Correction: Feasibility and preliminary findings of a bacterial diversity study in periodontitis: a pilot investigation from the Western Cape

Résumé

Introduction: Periodontitis is a significant health challenge caused by a complex interaction between bacterial infection, host immune response, and environmental factors, leading to tooth loss, bone loss, and potential associations with major systemic diseases and conditions. While the determinants of periodontitis have been extensively investigated in other populations, such studies are lacking in South Africa, which represents a high-risk population. Therefore, this study was conducted to characterize the subgingival bacterial biodiversity in the periodontal pockets of patients with periodontitis in a Western Cape population.Materials & methods: Pooled subgingival plaque samples were collected from the deepest pocket/crevices of five periodontitis cases and five controls using sterile paper points. Illumina MiSeq paired-end sequencing and QIIME2 software were employed for sequence filtration and analysis. Several alpha and beta-diversity metrics assessed biodiversity within-sample and population structure between different microbiota datasets, respectively. Statistical significance for alpha diversity was tested using the Kruskal–Wallis H test ( p < 0.05), and beta diversity differences were evaluated using PERMANOVA. Data visualization, including beta diversity plots, was conducted with the Phyloseq package in R.Results: Beta-diversity measures revealed significant differences between periodontitis cases and controls ( p-value = 0.04), whereas alpha-diversity was higher in cases, though without statistical significance ( p-value ≥ 0.05). Cases group showed high relative abundance of Fusobacterium (16%), Porphyromonas (10%), and Treponema (9%), while the periodontally healthy controls were dominated by Streptococcus (20%), Fusobacterium (15%), and Veillonella (10%), with g_Streptococcus showing a significant difference (p-value = 0.008). Differential abundance analysis revealed distinct bacterial genera enriched in cases (Bulleidia, Peptoanaerobacter, Phocaeiola, W5053) and controls (Abiotrophia, Haemophilus, Lautropia, Rothia, Streptococcus). Sample-specific variations included higher levels of Porphyromonas (15%) in grade B and Fusobacterium (20%) in grade C.Conclusion: This exploratory study highlights distinct bacterial communities associated with periodontitis in a South African population. The findings emphasize the need for larger, population-based cohorts to validate these results and lay a foundation for future research into region-specific microbial profiles and their implications for personalized treatment strategies.1.INTRODUCTION:According to the WHO’s Global Oral Health Status Report (2022), 19% of the global population aged 15 years and older is affected by severe periodontitis, with the highest prevalence in Africa (23%) (1). Periodontitis is a multifactorial disease triggered by dysbiosis in dental biofilm that promotes inflammation with both protective and destructive effects on periodontal tissues (2). This dysbiosis negatively impacts oral and general health, reducing the quality of life (3) and contributing to a global healthcare burden and social inequality (4).Advances in culture-independent molecular techniques have revealed distinct bacterial communities in periodontal health and disease (5). Despite limitations such as short sequencing reads, limited species-level resolution for certain bacterial genera (6), lack of standardization in selecting hypervariable regions for sequencing (7), and an inability to provide functional insights (8), 16S rRNA sequencing remains the gold standard for bacterial profiling (9). These techniques highlight the diagnostic and prognostic potential of microbiome biodiversity in periodontitis, where changes in microbial composition signal early disease, and biodiversity loss is linked to disease progression (10). Restoring microbial diversity could be a key therapeutic goal in periodontitis, promoting a balanced oral microbiome essential for achieving and maintaining periodontal stability (11).While the current classification system for periodontitis incorporates pathophysiological and host immune factors that justified the consolidation of periodontitis into a unified category (12), it does not include microbial criteria to differentiate between stages and grades. This limitation arises primarily from insufficient evidence-based data on microbiological diagnostics in periodontitis (13).Emerging evidence suggests that the subgingival microbial composition in periodontitis patients varies significantly based on population, demographic factors, and environmental conditions (14,15). These findings highlight the potential relevance of microbial profiling in enhancing and refining periodontal classification systems.However, much of our understanding of periodontitis microbiota is derived from studies conducted in non-African populations (16). Recent insights highlight the need for population-specific investigations. For instance, Aggregatibacter actinomycetemcomitans, strongly linked to Grade C Molar-Incisor periodontitis, appears to be highly prevalent among Africans, compared to other ethnic groups (17-20).Therefore, investigating periodontitis determinants in high-risk, diverse populations, such as South Africans (SAs), is imperative for developing a successful precision dentistry health system. Recent work established the microbial profile of the SA population who smoke (21). However, no study has been conducted to establish the baseline bacterial profile of SAs with periodontitis compared to those with a healthy periodontium. Given these considerations, the primary objective of this study was to characterize the subgingival bacterial communities within periodontal pockets of periodontitis patients from the Western Cape, SA, and to assess whether microbial composition differs across the various grades of periodontitis. This pilot study aims to lay the foundation for future, more comprehensive research by evaluating both the feasibility and potential benefits of the proposed study within a diverse population. 2.MATERIAL AND METHODS: 2.1 Study population: Ethical approval was obtained from the Biomedical Research Ethics Committee (BMREC) of the University of the Western Cape (UWC), reference number BM20/10/9. Twenty-three consecutive South African participants, aged 18 years or older and with at least 10 teeth, were recruited from the Oral Medicine and Periodontology Department at Tygerberg Oral Health Centre between August 2021 and October 2022. Participants were excluded if they had any systemic disease, were current smokers, pregnant or lactating, edentulous, had used antiseptics or anti-inflammatory drugs for more than one week, antibiotics, antimicrobials, undergone any periodontal management in the past three months. Therefore, a final sample size of 23 patients was included in this study.All potential participants underwent Basic Periodontal Examination (BPE) to assess their periodontal status. Eligible participants then received a comprehensive periodontal examination for detailed clinical data collection. Personal and demographic information, including age, gender, and self-reported ethnicity, were also collected.Panoramic radiographs were taken, and a calibrated periodontist with high intra-reliability (kappa > 0.81) conducted clinical examinations, documenting periodontal parameters such as full mouth plaque score (FMPS), full mouth bleeding score (FMBS), probable pocket depth (PPD), and clinical attachment level (CAL). Participants were categorized into periodontitis cases and periodontally healthy controls based on the case definitions outlined in the 2018 classification scheme of periodontal diseases (13,22). Following this, a complete diagnosis of periodontitis cases was established using the multidimensional staging and grading systems, in which disease severity was categorized into four stages (I-IV), ranging from mild clinical attachment loss, Stage I, to severe periodontitis with extensive bone and tooth loss, Stage IV. Staging was determined based on CAL, radiographic bone loss, disease complexity, and its extent and distribution; localized or generalized. Progression was further graded as A (slow progression), B (moderate progression), or C (rapid progression). Grading was based on CAL and bone loss in relation to age, case phenotype reflected through FMPS, and the presence of grade modifiers such as diabetes mellitus (DM) and smoking (13, 22). 2.2 Subgingival samples: After the removal of the supra-gingival biofilm, the teeth targeted for sampling were isolated with cotton rolls and dried. Sub-gingival dental biofilm samples were acquired from the mesobuccal surface of teeth with the deepest pathological pocket (or cervices in the healthy group) of each quadrant by gently introducing a sterile paper point # 35 (23-30). If a deeper pathological pocket (or cervices in the healthy group) was identified on another surface, it was used for sample collection. Paper points were immediately transferred from the participant's mouth and pooled into a sterile 2 ml Eppendorf tube containing 500μl of phosphate-buffered saline (PBS), then immediately placed on ice. As per the recommendation of the best storage temperature for microbiome material, samples were frozen at -80°C at IMBM until DNA extraction was conducted. 2.3 DNA extraction and sequencing: DNA extraction from the dental biofilm samples was performed using the PureLinkTM Microbiome DNA Purification Kit (#A29790; Thermo Fisher Scientific, Waltham, Massachusetts, USA), following the manufacturer's recommendations under sterilized conditions. The extracted DNA quality and concentration were evaluated using the NanoDrop® ND 1,000 Spectrophotometer and the Qubit® 2.0 fluorometer (Invitrogen, Thermo Fisher Scientific, Waltham, Massachusetts, USA), respectively. Samples with DNA quality metrics meeting the Illumina 16S metagenomics workflow requirements for optimal outcomes (≥20 μl of 10 ng/μl, A260/280: 1.8-2.0, A260/230: 1.5-2.2) were selected for downstream analysis. While the majority of the samples met the criteria, only the top ten with the highest quality and quantity were included in downstream analysis due to funding limitations.For PCR amplification of the hypervariable V3-V4 regions of the16S ribosomal RNA gene (16S rRNA), the following primer sequences were used:• Forward primer (341F primer + Illumina overhang adapter underlined): TCGTCGGCAGCGTCAGATGTGTATAAGAG ACAGCCTACGGGNGGCWGCA• Reverse primer (805R primer + Illumina overhang adapter underlined): GTCTCGTGGGCTCGGAGATGTGTATAAGAG ACAGGACTACHVGGGTATCTAATCC Following this, the Nextera XT v2 Indexes were used for amplicon barcoding, which were then multiplexed, spiked with 10% of a 6 pM PhiX, and sequenced using the MiSeq Reagent Kit v2 (500 cycles) on the Illumina MiSeq platform (#15044223, Illumina, San Diego, CA, USA) at the Centre for Proteomic and Genomic Research. 2.4 Data analysis:Raw sequencing reads were quality filtered and trimmed, retaining only a Q-score > 20 and overlapping regions were allowed up to two of the ambiguous bases. Analysis of raw sequence data was mainly performed using Quantitative Insights into Microbial Ecology 2 (QIIME2) 2022.2 (https://qiime2.org/, RRID:SCR_021258), with DADA2 plugin to correct sequencing errors and cluster the sequences into amplicon sequence variants (ASVs). Each ASV was aligned and classified at the genus level using the Greengenes database, V.2024.09 (https://qiime2.org/, RRID:SCR_002830).Differential abundance testing was conducted by the Wald test with Benjamin-Hochberg adjustment for false discovery (31) using an adjusted p-value < 0.05, as implemented in the DESeq2-package in R. Features appearing in <10% of the samples and a relative abundance of <5% were filtered out.Further statistical analysis and plot generation were conducted using R package, V4.2 (http://www.r-project.org/, RRID: SCR_001905).Alpha-diversity was assessed using various metrics, including Observed richness, Chao1, Abundance Coverage Estimator (ACE), Simpson and Shannon indices, to estimate richness, abundance, and diversity within the sample (32). The Kruskal-Wallis H test was applied to all alpha-diversity metrics to determine statistical significance, with a threshold set at pvalue < 0.05.Beta-diversity was evaluated using the Bray-Curtis, Jaccard, Weighted UniFrac, and Unweighted UniFrac distance metrics on the rarefied datasets to assess differences in microbial community structure between comparison groups. The Phyloseq package in R was used to visualize these distances through principal coordinate analysis (PCoA) plots. Distance based permutation multivariate analysis of variance (PERMANOVA) was conducted using Adonis 2 from the vegan R package (33). This was followed by a test for homogeneity. 3. Results: 3.1 Demographics and clinical parameters: The demographics and clinical parameters are detailed in Table 1. The majority of the participants in the study were females, with only one male in the control group. Within the control group, three participants self-identified as SA Coloured (SAC), while the case group had an equal distribution of Caucasian and African participants, with only one participant from the SAC ethnic group. Among the periodontitis cases examined, Stage IV was the most prevalent, observed in three out of five cases, while Stage III accounted for the remaining two. For grading, the cases were classified as either Grade B or C, with Grade C indicating the highest severity, also found in three out of five cases. Additionally, all periodontitis cases exhibited a generalized distribution, as detailed in Table 1. P-values for the participant's quantitative and qualitative variables were not included as this was a preliminary descriptive study with limited sample size.The observed distribution of the continuous variables between cases and controls is tabulated in Table 2. Based on the full-mouth clinical examination, periodontitis cases exhibited higher FMBS, FMPS, PPD, and CAL values, and fewer present teeth, when compared to the periodontally healthy controls. The differences between the median estimates all seem minimal. The control subjects seemed to be about 8 years younger on average but with larger variation between them (SD ≈ 21.49). 3.2 Sequence data: A total of 3.2 V3-V4 16S paired-end reads were from the 10 pooled After reads were The average of the filtered reads was A total of were with a total of quality Subgingival bacterial sequencing: The top 10 genera with the highest relative abundance in the periodontitis cases group were Fusobacterium (16%), Porphyromonas (10%), Treponema (9%), Streptococcus and Veillonella the control group was dominated by for of all at the genus This was followed by Fusobacterium (15%), Veillonella (10%), Porphyromonas Treponema and abundance analysis at the genus level showed that four Peptoanaerobacter, Phocaeiola, and were enriched in the cases group while five Haemophilus, Lautropia, Rothia, and were enriched in the controls significant difference was only for the g_Streptococcus when the top 10 genera between periodontitis cases and periodontally healthy controls at genus level ( p-value = periodontitis Fusobacterium was the most genus (20%) in grade C, while Porphyromonas (15%) and Treponema were more in grade grade sample 2 showed a equal abundance of all with higher levels of Treponema and was in a higher abundance of Porphyromonas among all grade C samples were dominated by However, sample had higher abundance of and followed by Samples and had high levels of and with sample in Porphyromonas and in A total of five were found to be significantly the and were enriched in grade B cases, while and were enriched in the grade C cases. other significant differences were identified among all genera between both grades ( p-value ≥ Despite higher median alpha-diversity in the periodontitis samples compared to the controls was no significant difference > in the alpha-diversity metrics significant for Shannon and potential differences Table of alpha diversity and conducted for cases and controls group samples are in Table distance the highest of variance compared to Bray-Curtis, Unweighted and which and of the respectively. The plot based on distance showed that all cases samples while the controls samples more revealed significant differences in the average community composition between cases and controls ( p-value = but with a test ( p-value = this the subgingival microbiota in patients with periodontitis within a SA was The analysis the progression of periodontitis not variations in bacterial diversity as assessed by alpha-diversity metrics, significant differences in community structure were identified using beta-diversity Weighted UniFrac distance analysis distinct within the periodontitis group, whereas the control group exhibited higher in microbiota composition and structure among healthy findings are with those of who the Unweighted UniFrac distance to microbial variation in periodontally healthy and who employed the to microbial composition in participants across different clinical and groups. studies identified subgingival plaque and the observed in healthy to the presence of environmental factors to microbial that the healthy developing a diverse community of both health and As disease the microbial community is then by in the of a more microbiota from this study are with studies conducted in and populations also with the results of who significant differences in alpha and beta diversity across ethnic groups in However, our findings with who observed no significant diversity differences in patients with periodontitis of Caucasian from exhibited between cases and it to them into distinct health groups across studies This challenge from the potential limitations in health at the microbial as such are based on clinical This was in the present where the relative of certain genera showed variation between cases with periodontitis and including Fusobacterium and differences were observed in Veillonella Streptococcus Porphyromonas and Treponema with Streptococcus significantly more in controls ( p = found and genera to be associated with periodontitis, while Streptococcus and linked to healthy showed findings with research and the associated with periodontitis, as by of studies across diverse populations Fusobacterium as the most genus in this which highly results were in and populations using and in a where Fusobacterium was in all periodontitis patients and in of healthy controls using PCR found Fusobacterium to be in healthy controls and in with or Fusobacterium is in periodontitis patients who smoke the participants in this study were for this study is Porphyromonas is as the key for periodontitis it is significantly to host than Fusobacterium as by Fusobacterium a to relative to showed that with Fusobacterium the potential of in oral This of its in Additionally, the high prevalence of Fusobacterium has been linked to various including and across different populations the abundance of Fusobacterium in the SA population with periodontitis a population-specific this among the top 10 genera in both periodontitis cases and controls. that its in periodontal contributing to disease progression The abundance of varies across populations with with prevalence of in population in population and in pockets and in pockets among of cases and of was as in patients with periodontitis and in the microbiome of patients with in periodontitis further the healthy group, Streptococcus and Veillonella were the with findings from studies a primary on tooth a key in promoting microbial while a of health, by Streptococcus and is associated successful periodontal proposed that Veillonella as an the of within was in of healthy controls. 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