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Archivos de medicina veterinaria

Print version ISSN 0301-732X

Arch. med. vet. vol.45 no.2 Valdivia  2013

http://dx.doi.org/10.4067/S0301-732X2013000200002 

REVIEW ARTICLE

 

Gastrointestinal microorganisms in cats and dogs: a brief review

Microorganismos gastrointestinales en gatos y perros: una revisión breve

 

JF Garcia-Mazcorroa*, Y Minamotob

a Facultad de Medicina Veterinaria y Zootecnia, Universidad Autónoma de Nuevo León, Nuevo León, México.
b
Gastrointestinal Laboratory, Department of Small Animal Clinical Sciences, Texas A&M University, Texas, USA.
* Francisco Villa s/n Col. Ex-Hacienda El Canadá C.P. 66050, Gral. Escobedo, Nuevo León, México; josegarcia_mex@hotmail.com.


RESUMEN

El tracto gastrointestinal (GI) de animales contiene diferentes tipos de microorganismos conocido como la microbiota GI. Por mucho tiempo, la microbiota GI ha generado interés porque los microorganismos GI están involucrados en múltiples procesos fisiológicos en el hospedero, así perpetuando salud o enfermedad. Estudios recientes han demostrado que la microbiota GI de gatos y perros es tan compleja como en humanos y otros animales, revelado con el uso de tecnologías de secuencia modernas y otras técnicas moleculares. La microbiota GI incluye miembros de todos los tres dominios principales de vida (Archaea, Bacterias y Eucariotas), pero las bacterias son el grupo de microorganismos más abundante y metabólicamente activo. El estómago de gatos y perros esta principalmente poblado de Helicobacter spp., el cual en perros puede representar tanto como el 98% de toda la microbiota bacteriana en el estómago. El intestino delgado contiene una microbiota más diversa, conteniendo representantes de al menos cinco diferentes filos bacterianos (principalmente Firmicutes y Bacteroidetes). El intestino grueso contiene el grupo de bacterias más abundante (~1011 células bacterianas por gramo de contenido intestinal), diverso (al menos diez diferentes filos han sido detectados) y metabólicamente relevante en el tracto GI. La mayoría de las bacterias en el intestino grueso son anaerobios estrictos, los cuales dependen de la fermentación de sustancias no digeridas para subsistir. Aunque estudios recientes han dilucidado las complejidades de la microbiota GI en gatos y perros, más investigación todavía es necesaria para encontrar maneras de manipular exitosamente los microorganismos GI para prevenir y/o tratar enfermedades GI.

Palabras clave: gastrointestinal, microbiota, gatos, perros.


SUMMARY

The gastrointestinal (GI) tract of animals contains different types of microorganisms known as the GI microbiota. The GI microbiota has long been of interest because of its involvement in multiple physiological processes in the host, influencing health or disease. Recent studies have shown that the GI microbiota of cats and dogs is as complex as the one present in humans and other animals, according to state-of-the-art sequencing technologies and other molecular techniques. The GI microbiota includes members of all three main life domains (Archaea, Bacteria, and Eukaryotes), with bacteria being the most abundant and metabolically active group of microorganisms. The stomach of cats and dogs is mainly inhabited by Helicobacter spp., which in dogs may account for as much as 98% of all gastric bacterial microbiota. The small intestine harbors a more diverse microbiota as it contains representatives from at least five bacterial phyla (mainly Firmicutes and Bacteroidetes). The large intestine harbors the most abundant (~1011 bacterial cells per gram of intestinal content), diverse (at least 10 bacterial phyla have been identified) and physiologically relevant group of bacteria in the GI tract. Most bacteria in the large intestine are strict anaerobes that depend on fermentation of non-digested dietary substances to subsist. Although recent studies are shedding light into the complexity of the GI microbiota in cats and dogs, further research is needed to find ways to successfully manipulate GI microorganisms to prevent and/or treat GI diseases.

Key words: gastrointestinal, microbiota, cats, dogs.


 

INTRODUCTION

The gastrointestinal (GI) tract of animals is colonised by a dense and heterogeneous group of microorganisms known as the GI microbiota, which supply more than nine million unique genes to the gene repertoire in the eukaryotic host (Yang et al 2009). The GI microbiota has long been of interest because of its involvement in multiple physiological processes in the host, including resistance against colonization by pathogens (Stecher and Hardt 2011), production of useful substances that act as energy source for intestinal epithelial cells (Louis and Flint 2009), modulation of the intestinal immune system (Hooper and Macpherson 2010), salvage of energy from undigested dietary components (Cummings and Macfarlane 1997), and stimulation of intestinal angiogenesis (Stappenbeck et al 2002).

Most of the current information about the composition and activity of the GI microbiota comes from studies in human populations. However, an increasing number of investigations have also studied intestinal microbes in other animals, especially cats and dogs (Suchodolski 2011). This review summarises current information about the GI microbiota with emphasis on the GI bacterial microbiota of cats and dogs.

THE GI MICROBIOTA

The GI tract of animals is one of the most complex microbial ecosystems on Earth, and it is continuously affected by factors associated with the host (Spor et al 2011, Van den Abbeele et al 2011) and the outside environment (Claesson et al 2012). This complexity has been an obstacle to study single independent factors associated with its changes over time and among different populations of animals (e.g., healthy and diseased). Also, it is often difficult to determine the nature of the interactions among the microorganisms during health or disease, although recent advances in mathematical modeling could help understand this phenomenon (Hellweger and Bucci 2009, Arciero et al 2010). Moreover, there are controversies with regards to the way we classify microbial species (Staley 2006, Schleifer 2009). Despite this complexity, there is a growing body of literature suggesting that the GI microbiota can be studied objectively, and that health could be enhanced in the host through manipulation of its constitutive intestinal microbial populations.

CHARACTERIZATION OF THE GI MICROBIOTA

CULTURE METHODS

The characterization of the GI microbiota is the first step in determining its role in health or disease. Classic culture methods have the advantages of being relatively inexpensive, widely available, and suitable for biochemical and physiological studies, and therefore have been extensively used to characterise the GI microbiota of cats and dogs (see below). However, the usefulness of culture techniques to characterise microorganisms in the gut and elsewhere has long been questioned because it is not representative enough regarding both enumeration and community structure (Ritz 2007). While experts generally agree that about 99% of all GI microorganisms have not been successfully cultured (Tap et al 2009), a recent article showed that about 70% of all fecal bacterial genera (as determined by pyrosequencing) could be successfully cultured using an in-house culture media containing a mixture of several commercially available ingredients (Goodman et al 2011). Modifications to this universal gut microbiota media will facilitate the culture of more intestinal microorganisms and make possible a correlation between microbial abundance and utilization of dietary substances.

MOLECULAR METHODS

In contrast to culture methods, which rely on the identification of GI microorganisms by means of a phenotypic characterization, molecular methodologies aim to identify and categorise microorganisms by means of detecting specific molecules inside the cells (e.g., DNA or RNA) (Zuckerkandl and Pauling 1965). The 16S rRNA gene has often been used to identify bacteria because it is universally distributed and appears to have undergone a relatively slow change in base pair composition throughout evolution (Fox et al 1980). In other words, the 16S rRNA gene contains conserved regions (same among all bacteria) as well as variable and highly variable regions that allow the distinction and classification of bacterial phylotypes, according to theories of molecular evolution (Lemey et al 2009). Some examples of methodological differences between culture-based and culture-independent approaches include survey depth (tens to hundreds of cultural isolates versus thousands to millions of 16S rRNA gene sequences), accuracy of bacterial 16S rRNA gene assignments, and documentation of the generated data (Goodman et al 2011). A summary of the most commonly used methods and techniques to study the gastrointestinal microbiota is presented in table 1.

 

Table 1. Summary of the most commonly used methods and techniques to study the gastrointestinal microbiota.
Resumen de los métodos y técnicas mas comúnmente usados para estudiar la microbiota gastrointestinal.
 

 

Polymerase chain reaction (PCR). PCR is a common and often indispensable molecular technique to characterize the GI microbiota. Currently, PCR is performed using a heat-stable DNA polymerase which can generate millions of copies of a given target sequence (e.g., a 16S rRNA gene fragment) in one hour or less. Some sequencing techniques require the use of PCR for generating amplicons (i.e., DNA fragments amplified by PCR). It is important to note that all PCR-based techniques suffer from several biases, including the fact that the generated 16S rRNA gene copies cannot be accurately extrapolated to the number of the microorganisms themselves, in part because different bacteria have different number of copies of this gene even within the same species (Acinas et al 2004, Lee et al 2008). Interestingly, these differences in the number of copies of the 16S rRNA gene may reflect ecological strategies of bacteria in respond to resource availability (Klappenbach et al 2000).

Fingerprinting methods. The obtained 16S rRNA gene amplicons (e.g., from intestinal contents) are often the same size in number of base pairs, and therefore would appear as a single band in an agarose or polyacrylamide gel. However, these amplicons are likely to differ from one another in their base pair composition. When exposed to a denaturing agent or to increasing temperatures, these differences in base pair composition make the amplicons migrate at a different speed throughout a gel matrix. Denaturing Gradient Gel Electrophoresis (DGGE) and Temperature Gradient Gel Electrophoresis (TGGE) are examples of molecular fingerprinting methods that separate amplicons based on this principle. In particular, DGGE has been shown to be useful to assess qualitative variations in the GI microbiota of dogs among different compartments of the intestinal tract (Suchodolski et al 2005). The result of DGGE or TGGE analysis is a specific banding pattern for every sample analysed, therefore providing a qualitative view of the microbial composition of the sample. However, fingerprinting techniques are not very useful to characterise microbial ecosystems because they often fail to accurately separate 16S rRNA gene fragments (Jackson et al 2000, Nikolausz et al 2005), thus underestimating the true bacterial diversity and its changes against external perturbations.

Quantitative real-time PCR (qPCR). In conventional PCR, the amplicons are routinely detected using electrophoresis on agarose gels after the PCR has finished. Because of this, traditional PCR is not capable of quantifying the genomic targets; it only provides information about the presence (band in the gel) or absence (no band in the gel) of the target. In contrast, PCR has been adapted to also allow the quantification of the unknown genomic targets as the PCR progresses (in real-time). This is possible by including in the PCR reaction a fluorescent molecule that reports an increase in the amount of DNA with a proportional increase in fluorescent signal. The fluorescent chemistries employed for this purpose include DNA-binding dyes and fluorescently-labeled sequence-specific primers or probes. qPCR has been widely used to assess the effect of different treatments on the abundance of the GI microbiota in cats and dogs (Gronvold et al 2010, Garcia-Mazcorro et al 2011) as well as in humans (Malinen et al 2005, Larsen et al 2011). However, bacterial cell numbers cannot directly be estimated from qPCR data in part because the cellular genome content varies with the growth phase of the organisms and bacteria have different number of copies of the 16S rRNA gene (see PCR above).

Fluorescence in situ hybridization (FISH). The detection of bacterial genomic targets using qPCR is useful when evaluating changes in the quantitative abundance of the microbiota, for example during administration of probiotics or therapeutic agents. However, the accurate extrapolation from amplified genomic targets to the actual numbers of bacterial cells is often difficult, mainly because bacteria have different copy numbers of the 16S rRNA gene. Unlike qPCR, FISH is capable of quantifying the actual bacterial cells by direct labeling of the 16S rRNA using fluorescently-labeled oligonucleotides. The FISH technique takes advantage of the fact that each bacterium usually contains thousands of ribosomes spread throughout the cell. Theoretically, like in PCR, it is possible to develop oligonucleotides that are capable to detect microorganisms at all taxonomic levels (i.e., Phylum, Class, Order, Family, Genus). However, this is often challenging due to high similarities in the 16S rRNA gene composition among phylogenetically related microorganisms. FISH can also provide important information about the morphology and spatial distribution of microorganisms in the GI tract (Simpson et al 2006).

Sequencing technologies. The identity of each 16S rRNA gene amplicon can be determined by estimating the order of the base pairs (sequencing). This has been traditionally done using nucleotides base analogs (dideoxy-nucleotides) that lack the 3'-hydroxil group essential in phosphodiester bond formation, which act as specific chain-terminating inhibitors of DNA polymerase (Sanger et al 1977). This Sanger method is still used routinely in many laboratories for sequencing low number of samples. However, complex microbial ecosystems such as the intestinal tract contain millions of microorganisms, which makes necessary to clone and sequence thousands of individual PCR amplicons in order to obtain a representative view of the microbial composition. Recently developed high-throughput techniques such as 454-pyrosequencing (Margulies et al 2005) are capable of sequencing millions of base pairs in one hour or less, and have shown to be useful to study the feline and canine GI microbiota (Suchodolski et al 2009, Middelbos et al 2010, Garcia-Mazcorro et al 2011, Handl et al 2011). Other high-throughput techniques are based on different principles (e.g., reverse termination) and are discussed elsewhere (Pettersson et al 2009). Interestingly, a non-optical genome sequencing has been developed (Rothberg et al 2011), which promises a better performance than traditional optical-based sequencing. Nonetheless, the cost and necessary expertise for both sequencing and after-sequencing analysis procedures make most of these techniques inaccessible for many scientists around the globe. Fortunately, a number of freely available software platforms have been developed such as QIIME (Quantitative Insights into Microbial Ecology1), which is capable of analyzing thousands of sequences in short periods of time. QIIME also offers free comprehensive guides for beginners as well as expert advice for more advanced users.

THE COMPOSITION OF THE GI MICROBIOTA

The composition and metabolic activity of the GI microbiota varies along the GI tract, in part reflecting anatomical and physiological conditions inherent to each of the intestinal sections. In cats and dogs, as well as in other monogastric animals, both the bacterial diversity (an index that incorporates the number of species in an area and their relative abundance) and richness (number of species) are higher in the large intestine when compared to the stomach and all regions of the small intestine (Ritchie et al 2008, Suchodolski et al 2008). The GI microbiota includes all three major domains of life (Archaea, Bacteria, and Eukaryotes), but bacteria make up the most abundant and metabolically active group of microorganisms in the GI tract. For example, a recent metagenomic study showed that bacteria may represent as much as 98% of all fecal microbiota in dogs, with Archaea, Eukaryotes, and viruses representing only about 2% (Swanson et al 2011). Similarly, a recent study also used a metagenomic approach and showed that Eukaryotes, Archaea, and viruses were minor constituents (< 3%) of the fecal microbiota in cats, while bacteria represented the great majority (97.8%) (Tun et al 2012).

In monogastric animals, the large intestine contains the most abundant, diverse and metabolically relevant group of bacteria in the GI tract. The large intestine contains bacterial groups mainly within the phyla Firmicutes and Bacteroidetes. Other phyla such as Actinobacteria, Proteobacteria, Fusobacteria, Spirochaetes, Verrucomicrobia, Cyanobacteria, and Tenericutes are also frequently identified but their proportions are usually low. However, the exact proportions of each bacterial group vary widely throughout the literature. For example, one study showed that healthy cats and dogs may harbor > 90% of Firmicutes in faeces (Handl et al 2011), while others have shown that these animal species may only harbor ~ 13% (cats) and ~ 35% (dogs) of this phylum also in faeces (Swanson et al 2011, Tun et al 2012). The reasons for these discrepancies (see below) are unknown but may include differences in DNA extraction protocols (Zoetendal et al 2001), intra-stool variability of intestinal microorganisms (Garcia-Mazcorro et al 2009), inter-individual differences (Handl et al 2011), the target region of the 16S rRNA gene (Baker et al 2003), as well as inherent differences among the techniques utilized to characterize the microbiota (Zoetendal et al 2004, Kunin et al 2010).

Early culture-based studies suggested that the distal part of the human intestinal tract may harbor about 300 different bacterial species (Moore and Holdeman 1975, Savage 1977). However, recent culture-independent studies suggest that on average humans have an estimated richness of 943 bacterial species (operational taxonomic units or OTUs at 98% similarity) in faeces per subject (Tap et al 2009). In contrast, one study suggested that cats and dogs may harbor only 60 (cats) and 39 (dogs) OTUs (97% similarity) in faeces per subject (Handl et al 2011). This agrees with other studies that showed the presence of only 84 and 52 OTUs in the colon of cats and dogs based on a 98% similarity criterion (Ritchie et al 2008, Suchodolski et al 2008).

THE GI MICROBIOTA OF CATS AND DOGS

An overview of some of the most relevant investigations of the GI microbiota in cats and dogs is presented in table 2. Among all regions of the GI tract of these and other animal species, the distal part of the intestinal tract (i.e. fecal microbiota) has been the most widely studied to date (figure 1), mainly because of the ease of sampling.

 

Table 2. Overview of some of the most relevant investigations about the gastrointestinal (GI) microbiota in cats and dogs.
Visión general de algunas de las investigaciones más relevantes acerca de la microbiota gastrointestinal (GI) en gatos y perros.
 

 

 
Figure 1. Simplified view of the faecal bacterial composition of dogs (A, left) and cats (B, right) at phylum, order and genus level. Numbers represent the average (minimum-maximum) of the relative proportions of sequences (number of sequences obtained from the bacterial group divided by the total number of sequences obtained), calculated according to both a published (Garcia-Mazcorro et al 2011, 12 dogs and 12 cats) and an unpublished (Weber et al 10 dogs and 10 cats) study using 454-pyrosequencing with the same primer set. Clostridium was the most abundant genus in both cats and dogs ( > 20% on average in both studies) but it does not appear in this figure due to uncertain taxonomic classification. At the phylum level, we also included the approximate estimates (*) published by Swanson et al (2011) and Tun et al (2012) using a metagenomics approach (please see main text for more details).
Visión simplificada de la composición bacteriana fecal en perros (A, izquierda) y gatos (B, derecha) al nivel de filo, orden y género. Los números son promedios (mínimo-máximo) de proporciones relativas de secuencias (número de secuencias obtenidas del grupo bacteriano dividido entre el número total de secuencias obtenidas) calculado de un estudio publicado (García-Mazcorro et al 2011, 12 perros y 12 gatos) y un estudio no publicado (Weber et al 10 perros y 10 gatos) usando 454-pirosecuenciacion con el mismo par de oligonucleótidos. Clostridium fue el género más abundante en gatos y perros (> 20% en promedio en ambos estudios) pero fue omitido en esta figura debido a clasificación taxonómica incierta. Al nivel de filo, también se incluyeron los estimados aproximados (*) publicados por Swanson et al (2011) y Tun et al (2012) usando un método metagenómico (ver texto para más detalles).

 

It is important to keep in mind that there are important differences in the reported abundances of GI microorganisms among different studies. This may be due to the DNA extraction method employed as well as the number of copies and the target region within the 16S rRNA gene (see above). A good example of these discrepancies is the recent summary of Armougom and Raoult (2008) about Firmicutes and Bacteroidetes in humans and mice.

THE GI MICROBIOTA OF CATS

Stomach. The stomach of animals was traditionally thought to lack a complex microbial ecosystem. This belief was sustained in part by the observation that gastric acid kills several microorganisms instantly (Giannella et al 1972). However, culture-independent molecular techniques are revealing a different story. An early study used several detection techniques and showed that the stomach of 91% of pet cats (n=58) were positive for the genus Helicobacter (Neiger et al 1998), suggesting a high occurrence of this bacterial group in the feline stomach. In another study, it was shown that cats and dogs are predominantly coloniszed by H. heilmannii (Priestnall et al 2004) but other species (e.g., H. felis, H. bizzozeronii, H. salomonis, H. pametensis) have also been identified in these animal species (Neiger and Simpson 2000).

Small intestine. Osbaldiston and Stowe (1971) were among the first to investigate the composition of the GI microbiota in cats (n = 12) using a wide variety of culture media. In this study, coliforms, Streptococcus, Enterococcus, and Lactobacillus were the predominant groups of bacteria along the feline GI tract. Other earlier studies suggested that Bacteroides and Clostridium spp. were the most common bacteria in the duodenum of cats (Papasouliotis et al 1998, Johnston et al 2001), also based on cultural isolates. Similarly, a recent study used molecular techniques and suggested that the small intestine (i.e., jejunum) of cats harbors mainly the orders Clostridiales and Lactobacillales (~ 90%) but also small proportions of at least five more orders, while the ileum and the colon both harbored a high proportion ( > 50%) of Clostridiales with low proportions of Actinobacteria (~ 5%) (Ritchie et al 2008).

Large intestine. A recent study sequenced the gene encoding the universal 60 kDa chaperonin and showed that the faecal microbiota of cats was dominated by Actinobacteria (~ 53%) and Firmicutes (~ 40%) (Desai et al 2009). Recent studies using 454-pyrosequencing suggest that > 90% of all sequences obtained from feces of healthy cats belong to the Phylum Firmicutes (Garcia-Mazcorro et al 2011, Handl et al 2011), especially members of the family Clostridiaceae, while a metagenomic study suggests that Bacteroidetes/Chlorobi is the most abundant bacterial group (~ 68%), followed by Firmicutes (~ 13%) and Proteobacteria (~ 6%) also in faeces of cats (Tun et al 2012). However, it is important to point out that the study by Tun et al also reports that Bacteroidetes only represented ~ 9% of the obtained sequence reads, while the phyla Chlorobi and Chloroflexi represented less than 1% of the reads. Thus, it is not clear which group represented the remaining ~ 59% of difference between the reported percentage of the Bacteroidetes/Chlorobi group (~ 68%) and the reported percentage of Bacteroidetes alone (~ 9%). We speculate that these discrepancies in the reported percentages may be due in part to the pipeline used to assign taxonomies.

In part because most GI microorganisms have not been successfully cultured, little is known about the phenotype of the GI microbiota in cats. The three major short-chain fatty acids (SCFA) found in cats are butyrate, acetate, and propionate (Brosey et al 2000). In particular, butyrate is considered to play a vital role in colonic human health (Hamer et al 2008, Louis and Flint, 2009) but little is known about its role in intestinal health of cats. Nonetheless, butyrate-producing bacteria are commonly found in feces of cats (Handl et al 2011).

THE GI MICROBIOTA OF DOGS

Stomach. A study published last year showed that the stomach of healthy dogs is home of a diverse microbiota (at least 4 phyla were identified), as evaluated by 454-pyrosequencing (Garcia-Mazcorro et al 2012a). Despite this diversity, one single genus (i.e., Helicobacter) was by far the most predominant (~ 98% of all gastric microbiota). These results are in accordance with one study that showed that the human stomach is also home of a diverse microbiota, although the genus Helicobacter (H. pylori only) constituted only 42% of all sequences analyzed (Bik et al 2006).

Small intestine. Clapper and Meade (1963) attempted one of the first characterizations of bacteria and fungi in the lower intestinal tract of dogs using twelve different types of culture media. Using rectal swabs from 25 healthy Beagle dogs, the authors isolated 20 species of bacteria and 10 species of fungi (Clapper and Meade 1963). More recent studies using molecular techniques have shown the presence of at least four different bacterial phyla in the intestinal tract of dogs, namely Firmicutes (47.7%), Proteobacteria (23.3%), Fusobacteria (16.6%), and Bacteroidetes (16.6%) (Suchodolski et al 2008). Interestingly, these proportions differed depending on the intestinal compartment analyzed, with duodenum and jejunum containing more than 50% Firmicutes, while the ileum and colon only harbored ~ 30% of this phylum (Suchodolski et al 2008). Still, a more recent study used 454-pyrosequencing and identified ten bacterial phyla in the jejunum of dogs (Suchodolski et al 2009), although more than half of these groups were only found in very low proportions (< 1% of all microbiota). A recent article used FISH to quantify bacteria in the duodenal biopsies of dogs and found a median of zero bacteria (range: 0-3) per microscopic field using almost 1000 microscopic fields (Garcia-Mazcorro et al 2012a). In contrast, the same article found a high bacterial diversity (median: 173 OTUs) using 454-pyrosequencing also in duodenal biopsies from the same dogs. The reasons for this discrepancy are unknown but it may relate to the destruction of intestinal mucus during formalin fixation of the biopsies before paraffin embedding.

Large intestine. Some studies suggest that, in faeces, Firmicutes represent the great majority (> 90%) of the faecal microbiota in dogs (Garcia-Mazcorro et al 2011, Handl et al 2011). On the other hand, a recent metagenomic study suggested that the Bacteroidetes/Chlorobi group and Firmicutes were the dominant bacterial phyla (~ 35%), followed by Proteobacteria (~ 15%) and Fuso-bacteria (~ 8%) also in faeces of dogs (Swanson et al 2011). However, the results of this study show, just as in the reports of Tun et al, that Bacteroidetes only represented ~ 3% of all the obtained reads, while the Chloroflexi and the Chlorobi groups represented less than 1% of the reads. Therefore, it is not clear which group represented the difference between the reported percentage of the Bacteroidetes/Chlorobi group (~ 35%) and the percentage of Bacteroidetes alone (~ 3%). It is possible that the remaining percentage represents unclassified members of Bacteroidetes, but this has been scarcely discussed in the available literature.

As mentioned above, little is known about the phenotype of GI microorganisms in cats and dogs. As in cats, the major SCFA in dogs are butyrate, acetate, and propionate (Swanson et al 2002). A butyrate-producer bacterium that has attracted much attention for its role in intestinal health of humans is Faecalibacterium prausnitzii (Sokol et al 2009). A recent article suggests that Faecalibacterium-relatives are also abundant in faeces of dogs (Garcia-Mazcorro et al 2012b), although it has been suggested that canine Faecalibacterium spp. may not be F. prausnitzii, based on phylogenetic analysis of near-full-length 16S rRNA gene sequences belonging to a canine clone and a human strain (Suchodolski et al 2008). Other butyrate-producers bacteria such as Eubacterium and Roseburia have been found in dogs and cats (Handl et al 2011).

MANIPULATION OF THE GI MICROBIOTA

Acknowledging that GI microbiota is closely involved in the wellbeing of the host led to the idea of manipulating intestinal microorganisms to enhance health. Several approaches have been used to accomplish this goal in cats and dogs (see below). In contrast, the consumption of therapeutic agents such as antibiotics can also lead to unintended modifications of the GI microbiota, although less research on this topic is available in cats and dogs.

PROBIOTICS AND PREBIOTICS

Probiotics can be deined as live microorganisms that, if consumed in adequate amounts, would provide a health benefit to the host (FAO/WHO, 2002). On the other hand, prebiotics are selectively fermented ingredients that cause speciic changes in the composition and/or activity of the gastrointestinal microbiota (Gibson et al 2010), thus also conferring health beneits on the host, while synbiotics are preparations containing both probiotics and prebiotics.

Sunvold et al (1995) were among the first to evaluate the in vitro effect of a prebiotic on faecal fermentation patterns of cats and dogs. In this study, the addition of iber (citrus pulp) led to a higher organic matter disappearance and lower acetate to propionate ratio in both dogs and cats; however, these changes were not correlated with modiication of the faecal microbiota. While other studies have also researched the properties and effects of probiotics and prebiotics on the composition and/or activity of the canine and feline intestinal microbiota in vitro (Strompfová et al 2004, Cutrignelli et al 2009) and in vivo (Vanhoutte et al 2005, Biagi et al 2007), most of these investigations have only studied selected intestinal bacterial groups, an approach that does not fully assess the effect of probiotics and prebiotics on the intestinal microbial ecosystem. A recent study investigated the effect of a commercial preparation of probiotics and prebiotics on the faecal microbial composition of healthy cats and dogs using several molecular techniques, including a high-throughput sequencing technique (Garcia-Mazcorro et al 2011). Similarly to other studies, the authors of this investigation showed that the consumption of the formulation leads to increases in faecal abundance of the ingested microorganisms, a change that rapidly disappears 2-3 days after consumption of the preparation. Interestingly, these quantitative changes in speciic bacterial groups did not seem to lead to major modifications in the overall phylogenetic composition of the fecal microbiota, as evaluated by 454-pyrosequencing. This is an interesting observation because probiotics are thought to modulate the intestinal microbiota, including other, unrelated to the ingested microorganisms, bacteria. This modulation effect of probiotics on the intestinal microbiota has also been suggested in humans, as evaluated by culture (Venturi et al 1999) and molecular techniques (Larsen et al 2011), although the results are also controversial. For example, one study showed that the consumption of a synbiotic preparation leads to changes in bacterial populations but no significant differences in fecal chemistry (Worthley et al 2009), while others propose that the intake of a synbiotic food leads to modulation of the gut metabolic activities with a maintenance of gut "biostructure" (Vitali et al 2010). The discrepancy among different investigations may be due to the amount and types of probiotics administered (Pagnini et al 2010), as well as the combination and potential synergistic effect of different microorganisms. While some researchers encourage the design and use of several strains and/or species of microorganisms in probiotic formulations (Timmerman et al 2004), few data support a more beneficial effect of these multi-strains/species preparations compared to single strain preparations.

ANTIBIOTICS

Antibiotics are commonly used in Veterinary Medicine, but concerns have been raised about the potential reservoir of antibiotic resistance among the native intestinal microbiota of animals (Moyaert et al 2006). While in humans the effect of antibiotics on the intestinal microbiota has been characterised in depth (Dethlefsen and Relman 2011), little is known about the effect of antibiotics on the GI microbiota of cats and dogs. Johnston et al (1999) evaluated changes in duodenal bacteria of cats (n = 6) during metronidazole treatment, but this study only used culture techniques. Suchodolski et al (2009) analyzed changes in the small intestinal microbiota of dogs (n = 5) during administration of tylosin using 454-pyrosequencing. In this study, several changes in the abundance of different bacterial groups were observed, including an increase in the proportions of Enterococcus spp. which have been reported to be resistant to tylosin. However, these changes in bacterial amounts were not accompanied by any obvious clinical effect. Gr0nvold et al (2010) studied changes in faecal microbiota of healthy dogs (n = 7) during administration of amoxicilin using DGGE and qPCR. In this study, most of the variation in DGGE band profiles could be attributed to dog-specific factors, suggesting a minimal change in the composition of the fecal microbiota, as determined by the employed techniques.

INHIBITORS OF GASTRIC ACID SECRETION

Gastric acid is one of the first physiological barriers to impede the passage of potentially harmful agents into the intestinal tract. It is believed that inhibitors of gastric acid secretion can change the composition of the GI microbiota (Heidelbaugh et al 2009, Lombardo et al 2010), but only few studies support this statement and have mainly used culture techniques to study specific microorganisms (e.g. Helicobacter pylori). A recent study used a combination of several molecular techniques and concluded that the proton-pump inhibitor omeprazole can change the quantitative abundance of several gastric, duodenal and faecal microorganisms in healthy dogs, a change that did not seem to lead to major shifts in the overall phylogenetic composition of the gastric and small intestinal microbiota (Garcia-Mazcorro et al 2012a). Interestingly, the observed effect of omeprazole on the canine GI microbiota was dependent on the gender of the animals, perhaps suggesting a distinctive metabolism of the drug in male and female dogs.

CONCLUDING REMARKS

The GI tract of cats and dogs harbors a complex microbiota. The study of GI microorganisms is of interest because of its close relationship with the wellbeing of the host. Also, an increasing number of investigations suggest that GI microorganisms may play a role in the etiology of various GI disorders. However, little is known about what represents a healthy microbiota, its normal biological variations within and among individuals, and how to successfully manipulate it to prevent or treat GI disease. In order to achieve this goal, future collaborative studies should complement phylogenetic characterizations of the GI microbiota with functional (metabolic) analyses.

NOTE

1 http://www.qiime.org/

 

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Accepted: 10.01.2013

 

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