Faecal microbiota of cats with insulin-treated diabetes mellitus

Association between Gut Microbiota and Metabolic Health and Obesity Status in Cats

Obesity is a major public health concern in both humans and animals, leading to several metabolic complications. Recent human studies have classified obesity into two phenotypes, metabolically healthy (MHO) and metabolically unhealthy (MUO) obesity based on cardiovascular and metabolic risk factors. MHO cases lack these risk factors and are protected from metabolic complications of obesity, whereas MUO cases exhibit the opposite characteristics. Moreover, recent studies have highlighted the possible role of the gut microbiome in determining metabolic health of obese individuals. However, studies on the association between the gut microbiome and obesity and metabolic abnormalities in cats are limited. Therefore, we aimed to examine the association between metabolic health phenotypes and gut microbiota composition and diversity in obese cats. We investigated hormone and serum biochemistry parameters and composition of the gut microbiota in non-obese (NO), MHO, and MUO groups. The abundances of Bifidobacteriaceae, Coriobacteriaceae, and Veillonellaceae were significantly higher in the obese versus NO group, showing a positive correlation with body mass index. The abundance of Ruminococcaceae was significantly higher in the MUO versus NO group, showing a positive correlation with triglyceride and total cholesterol levels. However, obesity, whether MHO or MUO, had only a minimal impact on fecal microbiota. Therefore, further studies are warranted to investigate whether gut microbiota could be a beneficial tool for the treatment or management of this condition.

Fecal identification markers impact the feline fecal microbiota

Fecal diagnostics are a mainstay of feline medicine, and fecal identification markers help to distinguish individuals in a multi-cat environment. However, the impact of identification markers on the fecal microbiota are unknown. Given the increased interest in using microbiota endpoints to inform diagnosis and treatment, the objective of this study was to examine the effects of orally supplemented glitter and crayon shavings on the feline fecal microbiota (amplicon sequencing of 16S rRNA gene V4 region). Fecal samples were collected daily from six adult cats that were randomized to receive oral supplementation with either glitter or crayon for two weeks, with a two-week washout before receiving the second marker. No adverse effects in response to marker supplementation were seen for any cat, and both markers were readily identifiable in the feces. Microbiota analysis revealed idiosyncratic responses to fecal markers, where changes in community structure in response to glitter or crayon could not be readily discerned. Given these findings, it is not recommended to administered glitter or crayon shavings as a fecal marker when microbiome endpoints are used, however their clinical use with other diagnostics should still be considered.

Effects of antimicrobials on the gastrointestinal microbiota of dogs and cats

Among several environmental factors, exposure to antimicrobials has been in the spotlight as a cause of profound and long-term disturbance of the intestinal microbiota. Antimicrobial-induced dysbiosis is a general term and includes decreases in microbial richness and diversity, loss of beneficial bacterial groups, blooms of intestinal pathogens and alterations in the metabolic functions and end-products of the microbiota. Mounting evidence from human and experimental animal studies suggest an association between antimicrobial-induced dysbiosis and susceptibility to gastrointestinal, metabolic, endocrine, immune and neuropsychiatric diseases. These associations are commonly stronger after early life exposure to antimicrobials, a period during which maturation of the microbiota and immune system take place in parallel. In addition, these associations commonly become stronger as the number of antimicrobial courses increases. The repeatability of these findings among different studies as well as the presence of a dose-dependent relationship between antimicrobial exposure and disease development collectively require careful consideration of the need for antimicrobial use. There are limited studies are available in dogs and cats regarding the long-term effects of antimicrobials on the microbiota and subsequent susceptibility to diseases. This review discusses the effects of antimicrobials on the gastrointestinal microbiota and the most important associations between antimicrobial-induced dysbiosis and diseases in humans, dogs, and cats.

Effect of a novel animal milk oligosaccharide biosimilar on macronutrient digestibility and gastrointestinal tolerance, fecal metabolites, and fecal microbiota of healthy adult cats

GNU100 is a novel animal milk oligosaccharide (AMO) biosimilar. In a recent in vitro fermentation study, GNU100 was shown to be fermentable by feline gastrointestinal microbiota and lead to increased short-chain fatty acid production. Our objectives herein were to evaluate the palatability, safety, and gastrointestinal tolerance of GNU100 in healthy adult cats. Exploratory end-points were measured to assess utility. In study 1, 20 adult cats were used to test the palatability of diets containing 0% or 1% GNU100. In study 2, 32 (mean age = 1.9 yr; mean body weight = 4.6 kg) male (n = 12) and female (n = 20) adult cats were used in a completely randomized design. After a 2-wk baseline, cats were assigned to one of the following treatment groups and fed for 26 wk: control (CT, no GNU100), low dose (LD, 0.5% GNU100), medium dose (MD, 1.0% GNU100), and high dose (HD, 1.5% GNU100). On weeks 2, 4, and 26, fresh fecal samples were collected for the measurement of stool quality and immune and inflammatory markers and on weeks 2 and 4 for microbiota and metabolites. On week 4, total feces were collected to measure apparent total tract macronutrient digestibility. On weeks 2, 4, and 26, blood samples were collected for serum chemistry, hematology, and inflammatory marker measurement. The palatability test showed that 1% GNU100 was strongly preferred (P < 0.05), with GNU100 having a 17.6:1 consumption ratio compared with control. In the long-term study, all cats remained healthy, without any signs of gastrointestinal intolerance or illness. All diets were well accepted, resulting in similar (P > 0.05) food intake, fecal characteristics, immunoglobulin A, and calprotectin, and dry matter, organic matter, fat, and crude protein digestibilities. Fecal butyrate was greater (P = 0.02) in cats fed HD than cats fed LD or MD. Fecal indole was lower (P = 0.02) in cats fed HD than cats fed LD. Cats fed CT had a higher (P = 0.003) relative abundance of Actinobacteria than cats fed LD. The relative abundance of Peptococcus was impacted by diet and time. At 4 wk, Campylobacter was lower in fecal samples of cats fed HD. Overall, the data suggest that dietary GNU100 supplementation was highly palatable, well tolerated, did not cause detrimental effects on fecal quality or nutrient digestibility, increased fecal butyrate concentrations, and reduced fecal indole concentrations, supporting the safety of GNU100 for inclusion in feline diets and suggesting potential benefits on gastrointestinal health of cats.

Pet-Human Gut Microbiome Host Classifier Using Data from Different Studies

(1) Background: microbiome host classification can be used to identify sources of contamination in environmental data. However, there is no ready-to-use host classifier. Here, we aimed to build a model that would be able to discriminate between pet and human microbiomes samples. The challenge of the study was to build a classifier using data solely from publicly available studies that normally contain sequencing data for only one type of host. (2) Results: we have developed a random forest model that distinguishes human microbiota from domestic pet microbiota (cats and dogs) with 97% accuracy. In order to prevent overfitting, samples from several (at least four) different projects were necessary. Feature importance analysis revealed that the model relied on several taxa known to be key components in domestic cat and dog microbiomes (such as Fusobacteriaceae and Peptostreptococcaeae), as well as on some taxa exclusively found in humans (as Akkermansiaceae). (3) Conclusion: we have shown that it is possible to make a reliable pet/human gut microbiome classifier on the basis of the data collected from different studies.

The gut microbiome in dogs with congestive heart failure: a pilot study

Compromised gut health and dysbiosis in people with heart failure has received a great deal of attention over the last decade. Whether dogs with heart failure have a similar dysbiosis pattern to what is described in people is currently unknown. We hypothesised that dogs with congestive heart failure have quantifiable dysbiosis compared to healthy dogs that are similar in sex and age. A total of 50 dogs (15 healthy dogs and 35 dogs with congestive heart failure) were prospectively recruited, and their faecal gut microbiome was assessed using 16S rRNA sequencing (Illumina MiSeq platform). There was no significant change in the microbial diversity and richness in dogs with congestive heart failure. However, there was an increase in abundance of Proteobacteria in the congestive heart failure group (p = 0.014), particularly due to an increase in the family Enterobacteriaceae (p = 0.002) and Escherichia coli (p = 0.033). We conclude that dogs with congestive heart failure have dysbiosis, and we show additional trends in our data suggesting that dogs may have a similar pattern to that described in people. The results of this study provide useful preliminary information and raise the possibility that dogs represent a clinically relevant animal model of dysbiosis in people with heart failure.

Past, Present, and Future of Gastrointestinal Microbiota Research in Cats

The relationship between microbial community and host has profound effects on the health of animals. A balanced gastrointestinal (GI) microbial population provides nutritional and metabolic benefits to its host, regulates the immune system and various signaling molecules, protects the intestine from pathogen invasion, and promotes a healthy intestinal structure and an optimal intestinal function. With the fast development of next-generation sequencing, molecular techniques have become standard tools for microbiota research, having been used to demonstrate the complex intestinal ecosystem. Similarly to other mammals, the vast majority of GI microbiota in cats (over 99%) is composed of the predominant bacterial phyla Firmicutes, Bacteroidetes, Actinobacteria, and Proteobacteria. Many nutritional and clinical studies have shown that cats' microbiota can be affected by several different factors including body condition, age, diet, and inflammatory diseases. All these factors have different size effects, and some of these may be very minor, and it is currently unknown how important these are. Further research is needed to determine the functional variations in the microbiome in disease states and in response to environmental and/or dietary modulations. Additionally, further studies are also needed to explain the intricate relationship between GI microbiota and the genetics and immunity of its host. This review summarizes past and present knowledge of the feline GI microbiota and looks into the future possibilities and challenges of the field.

Characterization of gut microbiomes of household pets in the United States using a direct-to-consumer approach

The role of gut microbiomes as important regulators of mammalian health is increasingly recognized, although feline and canine gut microbiomes remain poorly characterized. In this proof-of-concept study, we assessed the utility of a direct-to-consumer approach to executing pet microbiome studies. We characterized the gut microbiomes of 238 pets (46 cats and 192 dogs) by generating ~11 million merged reads that were mapped to the V4 region of 16S ribosomal RNA gene at a sequencing depth of 45,806 (±22,325) reads per sample. Analyses of these reads revealed that both feline and canine gut microbiomes are dominated by three major phyla, namely Firmicutes, Proteobacteria, and Bacteroides and that alpha diversity is higher in the feline gut. In addition to interspecies differences between the feline and canine gut, we also detected appreciable intraspecies bacterial variation within the canine population. While the dogs in this dataset could be assigned to three distinct clusters based on their gut microbiome, no clustering was observed within the feline population. Integration of additional data obtained from survey questionnaires revealed that geography and body weight may be associated with canine gut microbiome composition. Furthermore, we found that both the inter and intraspecies differences are more pronounced at finer taxonomic levels, indicating that strain-level investigations may be necessary in the future. This study demonstrates that the direct-to-consumer approach overcomes existing limitations in pet microbiome research, for example, it allows collection of large numbers of pet samples. The direct-to-consumer approach has proven successful in human genomics as well as human microbiomics and this study demonstrates that by building partnerships with an engaged general public this approach can also propel the field of pet microbiomics forward.

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.

Diabetic cats have decreased gut microbial diversity and a lack of butyrate producing bacteria

Obesity and inactivity are major risk factors of feline diabetes mellitus (FDM) and human type II diabetes mellitus (T2DM). In recent years, changes in the gut microbiota have been suggested as a contributing factor to T2DM. Whether the gut microbiota (GM) composition plays a role in FDM remains unknown. The aim of the current study was firstly a cross-sectional comparison of the GM of diabetic cats, to that of lean, and of obese/overweight non-diabetic cats of a similar age. Specifically, fecal samples from 82 privately-owned cats from Denmark and Switzerland were sequenced using 16S rRNA gene amplicon metabarcoding. Secondly dietary intervention data was generated, by obtaining additional samples from a subset of cats after placing them on a high-protein diet for four weeks. The GM diversity of diabetic cats was lower than that of lean cats in the cross-sectional study, and lower compared to lean and to overweight/obese cats after diet intervention. Diabetic cats also exhibited fewer Anaerotruncus, Dialister, and unknown Ruminococcaceae than lean cats. Serum fructosamine levels correlated negatively with Prevotellaceae abundance and positively with Enterobacteriaceae abundance. In summary the intestinal microbiota of diabetic cats was characterized by decreased GM diversity and loss of butyrate producing bacterial genera.

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.

The fecal microbiome and serum concentrations of indoxyl sulfate and p-cresol sulfate in cats with chronic kidney disease

Background

Intestinal dysbiosis has been documented in humans with chronic kidney disease (CKD) and is thought to contribute to production of the uremic toxins indoxyl sulfate (IS) and p‐cresol sulfate (pCS). Characteristics of the fecal microbiome in cats with CKD and correlation to serum concentrations of uremic toxins are unknown.

Objectives

To characterize the fecal microbiome and measure serum IS and pCS concentrations of cats with CKD in comparison to healthy older cats.

Animals

Thirty client‐owned cats with CKD (International Renal Interest Society stages 2‐4) and 11 older (≥8 years) healthy control cats.

Methods

Prospective, cross‐sectional study. Fecal samples were analyzed by sequencing of 16S rRNA genes and Escherichia coli quantitative PCR (qPCR). Serum concentrations of IS and pCS measured using liquid chromatography tandem mass spectrometry.

Results

Cats with CKD had significantly decreased fecal bacterial diversity and richness. Escherichia coli qPCR showed no significant difference in bacteria count between control and CKD cats. Cats with stage 2 (P = .01) and stages 3 and 4 (P = .0006) CKD had significantly higher serum IS concentrations compared to control cats. No significant difference found between stage 2 and stages 3 and 4 CKD. The pCS concentrations were not significantly different between CKD cats and control cats.

Conclusions and Clinical Importance

Decreased fecal microbiome diversity and richness is associated with CKD in cats. Indoxyl sulfate concentration is significantly increased with CKD, and cats with stage 2 CKD may suffer from a similar uremic toxin burden as do cats with later stage disease.

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.

The Fecal Microbiota in the Domestic Cat (Felis catus) Is Influenced by Interactions Between Age and Diet; A Five Year Longitudinal Study

In humans, aging is associated with changes in the gastrointestinal microbiota; these changes may contribute to the age-related increase in incidence of many chronic diseases, including Type 2 diabetes. The life expectancies of cats are increasing, and they are also exhibiting the same types of diseases. While there are some studies investigating the impacts of diets on gastrointestinal microbiota in young cats, the impacts of aging in older cats has not been explored. We followed a cohort of related kittens, maintained on two commercial diets (kibbled and canned) from weaning (8 weeks) to 5 years of age (260 weeks). We hypothesized that the long-term feeding of specific diet formats would (a) lead to microbial composition changes due to aging, (b) impact body composition, and (c) affect insulin sensitivity in the aging cat. We observed that both diet and age affected fecal microbial composition, and while age correlated with changes in body composition, diet had no effect on body composition. Similarly insulin sensitivity was not affected by age nor diet. 16S rRNA sequencing found unclassified Peptostreptococcaceae were prominent across all ages averaging 21.3% of gene sequence reads and were higher in cats fed canned diets (average of 25.7% of gene sequence reads, vs. 17.0% for kibble-fed cats). Age-related effects on body composition and insulin sensitivity may become apparent as the cats grow older; this study will continue to assess these parameters.

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.

Effect of dark sweet cherry powder consumption on the gut microbiota, short-chain fatty acids, and biomarkers of gut health in obese db/db mice

Cherries are fruits containing fiber and bioactive compounds (e.g., polyphenolics) with the potential of helping patients with diabetes and weight disorders, a phenomenon likely related to changes in the complex host-microbiota milieu. The objective of this study was to investigate the effect of cherry supplementation on the gut bacterial composition, concentrations of caecal short-chain fatty acids (SCFAs) and biomarkers of gut health using an in vivo model of obesity. Obese diabetic (db/db) mice received a supplemented diet with 10% cherry powder (supplemented mice, n = 12) for 12 weeks; obese (n = 10) and lean (n = 10) mice served as controls and received a standard diet without cherry. High-throughput sequencing of the 16S rRNA gene and quantitative real-time PCR (qPCR) were used to analyze the gut microbiota; SCFAs and biomarkers of gut health were also measured using standard techniques. According to 16S sequencing, supplemented mice harbored a distinct colonic microbiota characterized by a higher abundance of mucin-degraders (i.e., Akkermansia) and fiber-degraders (the S24-7 family) as well as lower abundances of Lactobacillus and Enterobacteriaceae. Overall this particular cherry-associated colonic microbiota did not resemble the microbiota in obese or lean controls based on the analysis of weighted and unweighted UniFrac distance metrics. qPCR confirmed some of the results observed in sequencing, thus supporting the notion that cherry supplementation can change the colonic microbiota. Moreover, the SCFAs detected in supplemented mice (caproate, methyl butyrate, propionate, acetate and valerate) exceeded those concentrations detected in obese and lean controls except for butyrate. Despite the changes in microbial composition and SCFAs, most of the assessed biomarkers of inflammation, oxidative stress, and intestinal health in colon tissues and mucosal cells were similar in all obese mice with and without supplementation. This paper shows that dietary supplementation with cherry powder for 12 weeks affects the microbiota and the concentrations of SCFAs in the lower intestinal tract of obese db/db diabetic mice. These effects occurred in absence of differences in most biomarkers of inflammation and other parameters of gut health. Our study prompts more research into the potential clinical implications of cherry consumption as a dietary supplement in diabetic and obese human patients.

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.

Microbiota modulation counteracts Alzheimer's disease progression influencing neuronal proteolysis and gut hormones plasma levels

Gut microbiota has a proven role in regulating multiple neuro-chemical pathways through the highly interconnected gut-brain axis. Oral bacteriotherapy thus has potential in the treatment of central nervous system-related pathologies, such as Alzheimer’s disease (AD). Current AD treatments aim to prevent onset, delay progression and ameliorate symptoms. In this work, 3xTg-AD mice in the early stage of AD were treated with SLAB51 probiotic formulation, thereby affecting the composition of gut microbiota and its metabolites. This influenced plasma concentration of inflammatory cytokines and key metabolic hormones considered therapeutic targets in neurodegeneration. Treated mice showed partial restoration of two impaired neuronal proteolytic pathways (the ubiquitin proteasome system and autophagy). Their cognitive decline was decreased compared with controls, due to a reduction in brain damage and reduced accumulation of amyloid beta aggregates. Collectively, our results clearly prove that modulation of the microbiota induces positive effects on neuronal pathways that are able to slow down the progression of Alzheimer’s disease.

Bacterial microbiome of the nose of healthy dogs and dogs with nasal disease

The role of bacterial communities in canine nasal disease has not been studied so far using next generation sequencing methods. Sequencing of bacterial 16S rRNA genes has revealed that the canine upper respiratory tract harbors a diverse microbial community; however, changes in the composition of nasal bacterial communities in dogs with nasal disease have not been described so far. Aim of the study was to characterize the nasal microbiome of healthy dogs and compare it to that of dogs with histologically confirmed nasal neoplasia and chronic rhinitis. Nasal swabs were collected from healthy dogs (n = 23), dogs with malignant nasal neoplasia (n = 16), and dogs with chronic rhinitis (n = 8). Bacterial DNA was extracted and sequencing of the bacterial 16S rRNA gene was performed. Data were analyzed using Quantitative Insights Into Microbial Ecology (QIIME). A total of 376 Operational Taxonomic Units out of 26 bacterial phyla were detected. In healthy dogs, Moraxella spp. was the most common species, followed by Phyllobacterium spp., Cardiobacteriaceae, and Staphylococcus spp. While Moraxella spp. were significantly decreased in diseased compared to healthy dogs (p = 0.005), Pasteurellaceae were significantly increased (p = 0.001). Analysis of similarities used on the unweighted UniFrac distance metric (p = 0.027) was significantly different when nasal microbial communities of healthy dogs were compared to those of dogs with nasal disease. The study showed that the canine nasal cavity is inhabited by a highly species-rich bacterial community, and suggests significant differences between the nasal microbiome of healthy dogs and dogs with nasal disease.

The Association of Specific Constituents of the Fecal Microbiota with Immune-Mediated Brain Disease in Dogs

Meningoencephalomyelitis of unknown origin (MUO) is a common, naturally-occurring, clinical disease of pet dogs. It is an immune-mediated condition that has many similarities with experimental autoimmune encephalitis (EAE) in rodents and so investigation of its pathogenesis may aid in understanding factors that contribute to development of multiple sclerosis in people. Gut microbiota are known to modulate immune responses that influence susceptibility to immune-mediated brain disease. In this study we aimed to compare abundance of specific constituents of the fecal microbiota, namely Faecalibacterium prausnitzii and Prevotellaceae, between dogs diagnosed with MUO and matched controls. Fecal samples were obtained from 20 dogs diagnosed with MUO and 20 control dogs matched for breed, age and gender. Bacterial abundance was measured using qPCR and 16S rRNA sequencing. We found that Prevotellaceae were significantly less abundant in cases compared with controls (p = 0.003) but there was no difference in abundance of F.prausnitzii. There was no evidence of other differences in gut microbiota between groups. These data, derived from this naturally-occurring canine clinical model, provide strong corroborative evidence that high abundance of Prevotellaceae in the gut is associated with reduced risk for developing immune-mediated brain disease.

Modulation of gut microbiota in rats fed high-fat diets by processing whole-grain barley to barley malt

SCOPE

The gut microbiota is linked with human health, and by manipulating its composition, health conditions might be improved. The aim of this study was to investigate whether two barley products, whole-grain barley and barley malt, caused differentiation of the cecal microbiota in rats fed high-fat diets and whether there were correlations with the short-chain fatty acids formed.

METHODS AND RESULTS

Male Wistar rats were given barley or malt (7-8 dietary fiber/100 g) for 4 weeks. Cellulose was used as a control, and the cecal microbiota was analyzed with next-generation sequencing of 16S rDNA. The barley group had higher abundances of Verrucomicrobia and Actinobacteria and lower abundances of Firmicutes and Deferribacteres than the control group; the alpha diversity was also lower. At the genus level, the barley group had higher abundances of Akkermansia, Ruminococcus, Blautia, and Bilophila. Turicibacter and Roseburia were more abundant in the malt group, and Parabacteroides, Dorea and rc4-4 were enriched in the control group. Most genera correlated with acetic and propionic acids, but Roseburia and Turicibacter instead correlated with butyric acid. Succinic acid correlated with Clostridium and Akkermansia.

CONCLUSION

Bioprocessing is a potential method to modulate the gut microbiota for enhanced effects on human health.

The fecal microbiome in cats with diarrhea

Recent studies have revealed that microbes play an important role in the pathogenesis of gastrointestinal (GI) diseases in various animal species, but only limited data is available about the microbiome in cats with GI disease. The aim of this study was to evaluate the fecal microbiome in cats with diarrhea. Fecal samples were obtained from healthy cats (n = 21) and cats with acute (n = 19) or chronic diarrhea (n = 29) and analyzed by sequencing of 16S rRNA genes, and PICRUSt was used to predict the functional gene content of the microbiome. Linear discriminant analysis (LDA) effect size (LEfSe) revealed significant differences in bacterial groups between healthy cats and cats with diarrhea. The order Burkholderiales, the families Enterobacteriaceae, and the genera Streptococcus and Collinsella were significantly increased in diarrheic cats. In contrast the order Campylobacterales, the family Bacteroidaceae, and the genera Megamonas, Helicobacter, and Roseburia were significantly increased in healthy cats. Phylum Bacteroidetes was significantly decreased in cats with chronic diarrhea (>21 days duration), while the class Erysipelotrichi and the genus Lactobacillus were significantly decreased in cats with acute diarrhea. The observed changes in bacterial groups were accompanied by significant differences in functional gene contents: metabolism of fatty acids, biosynthesis of glycosphingolipids, metabolism of biotin, metabolism of tryptophan, and ascorbate and aldarate metabolism, were all significantly (p<0.001) altered in cats with diarrhea. In conclusion, significant differences in the fecal microbiomes between healthy cats and cats with diarrhea were identified. This dysbiosis was accompanied by changes in bacterial functional gene categories. Future studies are warranted to evaluate if these microbial changes correlate with changes in fecal concentrations of microbial metabolites in cats with diarrhea for the identification of potential diagnostic or therapeutic targets.

Translational value of animal models of obesity-Focus on dogs and cats

A prolonged imbalance between a relative increase in energy intake over a decrease in energy expenditure results in the development of obesity; extended periods of a positive energy balance eventually lead to the accumulation of abnormally high amounts of fat in adipose tissue but also in other organs. Obesity is considered a clinical state of impaired general heath in which the excessive increase in adipose tissue mass may be associated with metabolic disorders such as type 2 diabetes mellitus, hyperlipidemia, hypertension and cardiovascular diseases. This review discusses briefly the use of animal models for the study of obesity and its comorbidities. Generally, most studies are performed with rodents, such as diet induced obesity and genetic models. Here, we focus specifically on two different species, namely dogs and cats. Obese dogs and cats show many features of human obesity. Interestingly, however, dogs and cats differ from each other in certain aspects because even though obese dogs may become insulin resistant, this does not result in the development of diabetes mellitus. In fact, diabetes in dogs is typically not associated with obesity because dogs present a type 1 diabetes-like syndrome. On the other hand, obese cats often develop diabetes mellitus which shares many features with human type 2 diabetes; feline and human diabetes are similar in respect to their pathophysiology, underlying risk factors and treatment strategies. Our review discusses genetic and endocrine factors in obesity, discusses obesity induced changes in lipid metabolism and includes some recent findings on the role of gut microbiota in obesity. Compared to research in rodent models, the array of available techniques and tools is unfortunately still rather limited in dogs and cats. Hence, even though physiological and pathophysiological phenomena are well described in dogs and cats, the underlying mechanisms are often not known and studies investigating causality specifically are scarce.