Intestinal Microbiota of Dogs and Cats: A Bigger World than We Thought

Department of Small Animal Clinical Sciences, Gastrointestinal Laboratory, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX 77843‑4474, USA.
Veterinary Clinics of North America Small Animal Practice (Impact Factor: 0.82). 03/2011; 41(2):261-72. DOI: 10.1016/j.cvsm.2010.12.006
Source: PubMed


Gut microbes play a crucial role in the regulation of host health, but the true complexity of the gastrointestinal microbiota has been underestimated using traditional culture techniques. Recent molecular-phylogenetic and metagenomic studies have revealed a highly diverse microbial community in the canine and feline gastrointestinal tract of healthy animals, consisting of bacteria, archaea, fungi, protozoa, and viruses. Alterations in microbial communities have also been reported in dogs and cats with chronic enteropathies, notably increases in Proteobacteria and depletions of Firmicutes. This review summarizes the current information about the intestinal microbial ecosystem in dogs and cats.

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Available from: Jan S Suchodolski,
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    • "Nevertheless, multiple 3% OTUs can be assigned to a single genus and thus still contain unexplained diversity. Differences in bacterial communities between species, however, are manifested on a bacterial species or strain level (Suchodolski, 2011) and are therefore not detectable with the conventional OTU approach. "
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    ABSTRACT: Recent gut microbiome studies in model organisms emphasize the effects of intrinsic and extrinsic factors on the variation of the bacterial composition and its impact on the overall health status of the host. Species occurring in the same habitat might share a similar microbiome, especially if they overlap in ecological and behavioral traits. So far, the natural variation in microbiomes of free-ranging wildlife species has not been thoroughly investigated. The few existing studies exploring microbiomes through 16S rRNA gene reads clustered sequencing reads into operational taxonomic units (OTUs) based on a similarity threshold (e.g., 97%). This approach, in combination with the low resolution of target databases, generally limits the level of taxonomic assignments to the genus level. However, distinguishing natural variation of microbiomes in healthy individuals from "abnormal" microbial compositions that affect host health requires knowledge of the "normal" microbial flora at a high taxonomic resolution. This gap can now be addressed using the recently published oligotyping approach, which can resolve closely related organisms into distinct oligotypes by utilizing subtle nucleotide variation. Here, we used Illumina MiSeq to sequence amplicons generated from the V4 region of the 16S rRNA gene to investigate the gut microbiome of two free-ranging sympatric Namibian carnivore species, the cheetah (Acinonyx jubatus) and the black-backed jackal (Canis mesomelas). Bacterial phyla with proportions >0.2% were identical for both species and included Firmicutes, Fusobacteria, Bacteroidetes, Proteobacteria and Actinobacteria. At a finer taxonomic resolution, black-backed jackals exhibited 69 bacterial taxa with proportions ≥0.1%, whereas cheetahs had only 42. Finally, oligotyping revealed that shared bacterial taxa consisted of distinct oligotype profiles. Thus, in contrast to 3% OTUs, oligotyping can detect fine-scale taxonomic differences between microbiomes.
    Frontiers in Microbiology 10/2014; 5(526):1-12. DOI:10.3389/fmicb.2014.00526 · 3.99 Impact Factor
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    • "Importantly, failure to identify compositional differences of faecal microbiota between diabetic and non-diabetic cats does not exclude the possibility of functional differences of the microbiota in affected individuals. Host metabolic effects may not be entirely predictable by a particular microbiota composition, as there is a large functional overlap in metabolic roles of bacteria within the gastrointestinal tract [38]. A metagenomic analysis of faecal microbiota in people with type 2 diabetes demonstrated that the disease was associated with marked functional alterations of the microbiota but only moderate compositional change [39]. "
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    ABSTRACT: Microorganisms within the gastrointestinal tract significantly influence metabolic processes within their mammalian host, and recently several groups have sought to characterise the gastrointestinal microbiota of individuals affected by metabolic disease. Differences in the composition of the gastrointestinal microbiota have been reported in mouse models of type 2 diabetes mellitus, as well as in human patients. Diabetes mellitus in cats has many similarities to type 2 diabetes in humans. No studies of the gastrointestinal microbiota of diabetic cats have been previously published. The objectives of this study were to compare the composition of the faecal microbiota of diabetic and non-diabetic cats, and secondarily to determine if host signalment and dietary factors influence the composition of the faecal microbiota in cats. Faecal samples were collected from insulin-treated diabetic and non-diabetic cats, and Illumina sequencing of the 16S rRNA gene and quantitative PCR were performed on each sample. ANOSIM based on the unweighted UniFrac distance metric identified no difference in the composition of the faecal microbiota between diabetic and non-diabetic cats, and no significant differences in the proportions of dominant bacteria by phylum, class, order, family or genus as determined by 16S rRNA gene sequencing were identified between diabetic and non-diabetic cats. qPCR identified a decrease in Faecalibacterium spp. in cats aged over ten years. Cat breed or gender, dietary carbohydrate, protein or fat content, and dietary formulation (wet versus dry food) did not affect the composition of the faecal microbiota. In conclusion, the composition of the faecal microbiota was not altered by the presence of diabetes mellitus in cats. Additional studies that compare the functional products of the microbiota in diabetic and non-diabetic cats are warranted to further investigate the potential impact of the gastrointestinal microbiota on metabolic diseases such as diabetes mellitus in cats.
    PLoS ONE 10/2014; 9(10):e108729. DOI:10.1371/journal.pone.0108729 · 3.23 Impact Factor

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