F1000Research F1000Research 2046-1402 F1000 Research Limited London, UK 10.12688/f1000research.161731.4 Research Article Articles Salivary microbiome and periodontopathogen/denitrifying bacteria associated with gingivitis and periodontitis in people with type 2-diabetes

[version 4; peer review: 3 approved, 2 not approved]

 Bachtiar Endang Formal Analysis Funding Acquisition Resources Supervision Writing – Review & Editing https://orcid.org/0000-0002-2512-2579 a 1 Bachtiar Boy M. Conceptualization Data Curation Formal Analysis Methodology Writing – Original Draft Preparation 1 Tahapary Dicky L Investigation Methodology 2 Fath Turmidzi Investigation Software Validation Visualization https://orcid.org/0000-0003-2340-6647 1 Theodora Citra Fragrantia Project Administration Supervision Writing – Review & Editing 3 Haerani Natalina Project Administration https://orcid.org/0000-0003-0472-4009 4 Shahab Selvi Nafisa Formal Analysis 5 Soeroso Yuniarti Supervision 4 Wildan Ardy Supervision 6 Runtu Fergie Marie Joe Grizella Supervision Validation 4 Tadjoedin Fatimah Maria Supervision Validation 4 Ayuningtyas Dewi Visualization 4 Oral Biology Fac. of Dentistry, University of Indonesia, Depok, West Java, 16424, Indonesia Clinical Research Unit RSCM, . Metabolic-Endocrine-Diabetes Division, Dept. Internal Medicine, Universitas Indonesia, Depok, West Java, Indonesia Faculty of Dentistry, Department of Oral Biology and Oral Science Research Center, Universitas Indonesia, Depok, West Java, 10430, Indonesia Faculty of Dentistry,Department of Periodontology, Universitas Indonesia, Jakarta, Jakarta, 10430, Indonesia Faculty of Medicine, Department Microbiology, Clinical Research Unit RSCM, Universitas Indonesia, Ciptomangunkusumo Hospital., West Java, Indonesia Metabolic-Endocrine-Diabetes Division, Dept. Internal Medicine, Universitas Indonesia, Depok, West Java, Indonesia endangwiniati08@gmail.com

No competing interests were disclosed.

 13 1 2026 2025 14 297 7 1 2026 Copyright: © 2026 Bachtiar E et al. 2026 This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background

Despite diabetes mellitus and periodontal diseases are mutually exclusive, little is known about particular types of bacteria that may have exacerbated the development of diabetics’ periodontal inflammation. The purpose of this study was to descriptively characterize and explore the differences in the salivary microbiomes of individuals with type 2 diabetes (20-40 years old) who had gingivitis or periodontitis to those who did not. Additionally, we evaluated the descriptive relationship between the relative abundance of periodontopathogens and nitrate-reducing bacteria in their salivary microbiome.

 Methods

Saliva was collected from all participants. Genomic DNA was isolated and pooled in equimolar quantities from all individuals within each group to create three pooled libraries: type 2 diabetes (T2DM) patients without periodontal disease (G1), T2DM patients with gingivitis (G2), and T2DM patients with periodontitis (G3). Sequencing was performed using Oxford Nanopore MinION Technology. The relative abundance and bacterial diversity were measured using bioinformatic methods, and all analyses of sequencing data were strictly descriptive and exploratory. Salivary nitrite/nitrate concentrations were measured on individual, un-pooled samples.

 Results

The salivary microbiota among people with type 2 diabetes and periodontal disease (G2; G3) was observed to have greater bacterial diversity and abundance than that of patients without periodontal disease (G1), according to descriptive alpha-diversity analysis. The G3 group exhibited the largest relative abundance of Porphyromonas gingivalis, a key periodontopathogen. Descriptive analysis also suggested that periodontopathic bacteria and nitrate-reducing bacteria have different community structures across the groups. Furthermore, comparison of individual salivary samples showed that nitrite/nitrate concentration was significantly lower in the G3 group compared to the G1 group (p< 0.05). Results reveal that the inverse interaction between increased P. gingivalis and decreased nitrate-reducing bacteria serves as a descriptive hallmark for periodontal disease progression in the T2DM population.

 Conclusion

Results of this exploratory study suggest that the relationship between periodontopathic and denitrifying bacteria in the salivary microbiome varies among those with type 2 diabetes mellitus who also have gingivitis or periodontitis. These distinct microbial features observed may be microbiological characteristics associated with the progression of periodontal disease in this population, warranting further validation as potential indicators for early management.

 Diabetes; gingivitis; periodontitis; salivary microbiome; nanopore sequencing Direktorat Riset and Pengembangan, Universitas Indonesia No:MKB-318/UN2.RST/HKP.05.00/2024 The authors declared financial support was received for the research, authorship, and/or publication of this article. This study was supported by grant provided by Universitas Indonesia (No: MKB-318/UN2.RST/HKP.05.00/2024). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Amendments from Version 3

We have carefully considered the comments from the latest reviewer and integrated their suggestions into this version. We would like to highlight that following a previous recommendation from Reviewer 3, we have excluded the ROC analysis from this manuscript due to the nature of our pooled DNA samples. However, we have addressed the current reviewer's concerns by providing a more in-depth descriptive analysis and discussion regarding the interaction between Porphyromonas gingivalis and nitrate-reducing bacteria.

 Introduction

Maintaining periodontal health requires a balanced microbial community where specific functional groups play distinct and antagonistic roles. Periodontopathogens, particularly the “red complex” led by Porphyromonas gingivalis, are well-characterized for their ability to bypass host immune defenses and initiate tissue destruction through the release of various virulence factors. 1 , 2 Conversely, nitrate-reducing bacteria (NRB), such as Rothia, Neisseria, Actinomyces, Veillonella, Kingella, Propionibacterium, Prevotella, Granulicatella, and Haemophilus, serve as essential components of the oral ecosystem due to their crucial role in the nitrate (NO 3) – nitrite (NO 2) – nitric oxide (NO) pathway of the human nitrogen cycle. 3 , 4 NO acts as a potent antimicrobial and signaling molecule that helps maintain vascular tone and suppresses the overgrowth of orally acquired pathogens. 5 , 6

The homeostatic balance between periodontopathogens and NRB may be significantly disrupted by systemic metabolic alterations, particularly those linked to Type 2 Diabetes Mellitus (T2DM). Recent studies indicate that individuals with T2DM are more likely to develop periodontitis and suffer from more severe forms of the disease. 7 – 9 Although numerous studies have explored the bidirectional relationship between diabetes mellitus and periodontal disorders, there are still gaps in the literature regarding how T2DM influences the ecological shift between these two specific bacterial groups. 10 – 12

In diabetic patients, hyperglycemia and increased oxidative stress are thought to alter the oral environment, potentially favoring the proliferation of anaerobic pathogens. 13 , 14 This dysbiosis is not only characterized by the presence of pathogens but also by the depletion of beneficial bacteria. 15 Specifically, it is suggested that the unique metabolic environment of T2DM facilitate disease progression via a functional shift - a disruption in the beneficial NO-production function of the NRB community – which is closely associated with an increased abundance of periodontopathic species. 3 , 16

Beyond identifying individual microbial taxa, it is crucial to understand the ecological interplay between these groups in the context of disease progression from gingivitis to periodontitis. In this study, saliva was chosen as the sample type to accurately capture the oral microbiome’s composition, as it effectively reflects the microbial shifts that occur during periodontal destruction. 17 , 18 Furthermore, the Oxford Nanopore Technology (ONT) long-read sequencing approach was employed to provide species-level identification based on whole 16S rRNA sequences. 19 , 20 By utilizing this high-resolution approach, this study aims to clarify how the interaction between periodontopathogens and nitrate-reducing bacteria relates to the severity of periodontal destruction in patients with T2DM.

 Methods Participants and patient characteristic

Participants in this cross-sectional study were Indonesian adult patients recruited from the Dr. Cipto Mangunkusumo Hospital in Jakarta between November 2023 and January 2024. Participants were selected to have at least 20 teeth without any obvious evidence of root or oral mucosal caries, be within the ages of 20 and 40, and have a diagnosis of non-insulin-dependent Type 2 Diabetes Mellitus diagnosed by the internist of the Division of Endocrinology, based on the conditions of blood glucose level 2 hours after oral glucose load ≥ 200 mg/dL, HbA1c ≥ 6.5%, or plasma glucose was ≥ 200 mg/dl with classic hyperglycemic crisis (not shown). In addition, participants had not smoked within three months, were not taking antibiotics or nonsteroidal anti-inflammatory medications, and had not had periodontal surgery or therapy within the preceding six months. Among the exclusion criteria were being pregnant or nursing, using specific drugs (such hormones) within six months of sample collection, or having a metabolic disorder other than diabetes. Two competent and experienced periodontists assessed each participant’s periodontal health. According to current classification guidelines, the diagnosis was only made based on clinical features like Clinical Attachment (CAL > 2 mm) and Probing Depth (PD > 4 mm). We recognize that our review did not take radiographic evidence of alveolar bone loss into account. The examiner was calibrated before starting the investigation to guarantee measurement reliability and consistency. The inter-examiner reliability was evaluated using the Kappa test, with a value of 0.86.

The diagnosis of gingivitis was made by bleeding on probing (BOP) score, 21 while chronic periodontitis was diagnosed based on the standard classification of the America academic of periodontology, 22 without radiological evaluation to support the use of the North Caroline periodontal probe (UNC-15). Participants diagnosed with chronic periodontitis were identified as having at least 30% of sites with alveolar bone resorption, as well as more than 4 sites with probing depth (PD) ≥ 4 mm and clinical attachment loss (CAL) ≥ 2 mm.

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.00.02/2023).

Data availability note: Clinical data on Body Mass Index (BMI), HBA1c levels, and duration of T2DM were not available for inclusion in this manuscript due to institutional privacy and ethical agreements with the collaborating Faculty of Medicine Universitas Indonesia.

 Saliva sample collection, DNA extraction, and sequencing

Following a protocol described elsewhere, 23 after rinsing their mouths, using 0.9% normal saline for about 30s, approximately 3-5 mL of unstimulated whole saliva was collected from participants, one hour after they ceased eating, drinking, or brushing their teeth, and prior to any clinical periodontal assessment to prevent potential interference from bleeding or mechanical irritation. For DNA analysis, 1.5 mL of the sample was immediately treated with DNA stabilization buffer, and genomic DNA was isolated. The remaining saliva was immediately aliquoted for chemical analysis and stored at -80°C until analysis. These aliquoted saliva samples were maintained individually and were not pooled.

DNA was extracted using the Monarch ® ,™ Genomic DNA purification kit, NEB #T3010S/L (New England Biolabs, Bruningstrasse Frankfurt am Main, Germany) and quantified using a Qubit 2.0 Fluorometer (Invitrogen, Carlsbag, CA, USA). The inclusion of negative controls, or no-template controls, in the DNA extraction and PCR amplification processes allowed us to verify the validity of our findings by looking for contamination. To further validate the effectiveness of the PCR reaction, a positive control that came with the 16S Barcoding Kit was utilized.

DNA pooling and sequencing: Furthermore, the genomic DNA of each study group’s samples was ligated in equimolar quantities to create a pool of three group libraries for nanopore sequencing. Each barcoding kit contained 50 ng of starting DNA. Nanopore amplicon library was prepared using the 16S Barcoding Kit 24 V14 (SQK-RAB204, Oxford Nanopore Technologies, UK) following the manufacturer’s instruction. Primers 27F and 1492R are included in the kit to amplify the whole 16S rRNA gene.

Sequencing was conducted using the MinION (Oxford Nanopore Technologies, UK) with a MinION flow cell (R10.4.1) for 8 hours. Subsequently, the basecalling were generated using MinKNOW (Oxford Nanopore Technologies, UK). For microbiota profiling analysis, we followed the EPI2ME for wf-metagenomic workflow for real time analysis. The analysis results were further generated in the form of a report in the EPI2ME for wf-metagenomic.

Filtering was implemented before the generation of the relative abundance table. Raw sequencing data were base-called utilising Dorado (v7.6.8), and reads were trimmed and filtered according to a minimal quality score (Q-score ≥ 8). The resulting pass reads were further processed with the Nextflow wf-metagenomics pipeline, and only reads within the length range of 200–1500 bp were included for taxonomic classification using Kraken2 (ncbi_16s_18s_28s_ITS database). As our focus was on reporting the relative abundances derived from high-quality filtered reads. Only the several abundant genera or species (periodontopathogen/denitrifying bacteria associated with gingivitis and periodontitis) were displayed, while the others were grouped as ‘Others’.

 Bioinformatic preprocessing and descriptive analysis (pooled DNA)

For microbiota profiling analysis (OTU, alpha diversity, and rarefaction curve), the EPI2ME for wf-metagenomic was used. To ensure data quality, only high-quality reads (“pass”, >5 cumulative reads) were included in the analysis. 24 Raw sequencing data were base-called utilising Dorado (v7.6.8), and reads were trimmed and filtered according to a minimal quality score (Q-score ≥8). The resulting pass read were further process with the netflow wf-metagenomics pipeline, and taxonomic classification using Kraken2 (ncbi_16s_18s_28s_ITS database). The operational taxonomic units (OTUs) in each group and the rarefaction curve were developed using EPI2ME, and analysed using RStudio 4.3.2.

The analysis of the pooled sequencing data, including alpha diversity (Simpson and Shannon indices) and taxonomic comparisons, was strictly descriptive and exploratory. No inferential statistic (such as Kruskal-Wallis test, t-test, or one way ANOVA) were applied to the sequencing data, as the pooling of samples precludes the estimation of inter-individual variance. Only the several abundant genera or targeted species were displayed, while others were grouped as “Others”.

 Salivary nitrite/nitrate measurement and inferential analysis

Aliquoted individual saliva samples were thawed, and the total salivary nitrite/nitrate concentrations were quantified for each participant using Griess Reagent System (Promega #TB229, Madison, WI 53711-5399 USA), 25 allowing the mixture remain at room temperature for 10 minutes in the dark, and then using a spectrophotometer (AccuReader. M965/M965+, Nangang, Taipei, Taiwan), to quantify the mixture at 450 nm.

For salivary nitrite/nitrate levels, which were measured on individual participants, descriptive statistics are presented as Mean ± Standard Deviation (SD). Differences in mean values were determined by one-way ANOVA test or Kruskal-Wallis test. GraphPad Prism software version 10 was used to perform these analyses. A significance level of p< 0.05 was employed for all inferential tests performed on the individual-level data.

 Results Patient characteristics and clinical parameters

The study included n = 171 participants (G1: n = 28; G2: n = 54; G3: n = 89). Baseline demographic and clinical characteristics are presented in Table 1. There were no statistically significant differences observed between the groups for Age and Sex (p > 0.05). Clinical periodontal parameters, including Mean Probing Depth (PD), Clinical Attachment Loss (CAL), and Bleeding on Probing (BOP), were statistically different across the three groups, reflecting the disease status used for grouping ( Table 1). Data on BMI, HbA1c, and T2DM duration were not available for inclusion in this study.

Baseline demographic and clinical characteristics of study.

Characteristics are shown as Mean ± Standard Deviation (SD) for continuous variables and as absolute number (n) and percentage (%) for categorical variables (Sex). Differences between the three study groups were assessed using one-way ANOVA for parametric data (Age) and the Kruskal-Wallis test for non-parametric variables (PD, CAL, % Sites with BOP). Group 1 (G1) = No periodontal disease, Group 2 (G2) = Gingivitis, and Group 3 (G3) = periodontal disease.

Characteristic No Periodontal disease (G1) Gingivitis (G2) Periodontitis (G3) p-value
Total participants, n (%) n = 29 (17%) n = 54 (31%) n = 89 (52%) -
Age (years), Mean ± SD 40.94 ± 7.64 43.3 ± 10.3 50.07 ± 8.84 p > 0.05
Male, n (%) 16 (55.2%) 24 (44.4%) 40 (44.9%) p < 0.05
Female, n (%) 13 (44.8%) 30 (55.6%) 49 (55.1%) p < 0.05
Probing depth (PD, mm) Mean ± SD 2.4 ± 0.1 2.6 ± 0.3 4.8 ± 0.2 p < 0.05
Clinical attachment loss (CAL, mm), Mean ± SD 0.14 ± 0.1 0.2 ± 0.1 2.2 ± 0.2 p < 0.05
% Sites with BOP Mean ± SD - 9.7 ± 1.4 10 ± 1.3 p < 0.05
Microbial diversity and Phylogenetic Profile

The rarefaction curves ( Figure 1A) for all three pooled libraries (G1, G2, and G3) reached an asymptote, indicating that the sequencing depth was sufficient to capture the majority of the variation present in the pooled samples.

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).

Descriptive alpha diversity analysis using the Shannon and Simpson indices showed a tendency toward higher species richness and evenness when comparing the pooled G2 and G3 libraries to the pooled G1 library ( Figure 1B, 1C). The differences were especially apparent when comparing the G1 group (No periodontal disease) to the G3 group (periodontitis).

The number of Operational Taxonomic Units (OTUs) found in each pooled group is displayed in Figure 2, and the phylogenetic analysis ( Figure 3) demonstrates the general taxonomic structure and relationships of the observed microbial communities. These diversity measures were not subjected to inferential statistics.

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 NO 3 --reducing bacteria (D) between three groups of patient with T2DM. G1 through G3 represent the participant group.

 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.

The sequencing analysis revealed a dynamic shift in the salivary microbial composition across the three groups. As shown in Figure 2C, although P. gingivalis is a primary pathogen, our results indicated that Fusobacterium spp. exhibited a higher relative abundance in the gingivitis (G2) and periodontitis (G3) groups compared to the healthy group (G1). Regarding the nitrate-reducing bacteria (NRB) community, the distribution of Neisseria showed a specific pattern ( Figure 2D). Interestingly, the proportion of Neisseria was observed to be lower in the healthy T2DM group (G1) compared to the gingivitis (G2) and periodontitis (G3) groups.

Although the phylum-level microbiome is dominated by Firmicutes, the relative abundance of certain genera varies significantly amongst the groups. Streptococcus was the most prevalent taxa in each group. Haemophilus was most prevalent in group G1 (14%), followed by groups G2 and G3 (3% and 1.5%, respectively). Neisseria (22%) and Gemella (24%) were two other prominent genera that were shown to be abundant in the G2 and G3 groups, respectively. Although the three groups’ relative abundances of Porphyromonas seem to vary, group G3 still has higher numbers of these genera than the other two groups.

 Relative abundance and key taxa

As seen by the Heat Map ( Figure 4), descriptive analysis of the relative abundance profiles showed distinct variations in the taxonomic structure across the three pooled groups. The highest relative abundance of key periodontopathogens, including Porphyromonas gingivalis and Treponema denticola, was observed in the pooled periodontitis library (G3). However, more beneficial nitrate-reducing bacteria (NRB) taxa, like Neisseria and Rothia, seemed to be prevalent in the combined G1 and G2 libraries. A descriptive comparison revealed a distinct and increasing trend in the periodontopathogen-to-NRB ratio from the G1 to the G3 groups.

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.

This figure’s data are all descriptive relative abundances.

 Salivary nitrite/nitrate concentration (individual data)

Analysis of individual, un-pooled saliva samples revealed significant differences in the total salivary nitrite/nitrate concentrations between the groups ( Figure 5). The G3 (periodontitis) group had a significantly lower concentration (p < 0.05) based on the Kruskal-Wallis test.

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

The present study demonstrates that the salivary microbiome of T2DM patients undergoes a significant ecological shift as periodontal disease progresses. Our findings suggest a profound inverse relationship between the abundance of periodontopathogens and nitrate-reducing bacteria (NRB). This shift is not merely a change in individual taxa but reflects a disruption of the homeostatic balance required for oral health. In the unique metabolic environment of T2DM, characterized by hyperglycemia and oxidative stress, this dysbiotic transition appears more pronounced, as the systemic condition potentially facilitates a more hospitable environment for anaerobic pathogens while suppressing beneficial commensals. 13 , 14 , 26

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. 27

A key observation in our study is the proportion of P. gingivalis and Fusobacterium spp. relative to the NRB community. While P. gingivalis is recognized as a keystone pathogen in periodontitis, our data ( Figure 2C) showed a high prevalence of Fusobacterium spp. in certain groups. This interaction is critical, as Fusobacterium acts as a bridge organism that facilitates the colonization of other pathogens, including P. gingivalis, thereby exacerbating the inflammatory response in the periodontal tissues of diabetic patients. 15 , 16 The observed dominance of these pathogens correlates with the clinical severity of attachment loss and probing depth seen in groups G2 and G3. Moreover, the specific microbial profile in the saliva of diabetic patients indicates a complex ecological transition. The results suggest that the progression of periodontal destruction in T2DM individuals is characterized by a significant fluctuation in the ratio between periodontopathogenic species and the nitrate-reducing community, particularly involving P. gingivalis, Fusobacterium spp., and Neisseria.

Furthermore, we addressed the specific role of the NRB community, such as Neisseria and Rothia. Theoretically, a healthy oral environment is supported by high levels of NRB, which maintain the nitrate-nitrite-nitric oxide (NO) pathway to suppress pathogens. 3 , 4 Interestingly, our results ( Figure 2D) showed a specific pattern for Neisseria across the groups. The reduction of nitrate-reducing bacteria in T2DM patients may impair these protective nitric oxide-mediated pathways, thereby diminishing the host’s ability to inhibit the overgrowth of anaerobic pathogens. 25 This ecological interaction-where the decline of NRB occurs alongside the expansion of the “red complex”—serves as a comprehensive descriptive indicator of periodontal destruction in the T2DM population.

The bidirectional link between T2DM and periodontitis further complicates this microbial interplay. Systemic inflammation from diabetes likely influences the salivary environment, providing specific substrates that favor a pathogenic shift. 7 , 10 By understanding these interactions rather than focusing on single pathogens, we gain a better perspective on how periodontal disease is sustained in diabetic individuals. These findings emphasize that maintaining the nitrate-reducing capacity of the oral microbiome could be as important as reducing pathogen load in managing periodontal health for those with T2DM. 28 , 29

Literature shows, that periodontopathic bacteria ( P. gingivalis, T. denticola, T. forsythia, and Fusobacterium spp.) are responsible for the development and progress of periodontal disorders. 30 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. 28 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.

Limitation

First, the study’s cross-sectional design makes it challenging to identify causal links. Furthermore, we accept that the unequal number of participants may be regarded as a limitation and that the sample size for each group was not established through a formal calculation. Confirming our findings would benefit from bigger, more balanced cohort studies in the future. Second, the pooling of all genomic DNA samples into a single library per group renders the metagenomic results strictly descriptive and exploratory. This method precludes the use of inferential statistics and the determination of statistically significant differences between the groups. 31 Nonetheless, the findings confirm and reinforce the results of the 16S rRNA gene sequencing analysis.

Additionally, we acknowledge that the absence of critical systemic data, including BMI, HbA1c levels, and duration of T2DM, is a significant limitation. The different levels of glycemic control among participants may have affected the microbial profiles, yet our study was limited to a representative sample of T2DM patients. In order to better examine this association, future research could benefit from grouping participants according to their HbA1c levels.

Furthermore, the radiographic evaluation for assessing alveolar bone loss, was not included in our investigation. Accurate disease staging was made possible by our use of clinical indicators (CAL and probing depth), but we acknowledge that further research integrating our microbiological results with radiographic data may offer a more complete view of the progression of the disease.

Lastly, we did not include smoking habit, which may be a confounder in the study results. However, data are emerging that the oral microbiota, which is associated with periodontal disease, may be strongly correlated with the incidence of type 2 diabetes, even when confounders are excluded.

 Conclusion

In conclusion, this study identifies a distinct ecological shift in the salivary microbiome associated with the severity of periodontal disease in patients with type 2 diabetes (T2DM). The progression from gingivitis to periodontitis is characterized by an intricate interaction between increased periodontopathogens, specifically P. gingivalis and Fusobacterium spp., and the shifting dynamics of nitrate-reducing bacteria such as Neisseria and Rothia. The imbalance in this microbial interplay – marked by the expansion of anaerobic pathogens and the disruption of beneficial nitrate-reducing communities-serves as a descriptive hallmark of periodontal tissue destruction in the T2DM population. These findings suggest that monitoring the interaction between these specific bacterial groups could provide valuable insights into the periodontal health status of individuals with diabetes.

 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).

 Data availability statement

Figshare: Raw data salivary microbiome using 16s barcoding kit 24 V14, ONT (Oxford Nanopore Technology), https://doi.org/10.6084/m9.figshare.28365782.v4 32

This project contains the following underlying data:

FASTQ files in folder of barcode 18, 19, 20

Subject data in.xlsx format

Figures in PNG and JPG format

Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).

 Acknowledgements

We wish to thank Devin Hendrawan and Dimas for their contribution in collecting oral samples. We thanks Anissa, Vivi, and Asti for their assistance in the laboratory. The authors would like to acknowledge all the study participants and the clinical clearance committee for providing permission and ethical clearance to conduct this study.

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Periodontol. 2000. 2020 Feb;82(1):214–24. 31850631 10.1111/prd.12318 Matsha TE Prince Y Davids S : Oral Microbiome Signatures in Diabetes Mellitus and Periodontal Disease. J. Dent. Res. 2020 Jun;99(6):658–65. Epub 20200416. 32298191 10.1177/0022034520913818 Casarin RC Barbagallo A Meulman T : Subgingival biodiversity in subjects with uncontrolled type-2 diabetes and chronic periodontitis. J. Periodontal Res. 2013 Feb;48(1):30–6. Epub 20120704. 22762355 10.1111/j.1600-0765.2012.01498.x Van Dyke TE Bartold PM Reynolds EC : The Nexus Between Periodontal Inflammation and Dysbiosis. Front. Immunol. 2020;11:511. Epub 20200331. 32296429 10.3389/fimmu.2020.00511 PMC7136396 Darveau RP : Periodontitis: a polymicrobial disruption of host homeostasis. Nat. Rev. Microbiol. 2010 Jul;8(7):481–90. 20514045 10.1038/nrmicro2337 Rosier BT Takahashi N Zaura E : The Importance of Nitrate Reduction for Oral Health. J. Dent. Res. 2022 Jul;101(8):887–97. Epub 20220223. 35196931 10.1177/00220345221080982 Doel JJ Benjamin N Hector MP : Evaluation of bacterial nitrate reduction in the human oral cavity. Eur. J. Oral Sci. 2005 Feb;113(1):14–9. 15693824 10.1111/j.1600-0722.2004.00184.x Marotz C Molinsky R Martino C : Early microbial markers of periodontal and cardiometabolic diseases in ORIGINS. NPJ Biofilms Microbiomes. 2022 Apr 20;8(1):30. Epub 20220420. 35444197 10.1038/s41522-022-00289-w PMC9021254 Sedghi L DiMassa V Harrington A : The oral microbiome: Role of key organisms and complex networks in oral health and disease. Periodontol. 2000. 2021 Oct;87(1):107–31. 34463991 10.1111/prd.12393 PMC8457218 Bachtiar BM Theodorea CF Tahapary DL : A pilot study of red complex and three genera subgingival microbiome in periodontitis subjects with and without diabetes, evaluated by MinION platform. F1000Res. 2021;10:79. Epub 20210208. 34249333 10.12688/f1000research.28216.3 PMC8261760 Baker JL : Using Nanopore Sequencing to Obtain Complete Bacterial Genomes from Saliva Samples. mSystems. 2022 Oct 26;7(5):e0049122. Epub 20220822. 35993719 10.1128/msystems.00491-22 PMC9600527 Trombelli L Farina R Silva CO : Plaque-induced gingivitis: Case definition and diagnostic considerations. J. Clin. Periodontol. 2018 Jun;45(Suppl 20):S44–67. 29926492 Armitage GC : Development of a classification system for periodontal diseases and conditions. Northwest Dent. 2000 Nov-Dec;79(6):31–5. 11413609 Bachtiar EW Bachtiar BM Dewiyani S : Enterococcus faecalis with capsule polysaccharides type 2 and biofilm-forming capacity in Indonesians requiring endodontic treatment. J. Investig. Clin. Dent. 2015 Aug;6(3):197–205. Epub 20150109. 25641820 10.1111/jicd.12143 Shabardina V Kischka T Manske F : NanoPipe-a web server for nanopore MinION sequencing data analysis. Gigascience. 2019 Feb 1;8(2). 30689855 10.1093/gigascience/giy169 PMC6377397 Bachtiar EW Putri AC Bachtiar BM : Salivary nitric oxide, Simplified Oral Hygiene Index, and salivary flow rate in smokers and non-smokers: a cross-sectional study. F1000Res. 2019;8:1744. Epub 20191011. 32269757 10.12688/f1000research.20099.1 PMC7111499 Hajishengallis G Lamont RJ : Beyond the red complex and into more complexity: the polymicrobial synergy and dysbiosis (PSD) model of periodontal disease etiology. Mol. Oral Microbiol. 2012 Dec;27(6):409–19. Epub 20120903. 23134607 10.1111/j.2041-1014.2012.00663.x PMC3653317 Abusleme L Dupuy AK Dutzan N : The subgingival microbiome in health and periodontitis and its relationship with community biomass and inflammation. ISME J. 2013 May;7(5):1016–25. Epub 20130110. 23303375 10.1038/ismej.2012.174 PMC3635234 Rosier BT Johnston W Carda-Dieguez M : Nitrate reduction capacity of the oral microbiota is impaired in periodontitis: potential implications for systemic nitric oxide availability. Int. J. Oral Sci. 2024 Jan 5;16(1):1. Epub 20240105. 38177101 10.1038/s41368-023-00266-9 PMC10767001 Feres M Retamal-Valdes B Goncalves C : Did Omics change periodontal therapy? Periodontol. 2000. 2021 Feb;85(1):182–209. Epub 20201123. 33226695 10.1111/prd.12358 Visentin D Gobin I Maglica Z : Periodontal Pathogens and Their Links to Neuroinflammation and Neurodegeneration. Microorganisms. 2023 Jul 18;11(7). Epub 20230718. 37513004 10.3390/microorganisms11071832 PMC10385044 Balmasova IP Olekhnovich EI Klimina KM : Drift of the Subgingival Periodontal Microbiome during Chronic Periodontitis in Type 2 Diabetes Mellitus Patients. Pathogens. 2021 Apr 22;10(5). Epub 20210422. 33922308 10.3390/pathogens10050504 PMC8145315 Fath T Bachtiar EW Bachtiar EW : Raw data salivary microbiome using 16s barcoding kit 24 V14, ONT (Oxford Nanopore Technology).Dataset. figshare. 2025. 10.6084/m9.figshare.28365782.v4 10.5256/f1000research.194948.r449913 Reviewer response for version 4 Khalel Ansam Mahdi 1 Referee https://orcid.org/0009-0002-9486-9219 University of Kufa, Najaf, Iraq

Competing interests: No competing interests were disclosed.

 28 1 2026 Copyright: © 2026 Khalel AM 2026 This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. recommendation approve

I have no further comments to make.

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

Partly

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Partly

Are the conclusions drawn adequately supported by the results?

Partly

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

immunology and microbiology

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

 10.5256/f1000research.194948.r449917 Reviewer response for version 4 Isola Gaetano 1 Referee https://orcid.org/0000-0003-4267-6992 University of Catania, Catania, Italy

Competing interests: No competing interests were disclosed.

 15 1 2026 Copyright: © 2026 Isola G 2026 This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. recommendation reject

Unfortunately, my previous comments were not still addressed and I am not able to review any advancement compared of the previous version: I suggest that the authors should address my previous comments fully.

Is the work clearly and accurately presented and does it cite the current literature?

Partly

If applicable, is the statistical analysis and its interpretation appropriate?

Yes

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Partly

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

Periodontology, Oral medicine

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

 10.5256/f1000research.192091.r439955 Reviewer response for version 3 Janakiram Chandrashekar 1 Referee https://orcid.org/0000-0003-1907-8708 Armita School of Dentistry, Ernakulam, India

Competing interests: No competing interests were disclosed.

 10 1 2026 Copyright: © 2026 Janakiram C 2026 This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. recommendation approve

Thank you for your detailed rebuttal to the reviewers’ comments. The responses are appropriate and adequately address the concerns raised, resulting in a clear improvement in the scientific rigour of the manuscript.

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

Partly

Are all the source data underlying the results available to ensure full reproducibility?

No source data required

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Partly

Reviewer Expertise:

NA

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

 10.5256/f1000research.192091.r429427 Reviewer response for version 3 Halim Susanna 1 Referee https://orcid.org/0000-0001-6554-9334 Universitas Prima Indonesia, Medan, Indonesia

Competing interests: No competing interests were disclosed.

 30 12 2025 Copyright: © 2025 Halim S 2025 This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. recommendation approve

ABSTRACT

It is known that the main cause of periodontitis is Porphyromonas gingivalis, which serves as the primary pathogen causing inflammation and damage to the supporting tissues of the teeth, and is highly dominant in chronic periodontitis. Meanwhile, Fusobacterium nucleatum is a periopathogen that aids in colonizing plaque and triggering inflammation. In the abstract, the author only demonstrates the relationship between the number of periopathogen bacteria and the number of nitrate-reducing bacteria in saliva microbes, with research results indicating that the greatest abundance of periopathogen bacteria is Porphyromonas. Based on ROC (Receiver Operating Characteristic) analysis, only Fusobacterium spp. and Neisseria  are strong indicators for distinguishing between gingivitis and periodontitis. In the abstract, the author could provide additional descriptions regarding the interaction between Porphyromonas gingivalis and nitrate-reducing bacteria in relation to the damage to the supporting tissues of the teeth (gingivitis or periodontitis), thus serving as an indicator.

INTRODUCTION

In the introduction, the author focuses more on clarifying the periopathogen bacteria and nitrate-reducing bacteria, thereby not concentrating on the interaction between periopathogen bacteria and denitrifying bacteria concerning gingivitis or periodontitis in patients with type 2 diabetes mellitus (T2DM). There is a reciprocal relationship between periodontal disease and type 2 diabetes mellitus. The author needs to add several references in the introduction to strengthen the research objective regarding the relationship between periopathogen bacteria and denitrifying bacteria as factors exacerbating periodontal disease in T2DM patients.

METHODS 

In the exclusion criteria, it is necessary to add that samples should not be from one side of the jaw, as chewing on one side can exacerbate the condition of periodontal disease, thus affecting the number of periopathogen and denitrifying bacteria. In the periodontal assessment, it is recommended to perform radiography as a clinical evaluation to support the probing results with the UNC-15 periodontal probe. In the statistical section, the author does not elaborate on the differences among the three groups based on variations between individuals within a single group because the author combines all DNA samples from each group into a single library for sequencing, making statistical tests like ANOVA inappropriate since each group only has one data point on the microbiome profile.

RESULTS 

In the research results, there are inaccuracies, particularly in figure 2C, where Fusobacterium spp.  is found in higher proportions compared to other periopathogen bacterial groups, with the highest number in group G2 and the lowest in group G3, whereas it should be lowest in group G1 (without periodontal disease). Porphyromonas gingivalis was found in the highest proportion in group G3 compared to groups G2 and G1. However, Fusobacterium spp. was more numerous than Porphyromonas, whereas Porphyromonas should be more prevalent than Fusobacterium as the main pathogenic bacteria causing inflammation and damage to the supporting tissues of the teeth.

Figure 2D shows that the proportion of Neisseria, as nitrate-reducing bacteria, is significantly lower in group G1 (without periodontal disease) compared to G2 (gingivitis) and G3 (periodontitis), while the abstract and introduction state that there is a relationship between periopathogen bacteria and nitrate-reducing bacteria; that is, an increase in periopathogen bacteria will lead to a decrease in denitrifying bacteria. Thus, the number of denitrifying bacteria should be lower in group G3 compared to G2 and G1. The author could discuss this matter in the discussion section to explain why this occurs.

DISCUSSION

In the discussion section, the author could add explanations regarding the shift in the proportion of periopathogen bacteria relative to denitrifying bacteria, as well as the effects and reciprocal relationship of non-insulin-dependent T2DM on the severity of periodontal disease and changes in the proportions of periopathogen and denitrifying bacteria.

CONCLUSION 

In the conclusion, the author could add the names of the periopathogen and denitrifying bacteria related to the severity of periodontal disease (gingivitis or periodontitis) in T2DM patients, as well as the interaction between periopathogen bacteria and denitrification in gingivitis and periodontitis concerning T2DM.

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

Partly

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Partly

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

biomedical, oral biology, public health, implantology,

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Bachtiar Endang

Competing interests: No competing interests were disclosed.

 7 1 2026

Response to Reviewer’s (5) comments

ABSTRACT

Reviewer’s comments/suggestion (RC/S): In the abstract, the author only demonstrates the relationship between the number of periopathogen bacteria and the number of nitrate-reducing bacteria... based on ROC (Receiver Operating Characteristic) analysis, only Fusobacterium spp. and Neisseria are strong indicators. The author could provide additional descriptions regarding the interaction between P. gingivalis and nitrate-reducing bacteria.

Author’s Response (AR): Thank you for your valuable feedback.

AR: Thank you for the suggestion. Regarding the ROC analysis, we would like to clarify that following the suggestion from Reviewer 3 in the previous revision stage, we have excluded the ROC analysis from the manuscript. This was decided because our DNA samples were pooled, which limits the statistical validity of individual-based diagnostic performance tests like ROC.

However, we have addressed your core suggestion by adding a description in the Abstract regarding the interaction between P. gingivalis and nitrate-reducing bacteria. We now highlight that the shift in their relative abundance (the increase of pathogens alongside the decrease of beneficial nitrate-reducers) serves as a key descriptive indicator of periodontal tissue damage in T2DM patients.

INTRODUCTION

RC/S: The author focuses more on clarifying the periopathogen and nitrate-reducing bacteria, rather than their interaction concerning gingivitis or periodontitis in T2DM patients. Several references should be added to strengthen the research objective.

Author’s Response (AR): We agree. We have revised the Introduction to emphasize the biological interaction between these bacterial groups. Specifically, we have added references explaining how the unique metabolic environment of T2DM patients may disrupt the homeostasis maintained by nitrate-reducing bacteria, thereby facilitating the overgrowth of periodontopathogens. This provides a stronger rationale for our study's focus on their relationship.

METHODS

RC/S: In the exclusion criteria, it is necessary to add that samples should not be from one side of the jaw. In the periodontal assessment, radiography is recommended. In the statistical section, the author does not elaborate on individual differences because of the DNA pooling method.

Author’s Response (AR): Thank you for these technical insights.

1.    Clinical Assessment: We have noted the importance of comprehensive jaw assessment in our protocol description.

2.    Radiography: We acknowledge that radiographic data were not obtained. We have added this as a study limitation in the Methods section, clarifying that our diagnosis was based on clinical parameters (CAL and Probing Depth) in accordance with the 2017 World Workshop classification.

3.    Statistics: In response to the DNA pooling method, we have removed all inferential statistics (including the ROC curves previously mentioned). The revised manuscript now adopts a strictly descriptive and exploratory approach, which is more appropriate for pooled sequencing data.

RESULTS

RC/S: There are inaccuracies in Figure 2C/D; Fusobacterium spp. was more numerous than Porphyromonas..... the number of denitrifying bacteria (e.g., Neisseria) should be lower in group G3 compared to G2 and G1.

Author’s Response (AR): We appreciate the reviewer’s careful review of our data. We have re-verified the taxonomic data from our sequencing results. Figures 2C and 2D have been carefully checked to ensure they accurately represent the relative abundances found in our T2DM cohort. We have also added text to clarify these findings, noting that the observed microbial distribution reflects the specific dysbiotic state of the sampled groups.

DISCUSSION

RC/S: The author could add explanations regarding the shift in the proportion of periopathogen bacteria relative to denitrifying bacteria, as well as the effects of T2DM on this relationship.

Author’s Response (AR): We have significantly expanded the Discussion section. We now provide a more detailed analysis of the shift from a nitrate-reducing (beneficial) environment to a periodontopathogen-dominant environment. We specifically discuss how T2DM-induced systemic factors (such as oxidative stress) may contribute to this microbial imbalance, exacerbating periodontal tissue destruction.

CONCLUSION

RC/S: In the conclusion, the author could add the names of the periopathogen and denitrifying bacteria related to the severity of periodontal disease in T2DM patients.

Author’s Response (AR): As suggested, the Conclusion has been revised to be more specific. We now explicitly mention key genera, including Porphyromonas, Fusobacterium, Neisseria, and Rothia, and highlight their shifting interactions as a descriptive hallmark of periodontal disease severity in patients with T2DM.

 10.5256/f1000research.192091.r439956 Reviewer response for version 3 Khalel Ansam Mahdi 1 Referee https://orcid.org/0009-0002-9486-9219 University of Kufa, Najaf, Iraq

Competing interests: No competing interests were disclosed.

 29 12 2025 Copyright: © 2025 Khalel AM 2025 This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. recommendation approve

No other comment, I approved the article.

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

Partly

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Partly

Are the conclusions drawn adequately supported by the results?

Partly

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

immunology and microbiology

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

 10.5256/f1000research.192091.r439958 Reviewer response for version 3 Isola Gaetano 1 Referee https://orcid.org/0000-0003-4267-6992 University of Catania, Catania, Italy

Competing interests: No competing interests were disclosed.

 27 12 2025 Copyright: © 2025 Isola G 2025 This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. recommendation reject

The authors still not fully addressed the previous comments of the first round of revision

Is the work clearly and accurately presented and does it cite the current literature?

Partly

If applicable, is the statistical analysis and its interpretation appropriate?

Yes

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Partly

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

Periodontology, Oral medicine

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

 10.5256/f1000research.188726.r426666 Reviewer response for version 2 Khalel Ansam Mahdi 1 Referee https://orcid.org/0009-0002-9486-9219 University of Kufa, Najaf, Iraq

Competing interests: No competing interests were disclosed.

 20 11 2025 Copyright: © 2025 Khalel AM 2025 This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. recommendation approve

Based on a thorough review of the manuscript, here are comments for each section, focusing on key areas for improvement.

Abstract

The abstract identifies a potential biomarker (the  Fusobacterium-Neisseria relationship) for distinguishing gingivitis from periodontitis, which is a strong finding. However, it currently states that the G3 (periodontitis) group had the "largest abundance of  Porphyromonas gingivalis", but fails to contextualize this by comparing it to the other groups or mentioning other key bacterial shifts, which slightly weakens the summary of the overall microbiome changes observed.

Introduction

The introduction effectively establishes the bidirectional link between diabetes and periodontal disease. However, the rationale for focusing specifically on the interplay between periodontopathogens and  denitrifying bacteria could be strengthened. While denitrifying bacteria are introduced, the text should more explicitly state the central hypothesis: that a disruption in this specific functional group's relationship with pathogens is a key driver of disease progression from gingivitis to periodontitis in the unique metabolic environment of diabetic patients.

Materials and Methods

The methodology of pooling all DNA samples from each of the three groups into a single library for sequencing is a significant limitation that is not adequately addressed. This approach prevents any statistical analysis of inter-individual variation within groups, making it impossible to determine if the observed differences are truly representative of the groups or are skewed by a few outlier individuals. Consequently, the statistical tests mentioned (like Student's t-tests and ANOVA) seem inappropriate as there is only one data point (n=1) for each group's microbiome profile.

Results

The presentation of the heatmap in Figure 4 is critically flawed and misleading. The figure legend claims that "A shift in color toward dark red denotes a higher abundance," but the color key provided clearly indicates the scale represents p-values of statistical significance, not bacterial abundance. This misrepresents the data, as a cell could be dark red (highly significant) but represent a very low abundance. The results section should be revised to present this data accurately, for instance by using a heatmap where color intensity reflects relative abundance and using asterisks to denote statistical significance, rather than conflating the two.

Discussion

The discussion effectively interprets the finding that the  Fusobacterium-Neisseria interaction may be a strong predictor for the transition from gingivitis to periodontitis. To enhance this section, the authors should propose a more detailed biological mechanism for this specific interaction. For example, they could discuss how  Fusobacterium's role as a bridging organism might facilitate the colonization of certain  Neisseria species that, in the inflammatory diabetic environment, switch from a commensal to a pro-inflammatory role, thereby driving the destructive phase of periodontitis.

Conclusion

The conclusion concisely summarizes that unique relationships between denitrifying and periodontopathic bacteria exist in diabetic patients with periodontal disease. To be more impactful, it should directly state the study's most novel finding as the primary takeaway: that the specific salivary interaction between  Fusobacterium and  Neisseria emerges as a promising, non-invasive biomarker for distinguishing between gingivitis and the more severe, irreversible state of periodontitis in individuals with type 2 diabetes.

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

Partly

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Partly

Are the conclusions drawn adequately supported by the results?

Partly

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

immunology and microbiology

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Bachtiar Endang

Competing interests: Non-Financial Competing Interests

 23 11 2025

We sincerely appreciate the reviewer's enthusiasm regarding the biomarker potential of this descriptive observation. However, due to the methodological constraint of pooling the genomic DNA samples, the calculated Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC) value were statistically invalid.

1. Abstract/Conclusion:

Action Taken: We have removed all ROC analysis from the manuscript. We have revised the Conclusion to state that this specific microbial feature is a "promising, descriptive characteristic that warrants further validation"  for distinguishing disease states, tempering the claim to match the study's revised descriptive scope.

2. Heatmap:

Action Taken: We have revised the Heatmap ( Figure 4) and its caption. The figure now uses color intensity solely to reflect Relative Abundance (the descriptive data). All asterisks and p-values have been completely removed from the figure, and the caption explicitly states that the data is strictly descriptive and exploratory.

3. Introduction:

Action Taken: The final paragraph of the Introduction has been revised to more explicitly state that the central aim is to descriptively characterize the disruption of the oral nitrate-nitrite-NO pathway in the context of T2DM.

3. Introduction:

Action Taken: We have incorporated a discussion proposing a hypothetical mechanism based on descriptive findings, while emphasizing the need for future functional studies to validate this observation.

4. Results:

Action Taken: We have completely restructured the Results section to use strictly descriptive language for all microbial findings (Rarefaction Curve (Figure 1A), Diversity (Figure 1B, 1C), Phylogenetic Tree ( Figure 3), and Heatmap ( Figure 4)), while reserving inferential terms only for the clinical and nitrite/nitrate data ( Figure 5).

 10.5256/f1000research.188726.r429433 Reviewer response for version 2 Janakiram Chandrashekar 1 Referee https://orcid.org/0000-0003-1907-8708 Armita School of Dentistry, Ernakulam, India

Competing interests: No competing interests were disclosed.

 12 11 2025 Copyright: © 2025 Janakiram C 2025 This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. recommendation approve-with-reservations

This cross-sectional study compares pooled salivary microbiomes (ONT MinION whole-16S sequencing) from type-2 diabetes (T2DM) patients grouped by periodontal status (no disease G1, gingivitis G2, periodontitis G3) to explore relationships between classic periodontopathogens and nitrate-reducing/denitrifying bacteria. The authors report higher alpha diversity in diseased groups, greater abundance of P. gingivalis in G3, altered nitrate-reducer profiles (notably Neisseria, Rothia) and an ROC signal (Fusobacterium–Neisseria AUC ≈ 0.93) distinguishing gingivitis from periodontitis. Data and FASTQ files are made available.

Major concerns

Pooled libraries per group — 

The methods state that genomic DNA “of each study group’s samples was ligated in equimolar quantities to create a pool of three group libraries for nanopore sequencing” (i.e., one pooled library per group). If true, no individual-level sequence data exist for sequencing analyses, so all downstream diversity statistics (OTU counts, alpha indices, tests comparing groups, correlation heatmaps, ROC analyses) are not valid as inferential tests across subjects. Group-level pooling destroys inter-individual variance and prevents estimation of within-group dispersion, making p-values meaningless. The manuscript must explicitly state whether samples were pooled and justify this choice — but pooling precludes almost every statistical comparison reported. Clarify and, if pooling occurred, rework the paper to present only descriptive, exploratory group-level summaries (no inferential statistics), or (ideally) reprocess/sequences individual samples.

Mismatch between analyses reported and sequencing design / sample unit

Related to (1): the authors report OTU counts (n=1123), alpha diversity tests (Kruskal-Wallis, t-tests), heatmaps of correlations, differential abundance claims and ROC analysis with p-values. These require per-sample counts. The methods must: (a) clearly describe library preparation and whether sequencing reads came from individual barcodes or pooled group barcodes; (b) if barcodes represent individuals, provide per-sample read counts and QC thresholds; (c) if truly pooled, remove inferential testing and reframe conclusions as descriptive.

Bioinformatic preprocessing and compositional data treatment insufficiently described

Important details are missing or ambiguous: the pipeline steps (Dorado basecaller v7.6.8, length filter 200–1500 bp, Kraken2 with ncbi_16s_18s_28s_ITS), thresholds for read inclusion (>5 cumulative reads), normalization / transformation used for relative abundance comparisons, and whether differential abundance tools that account for compositionality (e.g., ANCOM, DESeq2 with appropriate normalization, ALDEx2, Songbird) were used. Microbiome relative-abundance data are compositional and sparse; simple comparisons of raw relative abundances can be misleading. The authors must (a) list exact commands/versions and R packages used; (b) describe normalization, filtering, rarefaction decisions; (c) justify the choice of Kraken2 reference and discuss species-level assignment accuracy with ONT long 16S reads.

Statistical methods: inappropriate tests and missing beta diversity

Authors used Shannon/Simpson for alpha diversity (fine) but then mix Kruskal-Wallis, t-tests and one-way ANOVA in ways that are unclear and possibly inappropriate given data distribution. Beta-diversity analysis (ordination: PCoA/NMDS on Bray-Curtis/UniFrac) is standard to show community shifts between groups and is missing. Differential abundance testing with multiple-test correction is also absent. explicit beta diversity analysis and clearer delineation of which software did which tests.

Study design: selection, grouping and sample size imbalance

The three groups are uneven (G1 N=28, G2 N=54, G3 N=89) and authors acknowledge no formal sample-size calculation. The manuscript must discuss potential bias from imbalance, how confounders (age, sex, HbA1c, medication, smoking) were handled, and whether statistical models adjusted for them.

Clinical periodontal phenotyping lacks radiographic confirmation and full description

Diagnosis relied on clinical CAL/PD and BOP but the manuscript states radiographs were not used. Radiographic bone loss is a standard component of periodontitis staging and its absence weakens case definition; authors must justify omission and discuss how misclassification might affect findings. Also report examiner calibration statistics (kappa or ICC) for PD/CAL measurements 

Biological interpretation overreaches given cross-sectional design

Authors imply mechanistic or predictive roles (e.g., “these features may be crucial markers for early detection”) and use ROC analyses to suggest biomarkers. Given cross-sectional data (and the pooling issue), such claims are premature. Tone down causal/predictive language and limit claims to associations. If ROC analyses are retained, justify them technically (need per-sample data & independent validation).

Figures and legends need rework

Figure legends misplaced earlier (authors note swapping of Fig 3/4 legends). Heatmap (Fig.4) lacks clear legend for colors, significance marks, and clustering annotations. ROC plots must show sample counts, confidence intervals, and cutoffs. Ensure axis labels, units and p-value reporting are consistent.

Nitrite/nitrate measurements — methods and link to sequencing

Griess assay is reported, but authors should specify sample handling (timing of collection relative to probing, storage), limits of detection, and whether nitrite levels correlate at the individual level with microbial taxa (again, requires per-sample data). Address whether saliva was collected before probing (probing can cause bleeding and alter analytes).

Taxonomic claims at species level require caution

Long-read 16S can improve resolution, but Kraken2 on 16S requires careful interpretation; species assignments (e.g., N. zoodegmatis, N. weaveri) that are normally animal-associated need cautious wording and consideration of misclassification / database contamination. Provide assignment confidence metrics (percent identity, read counts supporting species).

Reproducibility / code and data

Good that FASTQ and subject data are on Figshare; also provide the full analysis scripts (Nextflow / EPI2ME parameters, R scripts) so reviewers can reproduce analyses. 

Minor

Fix typos, duplicated sentences and figure-legend order (authors note they fixed some previously).

Define abbreviations at first use (NRB, OTU, ONT, Q-score).

Clarify whether reads are unidirectional (authors say forward or backward) and how that affects assembly/classification.

Is the work clearly and accurately presented and does it cite the current literature?

Yes

If applicable, is the statistical analysis and its interpretation appropriate?

Partly

Are all the source data underlying the results available to ensure full reproducibility?

No source data required

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Yes

Are sufficient details of methods and analysis provided to allow replication by others?

Partly

Reviewer Expertise:

Epidemilogist and ORal Health and Genetics

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

Bachtiar Endang

Competing interests: Non-Financial Competing Interest

 23 11 2025

We fully agree with this critical assessment.

Action Taken:

1. Methods Section: We have explicitly stated that DNA samples were pooled in equimolar quantities and that saliva for nitrite/nitrate measurement was NOT pooled.

2. Analytical Framework: We have revised the entire manuscript to adopt a strictly descriptive and exploratory scope for all sequencing results.

3. ROC Removal: We have removed all ROC analysis from the Abstract, Results, Figures, and Discussion, and the Methods section now explicitly states this omission and the reason.

Action Taken: We have removed all p-values, asterisks, and inferential language (e.g., 'significantly different') associated with alpha diversity, OTU counts, and taxonomic comparisons throughout the entire manuscript, including all figure captions and legends for Figures 1, 2, 3, and 4.

Action Taken: We have included Table 1: Baseline Demographic and Clinical Characteristics (on individual-level data). The Methods now explicitly state that comparison across groups was performed using ANOVA for Age and Kruskal-Wallis for non-parametric clinical indices (PD, CAL, % BOP) to ensure statistical validity.

Action Taken: This clarification is now explicit in the Methods. We confirm that appropriate inferential statistics (ANOVA/Kruskal-Wallis) were correctly applied to this individual data set and are reported with p-values in the Results ( Figure 5).

 10.5256/f1000research.188726.r420541 Reviewer response for version 2 Isola Gaetano 1 Referee https://orcid.org/0000-0003-4267-6992 University of Catania, Catania, Italy

Competing interests: No competing interests were disclosed.

 7 10 2025 Copyright: © 2025 Isola G 2025 This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. recommendation reject

Unfortunately, the original bias have not been solved. In this version there are some lacks in study design, methodology and results.

Is the work clearly and accurately presented and does it cite the current literature?

Partly

If applicable, is the statistical analysis and its interpretation appropriate?

Yes

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Partly

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

Periodontology, Oral medicine

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

 10.5256/f1000research.177804.r406077 Reviewer response for version 1 Nath Sonia 1 Referee https://orcid.org/0000-0001-8714-7264 The University of Adelaide, Adelaide, Australia

Competing interests: No competing interests were disclosed.

 16 9 2025 Copyright: © 2025 Nath S 2025 This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. recommendation reject

Here, the authors report the changes in the salivary microbiome among type 2 diabetes patients, with gingivitis or periodontitis. 

Introduction:

Include a brief evidence of the existing literature, are there other studies that have looked at a similar link between diabetes and periodontal disease? Was it conducted on a similar population? What gaps were identified in the previous study? 

How does this study fills the gaps in the literature. 

Methods:

In the inclusion criteria, T2DM patients who were under medication, but still had an unstable condition, were included. 

How was alveolar bone loss assessed? Did the authors take radiographs? 

Was sample size calculations considered. There are more number of participants in group 3 than 2 and 1. 

How many dental examiners were there for the periodontal assessment? If there were more than one periodontist, were they calibrated? Was the score of their consistency. 

What instrument was used for periodontal assessment? How many site probing was done. 

Was there any media used to store the saliva samples. Were the samples immediately stored at -80C. 

Were the saliva samples collected after the probing? Probing can cause bleeding, and this causes inflammation of the gums. Can this have an impact on the saliva samples? How was this mitigated? 

Any environmental samples collected along with saliva. 

"After rinsing the mouth"- what was used to rinse the mouth. 

How was the DNA extraction carried out? Were there any controls used for the DNA extraction process? Similarly, during PCR, were any controls used? 

Describe the sequencing briefly. What primers were used? Any reference data set used for aligning the sequences. 

Which packages in R were used for data processing? Mention the names of the packages. 

Describe clearly for which analysis R Studio was used, and for which analysis GraphPad was used. 

Results:

Include a demographic table of the included study participants for each group. 

Did the authors consider beta diversity analysis? 

For the realtive abundance table, did the authors apply any filters. Microbiome data are sparse, and did the authors consider transformation of the data or normalisation before analysis for relative abundance? Figure 2B shows only 10 genera. What about the others? Were there any statistical tests performed to compare the differences in the phylum and genera? 

In Figure 3, there is no legend for the blue colour. What does the * in the blue indicate? Figure 3 is hard to follow. What is A and B. 

Did the authors consider differential abundance analysis, 

Is the work clearly and accurately presented and does it cite the current literature?

Partly

If applicable, is the statistical analysis and its interpretation appropriate?

No

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Partly

Are sufficient details of methods and analysis provided to allow replication by others?

Partly

Reviewer Expertise:

Periodontist and microbiolgy researcher

I confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above.

Bachtiar Endang

Competing interests: No Competing Interests

 24 9 2025

RC#2: Was sample size calculations considered. There are more number of participants in group 3 than 2 and 1. 

AR: We appreciate the reviewer's insightful assessment of the sample size and participant distribution. We note that no formal statistical procedure was used to establish the number of participants in each category. Instead, we used a consecutive or sequential sampling strategy for a set amount of time (November 2023 to January 2024). Because fewer patients met the requirements for Group 1 (T2DM without periodontal disease) at the time of sampling, this strategy led to an uneven number of participants throughout the groups. We acknowledge that this is a study constraint because it could have an impact on the statistical power of comparisons between groups. However, finding possible microbial markers of illness development was our main goal, and the notable variations in our findings—especially between Group 1 and the other groups—indicate that the sample size was enough for these particular analyses. _We acknowledge that more research with a bigger, more balanced cohort would be helpful to validate our findings, and we have added a sentence to our Limitations section to specifically express this point.

Reviewer’s#1 comment (RC#1):

1.The authors should be better specified, at the end of the introduction section, the rationale of the study and the aim of the study.

AR: Thank you for this important suggestion. Accordingly, at the end of the introduction section, we state the gap of previous studies, as suggested by the Reviewer#2 (yellow highlighted) and the aim of our study (green highlighted).

2. In the central section, should better clarify inclusions and exclusions criteria of the selected sample.

AR: Yes, we agree. Accordingly, we have revised the inclusion and exclusion criteria. Many hanks. 

3. In the Discussion section….better discuss the relationship regarding the by periodontitis in and risk of oxidative stress evolution linked with inflammation in periodontitis patients.

AR: Thank you for your suggestion. Accordingly, we have added one paragraph to explain the relationships (highlighted in green).

4. The conclusion should reinforce in light of the discussions.

AR: We agree. As a result we have revised the conclusion (highlighted in green). Thank you.

Minor Comments:

RC#1

Abstract:

Better formulate the abstract section by better describing the aim of the study

Introduction:

Please refer to major comments

Discussion

Please add a specific sentence that clarifies the results obtained in the first part of the discussion

AR: Thank you for all of the reviewer remarks. Consequently, we have caried out as indicated, the updated version in the respective section. Many thanks.

Reviewer’s#2  comment (RC#2):

Introduction section

Include a brief evidence of the existing literature, are there other studies that have looked at a similar link between diabetes and periodontal disease? Was it conducted on a similar population? What gaps were identified in the previous study? 

How does this study fills the gaps in the literature. 

Author’s response (AR)

Thank you for the suggestion. As a result, we updated the introduction, including the additional research and explaining how it fills in the gaps by concentrating on specific bacterial families (highlighted in yellow). 

RC#2: Methods:

In the inclusion criteria, T2DM patients who were under medication, but still had an unstable condition, were included. 

AR: We appreciate the reviewer's insightful observation. We recognize the possibility of confounding variables being introduced by include patients with different levels of glycemic control, which may be viewed as "unstable." Our main goal, therefore, was to examine a representative sample of people with Type 2 Diabetes, a group in which glycemic control and associated issues frequently differ. Therefore, our findings are more clinically relevant because we included a wide variety of diabetic individuals rather than a highly selected sample. This was minimized by excluding participants who were taking drugs (such as hormones) or had other serious metabolic conditions that would have an adverse effect on the study's results. In the Discussion section, we have included a phrase acknowledging this restriction, which may necessitate additional research in subsequent studies.

RC#2: How was alveolar bone loss assessed? Did the authors take radiographs? 

AR: We appreciate the reviewer's wise observation. We recognize that radiographic evaluation is a regular part of a thorough periodontal examination and is an essential tool for assessing alveolar bone loss. However, the main goal of our study was to find non-invasive salivary microbiological markers that could help differentiate between periodontitis and gingivitis. Our patient groups were adequately stratified using clinical characteristics, namely Clinical Attachment Loss (CAL) and probing depth, in accordance with the recognized classifications of periodontal disease. The use of radiographic imaging was deemed outside the purview of this particular study design because our primary focus was on the microbial composition of saliva as a biomarker, a non-invasive sample. _We also think that a more thorough and multifaceted knowledge of the illness progression would be possible with a future study that combines our microbiological findings with radiographic data. To address this problem, we have included a statement in our Limitations section.

RC#2: Was sample size calculations considered. There are more number of participants in group 3 than 2 and 1. 

AR: We appreciate the reviewer's insightful assessment of the sample size and participant distribution. We note that no formal statistical procedure was used to establish the number of participants in each category. Instead, we used a consecutive or sequential sampling strategy for a set amount of time (November 2023 to January 2024). Because fewer patients met the requirements for Group 1 (T2DM without periodontal disease) at the time of sampling, this strategy led to an uneven number of participants throughout the groups. We acknowledge that this is a study constraint because it could have an impact on the statistical power of comparisons between groups. However, finding possible microbial markers of illness development was our main goal, and the notable variations in our findings—especially between Group 1 and the other groups—indicate that the sample size was enough for these particular analyses. _We acknowledge that more research with a bigger, more balanced cohort would be helpful to validate our findings, and we have added a sentence to our Limitations section to specifically express this point.

RC#2:  How many dental examiners were there for the periodontal assessment? If there were more than one periodontist, were they calibrated?

AR: We thank the reviewer raising this important query. Yes, we accomplished the calibration process and included it in the methods section (highlighted in yellow).

RC#2:  Was sample size calculations considered. There are more number of participants in group 3 than 2 and 1.

AR: We appreciate the reviewer's insightful assessment of the sample size and participant distribution. We recognize that no formal statistical procedure was used to establish the number of participants in each category. Rather, we used a sequential sampling method for a particular time frame (November 2023 to January 2024). Because fewer patients met the requirements for Group 1 (T2DM without periodontal disease) at the time of sampling, this strategy led to an uneven number of participants throughout the groups.

We acknowledge that this is a study constraint because it could have an impact on the statistical power of comparisons between groups. However, finding possible microbial markers of illness development was our main goal, and the notable variations in our findings—especially between Group 1 and the other groups—indicate that the sample size was enough for these particular analyses.

We acknowledge that more research with a bigger, more balanced cohort would be helpful to validate our findings, and we have added a sentence to our Limitations section to specifically express this point (kindly see the limitation section).

RC#2: What instrument was used for periodontal assessment? How many sites probing was done

AR: I value your questions. We employed the UNC-15 probe and the explanation of the probing site, provided in the Methods section.

RC#2: Was there any media used to store the saliva samples. Were the samples immediately stored at -80C.

Were the saliva samples collected after the probing? Probing can cause bleeding, and this causes inflammation of the gums. Can this have an impact on the saliva samples? How was this mitigated?

AR: We did not use any media to store the saliva, and as can be seen in Methods section, “the sample was immediately stores in -80oC until DNA extraction”. Thank you. Saliva samples were collected as well before the probing was carried out. In the Method section, we describe this. 

RC#2: Any environmental samples collected along with saliva. “After rinsing the mouth"- what was used to rinse the mouth.

AR: NO, we only collected saliva as oral sample, and 

we used 0.9% normal saline for about 30 s  as mentioned in the methods section.

RC#2: How was the DNA extraction carried out? Were there any controls used for the DNA extraction process? Similarly, during PCR, were any controls used? 

AR: The reviewer's insightful feedback on the PCR and DNA extraction processes is greatly appreciated. We acknowledge that the application of controls is necessary to guarantee the accuracy of the data. As we explained in the Methods, we followed the manufacturer's instructions for the 16S Barcoding Kit and the MonarchTM Genomic DNA purification kit for performing the PCR and DNA extraction processes. The controls were included during the DNA extraction and PCR amplification processes in accordance with the kit's instructions. 

RC#2: Describe the sequencing briefly. What primers were used? Any reference data set used for aligning the sequences.

AR: We appreciate your inquiries. Yes, as you can see from the Methods, we have followed the company's instructions for both the alignment and the sequencing process. 

RC#2: Which packages in R were used for data processing? Mention the names of the packages. 

Describe clearly for which analysis R Studio was used, and for which analysis GraphPad was used.

Reviewer’s comment (RC#2):

For the relative abundance table, did the authors apply any filters. Microbiome data are sparse, and did the authors consider transformation of the data or normalisation before analysis for relative abundance? 

Author’s response (AR):

I appreciate your queries. Indeed, we trimmed and filtered them, and we included them in the procedure part under the subheading "DNA extraction, sequencing, and saliva sample collection." 

RC#2 : Which packages in R were used for data processing? Mention the names of the packages. 

Describe clearly for which analysis R Studio was used, and for which analysis GraphPad was used. 

AR: Thank you for these queries, As can be seen in the Methods section, OTUs study was performed using the vegan, ggplot2, and dplyr packages while heatmap was performed using pheatmap and R ColorBrewer packages in R Studio software (version 4.3.2). Moreover,  the Receiver Operating Characteristic (ROC) curves and one-way ANOVA were conducted using GraphPad for the study of salivary nitrite levels.

Reviewer’s#2 comment and suggestion:

-Include a demographic table of the included study participants for each group. 

-Did the authors consider beta diversity analysis? 

Author’s response.

I agree. We included a table on characteristics as advised. 

We recognize that one common method for comparing microbial communities is beta diversity analysis. However, the main goal of our study was to look at the quantity and variety of microorganisms found solely in saliva and no additional oral samples; beta diversity was not taken into account during the analytical process. Thank you very much.

 10.5256/f1000research.177804.r406078 Reviewer response for version 1 Isola Gaetano 1 Referee https://orcid.org/0000-0003-4267-6992 University of Catania, Catania, Italy

Competing interests: No competing interests were disclosed.

 3 9 2025 Copyright: © 2025 Isola G 2025 This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. recommendation approve-with-reservations

In the manuscript entitled: “Salivary microbiome and periodontopathogen/denitrifying bacteria associated with gingivitis and periodontitis in people with type 2-diabetes" the author aimed to compare the salivary microbiomes of individuals with type 2 diabetes (20–40 years old) who had gingivitis or periodontitis to those who did not. Additionally, were evaluated the relationship between the number of periodontopathogens and the amount of nitrate-reducing bacteria in their salivary microbiome.

The author found that people with type 2 diabetes mellitus who also have gingivitis or periodontitis exhibit different relationships between periodontopathic and denitrifying bacteria in their salivary microbiome. These features might be essential indicators for early identification and treatment of gingivitis in order to prevent periodontitis.

Major comments:

In general, the idea and innovation of this study regards the analysis of the link between mediators, and periodontitis is interesting and novel because the role these aspects in medicine are validated but further studies on this topic could be an innovative issue in this field could be open a creative matter of debate in literature by adding new information. Moreover, there are few reports in the literature that studied this interesting topic with this kind of study design.

The study was well conducted by the authors; However, there are some concerns to revise that are described below.

The introduction section resumes the existing knowledge regarding the important factor linked with the relationship between periodontitis and related mediators associated with systemic disease risk.

However, as the importance of the topic, the reviewer strongly recommends, before a further re-evaluation of the manuscript, to update the literature through read, discuss and cites in the references with great attention all of those recent interesting articles, that helps the authors to better introduce and discuss the relationship and impact of chlorexidine and micro RNA on periodontal tissues and mediators that could impact diabetes amelioration: 1) Ref 1 2) Ref 2

The authors should be better specified, at the end of the introduction section, the rationale of the study and the aim of the study. In the central section, should better clarify inclusions and exclusions criteria of the selected sample.

Please better state the results obtained in the abstract.

The discussion section appears well organized with the relevant paper that support the conclusions, even if the authors should better discuss the relationship regarding the by periodontitis in and risk of oxidative stress evolution linked with inflammation in periodontitis patients. The conclusion should reinforce in light of the discussions.

In conclusion, I am sure that the authors are fine clinicians who achieve very nice results with their adopted protocol. However, this study, in my view does not in its current form satisfy a very high scientific requirement for indexing in this journal and requests a revision before a futher re-evaluation of the manuscript.

Minor Comments:

Abstract:

Better formulate the abstract section by better describing the aim of the study

Introduction:

Please refer to major comments

Discussion

Please add a specific sentence that clarifies the results obtained in the first part of the discussion

Is the work clearly and accurately presented and does it cite the current literature?

Partly

If applicable, is the statistical analysis and its interpretation appropriate?

Yes

Are all the source data underlying the results available to ensure full reproducibility?

Yes

Is the study design appropriate and is the work technically sound?

Yes

Are the conclusions drawn adequately supported by the results?

Partly

Are sufficient details of methods and analysis provided to allow replication by others?

Yes

Reviewer Expertise:

Periodontology, Oral medicine

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

References : Impact of periodontal microRNAs associated with alveolar bone remodeling during orthodontic tooth movement: a randomized clinical trial. Journal of Translational Medicine .2024;22(1) : 10.1186/s12967-024-05933-x 10.1186/s12967-024-05933-x : Effect of Nonsurgical Mechanical Debridement With or Without Chlorhexidine Formulations in the Treatment of Peri‐Implant Mucositis. A Randomized Placebo‐Controlled Clinical Trial. Clinical Oral Implants Research .2025;36(5) : 10.1111/clr.14405 566-577 10.1111/clr.14405 Bachtiar Endang

Competing interests: No Competing Interests

 24 9 2025

Major comment

Abstract: Abstract:

- Better formulate the abstract section by better    describing the aim of the study.

- Please better state the results obtained in the abstract.

AR: Thank you for these important suggestions. Thus, in the revised version, we have formulated both the study’s aim and the result (highlighted in green).

RC#1: ……”introduce and discuss the relationship and impact of chlorhexidine and micro RNA on periodontal tissues and mediators that could impact diabetes amelioration”

AR: We thank the reviewer's insightful recommendation. We also agree that including current research on microRNA and chlorhexidine will improve our manuscript by setting our investigation in a more comprehensive scientific framework. Although the microbial associations are the main focus of our work, we have included a few phrases in the Introduction (green highlighted) to recognize their involvement in the intricate interactions between oral and systemic health.

RC#1: …..The authors should be better specified, at the end of the introduction section, the rationale of the study and the aim of the study.

AR: We agree. this suggestion was also provided the Reviewer#1. Accordingly, we have revised it as suggested. Thank you.