The gut microbiome contributes to host metabolism, protects against pathogens, educates the immune system, and, through these basic functions, affects directly or indirectly most physiologic functions of its host. Molecular techniques have allowed us to expand our knowledge by unveiling a wide range of unculturable bacteria that were previously unknown. Most bacterial sequences identified in the canine gastrointestinal (GI) tract fall into five phyla: Firmicutes, Fusobacteria, Bacteroidetes, Proteobacteria, and Actinobacteria. While there are variations in the microbiome composition along the GI tract, most clinical studies concentrate on fecal microbiota. Age, diet, and many other environmental factors may play a significant role in the maintenance of a healthy microbiome, however, the alterations they cause pale in comparison with the alterations found in diseased animals. GI dysfunctions are the most obvious association with gut dysbiosis. In dogs, intestinal inflammation, whether chronic or acute, is associated with significant differences in the composition of the intestinal microbiota. Gut dysbiosis happens when such alterations result in functional changes in the microbial transcriptome, proteome, or metabolome. Commonly affected metabolites include short-chain fatty acids, and amino acids, including tryptophan and its catabolites. A recently developed PCR-based algorithm termed “Dysbiosis Index” is a tool that allows veterinarians to quantify gut dysbiosis and can be used to monitor disease progression and response to treatment. Alterations or imbalances in the microbiota affect immune function, and strategies to manipulate the gut microbiome may be useful for GI related diseases. Antibiotic usage induces a rapid and significant drop in taxonomic richness, diversity, and evenness. For that reason, a renewed interest has been put on probiotics, prebiotics, and fecal microbiota transplantation (FMT). Although probiotics are typically unable to colonize the gut, the metabolites they produce during their transit through the GI tract can ameliorate clinical signs and modify microbiome composition. Another interesting development is FMT, which may be a promising tool to aid recovery from dysbiosis, but further studies are needed to evaluate its potential and limitations.

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.

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.

Feline chronic enteropathy (CE) is a common gastrointestinal disorder in cats and mainly comprises inflammatory bowel disease (IBD) and small cell lymphoma (SCL). Both IBD and SCL in cats share features with chronic enteropathies such as IBD and monomorphic epitheliotropic intestinal T-cell lymphoma in humans. The aim of this study was to characterize the fecal microbiome of 38 healthy cats and 27 cats with CE (13 cats with IBD and 14 cats with SCL). Alpha diversity indices were significantly decreased in cats with CE (OTU p = 0.003, Shannon Index p = 0.008, Phylogenetic Diversity p = 0.019). ANOSIM showed a significant difference in bacterial communities, albeit with a small effect size (P = 0.023, R = 0.073). Univariate analysis and LEfSE showed a lower abundance of facultative anaerobic taxa of the phylaFirmicutes(families Ruminococcaceae andTuricibacteraceae),Actinobacteria(genusBifidobacterium) andBacteroidetes(i.a.Bacteroides plebeius) in cats with CE. The facultative anaerobic taxaEnterobacteriaceaeandStreptococcaceaewere increased in cats with CE. No significant difference between the microbiome of cats with IBD and those with SCL was found. Cats with CE showed patterns of dysbiosis similar to those in found people with IBD.

Significance: Pathogenic mycobacteria can be transmitted by direct ejection from one host cell to another. However, the mechanism of ejection, and how lysing the host cell is prevented are unknown. This study explains how the host cell remains intact and alive while Mycobacterium marinum breaks through its plasma membrane during ejection. We show that a membraneous cup is specifically recruited to the distal pole of ejecting M. marinum . We demonstrate that these membranes are formed by the canonical autophagic pathway, though they do not mature to autophagolysosomes. Disruption of autophagy causes the host cells to become leaky and die during ejection. This dramatically reduces cell-to-cell transmission of the infection, demonstrating an important and unexpected role for autophagy in maintaining plasma membrane integrity during mycobacterial infection.

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.