Variations in facial conformation are associated with differences in nasal microbiota in healthy dogs

Comparison of culture-dependent and -independent bacterial detection results on nasal swabs in dogs with nasal discharge

OBJECTIVES

The role of bacterial communities in the pathophysiology of canine nasal disease is still unclear. How and when to treat dogs with suspected secondary bacterial rhinitis and on which test to rely before making a decision to treat with antimicrobials has not been established. The objective is to compare the results of bacterial identification using agar-plate cultures and 16S rRNA gene amplicon sequencing in dogs with nasal discharge suspected to be of bacterial origin.

MATERIALS AND METHODS

Twenty-nine client-owned dogs presented for investigation of nasal disease were included in the study. Paired swabs were collected from the same affected nasal cavity. One swab was streaked on 4 agar media (Columbia Blood Agar, MacConkey, Chapman and Edward's). The other swab was stored in a sterile cryotube at -80°. Extracted DNA underwent a polymerase chain reaction targeting the V1-V3 region of the 16S rRNA gene.

RESULTS

At least one of the species detected by amplicon sequencing with a relative abundance of >10% was also identified by culture in 14 cases (48.3%), in association with marked predominance of one taxon (>80% relative abundance) in six of 14 cases. In 12 dogs (41.4%), the cultured isolates were rare or undetected components of the corresponding sequence libraries. A negative culture in the face of bacterial predominance (>50% relative abundance) of a potentially pathogenic bacteria detected by sequencing occurred in 17% (n=5) of cases; however, the use of other agar media may have decreased this percentage.

CLINICAL SIGNIFICANCE

Standard culture does not reliably predict the bacterial profile detected by 16S rRNA gene amplicon sequencing.

Host-specific signatures of the respiratory microbiota in domestic animals

While the importance of respiratory microbiota in maintaining respiratory health is increasingly recognized, we still lack a comprehensive understanding of the unique characteristics of respiratory microbiota specific to individual hosts. This study aimed to address this gap by analyzing publicly available 16S rRNA gene datasets from various domestic animals (cats, dogs, pigs, donkeys, chickens, sheep, and cattle) to identify host-specific signatures of respiratory microbiota. The findings revealed that cattle and pigs exhibited the highest Shannon diversity index and observed features, indicating a greater microbial variety compared to other animals. Discriminant analysis demonstrated distinct composition of respiratory microbiota across different animals, with no overlapping abundant taxa. The linear discriminant analysis effect size highlighted prevalent host-specific microbiota signatures in different animal species. Moreover, the composition and diversity of respiratory microbiota were significantly influenced by various factors such as individual study, health status, and sampling sites within the respiratory tract. While associations between host and respiratory microbiota have been uncovered, the relative contributions of host and environment in the selection of respiratory microbiota and their impact on host fitness remain unclear. Further investigations involving diverse hosts are necessary to fully comprehend the significance of host-microbial coevolution in maintaining respiratory health.

The respiratory microbiota and its impact on health and disease in dogs and cats: A One Health perspective

Healthy lungs were long thought of as sterile, with presence of bacteria identified by culture representing contamination. Recent advances in metagenomics have refuted this belief by detecting rich, diverse, and complex microbial communities in the healthy lower airways of many species, albeit at low concentrations. Although research has only begun to investigate causality and potential mechanisms, alterations in these microbial communities (known as dysbiosis) have been described in association with inflammatory, infectious, and neoplastic respiratory diseases in humans. Similar studies in dogs and cats are scarce. The microbial communities in the respiratory tract are linked to distant microbial communities such as in the gut (ie, the gut-lung axis), allowing interplay of microbes and microbial products in health and disease. This review summarizes considerations for studying local microbial communities, key features of the respiratory microbiota and its role in the gut-lung axis, current understanding of the healthy respiratory microbiota, and examples of dysbiosis in selected respiratory diseases of dogs and cats.

Assessment of the nasal microbiota in dogs with fungal rhinitis before and after cure and in dogs with chronic idiopathic rhinitis

BACKGROUND

Pathogenesis of canine fungal rhinitis is still not fully understood. Treatment remains challenging, after cure turbinate destruction may be associated with persistent clinical signs and recurrence of fungal rhinitis can occur. Alterations of the nasal microbiota have been demonstrated in dogs with chronic idiopathic rhinitis and nasal neoplasia, although whether they play a role in the pathogenesis or are a consequence of the disease is still unknown. The objectives of the present study were (1) to describe nasal microbiota alterations associated with fungal rhinitis in dogs, compared with chronic idiopathic rhinitis and controls, (2) to characterize the nasal microbiota modifications associated with successful treatment of fungal rhinitis. Forty dogs diagnosed with fungal rhinitis, 14 dogs with chronic idiopathic rhinitis and 29 healthy control dogs were included. Nine of the fungal rhinitis dogs were resampled after successful treatment with enilconazole infusion.

RESULTS

Only disease status contributed significantly to the variability of the microbiota. The relative abundance of the genus Moraxella was decreased in the fungal rhinitis (5.4 ± 18%) and chronic idiopathic rhinitis (4.6 ± 8.7%) groups compared to controls (51.8 ± 39.7%). Fungal rhinitis and chronic idiopathic rhinitis groups also showed an increased richness and α-diversity at species level compared with controls. Increase in unique families were associated with fungal rhinitis (Staphyloccaceae, Porphyromonadaceae, Enterobacteriaceae and Neisseriaceae) and chronic idiopathic rhinitis (Pasteurellaceae and Lactobacillaceae). In dogs with fungal rhinitis at cure, only 1 dog recovered a high relative abundance of Moraxellaceae.

CONCLUSIONS

Results confirm major alterations of the nasal microbiota in dogs affected with fungal rhinitis and chronic idiopathic rhinitis, consisting mainly in a decrease of Moraxella. Besides, a specific dysbiotic profile further differentiated fungal rhinitis from chronic idiopathic rhinitis. In dogs with fungal rhinitis, whether the NM returns to its pre-infection state or progresses toward chronic idiopathic rhinitis or fungal rhinitis recurrence warrants further investigation.

Analysis and Comparison of Gut Microbiome in Young Detection Dogs

The detection dogs are well-known for their excellent capabilities to sense different kinds of smells, which can play an important role in completing various searching and rescuing missions. The recent studies have demonstrated that the excellent olfactory function of detection dogs might be related with the gut microbes via the bidirectional communications between the gastrointestinal tract and the brain. In this study, the gut microbial communities of three types of breeds of detection dogs (Springer Spaniel, Labrador Retriever, and German Shepherd) were studied and compared. The results revealed that the richness and the diversity of gut microbiome German Shepherd dogs were significantly higher than the Labrador Retriever dogs and the Springer Spaniel dogs. At the phylum level, the most predominant gut microbial communities of the detection dogs were comprised of Fusobacteriota, Bacteroidetes, Firmicutes, Proteobacteria, Campilobacterota, and Actinobacteriota. At the genus level the most predominant gut microbial communities were comprised of Fusobacterium, Megamonas, Prevotella, Alloprevotella, Bacteroides, Haemophilus, Anaerobiospirillum, Helicobacter, Megasphaera, Peptoclostridium, Phascolarctobacterium, and Streptococcus. However, the gut microbial communities of the three dogs group were also obviously different. The mean relative abundance of Fusobacterium, Prevotella, Alloprevotella, Megamonas, Bacteroides, and Phascolarctobacterium presented significant differences in the three groups. According to the portraits and characteristics of the gut microbiome in young detection dogs, multiple kinds of nutritional interventions could be applied to manipulate the gut microbiota, with the aim of improving the health states and the olfactory performances.