Introduction
The oral cavity in healthy mammals is colonized by large numbers of bacteria, viruses, phages, and fungi1 representing a high number of species and forming complex interkingdom ecological networks.2 These organisms provide benefits to the host but can also be involved in various disease processes, such as periodontitis.3 With the development of high-throughput DNA sequencing technologies that allow for culture-independent analysis of the microbiome, these complex communities are increasingly being studied and understood. However, most of these studies have been performed on human patients and focused on the bacteriome, rather than the entire microbiome, which also includes viruses, fungi, archaea, and protists. A large number of bacterial oral pathogens have been identified by means of 16S RNA sequencing in dogs with periodontal disease, showing that the oral cavity is characterized by a higher abundance of bacteria of the genera Bergeyella, Moraxella, Capnocytophaga, and Neisseria in healthy dogs than in dogs with various stages of periodontal disease.4
Fungi are ubiquitous and have been known to colonize the mammalian oral cavity for more than a century.5 Fungi are to a large degree unculturable, and those that can be cultured can take several weeks to grow in vitro.6 Sequencing of the conserved fungal internal transcribed spacer region offers clinicians a detailed understanding of the mycobial profile and its role in health and disease. Even though studies on the oral mycobiome in dogs are rare and have incorporated only standard culture techniques to date,7,8 the role of fungi in periodontal disease is increasingly recognized in human patients.6 Eighty-five fungal genera have been identified in healthy humans, with Candida and Cladosporium being the most dominant,9 and an individual typically has between 9 and 23 different fungal species in their oral cavity. Opportunistic pathogenic fungal species like Candida albicans have been shown to form complex interkingdom relationships with various bacteria and are implicated in the progression of periodontitis,1,10 and species of the genus Malassezia are increasingly recognized as commensals of the human oral cavity.6 To the best of our knowledge, no study has investigated the role of fungi in canine periodontitis to date. However, fungi form a large biomass in the oral cavity, can form biofilms, and have important immunomodulatory properties.1,11 Understanding the role of fungi in the oral ecosystem in the context of health and disease will provide new knowledge about the fungal etiology of periodontitis. Therefore, the objective of the study reported here was to investigate the composition of the mycobiome in healthy dogs and dogs with various stages of periodontal disease. We believe our findings may have important clinical implications in the treatment and outcome of periodontal disease in dogs.
Materials and Methods
Dogs
Dogs examined and treated during a planned veterinary visit to a dental specialty clinic (Veterinary Dental Specialties and Oral Surgery, San Diego, CA) were eligible for inclusion in the study. Dogs that had received any antimicrobial or antiseptic treatment or any active or passive oral hygiene treatment ≤ 2 weeks prior to the visit were excluded from the study. For dogs included in the study, no treatment decisions were made on the basis of study results. All samples were collected and analyzed with verbal owner consent; owners were aware that samples were taken for research purposes only.
Fifty-one dogs representing 31 breeds and ranging from 5 months to 13 years old were included in the study (Supplementary Table S1). Following a thorough examination of the oral cavity by a diplomate of the American Veterinary Dental College, each tooth was assigned a periodontal disease stage, as described by the American Veterinary Dental College.12 Teeth with stage 0 periodontal disease were clinically normal, with no gingival inflammation or periodontitis clinically evident; teeth with stage 1 disease had gingivitis without attachment loss; teeth with stage 2 disease had early periodontitis with < 25% attachment loss; teeth with stage 3 disease had moderate periodontitis with 25% to 50% attachment loss; and teeth with stage 4 disease had advanced periodontitis with > 50% attachment loss. Dogs were then grouped on the basis of the average stage of the majority of teeth, with 12 dogs assigned to group 0, 10 dogs assigned to group 1, 12 dogs assigned to group 2, 7 dogs assigned to group 3, and 10 dogs assigned to group 4. Because of the low number of dogs in group 3, dogs in groups 2 and 3 were combined into a single group (group 2.3; n = 19) for all analyses. In addition, in clinical practice, teeth with up to 50% attachment loss (ie, teeth with stage 2 or 3 disease) can qualify for periodontal treatment, whereas teeth with stage 4 disease are typically candidates for extraction. Mean ± SD age was 3.5 ± 4.6 years for dogs in group 0, 5.4 ± 3.1 years for dogs in group 1, 8.3 ± 2.5 years for dogs in group 2.3, and 9.8 ± 2.7 years for dogs in group 4. Dogs in group 4 were significantly older than dogs in group 0 (P = 0.001). Dietary information was not collected.
Sample collection and analysis
A single periodontal swab sample was obtained from each dog included in the study. A standardized upstream sampling protocol was provided to ensure samples were collected and preserved on a consistent basis. Samples were collected with a swab collection kit provided by a diagnostic service (MiDOG LLC; Tustin, CA). Detailed instructions for sample collection were provided. In brief, a sterile, DNA-free swab (HydraFlock; Puritan) was removed from its pouch and gently twisted and twirled 10 times back and forth over the entire maxillary arcade (the entire maxillary arcade was sampled because all dogs had generalized disease as opposed to disease involving a single tooth). The swab tip was then broken off in a sterile sample collection tube prefilled with a DNA-RNA preservative (DNA/RNA Shield; Zymo Research Corp).
Samples were processed by a commercial provider (ZymoBIOMICS Metagenomic Sequencing; Zymo Research Corp) as previously described,13 with minor modifications. Briefly, genomic DNA was purified by means of mechanical lysis (ZymoBIOMICS 96 DNA kit; Zymo Research Corp) on an automated handling robot (Microlab Star liquid handling robot; Hamilton Co). A library targeting the internal transcribed spacer 2 region was prepared with proprietary primer sequences (MiDOG LLC; Tustin, CA), and samples were analyzed with a commercial sequencing platform (HiSeq 1500; Illumina). Briefly, unique amplicon sequence variants were inferred from raw reads,14 and potential sequencing errors and chimeric sequences were removed. Phylotypes were computed as percentages on the basis of total number of sequences in each sample. Cell and DNA mock communities were used as positive controls for the extraction process and the bioinformatics pipeline (ZymoBIOMICS microbial community standard, catalog Nos. D6300 and D6305; Zymo Research Corp). The UCLUST algorithm was used to perform taxonomic classifications with a custom proprietary database (MiDOG LLC; Tustin, CA). For proprietary reasons, the FASTQ files generated for the present study are not publicly available but are available from the corresponding author on reasonable request.
Statistical analysis
Unless otherwise stated, results were expressed as arithmetic mean values. Measurements of α-diversity and evenness were calculated with the Shannon index and number of observed species. Because these data were not normally distributed, they were log transformed, with the Kolmogorov-Smirnov test used to confirm that log transformation normalized the data. Log-transformed data were then analyzed by means of ANOVA. β-Diversity was calculated by means of Bray-Curtis distance on the basis of the species taxonomic level. β-Diversity was compared among groups by means of permutational multivariate ANOVA. Composition visualization, α-diversity, and β-diversity analyses were performed with an open-source bioinformatics pipeline (Qiime version 1.9.1; Qiime).15 Linear discriminant analysis and linear discriminant effect size analysis were used to identify taxa that were significantly enriched in each disease group by means of the default settings.16 Analyses of variance and false discovery rate control to correct for type I errors were performed on the species-level relative abundance data of this analysis with standard software (R version 3.5.2 and stats package version 3.6.1; R Core Team). Species with a value of P < 0.05 were considered significant. A presence-absence data matrix of species by site was generated by assuming species with abundance > 1% to be present and species with abundance < 1% to be absent. The co-occur function of the statistical software (R version 3.5.2; R Core Team) was used to generate pairwise classifications of species having positive, negative, and random associations.
Results
Fungal diversity
Fungi were detected in all samples, with a total of 320 fungal species from 135 families detected in the data set. Although mean numbers of species for dogs in groups 0 and 1 (23.4 and 24.6 species/sample, respectively) were higher than mean numbers for dogs in groups 2.3 and 4 (17.32 and 14.8 species/sample, respectively), there were no significant differences in number of species per sample among groups (Figure 1), nor was there β-diversity clustering on the basis of disease group (Supplementary Figure S1). Species with the highest mean abundances (ie, highest mean percentages of the mycobiome composition) across the whole sample set were Asterostroma cervicolor (mean ± SD abundance, 17.2 ± 16.4%), Acremonium alternatum-egyptiacum-sclerotigenum (6.0 ± 14.7%), Sterigmatomyces hyphaenes (5.6 ± 12.7%), Aspergillus baarnensis (3.8 ± 7.3%), Cladosporium dominicanum (3.1 ± 10.7%), and Aureobasidium melanogenum (2.9 ± 4.2%). Fungal diversity was high among groups, with Cladosporium sp being the most abundant species in groups 0 and 4 and M pachydermatis being the most abundant species in groups 1 and 2.3 and between individuals, even individuals in the same group (Figure 2). The 3 species with the highest mean abundances in group 0 were Cladosporium sp (24.16%), Malassezia arunalokei (7.14%), and Malassezia restricta (6.06%). In group 1, the 3 species with the highest mean abundances were Cladosporium sp (6.34%), Malassezia pachydermatis (9.57%), and fungi sp (9.11%). In group 2.3, the 3 species with the highest mean abundances were Cladosporium sp (14.50%), M pachydermatis (7.62%), and Saccharomycetes sp (6.95%). In group 4, the 3 species with the highest mean abundances were Cladosporium sp (16.09%), M arunalokei (7.28%), and Candida parapsilosis (5.47%). Five species of Malassezia and 12 species of Cladosporium were detected. Five species of Candida were detected, with C parapsilosis being the most abundant Candida sp in groups 0, 2.3, and 4.
α-Diversity analysis of results of next-generation DNA sequencing targeting the internal transcribed spacer 2 region to characterize the oral cavity mycobiome in 51 dogs without periodontal disease (n = 12; group 0) or with mild (10; group 1), moderate (19; group 2.3), or severe (10; group 4) periodontal disease. α-Diversity was assessed by means of calculating evenness (ie, number of observed fungal species/sample; left panel) and the Shannon index (right panel). No significant differences were observed among groups (P = 0.520 and P = 0.175, respectively).
Citation: American Journal of Veterinary Research 83, 1; 10.2460/ajvr.20.11.0200
Area charts showing the taxonomic distribution of the species-level fungal profile for individual dogs in each group (the 20 most abundant species/group are shown; A) and mean abundances for each group for all species with ≥ 2% relative abundance (B). Species are consistently color coded for all graphs and are ordered on the basis of their mean abundances, with the most abundant species at the top.
Citation: American Journal of Veterinary Research 83, 1; 10.2460/ajvr.20.11.0200
Linear discriminant effect size analysis was used to identify members of the mycobiome that could differentiate the 4 groups (ie, taxa present at significantly different relative abundances among the 4 disease groups). However, this analysis showed that the mycobiome was not very distinct among the 4 groups (Figure 3; Supplementary Table S2). The family Irpicaceae was significantly enriched in group 4, and an unknown family of the order Pleosporales was significantly enriched in group 1. Two species had significantly higher relative abundance in group 1, compared with their abundance in the other groups, specifically species of the Didymellaceae family and of the Pleosporales order.
A cladogram (A) and bar graph (B) depicting results of linear discriminant effect size analysis to identify taxa that were present at significantly different relative abundances between groups. A—In the cladogram, each ring represents a taxonomic level, with phylum in the center and species on the outermost ring. Yellow nodes represent taxa that were not significantly different between groups. Only disease groups 1 (red) and 4 (green) had a significant difference at the family level. B—The bar graph illustrates species that were significantly different between groups. Shown is the relative abundance of a given species in those dogs that had that taxa present (left y-axis). Symbols show the frequency of that given species in the data set for each group (ie, how many dogs had that species in their mycobiome; right y-axis).
Citation: American Journal of Veterinary Research 83, 1; 10.2460/ajvr.20.11.0200
Role of Malasseziaceae
No single fungal species was found in all samples. The 3 most frequently found fungal species were Cladosporium sp (46/51 samples), M restricta (44/51 samples), and M arunalokei (36/51 samples). To determine which species were part of the core oral cavity microbiome and which were unique to each disease group, a core microbiome analysis was conducted. For this analysis, the only species that were selected were those present in ≥ 1% of the microbiome in each sample and in ≥ 50% of the samples from each group (ie, at least 6 samples in group 0, 5 samples in group 1, 10 samples in group 2.3, and 5 samples in group 4). This analysis showed that all groups shared Cladosporium sp as part of their shared core mycobiome. A species from the family Malasseziaceae was unique to group 0 (ie, the healthy group), potentially indicating a beneficial effect of this species (Figure 4). An unknown Ascomycota sp was unique to group 1, and M arunalokei and M restricta were part of the shared core mycobiome for groups 0 and 4. An unknown fungal species was shared between groups 0 and 1.
Illustration of the results of core microbiome analysis. The graph shows the species that were part of the shared mycobiome between all 4 disease groups (center), were shared between ≥ 2 groups, or were unique to a group.
Citation: American Journal of Veterinary Research 83, 1; 10.2460/ajvr.20.11.0200
Microbial composition clustering
A co-occurrence analysis was conducted to identify group-specific microbial interactions (Figure 5). There were no significant findings for group 4, but the other 3 groups all showed significant species interactions. Specifically, various species of Malassezia showed positive interactions with each other in groups 1 and 2.3. In group 0, 2 Cladosporium spp, Cladosporium cycadicola and C parapsilosis, significantly interacted with Alternaria sp and Malasseziaceae sp, respectively.
Illustration of the results of co-occurrence analysis used to identify significant group-specific microbial interactions. No significant interactions were detected for group 4; therefore, no graph is shown for group 4. Negative interactions are shown in yellow, positive interactions are shown in blue, and neutral interactions are shown in gray.
Citation: American Journal of Veterinary Research 83, 1; 10.2460/ajvr.20.11.0200
Discussion
The oral cavity mycobiome forms an important part of the microbial environment, and fungi are increasingly being recognized as the causative agent of infections.17 Results of the present study highlighted that fungi are present in the oral cavity of dogs and are characterized by substantial species diversity. The next-generation DNA sequencing used in the present study revealed substantially more species of fungi than previous culture-based studies7,8,18 have reported and identified several fungal organisms that could not yet be identified to the species level. This study suggested for the first time that there is a fungal component involved in the progression of canine periodontal disease and that certain fungi, specifically Didymellaceae, Irpicaceae, and Pleosporales, are significantly associated with the various stages of periodontitis. Fungi are ubiquitous in the environment, and many fungi can potentially be pathogenic in immunocompromised patients.19 As highlighted by this study and others, fungi are an essential part of the oral microbiome. For these fungi to survive and grow in the canine oral cavity, they need to maintain a symbiotic relationship with the host and other members of the microbiota.20 Understanding which fungi are part of the community balance in various stages of health, age, and disease is crucial to expand our understanding of the mycobiome and its contribution to periodontitis and to develop strategies to maintain and restore oral health.
Interestingly, Candida sp, one of the most frequently reported oral pathogens in people,21–23 was not the most dominant member of the mycobiome in any disease group in the present study. Only C parapsilosis was among the 20 most abundant fungi in groups 0, 2.3, and 4, although it was the third most abundant species in group 4. However, this species showed no significant enrichment in any group. The most frequently found fungus, A cervicolor, is an indoor fungus and therefore could have been a contaminant from the sampling procedure.24 The second most abundant fungus, Acremonium sp, is an opportunistic pathogen25 and was reported to be the cause of a systemic infection in a dog.26 The role of this taxon as potential pathogens in canine periodontitis needs to be further investigated.
Most importantly, 3 fungal taxa were identified to be significantly associated with disease group in the present study: Didymellaceae, Pleosporales, and Irpicaceae. At this time, relatively little is known about the involvement of these taxa in canine health and disease. Didymellaceae is a very diverse family in the Pleosporales order, and most reports highlight the importance of this family as a plant fungus.27 This family has been reported as a human28,29 and mammal pathogen17 and as the second most abundant fungus on the skin of West Highland White Terrier puppies.30 In the present study, Didymellaceae sp and Pleosporales sp were significantly enriched in group 1, which consisted of dogs with relatively less severe periodontal disease. Irpicaceae are spore forming and have not previously been detected in dogs. Two genera from this family, Irpex and Emmia, have been previously reported to cause pulmonary abscess formation and bronchopulmonary mycosis in humans, respectively.29 Interestingly, this taxon was significantly enriched in the highest disease stage, group 4. Because this taxon has not previously been reported in dogs, any potential association with canine health and disease would be highly speculative at this time, and future studies are needed. None of these taxa had a significant co-occurrence with other members of the mycobiome. Further in vivo and in vitro research is needed to understand the role of these fungi in the oral cavity microbiome, their potential to induce an immune response, their metabolism, and their potential role in oral interkingdom biofilms.
In total, 4 species of Malassezia were identified in the present study, which is higher than the number previously reported in culture-based studies of the canine oral cavity mycobiome8,31 or next-generation DNA sequencing–based studies of canine skin.32 Specifically, these were M arunalokei, M restricta, M pachydermatis, and Malassezia globosa. Members of the genus Malassezia have been increasingly recognized as important skin commensals as well as opportunistic pathogens in veterinary medicine.33,34 Malassezia pachydermatis has previously been described as part of the canine skin mycobiome32,33 and as part of the oral cavity mycobiome in female dogs with halitosis. Halitosis is a sign of oral or sometimes nasopharyngeal disease,35 supporting the findings described here. The lipid-dependent M globosa has been reported as a commensal of healthy canine skin but was also found in cats with otitis.33 In the present study, M globosa was among the 20 most abundant species in groups 0 and 4, was not significantly enriched in any group, and was not part of the core mycobiome. Therefore, no conclusions about the potential role of M globosa in canine periodontitis can be made it this time. Malassezia restricta is associated with skin diseases such as dandruff,36 and M arunalokei is a novel species only discovered in 2016.37 Both species were part of the core mycobiome shared between groups 0 and 4 in the present study. This finding suggests that they may not be useful as biomarkers for periodontal health in dogs. A different species belonging to the family Malasseziaceae, however, was part of the healthy core mycobiome in group 0. Co-occurrence analysis is a tool used to detect positive or negative interspecies dependencies, as they may occur in biofilms. For example, Malassezia and Cladosporium were the most dominant fungal genera detected, but currently no in vitro data are available to provide context for this finding. Different species of Cladosporium are reported as fungi in indoor environments, and some species may be involved in mammalian infections17 or are linked to allergies.38 Their role in the oral cavity in dogs is currently unknown.
Fungi actively contribute to the macrobiotic balance as competitors for space and nutrients, producers of various metabolites, and actors in the immune response.1,6,39,40 Further research is needed to understand specific interspecies and interkingdom population dynamics in health and disease. Several important questions remain to be answered, such as how fungi take part in periodontal disease, whether this role is dependent on the age or diet of the patient, whether their portfolio changes along with development of periodontal disease, and whether there is a causative component. Further, questions remain on how fungi contribute to the oral microbial balance, what can be considered normal or healthy, and at what point is a disease stage or dysbiosis reached. Such questions could be answered if metatranscriptomics and metagenomics were done to provide higher-level functional data in study cohorts like this. Not having these types of data available was a limitation of the present study.
Several aspects of our study could potentially influence future medical treatments. The overuse of antimicrobials in small animal veterinary practices has been recognized,41,42 and antimicrobials have an impact on the composition of the oral cavity bacteriome and, by extension, the oral cavity mycobiome. Antimicrobials should be used empirically only in cases of periodontal disease complications due to massive damage of the mucosa and gingiva, such as ulcers and erosions, or due to osteomyelitis or when the patient is immunocompromised.42 These drugs could potentially promote a larger role of fungi in periodontal disease etiopathogenesis. Potentially, there could be an indication to include antifungal medications when empirical treatment is used to ensure fungal microflora proliferation is prevented. In general, when antimicrobials are used systemically, implementation of special periodontal disease–monitoring tools, such as the oral health index, or simply a requirement to monitor the oral cavity in terms of the fungal profile, could be considered.
Another important situation in which to consider the role of the mycobiome in periodontal disease is when administering immunosuppressive treatment to patients with autoimmune disease, atopy, or allergy. Immunosuppression is a predictive factor for fungal infection.43 For example, oral candidiasis can be caused by long-term immunosuppression.44,45 The same concept applies to many other drugs that can alter the oral ecosystem as well as treatments for prophylaxis and home care (eg, antiseptic water additives and oral cleansing gels). Most of these supportive treatments have been assessed for their impact on the bacterial profile, but data on their impact on the fungal profile are missing. Owing to the inherent limitations of standard culture techniques to identify pathogens in patients with oral infections, culture is rarely indicated, except in instances of osteomyelitis. At this time, we have no data supporting the idea that monitoring or treating the mycobiome will be associated with a quicker recovery from periodontal disease. However, data from other studies and host species indicate an important role of the mycobiome,1,40,46 and additional efforts to increase the efficacy of periodontal disease management should be explored.
In summary, the present study showed that the oral cavity mycobiome in dogs is characterized by different fungal communities in various stages of periodontitis. These are important findings that should be considered along with the clinical diagnosis of periodontitis. Our hope is that this research will ultimately lead to better understanding of the disease and patient outcomes and lead to additional research that will result in new treatment modalities for this very common disease process.
Supplementary Materials
Supplementary materials are posted online at the journal website: avmajournals.avma.org.
Acknowledgments
No third-party funding or support was received in connection with this study or the writing or publication of the manuscript. The authors declare that there were no conflicts of interest.
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