Salivary and Plaque Microbiomes During Treatment With Different Orthodontic Appliances

Emily Duong, BS; Elaine Pham, BS; Julia Esfandi, BS; Kim-Sa Kelly, BS; Arvin Pal, DDS; Masooma Rizvi, DDS; Nini Tran, DDS, PhD; Tingxi Wu, DDS, PhD; Bhumika Shokeen, PhD; and Renate Lux, PhD

ABSTRACT

Background: This study investigated the microbial changes during treatment with clear aligners (CA) and fixed appliances (FA) and evaluated the utility of saliva as a diagnostic marker in orthodontic patients.

Methods: Ten patients each were enrolled in the FA and CA groups. Plaque (PI) and gingival indices (GI) were measured at baseline, three, six and 12 months. Saliva and plaque samples were collected at each time point for determination of the respective microbial community composition via 16S rRNA sequencing.

Results: PI and GI increased significantly over time only in FA patients. While alpha diversity was similar for FA or CA patients, beta diversity and microbial community composition analysis revealed significant differences between saliva and plaque for both treatment groups. Further analysis of the relative abundance of certain health- and disease-associated genera present in the saliva and plaque of FA and CA patients correlated with the clinical parameters.

Conclusions: Clinical parameters significantly worsened during orthodontic treatment with FA but not CA. The microbial composition of plaque and saliva differed significantly between treatment groups. However, the changes in abundance of some individual genera were similar in both saliva and plaque in correlation with the corresponding clinical parameters. These genera show potential as biomarkers for health and disease.

Practical implications: Monitoring of the microbial community composition during orthodontic treatment could reduce the risk of oral disease development. While the microbial composition of saliva is not reflective of the plaque communities implicated in oral health and disease, individual marker genera show promise as biomarkers.

Keywords: Orthodontics, fixed appliances, clear aligners, microbiome, saliva, plaque, gingival inflammation

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AUTHORS

Emily Duong, BS, is a DDS candidate at the University of California, Los Angeles (UCLA), School of Dentistry. She and Ms. Pham contributed equally to this paper.

Elaine Pham, BS, is a fourth-year student in the department of molecular, cell and developmental biology at UCLA. She and Ms. Duong contributed equally to this paper

Julia Esfandi, BS, is a DDS candidate at UCLA.

Kim-Sa Kelly, BS, is a DDS candidate at UCLA.

Arvin Pal, DDS, is a thirdyear orthodontics resident at UCLA.

Masooma Rizvi, DDS, is a first-year periodontics resident at UCLA.

Nini Tran, DDS, PhD, is an assistant professor in the section of pediatric dentistry at UCLA.

Tingxi Wu, DDS, PhD, is the director of orthodontic and craniofacial development research at the Forsyth Institute in Cambridge, Massachusetts.

Bhumika Shokeen, PhD, is a project scientist in the section of periodontics at the UCLA School of Dentistry.

Renate Lux, PhD, is a professor in the section of periodontics at the UCLA School of Dentistry.

Conflict of Interest Disclosure: None reported for any of the authors.

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Malocclusion has traditionally been treated with the use of orthodontic fixed appliances (FA) to correct tooth alignment. This treatment involves brackets and bands bonded onto the enamel and a flexible arch-wire ligated onto the brackets in order to produce light continuous forces to reposition teeth. However, FA can impede oral hygiene care and contribute to significant biofilm accumulation, resulting in a higher risk of caries and periodontal diseases. 1 The introduction of clear aligners (CA) in the 1990s as a removable option to address malocclusion has facilitated proper oral hygiene practices. While correct usage of CA can be very beneficial for oral hygiene, CA patients still run the risk of developing dental plaque on tooth surfaces due to the full coverage design of the CA. Dental plaque is a sticky film of bacteria that layers itself onto oral surfaces in an intricate, well-organized manner. 2,3 Accumulation of this dental plaque often leads to gingival inflammation and enamel demineralization, resulting in periodontal diseases and dental caries. 1

Several earlier studies investigating the clinical health in patients treated with different types of orthodontic appliances reported that in comparison to FAs, treatment with CA resulted in improved periodontal health 4–8 and reduction in plaque accumulation. 9,10 Generally, clinical outcomes are closely interrelated with the associated microbial communities. Therefore, investigating the changes in microbiome composition after the introduction of orthodontic appliances is critical for understanding their impact on oral health.

Most of the earlier efforts to evaluate the changes in microbial composition after the introduction of orthodontic appliances in the oral cavity were targeted to a few selected pathogens by quantitative methods. 10–12 While these approaches yielded some interesting insights, they did not allow a deep understanding of the changes occurring at the community level. More recently, several studies have investigated the effect of clear aligners treatment on the oral microbial community as a whole, 13,14 but only a selected few studies 15–17 have compared the microbiomes between two different orthodontic treatments (CAs and FAs). Additionally, these studies either analyzed plaque 15,16 or saliva to evaluate the microbial changes. 17 Comprehensive studies comparing the clinical implications of the two different treatment modalities along with the longitudinal assessment of the microbial composition of saliva and plaque are still missing. This lack of inclusive studies evaluating the effects of treatment leaves a significant gap in our understanding of the microbial shift and the associated oral health implications.

In the oral cavity, saliva serves a variety of functions including lubrication of oral tissues and plays important roles in the host defense against pathogens. Additionally, saliva acts as a buffer and prevents the progression of tooth decay by remineralizing the tooth enamel layer and neutralizing the acidity of bacterial metabolic waste products. As saliva is a repository of microbes and multiple other biomarkers, numerous studies have explored the use of saliva as a diagnostic tool. 18–20 Although, in periodontitis, some studies have demonstrated the potential of saliva as a reliable diagnostic tool, 21,22 the use of saliva as a dependable diagnostic tool for patients undergoing orthodontic treatment remains unclear.

The few studies 17,23 that have explored saliva for investigating changes in microbial composition during orthodontic treatment did not identify any significant changes in salivary microbial composition post-treatment. Thus, our aims in this longitudinal study were to investigate the microbial changes in plaque and saliva of patients with FA or CA and assess the corresponding clinical parameters. Furthermore, we evaluated the utility of saliva as a diagnostic marker for oral microbiome changes during orthodontic treatment.

Materials and Methods

This study was approved by the Institutional Review Board (IRB) at the University of California, Los Angeles (UCLA) (IRB #16-001258). The subjects who were starting their treatment at the UCLA orthodontics clinic were screened and recruited in the study. Informed consent was obtained and subjects were grouped based on their treatment modality, with 10 subjects each in the FA or CA groups. Patients with active caries, periodontal disease and chronic systemic diseases were excluded, along with patients who took antibiotic medications within 30 days of starting treatment.

Saliva and plaque samples were collected from patients at four different time points: pretreatment baseline (T0), three months (T1), six months (T2) and 12 months (T3) after treatment start. At each appointment, plaque and gingival indices were measured. Plaque accumulation was quantified using the Turesky Modified Quigley- Hein Plaque Index (TQHPI), 24 which utilizes a scale from 0-5 to evaluate supragingival tooth plaque after the patient rinsed with a TRACE disclosing solution (Young Dental LLC, Earth City, Missouri). For gingival health, swelling and bleeding, the two signs of inflammation, were assessed and the level of gingival disease was qualitatively measured with the Löe-Silness gingival index (GI) on a scale from 0-3. 25

Supragingival plaque samples were collected from the gingival third of the central incisors and premolars using sterilized periodontal scalers. To obtain saliva samples, patients expectorated into 50 ml sterile falcon tubes. The saliva was then aliquoted into cryotubes with 15% glycerol in phosphate buffered saline (1X PBS) and stored in a freezer at – 80° C until further use. In addition, tray plaque was collected from the intaglio of the patients’ clear aligner trays using interproximal brushes. All plaque samples were collected into sterile 1X PBS and placed into a – 80° C freezer until further use.

We evaluated the utility of saliva as a diagnostic marker for oral microbiome changes during orthodontic treatment.

DNA from the saliva and plaque samples was extracted using the MasterPure DNA Purification Kit (Epicentre, Biosearch Technologies, Middlesex, U.K.) based on manufacturer’s instructions with minor modifications. 26 A nanodrop (Thermo Scientific, Waltham, Massachusetts) was used to measure DNA quality and quantity. Further, the 16S rRNA library was constructed according to the HOMINGS protocol using V1-V3 primers instead of V3-V4 primers. Briefly, the V1 to V3 region of the 16S rRNA gene was amplified using gene specific primers with Illumina overhang adapters (Illumina, San Diego). Three PCR reactions were carried out for each sample and pooled together to reduce bias. Each PCR reaction mixture (25 µl) contained 25 ng DNA, 0.4 µM each of the forward and reverse primers and 1X of the HF Taq polymerase Master mix (NEB, Ipswich, Massachusetts). The PCR cycles consisted of an initial denaturation step of 98° C for three minutes followed by 35 cycles of 98° C for 30 seconds, 55° C for 30 seconds, 72° C for 30 seconds with a final extension of 72° C for five minutes. The PCR products were then pooled and cleaned with AMPure XP beads (Beckman Coulter, A63881, Indianapolis) before adding indices using the Nextera XT Index kit (Illumina). After quantification of the amplicons with the DNA KAPPA kit (Roche Diagnostics, Indianapolis), equal amounts of each sample were pooled into a single library. The quality and quantity of the library were checked at the Technology Center of Genetics and Bioinformatics Core at UCLA before MiSeq sequencing on the Illumina platform.

Following the demultiplexing and trimming of barcodes, low-quality sequences containing bases with Phred quality values < 20 were trimmed and denoised using the DADA2 package (Callahan, McMurdie, et al. 2016). The amplicon sequence variants (ASVs) generated were taxonomically assigned by comparison to the HOMD database (Chen, Yu, et al. 2010). Alpha and beta diversity analyses were performed using the core metrics plug-in in QIIME 2. The Shannon’s index diversity measure was used for calculating alpha diversity, while weighted UniFrac was used for assessing beta diversity.

The power of the study was calculated using the G*Power statistical analysis program 27,28 (version 3.1.9.4; Franz Faul, Christian-Albrechts-Universitat, Kiel, Germany). Data normality was determined using the Shapiro-Wilk analysis. 29 Statistical significance was calculated using a two-tailed t-test for the TQHPI and the Mann-Whitney U test for the GI scores at a level of p ≤ 0.05. GraphPad Prism (version 9.1.0; GraphPad Software Inc., San Diego) was used to assess significance of alpha diversity measures by the Kruskal-Wallis test.

Results

A total of 20 patients participated in this study and were divided into two groups based on the treatment they received: FA, n=10 or CA, n = 10. The average age of the FA group was 23.0 ± 13.6 years, while the average age of the CA group was 30.9 ± 12.3 years (TABLE 1). The difference in age was not statistically significant (p = 0.201). The sex distribution between groups was similar but not identical: The FA group consisted of six females and four males, while the CA group was comprised of seven females and three males (TABLE 1). To analyze the normality of the clinical data, the Shapiro-Wilk test 29 was used. As shown in TABLE 2, at a threshold of p = 0.05, it was determined that the plaque index (PI) followed a normal distribution, while the gingival index (GI) did not follow a normal distribution. Further, the G*Power statistical analysis program was used to calculate the implied and power of the study. The effect size for the PI data was 0.0670 and the calculated power was 0.9676. The effect size for the GI data was 0.1893 and the calculated power was 0.7105.

The assessment of clinical parameters such as PI showed a clear upward trend between baseline and 12 months in the FA group; however, no such increase was noted in the CA group (FIGURE 1A). A two-tailed t-test revealed a statistically significant difference in PI from baseline to six months and from baseline to 12 months (p < 0.05) in the FA group, while no significant difference was observed in the CA group. Because the GI data did not follow a normal distribution, the Mann-Whitney U test was performed to calculate significance. Similar to the PI values, the FA but not the CA group demonstrated an increasing trend in GI scores between baseline and 12 months (FIGURE 1B). This increase in GI was significant between baseline to six months and baseline to 12 months in patients receiving FA treatment (P < 0.05).

Following the analysis of clinical parameters, changes at the microbial level were assessed. To observe the within sample diversity, alpha diversity using Shannon’s index measure was calculated for the saliva and plaque samples from both FA and CA patients. No significant changes in alpha diversities were found over time for any of the sample types from either CA or FA (FIGURES 2A and 2B). Furthermore, when comparing the groups against each other, no significant differences were observed between saliva, tooth-associated plaque and trayassociated plaque at any of the time points (FIGURES 2A and 2B). Although a small decrease in the alpha diversity of saliva was observed in comparison to plaque in both FA and CA, the difference was not statistically significant (FIGURES 2A and 2B). The similarities and dissimilarities in the communities were further evaluated using beta diversity analysis, which was measured by weighted UniFrac distances. The distances were plotted using principal coordinate analysis (PCoA) for each collection time point (FIGURE 3). The saliva communities were very different from plaque communities irrespective of the FA or CA group and exhibited a distinct cluster from plaque at all time points (FIGURES 3A-3D). Additionally, the tray plaque biofilm community was markedly different from plaque and demonstrated its own cluster at all available time points (FIGURES 3B-3D). The greatest disparity in beta diversity analysis for saliva and plaque was observed at the 12-month time point for both the FA and CA groups (FIGURE 3D).

Next, the microbial composition in the FA and the CA group was analyzed at the genus level for both plaque as well as saliva samples. The microbial compositions of saliva and plaque were distinct (FIGURES 4). While some variation was apparent, the overall microbial profiles for each treatment did not seem to change much over time. However, when comparing the bacterial compositions between plaque and saliva at the individual genus level, saliva harbored a higher relative abundance of Streptococcus whereas plaque samples contained a greater abundance of Actinomyces in both FA and CA groups (FIGURES 4A and 4B). In CA patients, the tray plaque composition resembled the saliva community more than the tooth-associated plaque at all time points (FIGURE 4B). Although the communities were very similar in the same treatment group at all time points, some genera exhibited differential increase or decrease in relative abundance over time in both FA and CA. Notably, the relative abundance of Veillonella and Haemophilus varied throughout the course of treatment in both groups and correlated with the clinical parameters (FIGURE 5). In the FA group, the relative abundance of the disease-associated genus Veillonella increased in both plaque and saliva, whereas in the CA group, no change was observed. In contrast, the health-associated genus Haemophilus decreased in both saliva and plaque of the FA group, while in the CA group, relative abundance varied but no consistent trend was observed.

Discussion

With the increased use of CA and the continued widespread use of FA, which has long been associated with white spot lesions and gingival inflammation, a more thorough investigation of how these treatment modalities affect microbial community composition in both saliva and plaque is warranted. Therefore, in this longitudinal study, we investigated how both plaque and salivary microbiomes are affected by treatment with fixed appliances (FA) and clear aligners (CA) and how they are correlated with the clinical parameters.

The analysis of clinical parameters revealed a significant increase in PI and GI indices over time only in the FA group (FIGURE 1). This observation was consistent with previous research that showed higher levels of supragingival plaque accumulation in FA patients 6,7,15,16,30–32 and better maintenance of periodontal health in the CA group. 10,33 Consequently, FA treatment leads to increased gingival inflammation, whereas CA treatment poses no such risk to the periodontium. The stability of the PI and GI scores in the CA group throughout the 12 months of treatment suggests that the removable nature of such devices is advantageous by enabling better access for oral hygiene care and thus reducing plaque accumulation and gingival inflammation as compared to FA. 32 Although insignificant, the average between the two groups may also have played a role, as the average age was higher in the CA group suggesting that this group was better in following the directions and maintaining better oral hygiene.

Alpha diversity analysis demonstrated that there were no significant differences in saliva and plaque in either of the treatment groups, indicating similar microbial diversities within samples (FIGURE 2). Furthermore, no changes in alpha diversity were found over time for all the sample types. In agreement with this observation, a study by Wang et al. 17 as well as our own previous studies 15,16 did not find any significant differences in alpha diversity between CA and FA. Additionally, studies focusing only on CA also reported similar alpha diversities before and after orthodontic treatment. 13,14

Beta diversity is used to measure the similarity or dissimilarity of different microbial communities and can be defined as the variability in taxonomic composition among sampling units for a given area. 34 Beta diversity analysis showed that the microbial communities in plaque and tray plaque are highly distinct from each other (FIGURE 3). Interestingly, the tray plaque communities localize close to the salivary samples. Because saliva coats the entire oral cavity, it can act as an intermediary between supragingival tooth and tray plaque. Over time, plaque, tray plaque and saliva microbiomes gradually become more distinct in both the FA and CA groups, with the largest disparity seen at the 12-month time point.

Each group tested in this study (saliva, plaque and tray plaque) has a unique bacterial community at baseline that fluctuates throughout orthodontic treatment as shown in FIGURES 4A and 4B. However, if just plaque is considered, within the two groups, in accordance with our earlier study, 16 Leptotrichia increased over time in plaque of FA but not in the CA patients. This trend was not observed in saliva. In between CA and tray plaque, consistent with earlier findings, 16 Corynebacterium, Actinomyces and Selenomonas were higher in relative abundance in CA in comparison to tray plaque. Throughout treatment, changes occur in the oral microbiome, which are evident in saliva, plaque and CA tray plaque. Furthermore, the higher relative abundance of Streptococcus in saliva compared to the higher relative abundance of Actinomyces in plaque could be a factor in the dissimilarity in microbial community compositions of saliva and plaque. This finding along with the differences in beta diversity revealed that saliva does not accurately reflect the microbiome changes in plaque. Although saliva can be representative of the entire oral microbiome, it may not be specific enough to identify the pathogenic changes occurring on the tooth and gingiva, unlike plaque, which is indicative of the clinical changes at distinct oral locations.

The genus-level analysis in correlation with the clinical parameters revealed that some genera exhibited a strong correlation with the PI and GI. In accordance with some earlier studies, 16 Veillonella, previously associated with caries 35,36 and periodontitis, 37,38 showed a significant increase in the relative abundance with time in the FA group indicating correlation with higher PI and GI (FIGURE 5). However, in the CA group, no such increased abundance was observed. In contrast, Haemophilus, a health-associated bacterial genus, 16,39 exhibited decreased relative abundance with time in FA. 16 The relative abundance of Haemophilus was, however, similar in the CA group. This correlation of Veillonella and Haemophilus with time was detected both for saliva and plaque samples in FA and thus holds potential as biomarkers for future orthodontic treatment studies.

Conclusions

In this study, patients undergoing orthodontic treatment with FA demonstrated significantly more plaque accumulation and poor gingival health, whereas no such difference was observed in patients with CA. Although the alpha diversities were similar in patients with FA and CA for both plaque and saliva, beta diversity analysis revealed that the compositions of these communities were different. Saliva failed to reflect the same microbial changes that occur in plaque and thus cannot be used as a diagnostic tool in orthodontic treatment, but individual genera within saliva show potential as biomarkers for health and disease. However, future studies are necessary to better understand the clinical relationship between plaque and saliva in both treatment groups and to independently validate the potential utility of the identified genera as healthand disease-related biomarkers.