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The intestinal microbiota plays an important role in health and disease and produces, through fermentative reactions, several metabolic products, such as lactate, that can affect the host. The microbiota also interacts with and metabolizes compounds produced by the host, such as primary bile acids. Lactate and bile acids (BA) are of particular interest in gastrointestinal diseases because they have been associated with metabolic acidosis and bile acid diarrhea, respectively. The objectives of this study were to validate an enzymatic assay to quantify D-, L-, and total lactate in canine feces, and to characterize fecal lactate and BA concentrations as well as bacterial abundances in healthy dogs and dogs with gastrointestinal diseases. Fecal samples were collected from 34 healthy dogs, 15 dogs with chronic enteropathy (CE), and 36 dogs with exocrine pancreatic insufficiency (EPI). Lactate was quantified with an enzymatic assay, BA with gas chromatography-mass spectrometry, and 11 bacterial groups with qPCR. A fecal lactate reference interval was established from 34 healthy dogs and was 0.7-1.4 mM, 0.3-6.0 mM, and 1.0-7.0 mM for D-, L-, and total lactate, respectively. The assay to measure D-, L-, and total lactate in canine fecal samples was linear, accurate, precise, and reproducible. Significant increases in fecal lactate and decreases in secondary BA concentrations were observed in dogs with CE and dogs with EPI. Dogs with EPI had an increased abundance of Escherichia coli, Lactobacillus, and Bifidobacterium; a decreased abundance of Fusobacterium and Clostridium hiranonis; and a higher Dysbiosis Index when compared to healthy dogs. Further studies are necessary to determine the clinical utility of lactate and BA quantification in canine feces. These metabolites suggest functional alterations of intestinal dysbiosis and may become promising targets for further elucidating the role of the microbiota in health and disease.

Abstract 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). Conclusion and Clinical Importance Our results indicate a minimum 4-week effect of metronidazole on fecal microbiome and metabolome, supporting a cautious approach to prescription of metronidazole in dogs.

Feeding 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). Naturally 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. Dogs 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. Microbial communities and metabolome vary significantly between BARF and commercially fed dogs.

Limited information is available regarding the metabolic consequences of intestinal dysbiosis in dogs with acute onset of diarrhea. The aim of this study was to evaluate the fecal microbiome, fecal concentrations of short-chain fatty acids (SCFAs), as well as serum and urine metabolites in healthy dogs (n=13) and dogs with acute diarrhea (n=13). The fecal microbiome, SCFAs, and serum/urine metabolite profiles were characterized by 454-pyrosequencing of the 16S rRNA genes, GC/MS, and untargeted and targeted metabolomics approach using UPLC/MS and HPLC/MS, respectively. Significantly lower bacterial diversity was observed in dogs with acute diarrhea in regards to species richness, chao1, and Shannon index (p=0.0218, 0.0176, and 0.0033; respectively). Dogs with acute diarrhea had significantly different microbial communities compared to healthy dogs (unweighted Unifrac distances, ANOSIM p=0.0040). While Bacteroidetes, Faecalibacterium, and an unclassified genus within Ruminococcaceae were underrepresented, the genus Clostridium was overrepresented in dogs with acute diarrhea. Concentrations of fecal propionic acid were significantly decreased in acute diarrhea (p=0.0033), and were correlated to a decrease in Faecalibacterium (ρ=0.6725, p=0.0332). The predicted functional gene content of the microbiome (PICRUSt) revealed overrepresentations of genes for transposase enzymes as well as methyl accepting chemotaxis proteins in acute diarrhea. Serum concentrations of kynurenic acid and urine concentrations of 2-methyl-1H-indole and 5-Methoxy-1H-indole-3-carbaldehyde were significantly decreased in acute diarrhea (p=0.0048, 0.0185, and 0.0330, respectively). These results demonstrate that the fecal dysbiosis present in acute diarrhea is associated with altered systemic metabolic states.

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; = 11) or oral metronidazole (MET; = 7) for 7 days. On days 0, 7, and 28 fecal samples were obtained. Fecal samples from healthy dogs (HC; = 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 ( < 0.01) compared to day 0. However, on day 28 fecal consistency was significantly better in FMT compared to MET ( = 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.

Abstract Background Mounting evidence from human studies suggests that bile acid dysmetabolism might play a role in various human chronic gastrointestinal diseases. It is unknown whether fecal bile acid dysmetabolism occurs in dogs with chronic inflammatory enteropathy (CE). Objective To assess microbial dysbiosis, fecal unconjugated bile acids (fUBA), and disease activity in dogs with steroid-responsive CE. Animals Twenty-four healthy control dogs and 23 dogs with steroid-responsive CE. Methods In this retrospective study, fUBA were measured and analyzed. Fecal microbiota were assessed using a dysbiosis index. The canine inflammatory bowel disease activity index was used to evaluate remission of clinical signs. This was a multi-institutional study where dogs with steroid-responsive CE were evaluated over time. Results The dysbiosis index was increased in dogs with CE (median, 2.5; range, −6.2 to 6.5) at baseline compared with healthy dogs (median, −4.5; range, −6.5 to −2.6; P = .002) but did not change in dogs with CE over time. Secondary fUBA were decreased in dogs with CE (median, 29%; range, 1%-99%) compared with healthy dogs (median, 88%; 4%-96%; P = .049). The percent of secondary fUBA in dogs with CE increased from baseline values (median, 28%; range, 1%-99%) after 2-3 months of treatment (median, 94%; range, 1%-99%; P = 0.0183). Conclusions and Clinical Importance These findings suggest that corticosteroids regulate fecal bile acids in dogs with CE. Additionally, resolution of clinical activity index in dogs with therapeutically managed CE and bile acid dysmetabolism are likely correlated. However, subclinical disease (i.e., microbial dysbiosis) can persist in dogs with steroid-responsive CE.

Limited information is available describing the development of the neonatal fecal microbiome in dogs. Feces from puppies were collected at 2, 21, 42, and 56 days after birth. Feces were also collected from the puppies’ mothers at a single time point within 24 hours after parturition. DNA was extracted from fecal samples and 454-pyrosequencing was used to profile 16S rRNA genes. Species richness continued to increase significantly from 2 days of age until 42 days of age in puppies. Furthermore, microbial communities clustered separately from each other at 2, 21, and 42 days of age. The microbial communities belonging to dams clustered separately from that of puppies at any given time point. Major phylogenetic changes were noted at all taxonomic levels with the most profound changes being a shift from primarily Firmicutes in puppies at 2 days of age to a co-dominance of Bacteroidetes, Fusobacteria, and Firmicutes by 21 days of age. Further studies are needed to elucidate the relationship between puppy microbiota development, physiological growth, neonatal survival, and morbidity.

Chronic hepatic disease can present a diagnostic challenge with different etiologies being associated with similar clinical and laboratory findings. The histopathological assessment of a liver biopsy specimen is usually required in order to make a definitive diagnosis and the availability of non-invasive prognostic biomarkers is limited. The emerging science of metabolomics is used to detect changes in endogenous low molecular weight metabolites in biological samples and offers the possibility of identifying noninvasive markers of disease. The objective of this study was to investigate differences in the urine metabolome between healthy dogs, dogs with chronic hepatitis, dogs with hepatocellular carcinoma, and dogs with a congenital portosystemic shunt. Stored urine samples from 10 healthy dogs, 10 dogs with chronic hepatitis, 6 dogs with hepatocellular carcinoma, and 5 dogs with a congenital portosystemic shunt were analyzed. The urine metabolome was analyzed by gas chromatography-quadrupole time of flight mass spectrometry and 220 known metabolites were identified. Principal component analysis and heat dendrogram plots of the metabolomics data showed clustering between groups. Random forest analysis showed differences in the abundance of various metabolites including putrescine, gluconic acid, sorbitol, and valine. Based on univariate statistics, 37 metabolites were significantly different between groups. In, conclusion, the urine metabolome varies between healthy dogs, dogs with chronic hepatitis, dogs with hepatocellular carcinoma, and dogs with a congenital portosystemic shunt. Further targeted assessment of these metabolites is needed to assess their diagnostic utility.

The long-term impact of treatment of dogs with steroid-responsive enteropathy (SRE) on the fecal microbiome and metabolome has not been investigated. Therefore, this study aimed to evaluate the fecal microbiome and metabolome of dogs with SRE before, during, and following treatment with standard immunosuppressive therapy and an elimination diet. We retrospectively selected samples from 9 dogs with SRE enrolled in a previous clinical trial, which received treatment for 8 weeks, and had achieved remission as indicated by the post-treatment clinical scores. Long-term (1 year) samples were obtained from a subset (5/9) of dogs. Samples from 13 healthy dogs were included as controls (HC). We evaluated the microbiome using 16S rRNA sequencing and qPCR. To evaluate the recovery of gut function, we measured fecal metabolites using an untargeted approach. While improvement was observed for some bacterial taxa after 8 weeks of treatment, several bacterial taxa remained significantly different from HC. Seventy-five metabolites were altered in dogs with SRE, including increased fecal amino acids and vitamins, suggesting malabsorption as a component of SRE. One year after treatment, however, all bacterial species were evaluated by qPCR and 16S rRNA gene sequencing, and all but thirteen metabolites were no longer different from healthy controls.

Diabetes mellitus (DM) in humans has recently been associated with altered intestinal microbiota. The consequences of intestinal dysbiosis, such as increased intestinal permeability and altered microbial metabolites, are suspected to contribute to the host inflammatory state and peripheral insulin resistance. Human diabetics have been shown to have changes in bile acid (BA) metabolism which may be detrimental to glycemic control. The purpose of this study was to examine BA metabolism in dogs with naturally-occurring, insulin-dependent DM and to relate these findings to changes in the intestinal microbiota. A prospective observational study of adult dogs with a clinical diagnosis of DM ( = 10) and healthy controls (HC, = 10) was performed. The fecal microbiota were analyzed by 16S rRNA gene next-generation (Illumina) sequencing. Concentrations of fecal unconjugated BA (fUBA) were measured using gas chromatography and mass spectrometry. Analysis of bacterial communities showed no significant difference for any of the alpha-diversity measures between DM vs. HC dogs. Principal coordinate analysis based on unweighted Unifrac distance metric failed to show significant clustering between dog groups (ANOSIM : = 0.084; = 0.114). However, linear discriminate analysis effects size (LEfSe) detected differentially abundant bacterial taxa (α = 0.01, LDA score >2.0) on various phylogenetic levels. While was overrepresented in dogs with DM, the proportions of Erysipelotrichia, , and were increased in HC dogs. Dogs with DM had increased concentration of total primary fUBA compared to HC dogs ( = 0.028). The concentrations of cholic acid and the cholic acid percentage of the total fUBA were increased ( = 0.028 and = 0.035, respectively) in the feces of DM dogs relative to HC dogs. The levels of lithocholic acid (both absolute value and percentage of the total fUBA) were decreased ( = 0.043 and < 0.01, respectively) in DM dogs vs. HC dogs. Results indicate that dogs with DM have both intestinal dysbiosis and associated fUBA alterations. The pattern of dysbiosis and altered BA composition is similar to that seen in humans with Type 2 DM. The dog represents a novel large animal model for advancing translational medicine research efforts (e.g., investigating pathogenesis and therapeutics) in DM affecting humans.