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).人类微生物组的复杂性使得揭示群落组织原则颇具难度，而生成可检验的假说则更具挑战。有研究指出，在肠道微生物组中，多形拟杆菌（Bacteroides thetaiotaomicron）这类物种是维持微生物群落稳定性与功能适应性的关键类群。本研究运用系统生物学原理，探究复杂微生物生物膜中的物种间关联。通过相关网络分析，我们鉴定出代表口腔群落内重要微生物关联的细菌模块。我们以牙菌斑作为模式群落，因其具有高度的多样性，且口腔生物膜中普遍存在已知的物种间相互作用。我们分析了健康个体以及牙周炎（一种多微生物性疾病）患者的样本。利用针对可培养细菌的棋盘杂交法获得的结果，我们鉴定出与此前报道的微生物复合体高度吻合的模块。此外，我们借助人类口腔微生物鉴定微阵列（Human Oral Microbe Identification Microarray, HOMIM）拓展了分析范围，该芯片涵盖大量细菌物种，其中包括口腔内尚未培养的微生物。健康个体中存在两种截然不同的微生物群落，而疾病状态下仅存在一种主要类型。所有群落中的细菌模块均无重叠，这表明细菌可根据环境条件有效重新结合新的伙伴。我们进而鉴定出可作为细菌模块中关键物种的枢纽类群。基于上述结果，我们成功培养出一种此前未被培养的微生物：坦纳菌属（Tannerella sp.）OT286（克隆BU063）。通过选定的辅助菌——口炎普雷沃菌（Prevotella oris）OT311进行两轮富集培养后，我们在血琼脂平板上获得了坦纳菌属OT286的菌落。这种系统级研究方法为靶向操控微生物群落提供了可能，同时也可将特定细菌模块与临床表型（如肥胖、克罗恩病、牙周疾病等）建立关联。