Advances in the field of metagenomics using culture-independent methods of microbial identification have allowed characterization of rich and diverse communities of bacteria in the lungs of healthy humans, mice, dogs, sheep and pigs. These data challenge the long held belief that the lungs are sterile and microbial colonization is synonymous with pathology. Studies in humans and animals demonstrate differences in the composition of airway microbiota in health versus disease suggesting respiratory dysbiosis occurs. Using 16S rRNA amplicon sequencing of DNA extracted from rectal and oropharyngeal (OP) swabs, bronchoalveolar lavage fluid (BALF), and blood, our objective was to characterize the fecal, OP, blood, and lower airway microbiota over time in healthy cats. This work in healthy cats, a species in which a respiratory microbiota has not yet been characterized, sets the stage for future studies in feline asthma in which cats serve as a comparative and translational model for humans. Fecal, OP and BALF samples were collected from six healthy research cats at day 0, week 2, and week 10; blood was collected at week 10. DNA was extracted, amplified via PCR, and sequenced using the Illumina MiSeq platform. Representative operational taxonomic units (OTUs) were identified and microbial richness and diversity were assessed. Principal component analysis (PCA) was used to visualize relatedness of samples and PERMANOVA was used to test for significant differences in microbial community composition. Fecal and OP swabs provided abundant DNA yielding a mean±SEM of 65,653±6,145 and 20,6323±4,360 sequences per sample, respectively while BALF and blood samples had lower coverage (1,489±430 and 269±18 sequences per sample, respectively). Oropharyngeal and fecal swabs were significantly richer than BALF (mean number OTUs 93, 88 and 36, respectively; p < 0.001) with no significant difference (p = 0.180) in richness between time points. PCA revealed site-specific microbial communities in the feces, and upper and lower airways. In comparison, blood had an apparent compositional similarity with BALF with regard to a few dominant taxa, but shared more OTUs with feces. Samples clustered more by time than by individual, with OP swabs having subjectively greater variation than other samples. In summary, healthy cats have a rich and distinct lower airway microbiome with dynamic bacterial populations. The microbiome is likely to be altered by factors such as age, environmental influences, and disease states. Further data are necessary to determine how the distinct feline microbiomes from the upper and lower airways, feces and blood are established and evolve. These data are relevant for comparisons between healthy cats and cats with respiratory disease.

Probiotics have been advocated as a novel therapeutic approach to respiratory disease, but knowledge of how oral administration of probiotics influences the respiratory microbiota is needed. Using 16S rRNA amplicon sequencing of bacterial DNA our objective was to determine whether oral probiotics changed the composition of the upper and lower airway, rectal, and blood microbiota. We hypothesized that oral probiotics would modulate the respiratory microbiota in healthy cats, demonstrated by the detection and/or increased relative abundance of the probiotic bacterial species and altered composition of the microbial population in the respiratory tract. Six healthy young research cats had oropharyngeal (OP), bronchoalveolar lavage fluid (BALF), rectal, and blood samples collected at baseline and 4 weeks after receiving oral probiotics. 16S rRNA gene amplicon libraries were sequenced, and coverage, richness, and relative abundance of representative operational taxonomic units (OTUs) were determined. Hierarchical and principal component analyses (PCA) demonstrated relatedness of samples. Mean microbial richness significantly increased only in the upper and lower airways. The number of probiotic OTUs (out of 5 total) that significantly increased in relative abundance versus baseline was 5 in OP, 3 in BAL and 2 in feces. Using hierarchical clustering, BALF and blood samples grouped together after probiotic administration, and PERMANOVA supported that these two sites underwent significant changes in microbial composition. PERMANOVA revealed that OP and rectal samples had microbial population compositions that did not significantly change. These findings were visualized via PCA, which revealed distinct microbiomes in each site; samples clustered more tightly at baseline and had more variation after probiotic administration. This is the first study describing the effect of oral probiotics on the respiratory microbiota via detection of probiotic species in the airways. Finding bacterial species present in the oral probiotics in the upper and lower airways provides pilot data suggesting that oral probiotics could serve as a tool to target dysbiosis occurring in inflammatory airway diseases such as feline asthma, a disease in which cats serve as an important comparative and translational model for humans.

OBJECTIVE To evaluate effects of blood contamination on dipstick results, specific gravity (SG), and urine protein-to-urine creatinine ratio (UPCR) for urine samples from dogs and cats. SAMPLE Urine samples collected from 279 dogs and 120 cats. PROCEDURES Urine pools were made for each species (dogs [n = 60] and cats [30]). Blood was added to an aliquot of a pool, and serial dilutions were prepared with the remaining urine. Color and dipstick variables were recorded, and SG and UPCR were measured. For cats, 1 set of pools was used; for dogs, 2 sets were used. Comparisons were made between undiluted urine and spiked urine samples for individual colors. Repeated-measures ANOVA on ranks was used to compare dipstick scores and UPCR results; χ² tests were used to compare proteinuria categorizations (nonproteinuric, borderline, or proteinuric). RESULTS Any blood in the urine resulted in significantly increased dipstick scores for blood. In both species, scores for bilirubin and ketones, pH, and SG were affected by visible blood contamination. No significant difference for the dipstick protein reagent results was evident until a sample was visibly hematuric. The UPCR was significantly increased in dark yellow samples of both species. Proteinuria categorizations differed significantly between undiluted urine and urine of all colors, except light yellow. CONCLUSIONS AND CLINICAL RELEVANCE Any degree of blood contamination affected results of dipstick analysis. Effects depended on urine color and the variable measured. Microscopic blood contamination may affect the UPCR; thus, blood contamination may be a differential diagnosis for proteinuria in yellow urine samples.

This Perspectives in Veterinary Medicine article seeks to define, describe putative causes, and discuss key diagnostic tests for primary and secondary bronchiolar disorders to propose a classification scheme in cats with support from a literature review and case examples. The small airways (bronchioles with inner diameters <2 mm), located at the transitional zone between larger conducting airways and the pulmonary acinus, have been overlooked as major contributors to clinical syndromes of respiratory disease in cats. Because the trigger for many bronchiolar disorders is environmental and humans live in a shared environment with similar susceptibility, understanding these diseases in pet cats has relevance to One Health. Thoracic radiography, the major imaging modality used in the diagnostic evaluation of respiratory disease in cats, has low utility in detection of bronchiolar disease. Computed tomography (CT) with paired inspiratory and expiratory scans can detect pathology centered on small airways. In humans, treatment of bronchiolar disorders is not well established because of heterogeneous presentations and often late definitive diagnosis. A review of the human and veterinary medical literature will serve as the basis for a proposed classification scheme in cats. A case series of cats with CT or histopathologic evidence of bronchiolar lesions or both, either as a primary disorder or secondary to extension from large airway disease or interstitial lung disease, will be presented. Future multi-institutional and multidisciplinary discussions among clinicians, radiologists, and pathologists will help refine and develop this classification scheme to promote early and specific recognition and optimize treatment.

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.