Correlation network analysis applied to complex biofilm communities

Abstract

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).

Figure 1. WGCNA correlation network results of bacterial species in checkerboard hybridization results.

The images show the Cytoscape representation of the correlation networks for the 4 modules identified by WGCNA. Checkerboard analysis was performed for 40 species of oral bacteria on a total of 2,565 individual tooth from patients with periodontitis. R² used for scale free topology model fit was 0.40, the maximum value in the analysis. The identified modules correlated well with microbial complexes previously described .

Figure 2. WGCNA correlation network results of bacterial species in healthy and diseased individuals from HOMIM results.

Clustering dendrogram of species, with dissimilarity based on topological overlap, together with assigned module colors. a) Cluster 1 from healthy individuals (51 samples), R² used for scale free topology model fit was 0.90 and a total of 6 bacterial modules were identified. b) Cluster 2 from healthy individuals (37 samples), R² used for scale free topology model fit was 0.85 and a total of 10 bacterial modules were identified. c) Cluster 1 from diseased individuals (467 samples), R² used for scale free topology model fit was 0.90 and a total of 6 bacterial modules were identified. D) Cluster 2 from diseased individuals (49 samples), R² used for scale free topology model fit was 0.85 and a total of 7 bacterial modules were identified.

Figure 3. Selecting helpers to isolate the uncultivable organism Tannerella sp. OT286.

Red edges in the networks show yellow nodes connecting directly to Tannerella sp. OT286. The length of the edges is proportional to the strength of the association between species. Oral taxon (OT) for each species/phylotype followed the designation provided in Human Oral Microbiome Database (HOMD) www.homd.org. a) Connections in module turquoise from HOMIM results healthy cluster 1 (51 samples). b) Connections in module red from HOMIM results healthy cluster 2 (37 samples). c) Connections in module grey from HOMIM results from diseased cluster 1 (467 samples). d) Connections in module grey from HOMIM results from diseased cluster 2 (49 samples). In red we show the strains that were tested as helpers in our experiments. Additionally, as negative controls, we tested 2 strains not present in those networks: Propionibacterium acnes OT530 and Lactobacillus casei OT568.

Figure 4. Enrichment and isolation of Tannerella sp. OT286.

A) qPCR results of the number of 16S rDNA copies of Tannerella sp. OT286 after a week of incubation in the presence of different helpers. B1) Results of colony hybridization where the colonies from the initial agar plate enrichment were spread on a plate and a filter paper (black square) was soaked with Prevotella oris OT311 and placed on top of the plate. B2) Results of the same experiment but in this case Lactobacillus casei OT568, a negative control, was used to soak the filter paper. The black squares indicate where the paper filters were placed soaked with the 2 different species. C1) Streaking isolation of colonies from B1 positive region on agar plates. C2) Colony hybridization of C1 plate showing positively identified Tannerella sp. OT286 colonies.