Variations in Facial Conformation Are Associated With Differences in Nasal Microbiota in Healthy Dogs

doi:10.21203/rs.3.rs-69369/v1

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Research article

Variations in Facial Conformation Are Associated With Differences in Nasal Microbiota in Healthy Dogs

https://doi.org/10.21203/rs.3.rs-69369/v1

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published 24 Nov, 2021

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Background – Extrinsic and intrinsic factors have been shown to influence nasal microbiota (NM) in humans. Very few studies investigated the association between nasal microbiota and factors like facial/body conformation, age, and environment in dogs. Objectives are to investigate variations in NM in healthy dogs with different facial and body conformations and to assess the influence of age and living environment. A total of 46 dogs of different age, living environment and from 3 different breed groups were recruited: 22 meso-/dolichocephalic medium to large breed dogs, 12 brachycephalic dogs and 12 terrier breeds. The nasal bacterial microbiota was assessed through sequencing of 16S rRNA gene (V1-V3 regions) amplicons.

Results – We showed major differences in the NM composition together with increased richness and α-diversity in brachycephalic dogs, compared to meso-/dolichocephalic dogs and dogs from terrier breeds. We failed to detect any effect of age or environment.

Conclusion – Healthy brachycephalic breeds and their unique facial conformation is associated with a distinct NM profile. Description of the NM in healthy dogs serves as a foundation for future researches assessing the changes associated with disease and the modulation of NM communities as a potential treatment.

Small Animal Medicine

brachycephalic breeds

influence

facial/body

influence nasal microbiota

Studies investigating the composition of the microbial communities of the nasal cavities in healthy individuals using culture-independent molecular methods have arisen over the last decade in humans^1-6 and more recently in companion animal veterinary medicine^7-11.

In healthy men, both extrinsic and intrinsic factors have been reported to shape an individual’s upper airway microbiome. Extrinsic exposures reported to influence the nasal microbiota (NM) composition include delivery at birth mode¹², feeding type in infants¹³, exposure to tobacco smoke¹⁴ and air pollution¹⁵.

Intrinsic factors like host genetics¹⁶ and associated host mucosal immunity¹⁷ as well as age¹⁸ also seem to modulate the NM. Moreover, in specific anatomic sites in the upper respiratory tract as well as within the nasal cavities, distinct micro-niches containing specialized bacterial communities have been described, demonstrating intra-patient spatial variation of the NM².

Studies in men suggest that the NM is a key factor in maintaining respiratory health by affecting both resistance to pathogens and immunological responses^19-21. While a greater mucosal diversity may play a role in limiting inflammation and protecting against infections^22-24, potential microbial species known as “keystone species” may also have a beneficial effect on the ecosystem’s balance, function and health^21,25,26.

In dogs, complex bacterial communities dominated by the Moraxellaceae family have been detected in the nasal cavities of healthy animals^7,9,10. Spatial variations between nasal and oropharyngeal swabs^7,9, temporal variations⁹, changes associated with geographical location⁹ as well as variations associated with older age and lower bodyweight¹⁰ have been reported suggesting that extrinsic and intrinsic factors also influence upper airway bacterial composition in dogs.

Variable predispositions for chronic nasal disease are observed between different dog breeds. Indeed, chronic lymphoplasmacytic rhinitis (LPR) and sinonasal aspergillosis (SNA) are almost exclusively encountered in middle-aged medium to large meso- or dolichocephalic canine breeds^27,28. At the opposite, brachycephalic breeds, in which extreme breeding selection has progressively led to very distinct anatomical features of the nasal cavities^29,30are rarely affected by chronic inflammatory or infectious nasal diseases. Anatomical abnormalities described in the nasal cavities of brachycephalic dogs include marked global reduction of the size of the nasal cavities, stenosis of the nares and vestibulum, malformed rostral and caudal aberrant turbinates. Those abnormalities are associated with intranasal contact points, reduced lumen and increased collapsibility of the nasopharynx and missing paranasal sinuses and cause abnormal breathing patterns, differences in airflow distribution and increased resistance to airflow^31-33. Very few studies investigated the association between the NM and the facial¹⁰ or body conformation⁹ and these studies have not shown significant differences.

We hypothesized that distinct nasal microbial composition might exist which reflect differences in facial anatomical conformation and consequently in breathing pattern. Therefore, the aim of this study was to describe and compare the composition of the NM in healthy dogs of various breeds, categorized into 3 groups according to their body and facial conformation. An additional aim was to assess the influence of age and living environment.

Study population

Forty-six client-owned dogs were recruited between November 2017 and July 2018. Groups DL (meso-/dolichocephalic dogs of medium to large breeds), B (brachycephalic breeds) and T (terrier breeds) contained 22, 12 and 12 dogs respectively. Group DL included mixed breed (n=5), Belgian Shepherd (n=4), Australian Shepherd (n=4), Labrador (n=2), Beauceron (n=2), Border Collie (n=2), Golden retriever (n=1), Dalmatian (n=1), and White Swiss Shepherd (n=1). French Bulldog (n=6), English Bulldog (n=2), Pug (n=2) and Cavalier King Charles Spaniel (n=2) composed the group B. Group T was composed of 4 breeds: Jack Russel terrier (n=7), Yorkshire terrier (n=3), West Highland white terrier (n=1) and Pinscher (n=1). Distribution of age, bodyweight, sex and living environment among groups is reported in Table 1. Dogs of group B were younger (more dogs in age class 1) compared to group T (more dogs in age class 2 and 3). As expected, all three groups had marked differences in bodyweight associated with their breed type. Gender and environmental living conditions distributions were comparable in the 3 groups. Contact with tobacco smoke and food type were not taken into account because no dog lived in close contact with tobacco smoke (smokers were not smoking inside the house or in a place where the dog could be in regular contact with tobacco smoke) and because all dogs were fed with commercial dry food, at the exception of 4 of them (1 dog in group DL and 2 dogs in group T were eating a mix of commercial dry food and home-made diet; 1 dog in group B was eating a home-made diet). For these parameters, groups were too small to perform statistical analysis.

Most common taxa in study population

Good’s coverage index was superior to 99% in all dogs with a median value of 99.81% (99.70%-99.88%), indicating that all animals were sampled with a sufficiently high number of sequences and enough coverage.

At the finest taxonomic resolution, a total of 755 operational taxonomic units (OTUs) were found throughout all samples. Most common taxa at phylum and family level in healthy dogs from different breed groups are illustrated in figure 2. A total of 20 phyla were identified in the samples of the nasal cavities of healthy dogs, the most abundant being Proteobacteria followed by Tenericutes, Actinobacteria, Firmicutes and Bacteroidetes. Other phyla like Fusobacteria and Patescibacteria represented less than 1% of the mean relative abundance.

The most common taxon at family level was Moraxellaceae representing 41.6% of the total taxa: this family was detected in all samples at percentages ranging from 0.04% to 94.8%. Pseudomonadaceae, unclassified family of the Mollicutes class, Cardiobacteriaceae, unclassified family of the Pseudomonadales order, Microbacteriaceae, Streptococcaceae and Staphylococcaceae constituted the major part of the other frequently detected families although some of them were present in large amounts in only a few animals. Moraxella was the predominant genus in the majority of samples. Together with the genera Pseudomonas, Suttonella, Leucobacter, and unclassified genera of the class Mollicutes and of the order Pseudomonadales they represented 80.1% of all taxa throughout all samples.

Comparison of the breed groups (DL, B and T)

The total bacterial load did not significantly differ between groups of different breeds (Figure 3).

Non-metric multidimensional scaling (NMDS) plot of microbial communities at species level based on a Bray-Curtis dissimilarity matrix revealed a distinct separation between group B and the 2 other groups DL and T (Figure 4). A significant difference in bacterial community composition was verified by an analysis of molecular variance (AMOVA) (p=0.02) and pairwise comparison demonstrated that group B was different compared to groups DL and T (group B vs group DL p=0.017; group B vs group T p=0.008; group DL vs group T p=0.511). The analysis of the molecular variance homogeneity (HOMOVA) did not reveal a significant difference between groups (p=0.08).

Analysis of ecological indices showed that group B had a significantly higher species α-diversity (inverse Simpson index) and richness (Chao1 index) compared to group DL and T (Figure 5).

The similarities and differences in bacterial composition between the 3 groups were visualized using a Venn diagram based on the occurrences at species level (Figure 6) and showed that 74 OTU were shared between all groups which represents 16.9%, 18.7% and 35.6%, of groups DL, B, and T respectively. The relative proportion of unique OTUs to each group was comparable with a value around 45-50% for the 3 groups (group DL: 51.9%, group B: 47.1%, group T: 43.8%). As a result, the differences associated with group B were more related to differences in abundance of shared OTUs than to the presence of unique OTUs.

Despite of the fact that the community composition at the phylum level showed a dog-to-dog variation within each group (Figure 1), the most abundant phylum throughout the 3 groups was Proteobacteria since it was the most predominant (more than 50%) in all dogs of group T, 6/12 dogs of group B and 19/22 dogs of group DL.

Mean relative abundances of taxa that significantly differ between groups are presented in table 2. At phylum level the proportion of Proteobacteria was lower in group B, in comparison with DL and T, while the proportion of Actinobacteria, Firmicutes and other Proteobacteria was increased. In the phylum Proteobacteria, the genera Moraxella (family Moraxellaceae) and Suttonella (family Cardiobacteriaceae) were significantly lower in group B. Genera of other Proteobacteria that were more frequently observed in group B are Pseudomonadales_ge (family Pseudomonadales_fa) as well as Conchiformibus (family Neisseriaceae) and unclassified genus of the Pasteurellaceae family. Among the phylum Actinobacteria, the genera Corynebacterium (family Corynebacteriaceae) and Rothia (family Micrococcaceae) were more abundant in group B. Among the phylum Firmicutes, Streptococcus (family Streptococcaceae), Staphylococcus (family Staphylococcaceae), Abiotrophia (family Aerococcaceae) and Gemella (family Bacillales_Family_XI) were more abundant in group B.

The phylum Tenericutes (almost exclusively composed by an unclassified species of the class Mollicutes) was less abundant in group T compared to the two other groups while the abundance of the genus Pseudomonas was increased in this group although the increase in Pseudomonas was mainly represented by 3 individuals (Figure 2).

The genus Staphylococcus, in group B, was mainly composed by the species Staphylococcus pseudintermedius (3.07% (0%-36.74%)). On the opposite, the percentage of the species Staphylococcus aureus was slightly lower in group B (0.01%) compared to the two other groups (0.33% (0%-4.55%) in group DL, 0.41% (0%-4.97%) in group T).

Linear discriminant analysis (LDA) effect size (LEfSe) scores indicated bacterial taxa that were mainly present in group B. The genera Haemophilus (family Pasteurellaceae), Parvimonas (family Clostridiales_Family_XI), unclassified genus within the family Pasteurellaceae, Fusobacterium (family Fusobactericiaea), Gemella (family Bacillales_Family_XI), Rothia (family Micrococcaceae), Conchiformibius (family Neisseriaceae), Abiotrophia (family Aerococcaceae) and Streptococcus (family Streptococcaceae) were significantly more represented in dogs from the group B. At species level 8 taxa were enriched in group B while only one taxon was associated with group T (Figure 7).

Microbial composition and ecological indices in study population

When using an AMOVA at species level, there was no significant effect of age group (p=0.295), the sex (p=0.625), or the environmental living conditions (p=0.646). This was also suggested by the NMDS plots constructed based on Bray-Curtis matrix which failed to reveal any clustering for these three exposures. There were no differences in richness, α-diversity or evenness (Simpson index) for any of the variables: age group, sex and environmental living conditions.

The focus of this study was to investigate variations of the NM in healthy dogs of different breeds with different facial and body conformations. To this end the NM of 46 dogs of 3 different breed groups were compared. We showed major differences in the NM composition together with increased richness and α-diversity in brachycephalic dogs, compared to meso-/dolichocephalic medium to large dogs and dogs from terrier breeds. Additionally, we failed to detect an effect of age, sex or environment.

In the present study, the nasal microbial population was largely dominated by the phylum Proteobacteria and the family Moraxellaceae, in accordance with what has been described in previous studies using next-generation sequencing methods for bacterial analysis^7,9,10. The phylum Proteobacteria has been found to dominate in association with Tenericutes and Bacteroidetes^7,9or in association with Firmicutes and Bacteroidetes¹⁰ while in the current study it was associated with Tenericutes and Actinobacteria followed by Firmicutes and Bacteroidetes. The Actinobacteria phylum predominated in the group of brachycephalic dogs, likely explaining the difference with other studies in which this breed type was not sampled.

The group of brachycephalic dogs in this study was also characterized by a higher species α-diversity and richness, a decrease in Proteobacteria (mainly a decrease in Moraxella and Suttonella) associated with an increase in Actinobacteria (mainly an increase in Corynebacterium and Rothia), Firmicutes (mainly an increase in Streptococcus and Staphylococcus) and other Proteobacteria (mainly an increase in unclassified genus of the order Pseudomonadales, unclassified genus of the family Pasteurellaceae, and Conchiformibius). Different reasons could explain these changes.

A first hypothesis rests on the probable occurrence of an important reflux of oropharyngeal secretions in brachycephalic breeds³⁴. Indeed, in men, Wu et al. (2018) demonstrated an association between severe obstructive sleep apnea, local inflammation and alterations in NM. Such association was presumed to be due to recurrent obstruction during sleep causing reflux of oropharyngeal secretions that otherwise would be swallowed in a healthy subject. Human oral commensals, such as Streptococcus, Veillonella and Porphyromonas were frequently identified in men with obstructive sleep apnea. Dogs of brachycephalic breeds frequently have at least a certain degree of upper respiratory obstruction and in the English bulldog obstructive sleep apnea has been described and even evaluated as a model for obstructive sleep apnea in humans³⁶. In dogs, the oropharyngeal microbiota has been shown to be associated with higher abundance of Porphyromonas sp. (family Porphyromonadaceae), Pasteurellaceae, Conchiformibius sp. (family Neisseriaceae), with less Moraxella sp. (Moraxellaceae) and Pseudomonadaceae compared to the nasal cavities^7,9. Interestingly, these features corresponded to some of the variations observed in the NM of brachycephalic dogs in this study supporting the hypothesis of contamination of the NM by the oropharyngeal populations.

Another hypothesis to explain differences in NM composition in brachycephalic dogs is related to the changes in airflow distribution and increased airflow resistance described in brachycephalic breeds^32,33. Indeed, in one study in men investigating changes in bacterial communities after sinus surgery³⁷, greater airflow was suggested to cause reductions in temperature and humidity creating a cooler and drier postoperative ecosystem, with an effect on bacterial composition. According to this hypothesis, changes in intranasal temperature and humidity in brachycephalic dogs could be related to distinct intranasal microenvironment in these breeds compared to meso- and dolichocephalic dog. Unfortunately, intranasal temperature and relative humidity have not yet been analyzed in dogs.

In the same order of idea, the differences in NM found in brachycephalic dogs could also be associated with the reduced length of the nasal cavities in brachycephalic dogs, and the closer proximity between the nares and the deeper intranasal sites. In men Corynebacterium³⁸, Propionibacterium and Staphylococcus genera² have been shown to dominate in the anterior nares compared with deeper intranasal sites. Such differences have been suspected to be secondary to niche-specific micro-environmental conditions such as pH, humidity, temperature and epithelium type^2,6,39, with humidity and moisture representing more favorable environmental factors for Corynebacterium and Staphylococcus species on this mucosal site². In dogs, compared to the other sites of the skin, the nares were shown to be colonized by Moraxellaceae (genus Moraxella) in combination with Oxalobacteraceae (genus Ralstonia), Corynebacteriaceae (genus Corynebacterium) and Staphylococcaceae (genus Staphylococcus)⁴⁰. Therefore, the higher predominance of Staphylococcus (phylum Firmicutes) and Corynebacteriaceae (phylum Actinobacteria) found in the nasal cavities of brachycephalic breeds could be associated with the closer location between the sampled site and the nares.

The presence of population of the nares in NM of brachycephalic dogs could also be linked to contamination of the swab by the microbiota of the nares and surrounding skin, due to the reduced nasal passage in these breeds. However, such a contamination has been minimized by the use of a sterile speculum for introduction of the swab into the nasal cavity.

Finally, as only one of these hypotheses could hardly explain all the variations observed in the NM of brachycephalic dogs compared to the other breeds, most likely the differences in NM in brachycephalic dogs could be multifactorial and be initiated by more than one of these mechanisms.

As previously described^7,9,10Moraxella was the most abundant genus in the family Moraxellaceae in this study. Despite their numerical dominance, the genus Moraxella and associated family Moraxellaceae were significantly lower in brachycephalic breeds compared to the 2 other breed groups. In dogs, the abundance of Moraxella in the nasal passages has been reported to be decreased in dogs with nasal disease (chronic rhinitis and nasal neoplasia)¹⁰. Whether this is a cause or consequence remains to be discovered and the exact role of Moraxella in the nasal cavities is still unknown. The decreased amount of Moraxella observed in brachycephalic dogs in this study is not in favor of this alteration being at the origin of nasal diseases, as brachycephalic dogs are less prone to these pathologies compared with the other breed groups. Consequently, the decreased amount of Moraxella reported in dogs with nasal disease is more likely due to local changes in microenvironment secondary to the disease. This is consistent with our hypothesis that the lower abundance of Moraxellaceae in brachycephalic dogs in this study could be due to selection pressure by other taxa, such as those colonizing the nares or those brought by oropharyngeal reflux, and/or due to local changes in microenvironment as detailed earlier.

In young children, profiles dominated by Moraxella and Dolosigranulum combined with Corynebacterium form a stable nasal microbiome associated with lower rates of respiratory infections, suggesting that Moraxella might be a keystone bacterium in infants, at the exception of Moraxella catarrhalis, found to be associated with bronchiolitis, otitis in and chronic rhinosinusitis^19,25,41,42. In dogs, the vast majority of Moraxellaceae found in this study, besides the species Moraxella canis, were not resolved beyond genus level. As a result, the potential presence of M. catarrhalis in healthy dogs is unknown and the lower abundance of Moraxella in brachycephalic dogs makes the hypothesis of Moraxella as a keystone bacterium less likely in dogs.

Patterns of microbiota sharing have been described between humans and companion animals. Humans and pets living in the same household seem to share more microbiota with each other than humans and pets living in different households⁴³. Although Staphylococcus aureus is one of the most well-described pathobiont of the nasal cavities in men⁴⁴, its level of carriage was low in this study, particularly in brachycephalic breeds. Interestingly, an inverse correlation between the genus Corynebacterium, a family that was more abundant in brachycephalic breeds, and S. aureus has been reported in some studies of adult NM^2,45. However, conclusions cannot be drawn as inter-species interactions are very complex and have not been studied yet in the nasal cavities of dogs. The carriage of Staphylococcus pseudintermedius in companion animals has also received attention as it is also an opportunistic pathogen⁴⁶. In opposition to S. aureus, S. pseudintermedius was more prevalent in brachycephalic breeds. These informations could be of value when evaluating dog breeds as a potential source of Staphylococcus carriage.

Rodriguez et al. (2019) suggested canine nasal secretions as a novel transmission route for toxigenic Clostridium difficile but we failed to detect this bacterium in the nasal samples which does not support this route of transmission as being frequent.

Older age (>9 years) has previously been reported to be associated with an increase in Shannon diversity index in dogs¹⁰. Differences in NM have been described in humans between infants, adults and elderly with a nasal community shifting toward oropharyngeal population in elderly¹⁸. The present study failed to show an association between age and differences in α- or β-diversity. Shift of NM in association with age at first sight seem to be negligible in dogs compared to humans although studies specifically designed to address this question are needed to draw any conclusion.

Ahmed et al. (2019) reported differences in NM between individuals living in rural and industrial locations, the latter being associated with exposure to pollution which has been hypothesized to cause microbiota alteration. In dogs, the results of Isaiah et al. (2017) also suggested that the NM could differ based on location. Dogs of the same breed were compared between Alabama and California and showed differences in α- and β-diversity. Differences between dogs living in rural and industrial regions were not observed in that study. However, in contrast to the two studies cited above, differences in geographic locations and associated environmental conditions among the dogs of this cohort were probably quite limited (‘which could have influenced the results).

The sampling protocol described in this study aimed to limit contaminations by the nares and surrounding skin by introducing the swab through a sterile speculum and during anesthesia. Performing sampling during anesthesia allowed proper swabbing of the nasal mucosa of deeper subsites. This protocol as well as the swab that was used (Copan^, FLOQSwabs^TM, 553C, Brescia, Italy) seem suitable to sample the nasal microbial population as it yielded sufficient material. This is in agreement with other studies showing that swab samples are representative of the microbiome in the nasal cavities in healthy subjects⁴⁷.

Comparison across studies is made difficult by the potential introduction of bias due to variations in sampling technique, sampling site, DNA extraction and different variable regions of the 16S rRNA gene used to characterize the bacterial microbiota. It is possible that some of the differences with other publications in dogs are due to variations in sampling method. In the study of Tress et al (2017) the nasal mucosa was sampled in awake animals without speculum, which likely prevented sampling deep subsites and could have led to contamination by the nares and surrounding skin. In the study of Ericsson et al (2016) samples were performed in anesthetized dogs at midway between the tip of the nose and the medial canthus without speculum. And finally, in the study of Isaiah et al (2017), swabs were sampled without anesthesia and at a distance of half an inch from the nares, so again more in the cranial part of the nasal cavities. In all these studies a different region of the 16S rDNA was also sequenced (V4 or V4-V6).

Limitations in this study include the absence of information concerning spatial organization of the NM in groups DL and T as well as the absence of oro-pharyngeal and nostril swabs which would have allowed comparing the microbiota in the 3 adjacent niches, and the possible impact of reflux of oropharyngeal secretions and/or nares contamination on the NM. The possible influence of parameters like diet was not analyzed due to small group size and influence of other non-measured environmental parameters (season and crowding conditions for example) cannot be excluded. Finally, beside the bacterial composition, the nasal cavities host a complex viral and fungal community that has not been taken into account but could also influence the bacterial microbiota.

In conclusion, healthy brachycephalic breeds and their unique facial conformation is associated with a distinct nasal microbial profile. Whether this finding is associated with the lack of predisposition for nasal diseases in brachycephalic breeds is unknown. Results of the present study contribute to the current knowledge of the composition of healthy NM in dogs which is a necessary foundation for future research aimed at identifying the impact of various perturbations, e.g., antibiotics, vaccines, infections, diseases, on the ecology of canine nasal microbial communities.

Study population

Client-owned healthy dogs were prospectively recruited and categorized into 3 groups including young to middle aged meso-/dolichocephalic dogs of medium to large breeds (group DL), brachycephalic dogs (group B) and dogs of terrier breeds (group T). Dogs from the DL group were selected to represent an age and breed matched control population of dogs particularly predisposed to SNA or LPR, dogs from group B were recruited as they are not predisposed to chronic nasal diseases and have a very distinct body and facial conformation, and finally terriers dogs were selected to represent small breed dogs without the typical facial conformation of brachycephalic dogs.

All dogs were exempt of clinical signs and had a normal physical examination and normal hematology and biochemistry blood work. Dogs receiving antimicrobial, anti-inflammatory or immunosuppressive medication were excluded from the study. In order to investigate a possible effect of age or environmental living conditions on the NM, all dogs included were subsequently re-classified according to their age (< 3 years (age class 1), 3-8 years (age class 2) and > 8 years (age class 3)) and their environmental living conditions (living either in a city, considered as an environment with high pollution load, or in the countryside, considered as an environment with low pollution load). Owners were also asked about exposure of their pet to tobacco smoke and type of food provided.

Sample collection

This study was approved by the ethical committee of the University of Liege (approval number: 1854) and all samples were obtained with informed and written owner consent.

Dogs were premedicated with butorphanol (0.2 mg/kg; Butomidor®, Richter Pharma) intravenously in combination with medetomidine (5g/kg; Medetor®, CP-Pharma). Propofol (Propovet®, Zoetis) on demand was used for induction without intubation. Under general anesthesia the nostril was maintained open using a sterile speculum, and a sterile swab (Copan^, FLOQSwabs^TM, 553C, Brescia, Italy) was introduced through the speculum up to the distal third of the right nasal cavity (Figure 1). Three gentle complete circular movements were used to brush the mucosa before withdrawal of the swab through the speculum. The top of the swab was then cut, stored in a sterile cryotube and banked at -80°C until further analyses.

DNA extraction and high throughput sequencing

Total bacterial DNA was extracted from all nasal swabs at the same time with the DNeasy Blood and Tissue kit (QIAGEN Benelux BV; Antwerp, Belgium) following the manufacturer’s recommendations. Spectrophotometry (NanoDrop, Thermo Scientific) was used for total DNA concentration measurement.

Bacterial 16S rDNA amplicons were generated via amplification of the V1-V3 hypervariable regions of the 16S rRNA gene using the following primers (with Illumina overhand adapters): forward (5’-GAGAGTTTGATYMTGGCTCAG-3’) and reverse (5’-ACCGCGGCTGCTGGCAC-3’). The DNA was purified with the Agencourt AMPure XP beads kit (Beckman Coulter; Pasadena, CA, USA) and submitted to a second polymerase chain reaction (PCR) round for indexing, using the Nextera XT index primers 1 and 2. After purification, PCR products were quantified using the Quant-IT PicoGreen (ThermoFisher Scientific, Waltham, USA). A final quantification, by quantitative PCR, of each sample in the library was performed using the KAPA SYBR" FAST qPCR Kit (KapaBiosystems; Wilmington, MA, USA) before normalization, pooling and sequencing on a MiSeq sequencer using V3 reagents (Illumina; San Diego, CA, USA). Positive control using DNA from 20 defined bacterial species and a negative control (from the PCR step) were included in the sequencing run.

Bacterial load was performed with a quantitative real-time PCR targeting the V2-V3 region of the 16S rDNA after DNA extraction from samples. The quantitative real-time PCR were performed on the ABI 7300 real-time PCR system with Takyon™ ROX SYBR® Mastermix dTTP Blue reagents (Eurogentec, Seraing, Belgium) for a total reaction volume of 20µl. The amplification was carried out with 40 cycles of a 95°C denaturation phase followed by a 60°C annealing phase. The PCR results were expressed in number of copies of the 16S rDNA per swab. The standard curve was based upon 10-fold dilution of a quantified PCR product. This PCR product targeting the V2-V3 region of the 16S rDNA was purified (Wizard® SV Gel and PCR Clean-Up System, Promega, Leiden, The Netherlands) and quantified with PicoGreen targeting double-stranded DNA (Promega) before use.

Data analysis

Alignment and clustering were done with MOTHUR software package (v1.41.0) with an OTU clustering distance of 0.03 and based on the SILVA database (V1.32) of full-length 16S rDNA sequences. Vsearch⁴⁸ algorithm was used for chimera detection.

From 6,082,571 raw reads, we obtained 5,596,282 reads after cleaning (length and sequence quality). Finally, we retained 5,000 reads (median 4,997 reads per sample) to adjust for uneven sequencing depth across samples. Suspected contaminants were removed by filtering them from the OTU table.

Ecological indicators, including bacterial richness, evenness and α-diversity were obtained with MOTHUR using the Chao1 index, Simpson index-based measure and the inverse Simpson’s index respectively. β-diversity (bacterial community composition) was assessed with MOTHUR using a dissimilarity matrix of Bray-Curtis then estimated with AMOVA (10,000 iterations) and β-dispersion was assessed with HOMOVA (10,000 iterations) in MOTHUR.

Statistical analyses

Statistical analyses were performed using XLstat (2019.3.2, Addinsoft, Paris, France) and Rstudio (v1.1.463) vegan package. Differences were considered significant for a p-value < 0.05. Normality was first checked using the Shapiro-Wilk test for each analysis. The bacterial load was compared between the 3 groups (DL, B and T) using the Kruskal-Wallis H test. Statistical differences in the relative abundance between groups were assessed with ANOVA followed by Tukey’s multiple comparison test with Benjamini Hotchberg FDR correction. LEfSe was performed to detect differences in bacterial composition between groups at the species level with MOTHUR (significant for an LDA score >3.0⁴⁹).

The Good’s coverage index and the ecological indicators were compared between the 3 type of breed groups, the 3 age classes and the 2 categories of living conditions (city versus countryside) using Kruskal-Wallis tests and Dunn post-hoc tests with Bonferroni correction or Mann-Whitney tests in XLstat. NMDS figure was performed based on a Bray-Curtis dissimilarity matrix at the species level to represent the global bacterial composition (β-diversity) between the breed groups (R vegan package). The β-diversity between breed groups, age classes and living categories were calculated with MOTHUR v1.40 using AMOVA and HOMOVA.

All biosample raw reads were deposited at the National Center for Biotechnology Information (NCBI) and are available under de Bioproject ID PRJNA656294.

NM: nasal microbiota

LPR: chronic lymphoplasmacytic rhinitis

SNA: sinonasal aspergillosis

OTU: operational taxonomic unit

AMOVA: analysis of molecular variance

rRNA: ribosomal ribonucleic acid

NMDS: non-metric multidimensional scaling

qPCR: quantitative polymerase chain reaction

PCR: polymerase chain reaction

HOMOVA: homogeneity of molecular variance

LDA: linear discrimination analysis

LEfSe: linear discriminant analysis effect size

rDNA: ribosomal deoxyribonucleic acid

B: brachycephalic breeds

T: terrier breeds

DL: meso- or dolichocephalic medium to large breeds

Ethics approval and consent to participate
Samples from healthy domestic dogs were collected according to a protocol approved by the Ethical Committee of the University of Liège (protocol #1854) and with the informed consent of the owners.
Consent for publication
Not applicable.
Availability of data and materials
All sample raw reads associated with this study have been deposited at the National Center for Biotechnology Information (NCBI) under the accession number PRJNA656294.
Competing interests
The authors declare that they have no competing interests.
Funding
The study was conducted with personal funding.
Authors' contributions
EV and CC conceived and designed the study. EV, AF, FB, BT, GD and CC participated in data acquisition for the study. EV, AF and BT analyzed the data. EV, AF and BT performed the statistical analyses. EV and CC interpreted the results. EV and CC wrote the manuscript and the authors read and approved the final version of the manuscript.
Acknowledgements
The authors would like to thank Albert Belinda, Phan Kim-Thu and Romijn Sylvain for their help in samples collection and storage.
Authors' information (optional)
Vangrinsven Emilie, DVM Dipl. ECVIM-CA
Department of Clinical Sciences, Faculty of Veterinary Medicine, University of Liège, Quartier Vallée 2, Avenue de Cureghem 3, 4000 Liège, Belgium.

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Table 1: Distribution of age, bodyweight, sex, and environmental living conditions among the 3 breed groups of healthy dogs.

Table 2: Bacterial groups at >1% mean relative abundance among the 3 breed groups of healthy dogs at phylum, family and genus level.

Taxon	Group DL			Group B			Group T
Phylum	Mean rel. Freq. (%)	SD (%)	Tukey's multiple comparisons test (p<0.05)	Mean rel. Freq. (%)	SD (%)	Tukey's multiple comparisons test (p<0.05)	Mean rel. Freq. (%)	SD (%)	Tukey's multiple comparisons test (p<0.05)
Family
Genus
Proteobacteria	73.5	27.6	A***	53.3	25.6	B	81.1	12.8	A****
Moraxellaceae	48.9	38.1	A****	16.4	15.7	B	53.5	30.1	A****
Moraxella	48.9	38.1	A****	16.3	15.7	B	53.0	30.7	A****
Pseudomonadaceae	6.8	13.0	A	10.0	19.2	AB	16.0	27.1	B**
Pseudomonas	6.8	13.0	NS	10.0	19.2	NS	15.8	26.8	NS
Pseudomonadales_fa	3.1	10.0	A**	14.0	19.1	B	0.6	1.2	A***
Pseudomonadales_ge	3.1	10.0	A**	14.0	19.1	B	0.6	1.2	A**
Cardiobacteriaceae	12.8	26.7	A**	1.9	3.0	B	8.8	14.2	AB
Suttonella	12.8	26.7	A**	1.9	3.0	B	8.8	14.2	AB
Pasteurellaceae	0.2	0.6	NS	5.8	6.3	NS	0.2	0.5	NS
Pasteurellaceae_ge	0.1	0.5	NS	4.7	5.6	NS	0.2	0.5	NS
Neisseriaceae	0.4	1.7	NS	3.2	5.5	NS	0.3	0.8	NS
Conchiformibius	0.4	1.7	NS	3.1	5.3	NS	0.3	0.7	NS
Burkholderiaceae	0.4	0.8	NS	1.0	2.1	NS	0.5	1.1	NS
Gammaproteobacteria_fa	0.7	0.8	NS	0.4	0.5	NS	1.0	1.0	NS
Gammaproteobacteria_ge	0.7	0.8	NS	0.4	0.5	NS	1.0	1.0	NS
Actinobacteria	4.7	5.2	A*	18.2	19	B	8.8	14.2	AB
Corynebacteriaceae	0.6	1.2	NS	4.9	7.7	NS	0.6	1.0	NS
Corynebacterium_1	0.2	0.4	NS	2.6	5.6	NS	0.3	0.8	NS
Corynebacterium	0.4	1.2	NS	1.8	5.2	NS	0.2	0.7	NS
Micrococcaceae	0.2	0.5	NS	6.1	16.2	NS	0.4	0.7	NS
Rothia	0.1	0.3	NS	6.0	16.2	NS	0.1	0.4	NS
Microbacteriaceae	2.9	4.7	NS	5.7	12.0	NS	6.5	8.7	NS
Leucobacter	2.4	4.6	NS	5.7	12.0	NS	6.4	8.7	NS
Tenericutes	12.8	23	NS	11.4	25.8	NS	3.7	10.8	NS
Mollicutes_fa	12.6	23	A	11.4	25.8	AB	3.7	10.7	B*
Mollicutes_ge	12.6	23	NS	11.4	25.8	NS	3.7	10.7	NS
Firmicutes	6.2	8.7	NS	12.3	14.5	NS	3.6	4.2	NS
Streptococcaceae	1.7	4.1	NS	4.8	7.1	NS	0.3	1.1	NS
Streptococcus	1.7	4.1	NS	4.8	7.1	NS	0.3	1.1	NS
Staphylococcaceae	1.3	2.8	NS	3.3	10.3	NS	1.6	3.1	NS
Staphylococcus	1.2	2.8	NS	3.3	10.3	NS	1.6	3.1	NS
Aerococcaceae	0.8	3.1	NS	1.6	3.2	NS	0.0	0.1	NS
Abiotrophia	0.7	3.0	NS	1.5	3.1	NS	0.0	0.1	NS
Carnobacteriaceae	1.1	2.6	NS	0.0	0.2	NS	0.0	0.0	NS
Bacillales_Family_XI	0.2	0.8	NS	1.0	1.9	NS	0.0	0.1	NS
Gemella	0.2	0.8	NS	1.0	1.9	NS	0.0	0.1	NS
Clostridiales_Family_XI	0.8	1.7	NS	0.5	0.9	NS	1.0	1.7	NS
Helcococcus	0.7	1.7	NS	0.4	0.8	NS	1.0	1.7	NS
Bacteroidetes	2.5	6.3	NS	3.3	4.3	NS	1.7	3.5	NS
Porphyromonadaceae	0.9	4.1	NS	1.7	3.3	NS	1.0	3.3	NS
Porphyromonas	0.9	4.1	NS	1.7	3.3	NS	1.0	3.3	NS
Weeksellaceae	1.3	3.3	NS	0.8	1.0	NS	0.5	0.9	NS
Fusobacteria	0.1	0.2	NS	1.0	1.8	NS	0.2	0.6	NS

Mean relative percentages (mean rel. freq) and standard deviation (SD) of the most abundant bacterial groups, annotated to the level of phylum, family and genus, based on sequencing of the V1-V3 region of the 16S rDNA.

Group DL = mesocephalic or dolichocephalic dogs of medium to large breeds

Group B = dogs of brachycephalic breeds

Group T = dogs of Terrier breeds

A,B: OTUs not sharing a common letter between breed groups differ significantly. *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001; NS not significant

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Variations in Facial Conformation Are Associated With Differences in Nasal Microbiota in Healthy Dogs

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