previously assigned to the ‘red-complex.'

Figure 3

Heat maps of gene expression profiles in the metatranscriptomes. (a) Profiles of the 1212 most highly expressed genes across samples. Genes were first normalized by gene length and χ² transformed before analysis. Most highly expressed genes were selected according to the sum of normalized counts across samples. (b) Profiles of the 1000 most highly differentially expressed genes across samples. Genes were selected from the NOISeq results and counts were χ² transformed before analysis. Color bars in red correspond to healthy samples and in green to periodontitis samples.

Figure 4

GO enrichment analysis summarized and visualized as a scatter plot using REVIGO. (a) Summarized GO terms related to biological processes in periodontitis. (b) Summarized GO terms related to biological processes in health. (c) Summarized GO terms related to molecular function in periodontitis. (d) Summarized GO terms related to molecular function in health. GO terms are represented by circles and are plotted according to semantic similarities to other GO terms (adjoining circles are most closely related). Circle size is proportional to the frequency of the GO term, whereas color indicates the log10 P value (red higher, blue lower).

Figure 5

Ranked species by the number of upregulated putative virulence factors in the metatranscriptome. Putative virulence factors were identified by alignment of the protein sequences from the different genomes against the Virulence Factors of Pathogenic Bacteria Database as described in the Materials and methods section. Number in the graph are the absolute number of hits for the different species for the putative virulence factors identified. In red are the members of the ‘red-complex.'