A dysbiosis index to assess microbial changes in fecal samples of dogs with chronic inflammatory enteropathy

Fecal short-chain fatty acid concentrations and dysbiosis in dogs with chronic enteropathy

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.

Methods and basic concepts for microbiota assessment

There has been a marked increase in interest regarding complex microbial populations in recent years. The methodology used for microbial assessment has drastically changed over the last two decades and continues to advance at a rapid pace. Culture-based studies have been superseded by those based upon molecular methods, which have been largely used to discover new species and to better characterize complex communities, mainly driven by the advances in DNA sequencing, termed 'next generation sequencing'. These methodologies have allowed for a better understanding of the relationship between hosts and their microbiotas, which have important roles in health maintenance and in the pathophysiology of wide ranging conditions such as obesity, diabetes, allergic diseases and even behavioural changes. While most widely used in humans, these approaches are now commonly used in veterinary research, with increasing interest in direct clinical applications. As these methods provide novel insights that will constitute the basis for the development of new therapeutic and prevention strategies, and as commercial efforts to offer microbiota assessment as a clinical tool expand, it is essential for researchers and clinical veterinarians to understand and have the tools to be able to interpret research performed in this new fascinating field. The objective of this review is to describe some of the most common methods for characterization of microbial communities and to provide an overview of the basic concepts necessary for good interpretation of the research performed in this field.

Longitudinal assessment of microbial dysbiosis, fecal unconjugated bile acid concentrations, and disease activity in dogs with steroid-responsive chronic inflammatory enteropathy

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.

Effects of a synbiotic on the fecal microbiome and metabolomic profiles of healthy research cats administered clindamycin: a randomized, controlled trial

Reduction in antibiotic-associated gastrointestinal signs (AAGS) in people co-administered probiotics is believed to result from shifts in the microbiome and metabolome. Amelioration of AAGS in cats secondary to synbiotic administration has recently been demonstrated. Thus, the aim of this randomized, double-blinded, placebo-controlled trial was to characterize associated changes in the fecal microbiome and metabolome. Sixteen healthy research cats received clindamycin with food, followed 1 h later by either a placebo or synbiotic, daily for 21 days. Fecal samples were collected during baseline, antibiotic administration, and 6 weeks after antibiotic discontinuation. Sequencing of 16S rRNA genes was performed, and mass spectrometry was used to determine fecal metabolomic profiles. Results were compared using mixed-model analyses, with P < 0.05 considered significant. Alpha and beta diversity were altered significantly during treatment, with persistent changes in the Shannon and dysbiosis indices. The relative abundance of Actinobacteria (Adlercreutzia, Bifidobacterium, Collinsella, Slackia), Bacteroidia (Bacteroides, Prevotella), Ruminococcaceae (Faecalibacterium, Ruminococcus), Veillonellaceae (Megamonas, Megasphaera, Phascolarctobacterium) and Erysipelotrichaceae ([Eubacterium]) decreased and relative abundance of Clostridiaceae (Clostridium) and Proteobacteria (Enterobacteriaceae) increased during treatment, followed by variable return to baseline relative abundances. Derangements in short-chain fatty acid (SCFA), bile acid, tryptophan, sphingolipid, polyamine, benzoic acid, and cinnaminic acid pathways occurred with significant group by time, group, and time interactions for 10, 5, and 106 metabolites, respectively. Of particular note were changes related to polyamine synthesis. Further investigation is warranted to elucidate the role of these alterations in prevention of AAGS in cats, people, and other animals treated with synbiotics.

Associations between the gut microbiota and host responses to high altitude

Hypobaric hypoxia and dietary protein and fat intakes have been independently associated with an altered gastrointestinal (GI) environment and gut microbiota, but little is known regarding host-gut microbiota interactions at high altitude (HA) and the impact of diet macronutrient composition. This study aimed to determine the effect of dietary protein:fat ratio manipulation on the gut microbiota and GI barrier function during weight loss at high altitude (HA) and to identify associations between the gut microbiota and host responses to HA. Following sea-level (SL) testing, 17 healthy males were transported to HA (4,300 m) and randomly assigned to consume provided standard protein (SP; 1.1 g·kg^-1·day^-1, 39% fat) or higher protein (HP; 2.1 g·kg^-1·day^-1, 23% fat) carbohydrate-matched hypocaloric diets for 22 days. Fecal microbiota composition and metabolites, GI barrier function, GI symptoms, and acute mountain sickness (AMS) severity were measured. Macronutrient intake did not impact fecal microbiota composition, had only transient effects on microbiota metabolites, and had no effect on increases in small intestinal permeability, GI symptoms, and inflammation observed at HA. AMS severity was also unaffected by diet but in exploratory analyses was associated with higher SL-relative abundance of Prevotella, a known driver of interindividual variability in human gut microbiota composition, and greater microbiota diversity after AMS onset. Findings suggest that the gut microbiota may contribute to variability in host responses to HA independent of the dietary protein:fat ratio but should be considered preliminary and hypothesis generating due to the small sample size and exploratory nature of analyses associating the fecal microbiota and host responses to HA. NEW & NOTEWORTHY This study is the first to examine interactions among diet, the gut microbiota, and host responses to weight loss at high altitude (HA). Observed associations among the gut microbiota, weight loss at HA, and acute mountain sickness provide evidence that the microbiota may contribute to variability in host responses to HA. In contrast, dietary protein:fat ratio had only minimal, transient effects on gut microbiota composition and bacterial metabolites which were likely not of clinical consequence.

Comparison of intestinal expression of the apical sodium-dependent bile acid transporter between dogs with and without chronic inflammatory enteropathy

BACKGROUND

Intestinal absorption of bile acids is mediated by the apical sodium-dependent bile acid transporter (ASBT). Fecal bile acid dysmetabolism has been reported in dogs with chronic inflammatory enteropathy (CIE).

OBJECTIVE

Characterization of ASBT distribution along the intestinal tract of control dogs and comparison to dogs with CIE.

ANIMALS

Twenty-four dogs with CIE and 11 control dogs.

METHODS

The ASBT mRNA and protein expression were assessed using RNA in situ hybridization and immunohistochemistry, respectively. The concentrations of fecal bile acids were measured by gas chromatography-mass spectrometry. The fecal microbiota dysbiosis index was assessed with a quantitative polymerase chain reaction panel.

RESULTS

In control dogs, ASBT mRNA expression was observed in enterocytes in all analyzed intestinal segments, with highest expression in the ileum. The ASBT protein expression was restricted to enterocytes in the ileum, cecum, and colon. Dogs with CIE had significantly decreased expression of ASBT protein in the ileum (P = .001), which was negatively correlated with histopathological score (ρ = -0.40; Pcorr = .049). Additionally, dogs with CIE had a significantly increased percentage of primary bile acids in feces compared to controls (P = .04). The fecal dysbiosis index was significantly higher in dogs with CIE than in control dogs (P = .01).

CONCLUSIONS AND CLINICAL IMPORTANCE

These findings indicate that ileal protein expression of ASBT is downregulated in dogs with CIE. This change may be linked to the inflammatory process, intestinal dysbiosis, and fecal bile acid dysmetabolism observed in these patients.

Effect of probiotic treatment on the clinical course, intestinal microbiome, and toxigenic Clostridium perfringens in dogs with acute hemorrhagic diarrhea

INTRODUCTION

The impact of probiotics on dogs with acute hemorrhagic diarrhea syndrome (AHDS) has not been evaluated so far. The study aim was to assess the effect of probiotic treatment on the clinical course, intestinal microbiome, and toxigenic Clostridium perfringens in dogs with AHDS in a prospective, placebo-controlled, blinded trial.

METHODS

Twenty-five dogs with AHDS with no signs of sepsis were randomly divided into a probiotic (PRO; Visbiome, ExeGi Pharma) and placebo group (PLAC). Treatment was administered for 21 days without antibiotics. Clinical signs were evaluated daily from day 0 to day 8. Key bacterial taxa, C. perfringens encoding NetF toxin and enterotoxin were assessed on days 0, 7, 21.

RESULTS

Both groups showed a rapid clinical improvement. In PRO a significant clinical recovery was observed on day 3 (p = 0.008), while in PLAC it was observed on day 4 (p = 0.002) compared to day 0. Abundance of Blautia (p<0.001) and Faecalibacterium (p = 0.035) was significantly higher in PRO on day 7 compared to day 0, while in PLAC the abundance of Faecalibacterium was not significantly higher on any study day and Blautia (p = 0.016) was only significantly higher on day 21 compared to day 0. Abundance of C. perfringens was significantly lower on day 7 (p = 0.011) compared to day 0 in PRO but not in PLAC. Enterotoxin genes were significantly lower in PRO on day 21 (p = 0.028) compared to PLAC. Fecal samples of 57% of all dogs were positive for netF toxin genes on day 0 and the abundance was significantly lower on day 7 compared to day 0 in PRO (p = 0.016) and PLAC (p = 0.031).

CONCLUSION

The probiotic treatment was associated with an accelerated normalization of the intestinal microbiome. Dogs with aseptic AHDS showed a rapid decrease of netF toxin genes and fast clinical recovery in both groups under symptomatic treatment without antibiotics.

Clinical utility of currently available biomarkers in inflammatory enteropathies of dogs

Chronic inflammatory enteropathies (CIE) in dogs are a group of disorders that are characterized by chronic persistent or recurrent signs of gastrointestinal disease and histologic evidence of mucosal inflammation. These CIEs are classified as either food-responsive, antibiotic-responsive, or immunosuppressant-responsive enteropathy. Patients not clinically responding to immunomodulatory treatment are grouped as nonresponsive enteropathy and dogs with intestinal protein loss as protein-losing enteropathy. Disease-independent clinical scoring systems were established in dogs for assessment of clinical disease severity and patient monitoring during treatment. Histopathologic and routine clinicopathologic findings are usually not able to distinguish the subgroups of CIE. Treatment trials are often lengthy and further diagnostic tests are usually at least minimally invasive. Biomarkers that can aid in defining the presence of disease, site of origin, severity of the disease process, response to treatment, or a combination of these would be clinically useful in dogs with CIE. This article summarizes the following biomarkers that have been evaluated in dogs with CIE during the last decade, and critically evaluates their potential clinical utility in dogs with CIE: functional biomarkers (cobalamin, methylmalonic acid, folate, α1 -proteinase inhibitor, immunoglobulin A), biochemical biomarkers (C-reactive protein, perinuclear anti-neutrophilic cytoplasmic antibodies, 3-bromotyrosine, N-methylhistamine, calprotectin, S100A12, soluble receptor of advanced glycation end products, cytokines and chemokines, alkaline phosphatase), microbiomic biomarkers (microbiome changes, dysbiosis index), metabolomic biomarkers (serum metabolome), genetic biomarkers (genomic markers, gene expression changes), and cellular biomarkers (regulatory T cells). In addition, important performance criteria of diagnostic tests are briefly reviewed.

The fecal microbiome and metabolome differs between dogs fed Bones and Raw Food (BARF) diets and dogs fed commercial diets

INTRODUCTION

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).

METHODS

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.

RESULTS

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.

CONCLUSION

Microbial communities and metabolome vary significantly between BARF and commercially fed dogs.

Effects of prebiotic inulin-type fructans on blood metabolite and hormone concentrations and faecal microbiota and metabolites in overweight dogs

Because obesity is associated with many co-morbidities, including diabetes mellitus, this study evaluated the second-meal effect of a commercial prebiotic, inulin-type fructans, and the effects of the prebiotic on faecal microbiota, metabolites and bile acids (BA). Nine overweight beagles were used in a replicated 3×3 Latin square design to test a non-prebiotic control (cellulose) against a low (equivalent to 0·5 % diet) and high dose (equivalent to 1·0 % diet) of prebiotic over 14-d treatments. All dogs were fed the same diet twice daily, with treatments provided orally via gelatin capsules before meals. On days 13 or 14 of each period, fresh faecal samples were collected, dogs were fed at 08.00 hours and then challenged with 1 g/kg body weight of maltodextrin in place of the 16.00 hours meal. Repeated blood samples were analysed for glucose and hormone concentrations to determine postprandial incremental AUC (IAUC) data. Baseline glucose, insulin and active glucagon-like peptide-1 levels were similar between all groups (P>0·10). Glucose and insulin IAUC after glucose challenge appeared lower following the high dose, but did not reach statistical relevance. Prebiotic intervention resulted in an increase in relative abundance of some Firmicutes and a decrease in the relative abundance of some Proteobacteria. Individual and total faecal SCFA were significantly increased (P<0·05) following prebiotic supplementation. Total concentration of excreted faecal BA tended to increase in dogs fed the prebiotic (P=0·06). Our results indicate that higher doses of inulin-type prebiotics may serve as modulators of gut microbiota, metabolites and BA pool in overweight dogs.

Short and long-term effects of a synbiotic on clinical signs, the fecal microbiome, and metabolomic profiles in healthy research cats receiving clindamycin: a randomized, controlled trial

Background

Antibiotic-associated gastrointestinal signs (AAGS) occur commonly in cats. Co-administration of synbiotics is associated with decreased AAGS in people, potentially due to stabilization of the fecal microbiome and metabolome. The purpose of this double-blinded randomized-controlled trial was to compare AAGS and the fecal microbiome and metabolome between healthy cats that received clindamycin with a placebo or synbiotic.

Methods

16 healthy domestic shorthair cats from a research colony were randomized to receive 150 mg clindamycin with either a placebo (eight cats) or commercially-available synbiotic (eight cats) once daily for 21 days with reevaluation 603 days thereafter. All cats ate the same diet. Food consumption, vomiting, and fecal score were recorded. Fecal samples were collected daily on the last three days of baseline (days 5–7), treatment (26–28), and recovery (631–633). Sequencing of 16S rRNA genes and gas chromatography time-of-flight mass spectrometry was performed. Clinical signs, alpha and beta diversity metrics, dysbiosis indices, proportions of bacteria groups, and metabolite profiles were compared between treatment groups using repeated measures ANOVAs. Fecal metabolite pathway analysis was performed. P < 0.05 was considered significant. The Benjamini & Hochberg’s False Discovery Rate was used to adjust for multiple comparisons.

Results

Median age was six and five years, respectively, for cats in the placebo and synbiotic groups. Hyporexia, vomiting, diarrhea, or some combination therein were induced in all cats. Though vomiting was less in cats receiving a synbiotic, the difference was not statistically significant. Bacterial diversity decreased significantly on days 26–28 in both treatment groups. Decreases in Actinobacteria (Bifidobacterium, Collinsella, Slackia), Bacteriodetes (Bacteroides), Lachnospiraceae (Blautia, Coprococcus, Roseburia), Ruminococcaceae (Faecilobacterium, Ruminococcus), and Erysipelotrichaceae (Bulleidia, [Eubacterium]) and increases in Clostridiaceae (Clostridium) and Proteobacteria (Aeromonadales, Enterobacteriaceae) occurred in both treatment groups, with incomplete normalization by days 631–633. Derangements in short-chain fatty acid, bile acid, indole, sphingolipid, benzoic acid, cinnaminic acid, and polyamine profiles also occurred, some of which persisted through the terminal sampling timepoint and differed between treatment groups.

Discussion

Cats administered clindamycin commonly develop AAGS, as well as short- and long-term dysbiosis and alterations in fecal metabolites. Despite a lack of differences in clinical signs between treatment groups, significant differences in their fecal metabolomic profiles were identified. Further investigation is warranted to determine whether antibiotic-induced dysbiosis is associated with an increased risk of future AAGS or metabolic diseases in cats and whether synbiotic administration ameliorates this risk.

Metagenomic insights into the roles of Proteobacteria in the gastrointestinal microbiomes of healthy dogs and cats

Interests in the impact of the gastrointestinal microbiota on health and wellbeing have extended from humans to that of companion animals. While relatively fewer studies to date have examined canine and feline gut microbiomes, analysis of the metagenomic DNA from fecal communities using next‐generation sequencing technologies have provided insights into the microbes that are present, their function, and potential to contribute to overall host nutrition and health. As carnivores, healthy dogs and cats possess fecal microbiomes that reflect the generally higher concentrations of protein and fat in their diets, relative to omnivores and herbivores. The phyla Firmicutes and Bacteroidetes are highly abundant, and Fusobacteria, Actinobacteria, and Proteobacteria also feature prominently. Proteobacteria is the most diverse bacterial phylum and commonly features in the fecal microbiota of healthy dogs and cats, although its reputation is often sullied as its members include a number of well‐known opportunistic pathogens, such as Escherichia coli, Salmonella, and Campylobacter, which may impact the health of the host and its owner. Furthermore, in other host species, high abundances of Proteobacteria have been associated with dysbiosis in hosts with metabolic or inflammatory disorders. In this review, we seek to gain further insight into the prevalence and roles of the Proteobacteria within the gastrointestinal microbiomes of healthy dogs and cats. We draw upon the growing number of metagenomic DNA sequence‐based studies which now allow us take a culture‐independent approach to examine the functions that this more minor, yet important, group contribute to normal microbiome function.

The fecal microbiomes of healthy dogs and cats often include Proteobacteria at varying abundances. This phylum can have a sullied reputation as it contains a number of well‐known pathogenic members. We explored the functions of the Proteobacteria in fecal shotgun metagenome datasets from healthy dogs and cats. The Proteobacteria appeared to be enriched for functions that are consistent with a role in helping to maintain the anaerobic environment of the gut for normal microbiome function.

When the Nose Doesn't Know: Canine Olfactory Function Associated With Health, Management, and Potential Links to Microbiota

The impact of health, management, and microbiota on olfactory function in canines has not been examined in review. The most important characteristic of the detection canine is its sense of smell. Olfactory receptors are primarily located on the ethmoturbinates of the nasal cavity. The vomeronasal organ is an additional site of odor detection that detects chemical signals that stimulate behavioral and/or physiological changes. Recent advances in the genetics of olfaction suggest that genetic changes, along with the unique anatomy and airflow of the canine nose, are responsible for the macrosmia of the species. Inflammation, alterations in blood flow and hydration, and systemic diseases alter olfaction and may impact working efficiency of detection canines. The scientific literature contains abundant information on the potential impact of pharmaceuticals on olfaction in humans, but only steroids, antibiotics, and anesthetic agents have been studied in the canine. Physical stressors including exercise, lack of conditioning, and high ambient temperature impact olfaction directly or indirectly in the canine. Dietary fat content, amount of food per meal, and timing of meals have been demonstrated to impact olfaction in mice and dogs. Gastrointestinal (GI) microbiota likely impacts olfaction via bidirectional communication between the GI tract and brain, and the microbiota is impacted by exercise, diet, and stress. The objective of this literature review is to discuss the specific effects of health, management, and microbiota shifts on olfactory performance in working canines.

Faecal microbiota in dogs with multicentric lymphoma

Malignant lymphoma B-cell type is the most common canine haematopoietic malignancy. Changes in intestinal microbiota have been implicated in few types of cancer in humans. The aim of this prospective and case-control study was to determine differences in faecal microbiota between healthy control dogs and dogs with multicentric lymphoma. Twelve dogs affected by multicentric, B-cell, stage III-IV lymphoma, and 21 healthy dogs were enrolled in the study. For each dog, faecal samples were analysed by Illumina sequencing of 16S rRNA genes and quantitative PCR (qPCR) for selected bacterial groups. Alpha diversity was significant lower in lymphoma dogs. Principal coordinate analysis plots showed different microbial clustering (P = .001) and linear discriminant analysis effect size revealed 28 differentially abundant bacterial groups in lymphoma and control dogs. The qPCR analysis showed significant lower abundance of Faecalibacterium spp. (q < .001), Fusobacterium spp. (q = .032), and Turicibacter spp. (q = .043) in dogs with lymphoma compared with control dogs. On the contrary, Streptococcus spp. was significantly higher in dogs with lymphoma (q = .041). The dysbiosis index was significantly higher (P < .0001) in dogs with lymphoma. In conclusion, both sequencing and qPCR analyses provided a global overview of faecal microbial communities and showed significant differences in the microbial communities of dogs presenting with multicentric lymphoma compared with healthy control dogs.