Recent studies have identified various bacterial groups that are altered in dogs with chronic inflammatory enteropathies (CE) compared to healthy dogs. The study aim was to use quantitative PCR (qPCR) assays to confirm these findings in a larger number of dogs, and to build a mathematical algorithm to report these microbiota changes as a dysbiosis index (DI). Fecal DNA from 95 healthy dogs and 106 dogs with histologically confirmed CE was analyzed. Samples were grouped into a training set and a validation set. Various mathematical models and combination of qPCR assays were evaluated to find a model with highest discriminatory power. The final qPCR panel consisted of eight bacterial groups: total bacteria, Faecalibacterium, Turicibacter, Escherichia coli, Streptococcus, Blautia, Fusobacterium and Clostridium hiranonis. The qPCR-based DI was built based on the nearest centroid classifier, and reports the degree of dysbiosis in a single numerical value that measures the closeness in the l2 - norm of the test sample to the mean prototype of each class. A negative DI indicates normobiosis, whereas a positive DI indicates dysbiosis. For a threshold of 0, the DI based on the combined dataset achieved 74% sensitivity and 95% specificity to separate healthy and CE dogs.

Background: Metronidazole has a substantial impact on the gut microbiome. However, the recovery of the microbiome after discontinuation of administration, and the metabolic consequences of such alterations have not been investigated to date. Objectives: To describe the impact of 14-day metronidazole administration, alone or in combination with a hydrolyzed protein diet, on fecal microbiome, metabolome, bile acids (BAs), and lactate production, and on serum metabolome in healthy dogs. Animals: Twenty-four healthy pet dogs. Methods: Prospective, nonrandomized controlled study. Dogs fed various commercial diets were divided in 3 groups: control group (no intervention, G1); group receiving hydrolyzed protein diet, followed by metronidazole administration (G2); and group receiving metronidazole only (G3). Microbiome composition was evaluated with sequencing of 16S rRNA genes and quantitative polymerase chain reaction (qPCR)-based dysbiosis index. Untargeted metabolomics analysis of fecal and serum samples was performed, followed by targeted assays for fecal BAs and lactate. Results: No changes were observed in G1, or G2 during diet change. Metronidazole significantly changed microbiome composition in G2 and G3, including decreases in richness (P < .001) and in key bacteria such as Fusobacteria (q < 0.001) that did not fully resolve 4 weeks after metronidazole discontinuation. Fecal dysbiosis index was significantly increased (P < .001). Those changes were accompanied by increased fecal total lactate (P < .001), and decreased secondary BAs deoxycholic acid and lithocholic acid (P < .001).

Background Accumulating evidence shows an important relationship between the gastrointestinal (GI) microbiota and host health. Microbial metabolites are believed to play a critical role in host‐microbial interactions. Short‐chain fatty acids (SCFAs) are major end products of bacterial carbohydrate fermentation in the intestinal tract. Decreased concentrations of SCFAs have been observed in humans with GI disease. However, large‐scale clinical data in dogs are lacking. Hypothesis/Objective To evaluate fecal concentrations of SCFAs and the fecal microbiota in healthy control (HC) dogs and dogs with chronic enteropathy (CE). Animals Forty‐nine privately owned HC dogs and 73 dogs with CE. Methods Prospective cohort study. Fecal concentrations of SCFAs were measured using gas chromatography/mass spectrometry. Illumina sequencing and quantitative real‐time polymerase chain reaction were utilized to evaluate the fecal microbiota. Results Fecal concentrations (median [range] μmol/g of dry matter) of acetate were lower ( P = .03) in dogs with CE (185.8 [20.1‐1042.1]) than in HC dogs (224.0 [87.7‐672.8]). Propionate were also lower ( P < .001) in dogs with CE (46.4 [0.4‐227.9]) than in HC dogs (105.9 [1.6‐266.9]). Moreover, total SCFAs were lower ( P = .005) in dogs with CE (268.1 [21.8‐1378.2]) than in HC dogs (377.2 [126.6‐927.0]). Dysbiosis in dogs with CE was characterized by decreased bacterial diversity and richness, distinct microbial community clustering compared with that in HC dogs, and a higher dysbiosis index. Conclusions and Clinical Importance Dogs with CE had an altered fecal SCFA concentration accompanied by significant changes of the fecal microbiota.

The aim was to characterize differences in fecal consistency, and fecal microbiota and metabolome profiles in dogs with acute diarrhea (AD) treated with either fecal microbiota transplantation as enema (FMT; n = 11) or oral metronidazole (MET; n = 7) for 7 days. On days 0, 7, and 28 fecal samples were obtained. Fecal samples from healthy dogs (HC; n = 14) were used for comparison. Samples were analyzed by the previously validated qPCR based canine Dysbiosis Index (DI; increased values indicate microbiota dysbiosis) and 16S rRNA gene sequencing. The fecal metabolome was analyzed using a previously validated targeted canine assay for fecal unconjugated bile acids, and untargeted metabolomics. Fecal consistency improved significantly in dogs treated with FMT and MET by day 7 and day 28 (p < 0.01) compared to day 0. However, on day 28 fecal consistency was significantly better in FMT compared to MET (p = 0.040). At day 0, dogs with AD had an altered microbiota indicated by significantly increased DI, decreased alpha-diversity, and altered beta-diversity. In the FMT group, the DI decreased over time, while MET led to a significant increase in the dysbiosis index at day 7 and 28 compared to FMT. Sequencing data revealed that in FMT microbial diversity and beta-diversity was similar to HC at day 28, while in MET these parameters were still significantly different from HC. In dogs treated with FMT, a decrease in cholic acid and the percentage of primary bile acids was observed, whereas treatment with metronidazole led to an increase in cholic acid at day 7 and an increase in percentage of primary bile acids over time. Based on untargeted metabolomics, dogs with AD had an altered fecal metabolome compared to HC. Dogs treated with FMT clustered closer to HC at day 28, while dogs treated with MET did not. In this pilot study, dogs with AD had significant differences in fecal microbiota and metabolome profiles. Dogs treated with MET still had altered microbial and metabolic profiles at day 28 compared to dogs treated with FMT or healthy dogs.

IntroductionFeeding a Bones and Raw Food (BARF) diet has become an increasing trend in canine nutrition. Bones and Raw Food diets contain a high amount of animal components like meat, offal, and raw meaty bones, combined with comparatively small amounts of plant ingredients like vegetables and fruits as well as different sorts of oil and supplements. While many studies have focused on transmission of pathogens via contaminated meat and on nutritional imbalances, only few studies have evaluated the effect of BARF diets on the fecal microbiome and metabolome. The aim of the study was to investigate differences in the fecal microbiome and the metabolome between dogs on a BARF diet and dogs on a commercial diet (canned and dry dog food).MethodsNaturally passed fecal samples were obtained from 27 BARF and 19 commercially fed dogs. Differences in crude protein, fat, fiber, and NFE (Nitrogen-Free Extract) between diets were calculated with a scientific nutrient database. The fecal microbiota was analyzed by 16S rRNA gene sequencing and quantitative PCR assays. The fecal metabolome was analyzed in 10 BARF and 9 commercially fed dogs via untargeted metabolomics approach.ResultsDogs in the BARF group were fed a significantly higher amount of protein and fat and significantly lower amount of NFE and fiber. There was no significant difference in alpha-diversity measures between diet groups. Analysis of similarity (ANOSIM) revealed a significant difference in beta-diversity (p < 0.01) between both groups. Linear discriminant analysis effect size (LefSe) showed a higher abundance of Lactobacillales, Enterobacteriaceae, Fusobacterium and, Clostridium in the BARF group while conventionally fed dogs had a higher abundance of Clostridiaceae, Erysipelotrichaceae, Ruminococcaceae, and Lachnospiraceae. The qPCR assays revealed significantly higher abundance of Escherichia coli (E. coli) and Clostridium (C.). perfringens and an increased Dysbiosis Index in the BARF group. Principal component analysis (PCA) plots of metabolomics data showed clustering between diet groups. Random forest analysis showed differences in the abundance of various components, including increased 4-hydroxybutryric acid (GBH) and 4-aminobutyric acid (GABA) in the BARF group. Based on univariate statistics, several metabolites were significantly different between diet groups, but lost significance after adjusting for multiple comparison. No differences were found in fecal bile acid concentrations, but the BARF group had a higher fecal concentration of cholesterol in their feces compared to conventionally fed dogs.ConclusionMicrobial communities and metabolome vary significantly between BARF and commercially fed dogs.