Salivary microbiome and periodontopathogen/denitrifying bacteria associated with gingivitis and periodontitis in people with type 2-diabetes

Introduction

The development of periodontal disease is known to be significantly influenced by the oral microbiota, which may also be an important variable in systemic disorders including diabetes and heart disease.¹ Additionally, recent studies indicate that those with type 2 diabetes (T2DM) are more likely to develop periodontitis and to have more severe forms of disease.^2–4 Even though numerous studies have looked at the bidirectional relationship between diabetes mellitus and periodontal disorders, there are still gaps in the quantity and quality of study on the subject.^5,6 For example, existing literature has explored the link between diabetes and periodontal disease, but these studies often have limitations. While some have been constrained by comparatively small sample sizes,^7,8 others have concentrated on particular geographic regions.^9,10 Furthermore, although current literature^1,2 indicates that therapeutic medications like chlorhexidine are commonly used to manage oral bacteria and that microRNAs (miRNAs) are significant regulators of inflammation, studies are still ongoing to determine the precise microbial changes and how they relate to host factors. Our study expands on that approach by specifically looking at the salivary microbiome to identify potential microbial indicators for disease progression.

The most common types of periodontal disease are gingivitis and periodontitis. In many respects, gingivitis is a state of stable inflammation that represents equilibrium (homeostasis). Hence, gingivitis is mostly reversible.¹¹ However, the prolonged or recurrent occurrence of the condition, particularly in predisposed individuals, may lead to irreversible destruction of hard and soft tissues (periodontitis). Both gingivitis and periodontitis have been recognized as polymicrobial, biofilm-based inflammatory diseases¹² in which a disruption of the ecological balance between the biofilm and the periodontal tissue homeostasis plays a more important role than specific infections,^13–15 alongside other environmental, lifestyle and genetic risk factors.

In patients with periodontitis, the number of periodontopathogens (Porphyromonas gingivalis, Treponema denticola, and Tannerella forsythia) and Fusobacterium spp. is increasing, while the number of normal flora bacteria is decreasing.^16–18 Healthy microbial populations include all genera; Rothia, Neisseria, Actinomyces, Veillonella, Kingella, Propionibacterium, Prevotella, Granulicatella, and Haemophilus. They are all recognized to be nitrate-reducing bacteria (NRB),^19,20 and have antimetabolic disease activities.²¹ These NRB have attracted much attention currently given their crucial function in the human nitrogen cycle’s nitrate (NO3-) - nitrite (NO2-) - nitric oxide (NO) pathway.^22,23 Additionally, blood pressure regulation and insulin resistance are positively impacted by oral nitrate-reducing bacteria.²⁴ The intricate relationship between nitrate-reducing bacteria (NRB) and periodontopathogens has not been well investigated in many studies. Our previous study, which used real-time PCR,²⁵ showed that individuals with T2DM who did not have periodontitis had different prevalence of specific periodontopathogens and nitrate-reducing bacteria. Therefore, the purpose of this study was to descriptively characterize and explore the community structure and differences in the salivary microbiomes of individuals with T2DM who had gingivitis or periodontitis to those who did not. We focused specifically on descriptive interplay between key periodontopathogens (such as P. gingivalis and Fusobacterium spp.) and nitrate-reducing bacteria (NRB) community (including Haemophilus, Neisseria, Rothia, and Veillonella). We hypothesize that the unique metabolic environment of diabetic patients facilitates disease progression via a functional shift – a disruption in the beneficial nitric oxide (NO)-production function of the NRB community – which is associated with increased abundance of periodontopathic species.

In addition to subgingival biofilm (SGB), saliva was chosen as the sample type to accurately capture the oral microbiome’s composition, since it is commonly used to explain the microbial shifts that occur in periodontal sites as they progress from health to disease.^26–29 Furthermore, the Oxford Nanopore Technology (ONT) long-read sequencing approach was performed to identify taxa based on whole 16S rRNA sequences, which allows the species-level identification of the representative microbes, including periodontopathogen³⁰ and oral bacteria associated with nitrate-reducing.³¹

Methods

Results

Figure 1. The salivary microbiome's rarefaction curve and alpha diversity among different T2DM patient groups.

The total number of sequences is displayed on the horizontal axis, while the number of operational taxonomic units (OTUs) at a 97% intersequence similarity level is shown on the vertical axis of the rarefaction curve (A). The diversity indices of Shannon (B) and Simpson (C) show how alpha diversity varies among the three groups in terms of evenness and richness. Species diversity and evenness seem to be larger in gingivitis group (G2) and periodontitis group (G3) compared to oral health group (G1).

Figure 2. Saliva microbiota taxonomic composition in T2DM patients with and without periodontal diseases.

Relative abundance of mayor of salivary bacterial taxa, which relative abundance >5%, are presented at the phylum (A) and genus (B) level. “Others” refers to the remaining phyla. A comparison of the relative abundance of periodontopathic bacterial species (C) and genus of NO₃^--reducing bacteria (D) between three groups of patient with T2DM. G1 through G3 represent the participant group.

Figure 3. Phylogenetic variations among nitrate-reducing bacteria between T2DM patients with periodontitis (G3) and gingivitis (G2).

Overall phylogenetic diversity of nitrate-reducing bacteria was considerably lower in T2DM individuals with periodontitis than in those with gingivitis. Patients with periodontitis (A and B) or gingivitis (C and D), but not both, have specific Neisseria species (Blue box). The distribution of Rothia species (Red box) also differed among the groupings.

Figure 4. The heatmap displays the quantity of periodontopathic and nitrate-reducing bacteria in the groups under study.

The study groups and the targeted bacteria were represented by rows and columns, respectively. The relative proportion of the bacterial assignment within each group is represented by the colors in the heatmap. A shift in color toward dark red denotes a higher abundance.

Figure 5. Salivary nitrite concentration in unstimulated saliva from T2DM subject groups.

All participants with gingivitis (G2), periodontitis (G3), and no periodontal disease (G1) had their salivary nitrite levels measured using the Griess reaction method. Bars represent mean + SD. An asterisk (*) indicates a statistically significant difference (p-value < 0.05) and ns = not significant.

Discussion

This study’s main finding is that diabetes mellitus and periodontal diseases together have significantly greater effects on alterations in the composition of salivary microbiota than do diabetes mellitus alone. This descriptively suggests that the most important factors modifying the composition of salivary microorganisms are periodontal diseases (gingivitis and periodontitis). Thus, we evaluated which oral bacteria increase the risk of periodontal diseases and how specifically diabetes affects them from the perspective of the oral microbiome. Since both polymicrobial synergy and dysbiosis have a major influence on periodontal disorders,^36,37 we intended to better understand any potential relationships between the relative abundance of periodontopathogens and nitrate-reducing bacteria, in diabetics with and without periodontal diseases.

First, we found that the 16S rRNA-based MinION technology’s sequencing depth allowed for the identification of 97% of the bacterial population, allowing the ability to identify bacterial cells in pooled saliva samples. Subsequently, these studies’ findings showed that T2DM patients with periodontal diseases were observed to have a greater alpha diversity in their saliva than those without the disease. The result suggests that the salivary microbiota’s composition significantly shifted from symbiosis to dysbiosis as our subjects’ periodontal health deteriorated. The findings may also imply that the diversity of individual microbial patterns among our diabetes group members may have led to the difference in alpha diversity seen in this study. Additionally, using the Shannon and Simpson indices, we descriptively found that T2DM participants with gingivitis (G2 group) and periodontitis (G3 group) had higher species variety than those without periodontal diseases (G1 group). However, people with T2DM and gingivitis may have more low-abundance bacterial species in their saliva, which could explain the higher Shannon index. Although they have little effect on the Simpson’s index, these rare species add to the total diversity measured by the Shannon index. This implies that, despite the fact that gingivitis and periodontitis displayed different clinical symptoms, species abundance rather than species diversity is the primary factor influencing the observed differences in salivary microbiome between the two groups. Further research is necessary to fully understand the implications of these findings and their potential therapeutic relevance. However, it should be remembered that these diversity shifts may not always be associated with changes in the relative abundances of the microbiome; they may instead be explained by certain ecological conditions that influence the patterns of microbial succession.³⁸

These results allowed us to distinguish between the two distinct “microbiota states” associated with the G2 and G3 groups of gingivitis and periodontitis, respectively. At the phylum level, Bacillota (Firmicutes) are consistently the most prevalent bacteria across all groups, but their relative abundance in the G2 and G3 groups appears to be slightly higher than in the G1 group (those without periodontal disease). Shannon’s diversity index additionally indicated that the changes were most noticeable at the genus level, with Streptococcus being the most prevalent bacteria found in the current study. The results were similar to those published by Shaalan et al. (2022)³⁹ and Omori et al. (2022).⁴⁰ Since the phylum Bacillota, which includes numerous genera, is involved in both periodontal health and diseases,^41,42 higher proportions of patients with type 2 diabetes who have periodontal disease may indicate a dysbiosis, in which bacteria from this phylum predominate and exacerbate the inflammatory process of periodontal disease.

Additionally, we discovered that the gingivitis (G1 group) and periodontitis G2 group) have a greater proportion of Pseudomonadota. This phyla is the second largest group in the oral microbiome,⁴³ and oral pathobionts may belong to this phylum.⁴⁴ Descriptively, Pseudomonadota was observed to be more common in patients with gingivitis but less prevalent in patients with periodontitis, relative to Bacteroidota. A similar finding was also reported in China, where younger patients with T2DM had a descriptive abundance of Proteobacteria (synonym Pseuodomonadota).⁹ Even though our adult diabetic participants may be more susceptible to early inflammation of periodontal disease due to Pseudomonadota-related bacteria, the relative abundance of Actinomycetota did not differ descriptively across all groups assessed, which is consistent with previous reports.⁴⁵

One possible explanation for the bacterial shifting mentioned above is the decrease in number or extinction of bacterial species related to nitrate reducers. Therefore, we aimed to determine if the observed compositionality of microbiota in each group could be explained by different prevalence rates of nitrate reducer bacteria. We noticed, that several genera, including Porphyromonas, Fusobacterium, Haemophylus, Neisseria, Rothia, and Veillonela, were found in this study. All of them have the ability to regulate nitrate-nitrite-nitric oxide (NO).^20,46–48 Among these bacteria, Porphyromonas and Fusobacterium are periodontopathic bacteria,⁴⁹ while the remaining bacteria are linked to oral health.^50,51 Descriptively, this study found that among T2DM patients with periodontal diseases (G2 and G3 groups), the relative abundance of Neisseria and periodontopathic bacteria (P. gingivalis and Fusobacteria spp.) appeared to follow a similar pattern as compared with those without periodontal diseases (G1 group). Furthermore, the existence of Rothia species in both groups raises the possibility that the main differences or functional role of the species may change depending on the severity of periodontal disease and type 2 diabetes. On the other hand, this highlights Neisseria’s significance as a key element of the oral cavity’s core microbiota,⁵² and this descriptive data demonstrated how the nitrate reducer bacteria and periodontopathogen collaborate to boost periodontal inflammation in individuals with type 2 diabetes.⁷ Indeed, finding that people with type 2 diabetes who also have periodontal disease have a low amount of Rothia in their saliva indicates that the bacteria could benefit people with periodontal health.^48,53,54 Therefore, in our diabetic patients, Neisseria spp. and Rothia spp. could be the main oral nitrate-reducing bacteria⁵³ in responsible for periodontal health and inflammation. Consequently, to simplify the interpretation and presentation of our results, we disregarded the other nitrate-reducing bacteria that did not demonstrate the largest descriptive difference. As a result, we discovered that T2DM patients with periodontitis had much less phylogenetic diversity of these bacteria than those with gingivitis. We noticed, Neisseria flavescens, N. iguanae, N. macacae, N. oralis and N. zoodegmatis were only found in the pooled metagenomic salivary samples of the gingivitis patient (G2 group), while N. weaveri was detected only in the periodontitis patients (G3). The zoonotic pathogens Neisseria zoodegmatis and N. weaveri have been reported to cause soft tissue infections,^55,56 even though their presence in the human salivary microbiome has not been reported.

For Rothia, R. aeria was exclusively present in the G2 group, while R. mucilaginosa and R. dentocariosa were discovered in both patient groups (G2 and G3). Indeed, we speculated that the way that bacteria interact with periodontopathogen in T2DM patients may be indicative that gingivitis develops into periodontitis. In this sense, the descriptive differences in the association patterns between Neisseria or Rothia and specific periodontopathic bacteria may be characteristic of the progression of periodontal disease in patients with type 2 diabetes. First, we focused on the red complex bacteria (P. gingivalis, T. denticola, and T. forsythia), and Fusobacterium spp. which are the most threatening or potential pathogens that contribute to periodontal disease in adults.⁵⁷ We noted, that the red complex bacteria were found in the saliva of each participant group, supporting previous findings that periodontal pathogens were present in individuals with both periodontal disease and periodontal health.^58,59

Accordingly, group G3 (diabetic individuals with periodontitis) had the highest descriptive abundance of periodontopathogens, especially P. gingivalis. This finding suggests a more severe dysbiosis in this population, where P. gingivalis plays a crucial role.¹³ The result is in line with a study that examined the subgingival microbiota of individuals with periodontal disease.³⁸ However, it should be mentioned that variations in the host’s specific response to the opportunistic infection may have important variable in the disease’s severity.⁶⁰ Furthermore, it’s also noteworthy that our diabetes patients have a descriptively higher density of bridging periodontopathic bacteria (Fusobacterium spp.), which have been shown to restrict and prepare the environment for the colonization of pathogenic red complex species that lead to periodontitis.^61,62 The high concentration of Fusobacterium DNA found in this study suggests that more periodontopathic bacteria colonized the oral cavity of patients with T2DM. Although a previous study has linked Fusobacterium spp. to bleeding on probing (BOP),⁶³ our findings demonstrated that in patient without periodontal disease G1 group), as indicated in Table 1, the absence of gingivitis was consistent with a BOP < 10%. Subsequently, our finding which include the dendrogram analysis, indicate a higher diversity of Neisseria and Rothia species in gingivitis (G2 group) than in periodontitis (G3 group). Our result suggests that specific species within these genera may be more influential in the initiation and early progression of gingival inflammation, while their roles might shift or diminish in chronic periodontitis.⁶⁴ Neisseria may contribute synergistically with periodontopathic bacteria like Fusobacterium to establish the inflammation, whereas Rothia appears to have a unique, potentially protective, association with the inflammatory process.⁶⁴

Moreover, it has been reported that the abundance of Neisseria in saliva is associated with periodontal health⁶⁵ and the abundance of Rothia decreased in periodontitis.¹⁷ Both bacteria are essential for reducing oral nitrate.^53,54 Another study found that while the overall diversity of the oral microbiome declined in mice with diabetes mellitus, Proteobacteria along with Firmicutes numbers increased.⁶⁶ The information support our findings that elevated Proteobacteria abundance, with Neisseria being the most prevalent, seemed to be triggered by inflammation of the periodontal tissue in people with type 2 diabetes. However, we recommend more studies to validate these findings.

Since Actinomycetota’s Rothia are known NO^-₃ reducers,⁶⁷ the lower salivary nitric oxide content indicated by the Griess reaction could be the reason why our T2DM patients with periodontal disease (G2 and G3 groups) had a smaller number of these bacteria than those without periodontal disease (G1 group). Nonetheless, the nitrate concentration of the G2 and G3 groups were comparable. This suggests that the advancement of periodontal disease (gingivitis and periodontitis) may impair the activity of nitrate reducer in either periodontal inflammation conditions.¹⁶ Interestingly, groups G2 and G3 displayed a decrease in salivary nitrate concentration despite a higher number of Neisseria. Hence, this study indicate that there is a complex interaction between different bacterial species and their metabolic activity in the oral microbiome of our T2DM subjects, which is not covered in our study. Indeed, additional study is required to ascertain whether the increased Neisseria proportion in the microbiome of T2DM subjects with gingivitis or periodontitis causes or results from periodontal inflammation.

In addition to the microbial changes, our results might possibly be connected to the oxidative stress and systemic inflammation pathways that define diabetes and periodontitis. Reactive oxygen species (ROS) are produced by the host’s immunological response to oral infections in periodontitis, a chronic inflammatory disease that causes tissue damage and oxidative stress.⁶⁸ By producing systemic oxidative stress, which in turn interferes with insulin signaling, the inflammatory burden of the oral cavity may make glycemic control worse.⁶⁹ This cycle of inflammation and oxidative stress may be exacerbated by our G3 group’s greater abundance of periodontopathogens and lower amounts of nitrate-reducing bacteria like Rothia. The low salivary nitrite levels and the different microbial relationships we found between the gingivitis and periodontitis groups imply that the oral microbial dysbiosis in these patients may be a contributing factor to the increased oxidative stress and inflammation observed in both conditions.

It should be mentioned that the observed variation in bacterial counts between the gingivitis and periodontitis groups in our T2DM participants is not necessarily indicative of a biomarker’s diagnostic value.⁷⁰

Literature shows, that periodontopathic bacteria (P. gingivalis, T. denticola, T. forsythia, and Fusobacterium spp.) are responsible for the development and progress of periodontal disorders.⁷¹ The study’s findings clearly showed that people with type 2 diabetes accompanied with gingivitis or periodontitis have reduced nitrate reduction efficiency, with the exception of Neisseria, which affects the ability of microorganisms to reduce nitrate in saliva.¹⁶ Therefore, the shifting of oral microbial equilibrium, particularly the balance of nitrate-reducing bacteria activities, may be the cause of periodontal inflammation in our diabetic subjects. Furthermore, a previous study demonstrated that the activity of bacteria that reduce nitrate may help minimize the risk of systemic diseases like hypertension and insulin resistance. Our descriptive finding suggest an association where these bacteria are more prevalent in gingivitis prior to periodontitis. Nevertheless, more study is required to validate this finding.

Conclusion

The study’s findings showed that there are notable variations in the microbial communities in saliva between periodontal disease and oral health, with the development of periodontal inflammation in diabetics playing a substantial role in these differences. Overall, the results show that people with type 2 diabetes mellitus who also have periodontitis or gingivitis may have unique relationships between nitrate-reducing and periodontopathic bacteria in their salivary microbiome. In order to prevent periodontitis, these characteristics may be promising microbiological features that warrant validation for the early identification and treatment of gingivitis.

Author contributions

BB: Data curation, Funding acquisition, Writing-review & editing. DT: Validation, Visualization, Review & editing. CT: Resources, Supervision, Review &editing. NH:, Resources, Validation. CT: Project administration, Validation.YS: Data curation, Validation. SS: Validation, Visualization, Review & editing. AW: Data curation, Validation. FR: Resources and Supervision FT: Data curation, Validation, Visualization. DA: Resources and Supervision. EB: Conceptualization, Writing-Original draft.

Ethics and consent

In accordance with the criteria of the institutional ethics committee, All participants provided written informed consent before they participated part in the study, and the Dr. Cipto Mangunkusumo Hospital’s Ethics Committee approved the study’s protocols (Ethics Reference Number: KET-1203/UN2.F1/ETIK/PPM.06.02/2023).