Critical differences between supragingival and subgingival microbiome.
Our study found that in periodontal and peri-implant microbiota, supra- and subgingival communities were distinct in terms of alpha and beta diversity. Supragingival communities had a significantly higher Chao1 index but a similar Shannon index when compared with subgingival communities. These findings indicated that supragingival plaque contained more bacterial species, but a certain number of these species were either too little or too much in abundance, which resulted in greater species richness but poorer evenness. A possible explanation is that supragingival plaque was more prone to foreign bacterial attachment due to its exposed position in the oral cavity. Therefore, supragingival communities might have more passersby species that were absent in subgingival communities. Former studies on the plaque composition have shown that supragingival plaque may play a role as a reservoir of some pathogens for the spread of subgingival infection[34, 35], and some suspected pathogens could only be detected in supragingival plaque but not in subgingival plaque, which corroborated with our findings.
Similar core microbiome in healthy and diseased communities.
We computed the core bacterial species in supra- and sub-gingival communities and revealed similar core microbiome in healthy and diseased sites. Briefly, core species were those predominantly abundant in most samples, notably this core microbiome mainly consisted of species from genera Streptococcus, Capnocytophaga, Actinomyces, Veillonella, and Fusobacterium. According to Socransky’s findings and other previous studies[32, 36–38], Streptococcus species from yellow complex, Veillonella parvula from purple complex, and Actinomyces speices from blue complex were considered to be early colonizers. These species were capable of rapid and firm attachment on teeth surface via expressing receptors for host ligands, and therefore modified the ecological environment for later succession. Capnocytophaga species from the green complex were identified in the biofilm milieu and were considered to be associated with periodontal diseases by producing bacterial enzymes that may lead to periodontal destruction. Fusobacterium species belonged to the orange complex. This complex formed a co-aggregational “microbial bridge” by using and releasing nutrient substances in the biofilm and expressing certain structures that bind both early colonizers and pathogens from the red complex.
In our study, although the detailed lists of core members were different in supra- and sub-gingival microbiome, the predominant species in both cores were quite similar, as they were mainly from yellow, blue, and orange complexes. According to the relative abundance of core members between healthy and diseased samples, we found that the core microbiome in health and disease was not statistically different. This result indicated that members of the core microbiome, especially those from genera Streptococcus, Actinomyces, and Capnocytophaga, may constitute a general “background” in supra- and sub-gingival microbiome, and such bacterial background does not shift easily with the change of health conditions. We hypothesized that the common background referred to not only the core members and the correlations within themselves but also their interactions with hosts and biofilms to adjust and modify the bacterial habitat. One example is that Streptococcus sanguinis was believed to be essential in developing oral biofilms in both teeth and implants, as it first facilitated its attachment by fimbriae and adhesins, and then produced glucans to promote biofilm maturation. Species from Streptococcus were also shown to have the ability to modulate host response and the expression of other bacteria species[40, 41]. Besides, Actinomyces were also among the earliest colonizers during biofilm formation and were found to attach directly to the acquired pellicle, which indicated their important role in regulating the microenvironment. The facts listed above are examples that the core species and their functionalities were of equal importance to both healthy and diseased conditions, as a general background for the formation, maturation, and further changes in the microbial communities.
Distinct bacterial networks between healthy and diseased communities.
The oral microbiome is structurally and functionally organized, which is to say, the properties of a microbial community are more than the sum of the components within it. To study a microbial community, we are supposed to explore the whole structure and the aggregation of all interactions instead of focusing on single or pairwise species. Therefore, we investigated the bacterial co-occurrence network to learn the importance of interactions to the oral microbiome.
Our study revealed that when inflammation arose around teeth and implants, subgingival microbial networks tended to become less connected and less competitive, but, on the contrary, supragingival networks tended to become more connected and more competitive. We hypothesized that in a healthy subgingival microbiome around teeth and implants, an extensive competitive inter-species correlations played an essential role in the preservation of healthy subgingival equilibrium, where growth and metabolism of potential pathogens could be inhibited. In the diseased subgingival communities, such correlations were weakened, and the total connectivity amongst species was decreased. This might allow those pathogens to enlarge in abundance and upregulate in metabolism associated with periodontal and peri-implant destruction. In our study, the relative abundance of Porphyromonas gingivalis and Treponema denticola from the red complex was significantly higher in diseased subgingival microbiota than in healthy subgingival microbiota around teeth (p < 0.05, Man-Whitney), which agreed with our hypothesis. However, networks in diseased supragingival communities seemed to shift in the opposite direction, as there were more inter-species correlations, and the proportion of competitive correlations was, instead, increased when compared with healthy supragingival communities. This might be the consequence that the supragingival microbiome serving as a reservoir for potential pathogens and was more delicate to influences. The various influences made the taxonomical changes in supragingival communities far more complex than those in subgingival communities. We appealed that detailed mechanisms behind these changes require further exploration for better understanding.
Relationship between hub species and health conditions.
Hub species were those with a large number of inter-species correlations. Whether abundant or not, these species played roles as “traffic centers” in the bacterial network and were highly associated with microbial equilibrium, for changes in their abundance might lead to a massive shift in the whole network as they were related to so many other species. Our study showed that the healthy subgingival network had the highest count of hub species, whereas the diseased subgingival network had the lowest. To be more specific, in the healthy supragingival network, species from the genus Prevotella made up a major part of the hub species. Prevotella, together with Eubacterium nodatum and Campylobacter rectus were considered members of the orange complex. Their presence in the hub nodes corresponded with their bridging function in the biofilm. Besides, Streptococcus sanguinis from yellow complex, Capnocytophaga sputigena from green complex, Actinomyces massiliensis from blue complex, and Treponema denticola from red complex were also found in the hub nodes of healthy subgingival network. In the diseased subgingival network, there were only two hub species, Capnocytophaga granulosa and Selenomonas noxia. These two species had been proven associated with calculus formation and periodontal disease[37, 44, 45]. Their emergence in the diseased hub nods indicated that their pivotal places in the bacterial network might contribute to their pathogenicity.
An interesting phenomenon is that Streptococcus sanguinis and Capnocytophaga sputigena were also from the core microbiome illustrated above, but they showed up only in healthy subgingival hub nodes but not in diseased subgingival hub nodes. This indicated that although their presence formed a general bacterial background in both healthy and diseased microbiome, the downregulation in their interactions with other species might be associated with the onset and progress of the inflammatory diseases.
As for the supragingival microbiome, differences between healthy and diseased networks were not as distinct as subgingival microbiome and seemed to change in an opposite direction where the diseased network had more hub species than the healthy one. Spirochaetes, or more specifically those in genus Treponema, took up most places in the hub nodes of healthy network. Treponema socranskii and Treponema vincentii had been reported in association with periodontal tissue breakdown[46–48]. Yet their presence in the pivots of healthy supragingival network also suggested that they might contribute to the equilibrium of healthy microenvironment. Besides, the proportion of Prevotella was much less than subgingival hub species, meaning their bridging function connecting early colonizers and red complex pathogens might be weakened. This inference was corroborated by the fact that relative abundance of red complex pathogens was significantly lower in supragingival microbiome than that in subgingival microbiome (p < 0.05, Mann-Whitney).
Former studies on the differences between healthy and diseased oral microbiota mainly focused on abundance and functionality variances. Here we revealed structural differences between healthy and diseased communities and suggested that the structure of bacterial networks and the hub species within them should be given more concern in later studies on the prevention and treatment of periodontal and peri-implant diseases.
Association between microbial stability and health conditions.
As we stressed above, patterns of the bacterial network in supra- and sub-gingival microbiome were associated with health and disease. And the multiple interactions gave the community a resilience to environmental perturbations. The capability of a microbial community to resist perturbations is defined as its stability. In our study, we found that diseased subgingival microbiome had the highest local stability among four groups while healthy subgingival microbiome had the lowest. This meant the equilibrium of healthy subgingival microbiome was more delicate and more prone to perturbations. When perturbations reached beyond resilience, equilibrium may break down with changes in microbial composition and shift in the structure of bacterial co-occurrence network. That could be where dysbiosis happened and be the essence of the initiation of periodontal and peri-implant diseases. On the other hand, the high local stability in diseased subgingival microbiome explained why, if without interventions, the periodontal and peri-implant microbiome could not spontaneously change back to health once infected by periodontitis or peri-implantitis. Previous studies found that cooperative correlations, enhanced interactions, and higher connectance tended to decrease stability[30, 49], which agreed with our calculation where healthy subgingival microbiome had the most amount of positive correlations and the most connectance in the bacterial network. We also proved that having more hub species in the network might destabilize the microbiome for changes in these species could trigger a shift in the whole network (see supplementary materials). This meant that the hub species were in some way a weak point during the breakdown of the current equilibrium.
In this scenario, we hereby suggest that the key point in the treatment of periodontitis and peri-implantitis is to break the firm equilibrium of the diseased subgingival communities and try to reestablish the healthy equilibrium, for example by antibiotic therapy, total debridement, or even microbial therapy by introducing new species to oral microbiota and thereby restore a healthy structure of bacterial network.
Limitations and deficiencies of the study.
Despite the findings we put forward, there are also limitations and deficiencies in our study. One major limitation is that the sample size in our study, although equivalent to other similar studies[19, 20, 22], is too small to describe the oral microbiome of the whole population as the oral microbiome is considered to be highly individualized. To generalize our findings and hypotheses, more bacterial samples are required for metagenomic studies. Besides, most of our findings are based on taxonomical information we annotated, which is to say, our work merely revealed those phenomena we observed yet did not verified the mechanisms in biochemistry or molecular view. Further studies on these mechanisms are required for the validation of our findings.