Objectives: Previous studies have identified various bacterial taxa that are altered in cats with chronic enteropathies (CE) vs healthy cats. Therefore, the aim of this study was to develop a targeted quantitative molecular method to evaluate the fecal microbiota of cats. Methods: Fecal samples from 80 client-owned healthy cats and 68 cats with CE were retrospectively evaluated. A panel of quantitative PCR (qPCR) assays was used to measure the fecal abundance of total bacteria and seven bacterial taxa: Bacteroides, Bifidobacterium, Clostridium hiranonis, Escherichia coli, Faecalibacterium, Streptococcus and Turicibacter. The nearest centroid classifier algorithm was used to calculate a dysbiosis index (DI) based on these qPCR abundances. Results: The abundances of total bacteria, Bacteroides, Bifidobacterium, C hiranonis, Faecalibacterium and Turicibacter were significantly decreased, while those of E coli and Streptococcus were significantly increased in cats with CE ( P <0.027 for all). The DI in cats with CE was significantly higher compared with healthy cats ( P 0. Conclusions and relevance: A qPCR-based DI for assessing the fecal microbiota of cats was established. The results showed that a large proportion of cats with CE had an altered fecal microbiota as evidenced by an increased DI. Prospective studies are warranted to evaluate the utility of this assay for clinical assessment of feline CE.

DNA shotgun sequencing is an untargeted approach for identifying changes in relative abundances, while qPCR allows reproducible quantification of specific bacteria. The canine dysbiosis index (DI) assesses the canine fecal microbiota by using a mathematical algorithm based on qPCR results. We evaluated the correlation between qPCR and shotgun sequencing using fecal samples from 296 dogs with different clinical phenotypes. While significant correlations were found between qPCR and sequencing, certain taxa were only detectable by qPCR and not by sequencing. Based on sequencing, less than 2% of bacterial species (17/1190) were consistently present in all healthy dogs (n = 76). Dogs with an abnormal DI had lower alpha-diversity compared to dogs with normal DI. Increases in the DI correctly predicted the gradual shifts in microbiota observed by sequencing: minor changes (R = 0.19, DI < 0 with any targeted taxa outside the reference interval, RI), mild-moderate changes (R = 0.24, 0 < DI < 2), and significant dysbiosis (R = 0.54, 0.73, and 0.91 for DI > 2, DI > 5, and DI > 8, respectively), compared to dogs with a normal DI (DI < 0, all targets within the RI), as higher R-values indicated larger dissimilarities. In conclusion, the qPCR-based DI is an effective indicator of overall microbiota shifts observed by shotgun sequencing in dogs.

Chronic enteropathy (CE) in cats encompasses food-responsive enteropathy, chronic inflammatory enteropathy (or inflammatory bowel disease), and low-grade intestinal T-cell lymphoma. While alterations in the gut metabolome have been extensively studied in humans and dogs with gastrointestinal disorders, little is known about the specific metabolic profile of cats with CE. As lipids take part in energy storage, inflammation, and cellular structure, investigating the lipid profile in cats with CE is crucial. This study aimed to measure fecal concentrations of various fatty acids, sterols, and bile acids. Fecal samples from 56 cats with CE and 77 healthy control cats were analyzed using gas chromatography-mass spectrometry, targeting 12 fatty acids, 10 sterols, and 5 unconjugated bile acids. Fecal concentrations of nine targeted fatty acids and animal-derived sterols were significantly increased in cats with CE. However, fecal concentrations of plant-derived sterols were significantly decreased in cats with CE. Additionally, an increased percentage of primary bile acids was observed in a subset of cats with CE. These findings suggest the presence of lipid maldigestion, malabsorption, and inflammation in the gastrointestinal tract of cats with CE. Understanding the lipid alterations in cats with CE can provide insights into the disease mechanisms and potential future therapeutic strategies.

Bile acid metabolism is a key pathway modulated by intestinal microbiota. Peptacetobacter (Clostridium) hiranonis has been described as the main species responsible for the conversion of primary into secondary fecal unconjugated bile acids (fUBA) in dogs. This multi-step biochemical pathway is encoded by the bile acid-inducible (bai) operon. We aimed to assess the correlation between P. hiranonis abundance, the abundance of one specific gene of the bai operon (baiCD), and secondary fUBA concentrations. In this retrospective study, 133 fecal samples were analyzed from 24 dogs. The abundances of P. hiranonis and baiCD were determined using qPCR. The concentration of fUBA was measured by gas chromatography–mass spectrometry. The baiCD abundance exhibited a strong positive correlation with secondary fUBA (ρ = 0.7377, 95% CI (0.6461, 0.8084), p < 0.0001). Similarly, there was a strong correlation between P. hiranonis and secondary fUBA (ρ = 0.6658, 95% CI (0.5555, 0.7532), p < 0.0001). Animals displaying conversion of fUBA and lacking P. hiranonis were not observed. These results suggest P. hiranonis is the main converter of primary to secondary bile acids in dogs.

While shifts in gut microbiota have been studied in diseased states, the temporal variability of the microbiome in cats has not been widely studied. This study investigated the temporal variability of the feline dysbiosis index (DI) and the abundance of core bacterial groups in healthy adult cats. The secondary aim was to evaluate the relationship between the fecal abundance of Clostridium hiranonis and the fecal concentrations of unconjugated bile acids. A total of 142 fecal samples collected from 17 healthy cats were prospectively included: nine cats with weekly collection over 3 weeks (at least four time points), five cats with monthly collection over 2 months (three time points), and three cats with additional collections for up to 10 months. The DI remained stable within the reference intervals over two months for all cats (Friedman test, p > 0.2), and 100% of the DI values (n = 142) collected throughout the study period remained within the RI. While some temporal individual variation was observed for individual taxa, the magnitude was minimal compared to cats with chronic enteropathy and antibiotic exposure. Additionally, the abundance of Clostridium hiranonis was significantly correlated with the percentage of fecal primary bile acids, supporting its role as a bile acid converter in cats.

Feline chronic enteropathies (FCE) are common causes of chronic gastrointestinal signs in cats and include different diseases such as food-responsive enteropathy (FRE), inflammatory bowel diseases (IBD), and low-grade intestinal T-cell lymphoma (LGITL). Although changes in intestinal microbiota and fecal metabolites have been reported in dogs and humans with chronic enteropathy, research in cats has been limited. Therefore, this study aimed to evaluate the fecal microbiota and lipid-related fecal metabolites in cats with FCE to a clinically healthy comparison group (CG). A total of 34 cats with FCE (13 FRE, 15 IBD, and 6 LGITL) and 27 cats in the CG were enrolled in this study. The fecal microbiota was evaluated by the qPCR-based feline Dysbiosis Index (DI). The feline DI in cats with CE (median: 1.3, range: −2.4 to 3.8) was significantly higher (p < 0.0001) compared to CG (median: - 2.3, Range: −4.3 to 2.3), with no difference found among the FCE subgroups. The fecal abundances of Faecalibacterium (p < 0.0001), Bacteroides (p < 0.0001), Fusobacterium (p = 0.0398), Bifidobacterium (p = 0.0004), and total bacteria (p = 0.0337) significantly decreased in cats with FCE. Twenty-seven targeted metabolites were measured by gas chromatography–mass spectrometry, including long-chain fatty acids (LCFAs), sterols, and bile acids (BAs). Fecal concentrations of 5 of 12 LCFAs were significantly increased in cats with FCE compared to CG. Fecal concentrations of zoosterol (p = 0.0109), such as cholesterol (p < 0.001) were also significantly increased in cats with FCE, but those of phytosterols were significantly decreased in this group. No differences in fecal BAs were found between the groups. Although no differences were found between the four groups, the fecal metabolomic pattern of cats with FRE was more similar to that of the CG than to those with IBD or LGITL. This could be explained by the mild changes associated with FRE compared to IBD and LGITL. The study showed changes in intestinal microbiota and alteration of fecal metabolites in FCE cats compared to the CG. Changes in fecal lipids metabolites suggest a dysmetabolism of lipids, including LCFAs, sterols, and unconjugated BAs in cats with CE.