# Ecological Characterization of the Colonic Microbiota of Normal and Diarrheic Dogs

Authors: Julia A. Bell; Jamie J. Kopper; Judy A. Turnbull; Nicholas I. Barbu; Alice J. Murphy; Linda S. Mansfield
Journal: Interdisciplinary Perspectives on Infectious Diseases
 (2008)

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## Abstract

We used terminal restriction fragment polymorphism (T-RFLP) analysis to assess (1) stability of the fecal microbiota in dogs living in environments characterized by varying degrees of exposure to factors that might alter the microbiota and (2) changes in the microbiota associated with acute episodes of diarrhea. Results showed that the healthy canine GI tract harbors potential enteric pathogens. Dogs living in an environment providing minimal exposure to factors that might alter the microbiota had similar microbiotas; the microbiotas of dogs kept in more variable environments were more variable. Substantial changes in the microbiota occurred during diarrheic episodes, including increased levels ofClostridium perfringens, Enterococcus faecalis, and Enterococcus faecium. When diet and medications of a dog having a previously stable microbiota were changed repeatedly, the microbiota also changed repeatedly. Temporal trend analysis showed directional changes in the microbiota after perturbation, a return to the starting condition, and then fluctuating changes over time.


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## Body

## 1. Introduction

Acute infectious diarrhea is a worldwide public health problem with a long list of differential
diagnoses. In the US, major pathogens responsible for most cases includeSalmonella, Campylobacter, Shigella, Escherichia coli O157:H7, and Cryptosporidium [1].
Vibrio, Yersinia, Listeria, Cyclospora, Clostridium difficile, Giardia,
rotavirus, and Entamoeba histolytica are also reported at lower rates [1]. Enterotoxigenic,
enteropathogenic, enteroaggregative, and enteroinvasive strains of E.
coli, toxin-producing Clostridium perfringens, Staphylococcus
aureus, Bacillus cereus, and norovirus also cause infectious diarrheas, but
may not be included in routine testing [1]. Main etiologies for acute
diarrhea in the dog are the same or similar to organisms seen in humans [2–6]. Other known pathogens of dogs include Clostridium
piliforme [7], Brachyspira
(Serpulina) spp. [8], Enterococcus spp. [9],
and Helicobacter spp.
[10–12]. In both humans and dogs, a number of bacteria, such as Enterococcus
spp. and certain Clostridia spp., are recognized as opportunistic pathogens or enhance disease from other organisms when conditions are ideal for their growth and when competitors are absent [13–15]. Most cases of acute infectious diarrhea are self-limiting illnesses and resolve in a few days with or without symptomatic treatment with rehydration along with antimicrobial or antiparasitic drugs targeting the “etiological agent” [16]. The presence of known GI tract pathogens recovered or demonstrated is used to attribute an etiology during a diarrheic episode; however, causation is seldom proved.Few animal models of functional GI disorders exist, but the dog GI tract and microbiota bear many
similarities to those of humans. Dogs are monogastric omnivores in which dietary manipulations are easy to achieve and a small-sized cecum provides only a small component of hind gut fermentation. Dogs are litter bearers with a
short reproductive interval, where families of related individuals are easy to acquire and where management can be manipulated to control environmental exposures. Early work has been done to describe GI microbiota in healthy dogs.
Microbial community analysis of feces from 4 Labrador breed dogs was performed using culture followed by 16S rRNA gene sequencing [17].
Despite intensive efforts, these methods underestimated community diversity and
skewed results toward organisms more successful on particular culture media. These
results did support the use of molecular-based methodologies for determining
community profiles, but at the time, sequences of many isolates were not found
in the Ribosomal Database Project and EMBL databases. Suchodolski et al.
described the microbial community in duodenum, jejunum, ileum, and colon
contents from six healthy unrelated dogs using near-full-length 16S rRNA gene
PCR and cloned libraries [18]. Here, Firmicutes was the most diverse and abundant phylum; Clostridiales was the most diverse
bacterial order, forming several Clostridium clusters; anaerobic Fusobacteriales and Bacteroidales
increased in their relative abundance along the intestinal tract, peaking in
ileum and colon; and Lactobacillales occurred commonly in all parts of the intestine. These results on Firmicutes and Clostridiales were similar in humans [19] with Clostridium
cluster XIVa being the predominant contributor to Clostridiales
sequences in both dogs and humans. Furthermore,
Fusobacteria appeared to be a minor part of
the intestinal community in other species, including humans [19]. Also, Proteobacteria—including E. coli-like organisms—predominated in
the duodenum and were sparse in the colon in both dogs [18] and humans [19]. In another study designed to
define host distribution patterns of fecal bacteria of the order Bacteroidales as markers for fecal
source identification in aquatic environments, human, dog, cat, and gull sequences
were clustered together in phylogenetic analysis [20]. Swanson et al. performed a study using healthy dogs to examine whether prebiotic (fructooligosaccharides)
or probiotic (Lactobacillus acidophilus) treatments would alter gut microbial populations, fermentative end products, and nutrient digestibilities [21]. In one experiment, fructooligosaccharide treatment decreased C. perfringens and increased fecal butyrate and lactate concentrations, while in a second experiment, this treatment increased bifidobacteria, lactobacilli, and
fecal lactate and butyrate and decreased fecal ammonia, isobutyrate, isovalerate, and total branched-chain fatty acid concentrations. Finally, recent global vertebrate gut microbiota studies showed that captive (zoo) bush dogs on
carnivorous diets had microbial communities that clustered with other carnivores, and that primates on omnivorous diets had fecal microbiota most like humans [22, 23]. In these studies using tree-based and network-based analyses of microbial communities, clustering by
diet (herbivore, omnivore, or carnivore) was highly significant. However, these investigators did not consider the microbiota of modern pet dogs on highly processed diets and cohabiting with humans. Taken together, these studies show that dogs are a reasonable model for study of the role of microbiota in GI disorders and that understanding of the GI microbial community in dogs is at a stage of readiness for this to be pursued.Many diarrheal diseases are attributable to specific pathogens, to polymicrobial interactions,
or to shifts or imbalances in the resident microbial community in response to external stress(s). Thus, acute diarrheas can result from myriad etiologies making attribution difficult. Lately, attention has been focused on the role of
the microbiota. The normal gut biota or “enterome” is a complex microbial ecosystem that plays a crucial role in maintaining GI homeostasis and in certain disease states [24].
However, 300–500 different bacterial species are estimated to inhabit the human colon, many of which are
not cultivatable [25]. This estimate of diversity has changed little over the years, even with the application of molecular
techniques to the study of the colonic microbiota [26, 27]. Eckburg et al. [26] used collector's curves to estimate that extensive sequencing would reveal at least 500 species. Adding to complexity during
analysis are the sheer numbers of GI organisms, which can reach a density of 1012 organisms/gram of feces, with a total gut population of 1014–1015 microbes [28]. In the dog, breed and age
were shown to have significant effects on particular aerobic and anaerobic
bacterial counts using denaturing gradient gel electrophoresis of PCR amplified
16S ribosomal fragments. Here, each individual dog harbored a characteristic
fecal bacterial community which was independent of diet [29].
We hypothesized that dogs
have a stable composition of the colon microbial community and that episodes of
diarrhea lead to long lasting changes in community composition and/or function;
furthermore, treatment for specific pathogens can
compound these effects. To address this hypothesis, we required (1)
diarrheic perturbations of the GI tract with or without treatment to study, (2)
documentation of the presence of pathogens in the GI tract, (3) a
cost-effective technique for assessing shifts in the GI tract microbiota, and
(4) the assurance that the microbiota in an individual is stable enough for us
to be able to detect meaningful changes. We used diagnostic PCR assays to
document the presence of pathogens in the GI tract. The GI tract perturbations
we studied were (1) acute episodes of diarrhea with or without antibiotic
treatment and (2) changes in diet and medications. The technique we chose for
assessing shifts in the GI tract microbiota was terminal restriction fragment
length polymorphism (T-RFLP) analysis.T-RFLP is one of a family of related
techniques used to describe microbial communities containing large numbers of
organisms that are undescribed and/or difficult to cultivate. T-RFLP is based
on PCR amplification and restriction enzyme digestion of 16S rDNA PCR products
followed by capillary electrophoresis on a DNA sequencer. Here, data were
analyzed using exploratory statistical techniques that help reveal patterns
rather than the more familiar inferential statistics that help discriminate
between hypotheses. Community studies using these techniques that have been
reported to date have involved small numbers of samples. For example, Nielsen et al. characterized
populations of lactic acid bacteria and total bacterial communities in one
sample each from three colon segments in four human subjects [30]. In this study, the total
communities from different parts of the colon in the same individual were
similar to each other, but total communities varied between individuals. In
another trial, fecal communities were studied in eight individuals of different
ages and sexes; five adults and two children had similar arrays of
microorganisms in their fecal communities but different proportions of the bacterial
species, while a two-week-old infant had a much simpler community [31]. Thus, T-RFLP data revealed
valuable results even though attribution of gains or losses of specific
bacterial genera or species was not possible. Also, we recognize that many
factors may affect the results obtained with the T-RFLP technique; these
factors include choice of primers; choice of restriction enzymes; and various
amplification biases due to PCR reaction parameters such as amount and
complexity of the template DNA, annealing temperature, and number of cycles in
the amplification reaction [32–35]. Nevertheless, T-RFLP is
rapid, sensitive, and reproducible [31, 34], and, unlike many other
community analysis techniques, it yields both taxonomic information regarding
organisms in the community and estimates of their relative proportions in the
total microbial population. It is considered a useful tool in the study of
microbial communities and can be used to generate data that help to determine
whether further studies employing more precise, laborious, and expensive
techniques, such as targeted real-time PCR for the detection and quantization
of specific microorganisms or the generation, sequencing, and analysis of
cloned 16S rDNA libraries, are justified [31].To address our
hypothesis, we studied the microbial
communities of dogs during diarrheic episodes and compared them to those of
healthy control dogs to make a preliminary assessment of the contribution of
members of the normal community to acute diarrheal disease processes. Results of these studies showed that fecal microbiotas varied
among dogs, even those that were closely related, and were largely
influenced by diet. A dog treated for diarrhea with metronidazole did exhibit
loss of richness followed by return to a stable microbiota; the same treatment
aimed at a second bout of diarrhea resulted in an unstable microbiota that
ultimately lost richness and evenness. Thus, our hypothesis, that dogs have
relatively stable colon microbial communities and episodes of diarrhea lead to
instability which is compounded by antimicrobial treatments
for specific pathogens, can be addressed using these methods particularly
if environmental exposures are limited. This work demonstrates that dogs can be
used to study changes in microbial communities associated with naturally occurring
diarrheas.


## 2. Materials and Methods

### 2.1. Enrollment of Study Dogs and Experimental Design

We established a standard operating procedure for
sample collection and processing that was approved by the Michigan State
University Institutional Animal Care and Use Committee (2-16-2006). The study
also followed all guidelines and standard protocols of the Michigan State
University (MSU) Veterinary Teaching Hospital (VTH). Information on all animals
included in the study is given in Table1. A panel of eight household pet dogs was enrolled in the study over one
year. These eight dogs included two pets from a single household (Pets 1 and 2
in Table 1; Pet 1 suffered one episode of diarrhea), a single pet from a second
household (Pet 3 in Table 1; this pet suffered two episodes of diarrhea which
were treated at the MSU VTH), a single healthy pet from a third household
(Pet 4 in Table 1), two healthy pets from a fourth household (Pets 5 and 6 in
Table 1), and two pets from different households presenting to the MSU VTH with
diarrhea (Pets 7 and 8 in Table 1). Five
control dogs from an extended genetically related family were enrolled that
were housed in an MSU-closed research colony, were fed the same food daily, and
were exercised indoors to prevent infections. Feces were collected from these
dogs to assess repeatability and technical quality of our protocols and to
provide comparisons to diarrhea cases.Table 1
Characteristics of dogs enrolled in the study.
BreedSexAgeDiet (%)CommentsproteinfatfiberPet 1Beagle × schnauzer; related to research colony dogsF4 years21.513.03.0Time series; one diarrheic samples (dietary indiscretion; no treatment),
three normal samplesPet 2Labrador retriever puppy; same household as Pet 1M9 weeks26.08.53.0Time series; six normal samplesPet 3Golden retrieverM12 years25.06.0–8.012.0Time series with normal and diarrheic samples (dietary indiscretion;
metronidazole treatment)Pet 4Golden RetrieverM6 years22.012.05.0One normal samplePet 5DachshundM7 years22.013.03.0Normal samplePet 6American Eskimo mixM3 years22.013.03.0Normal samplePet 7Retriever mixF2 yearsNDNDNDDiarrheic samplePet 8Mixed breedF12 yearsNDNDNDDiarrheic sampleResearch 1Beagle × SchnauzerF4 years25.09.05.0Normal sampleResearch 2Beagle × SchnauzerF6 years25.09.05.0Normal sampleResearch 3Beagle × SchnauzerM4 years25.09.05.0Normal sampleResearch 4Beagle × SchnauzerF6 years25.09.05.0Normal sampleResearch 5Beagle × SchnauzerF4 years25.09.05.0Normal sampleAll diagnostic tests (except for an ELISA test
forGiardia) and T-RFLP analyses were conducted on DNA isolated from
fecal samples. DNA of sufficient quality for T-RFLP analysis could not be
isolated from one of two samples from Pet 4 or from Pets 5, 6, 7, or 8.
Diagnostic PCR results are presented for all thirteen dogs: T-RFLP results are
presented for the five research colony dogs and four household pet dogs (Pets
1, 2, 3, and 4). For T-RFLP analysis of fecal microbiota over time, we
collected repeated fecal samples from three household pet dogs to assess
variability of the microbiota based on housing and feeding regimes. As
mentioned above, two of these three dogs experienced diarrhea, one of them
twice. Therefore, we collected samples from these dogs during and after treatment,
if any, with the prescribed antibiotic.


### 2.2. History and Clinical Examination

The overall strategy for sampling of dogs is shown in Figure1. The case definition for a dog with diarrhea was a
dog that presented with acute diarrhea. If dogs presented to the MSU VTH with
diarrhea, we instituted resampling three to five days after completion of
treatment. For one of the two diarrheic household pets studied (Pet 3 in Table 1), two original samples were taken before antibiotic treatment and further
samples were taken during and after antibiotic treatment; for Pet 1 in Table 1,
the initial sample was diarrheic and subsequent samples were taken after resolution of disease, which was not treated.Figure 1
Scheme for sample processing.With cases presenting with signs of acute large bowel diarrhea, the typical MSU small
animal clinic protocol includes a fecal flotation,Giardia test, and
fecal cytology. Treatment usually comprises a short course of metronidazole (10–50 mg/kg BID) and
institution of a low-residue diet. In this study, our protocol involved taking
a history, performing a physical examination, and initiating diagnostic tests
according to standard methods currently employed in the MSU VTH.


### 2.3. Sample Handling and DNA Isolation

Preliminary studies were conducted to define the best
method of handling fecal samples to optimize T-RFLP analysis. Using clean
gloves for each animal, samples from research colony dogs and Pets 1 and 2 were
taken as free catch or rectal samples; samples from other dogs were taken from
the ground immediately after defecation taking care to avoid taking any part of
the sample that touched the ground. Subsamples were taken from the interior of
the fecal mass for analysis. The feces was placed into tryptose soy broth with
15% glycerol, mixed well, aliquoted into at least 4-5 identical
subsamples; three were frozen back at −80 and one had DNA extracted that day.
Samples were subjected to one of the following treatments: holding on ice only
long enough for transport to the laboratory, holding at room temperature for 24
hours prior to DNA extraction, holding on ice for 24 hours prior to DNA
extraction, refrigeration for 24 hours prior to DNA extraction, and freezing
for 24 hours prior to DNA extraction. These conditions were intended to mimic
the possible fates of clinical specimens prior to submission to the
laboratory. DNA could be recovered in
quantities sufficient for diagnostic PCR and T-RFLP analysis from samples
subjected to all treatments, although yields were greater when samples were
held on ice only long enough for transport to the laboratory. Freezing was
preferred when samples could not be processed immediately in order to avoid
changes in microbiota that have been documented in samples held at room or
refrigeration temperatures [36–38].Bacterial
populations were recovered from 200 mg of feces by suspending samples in 300 mM
sucrose solution followed by two low-speed centrifugations as described [39]. Bacteria were then
collected by high-speed centrifugation and the pellets resuspended in 200
microliters 10 mM Tris 1 mM EDTA, pH 8.0. Klijn et al. [39]
reported that this method results in the recovery of over 80% of
aerobic/facultatively anaerobic bacteria able to grow on Columbia blood agar
medium (they did not assay obligately anaerobic bacteria). Similar differential
centrifugation methods have been used to isolate bacterial DNA for microbial
community analysis from digesta from chicken gastrointestinal tracts [40, 41], rat cecal digesta [42], and human feces [43]. Community DNA was isolated from the
harvested bacterial cells using
QIAgen DNeasy Tissue Kit (QIAgen, Valencia, Calif, USA) according to the
manufacturer's instructions for Gram-positive bacteria, including digestion
first with 20 mg/mL lysozyme for one hour at 37°C followed by proteinase K (20 mg/mL) overnight at 55°C; DNA was then purified from the lysates using QIAgen
spin columns.


### 2.4. Screening for Common Pathogens in Normal and Diarrheic Dogs

Fecal samples were screened for parasites by the Cornell-Wisconsin saturated sucrose
flotation technique [44]. Giardia tests were
performed using the ProSpect Giardia-ELISA-microplate assay (Remel, Lenexa, Kan, USA) according to the
manufacturer's instructions. DNA preparations were screened for
the presence of DNA from the following bacterial pathogens by standard
polymerase chain reaction assays using published primer pairs and cycling
conditions: Clostridium perfringens [45], Campylobacter spp. [5], Enterococcus spp. [46], Enterococcus faecium [47], Helicobacter spp. [48], Salmonella spp. [49], and  Brachyspira (Serpulina) spp. [50]. Purified DNA samples from
cultured known bacterial species were used as positive controls for the PCR
assays. In addition, quantitative PCR assays (Q-PCR) were performed using
primers and cycling conditions developed by Rinttilä et al. [51] for Bacteroides spp.
and related organisms, Clostridium group I, and Clostridium group
XIVa. However, Q-PCR assays for Escherichia coli were performed as
published [52]; Q-PCR assays for Enterococcus faecium, and Enterococcus faecalis were performed as described below [53].


### 2.5. T-RFLP Analysis

Terminal restriction fragment polymorphism analysis was conducted using the 516f and
1510r primers, PCR reaction mixture, PCR cycling conditions, and restriction
enzyme digestion conditions described by Nagashima et al. [31], except that reactions were
carried out using 50 ng template DNA in a total volume of 100 μL. The forward primer carried a 6-FAM
fluorescent probe. The PCR products were purified using QIAquick PCR
purification columns (QIAgen; Valencia, Calif, USA) according to the
manufacture's protocol prior to digestion with BslI (New England
Biolabs, Inc., Ipswich, Mass, USA); the resulting fragments were separated by
electrophoresis on an automated DNA sequencer (ABI
Prism 3100) at the MSU Genomic Technology Support Facility. An internal
lane standard (MapMarker1000; BioVentures, Murfreesboro, Tenn, USA) was added to every sample, and
the standard peak sizes were used by the GeneScan Analysis software to compute
peak sizes. Electropherograms were
stored as computer files for later analysis.


### 2.6. T-RFLP Data Analysis

Analysis of T-RFLPBslI peak patterns was conducted as follows. Only peaks
corresponding to DNA fragment lengths between 100 and 990 bp in length, having
a height of at least 25 fluorescent units, and contributing at least 1% of the
total area under the electropherogram were considered; electropherograms having
a total area less than 5000 fluorescence units were not analyzed. Likely
identities of the phylogenetic groups of bacteria detected were determined
manually by comparing peak fragment sizes to fragment sizes assigned to various
bacterial groups by Nagashima et al. [31], allowing for an error of ±1 bp. Peaks that did not fall into the size classes defined by Nagashima et al. [31] were combined to form an
“unknown” class. The identities of the bacterial groups and the range of peak
sizes that contributed to each group are shown in Table 2. The community
profile consisted of a list of the bacterial groups present or absent in a
sample and the % area under the electropherogram contributed by each group.Table 2
Assignment of T-RFLP fragment size classes to bacterial taxa based on data
of Nagashima et al. [31].
Fragment class according to Nagashima et al.[31]Fragment size range (bp)Predominant genusOther genera includedBslI 110110–115NoneClostridium, Eubacterium, Lactobacillus, VeillonellaBslI 124125–128BifidobacteriumNoneBslI 317316–319PrevotellaLactobacillusBslI 332326–338StreptococcusBifidobacterium, Clostridium, Eubacterium, Lactobacillus, PrevotellaBslI 370364–378ClostridiumBacteroides, Bifidobacterium, Eubacterium, Lactobacillus, PrevotellaBslI 469464–473BacteroidesClostridium, Eubacterium, PrevotellaBslI 494487–502ClostridiumEubacterium, Ruminococcus, StreptococcusBslI 520513–519EnterococcusClostridium, Eubacterium, LactobacillusBslI 657655–665Lactobacillus; StreptococcusBacteroides, Clostridium, Enterococcus, Eubacterium, RuminococcusBslI 749748–757ClostridiumEubacterium, Fusobacterium, RuminococcusBslI 853848–854BacteroidesBacteroidesBslI 919911–921RuminococcusEnterococcus, EubacteriumBslI 940935–941EscherichiaClostridium, Eubacterium, Fusobacterium, RuminococcusBslI 955955–960NoneClostridium, Eubacterium, RuminococcusFor cluster
analysis, the % area data were fourth-root transformed, and single linkage cluster
analysis using the Bray-Curtis similarity index was performed on the
transformed data [54]; a dendrogram was
constructed, and its stability was evaluated using the jackknife procedure [55]. These calculations were
performed using utilities made available online by John Brzustowski at http://www2.biology.ualberta.ca/jbrzusto/cluster.php.
The Bray-Curtis similarity index is widely used in community ecology studies
because it is less affected than other indices by differences involving rare,
low abundance organisms and it is thought to perform better with datasets
containing widely differing sets of communities [55, 56]. This index takes into
account both the presence and absence of peaks and differences in the
areas under same-sized peaks in the electropherograms, which indicate
differences in the proportions of a particular organism in two
populations.We also
calculated the descriptive microbial community parameters developed
specifically for molecular ecological fingerprinting by Marzorati et al. [57]; the community parameters
summarize community richness (R0), functional organization (Fo,
evenness), and dynamics (% change and Δt). These parameters were calculated
and interpreted for T-RFLP profiles generated in this study as described in
Marzorati et al. [57], except that the Bray-Curtis
similarity index was used in the calculation of the % change parameter instead
of the similarity index used by Marzorati et al. [57]. Finally, patterns of variability in T-RFLP
profiles for Pet 3 over time were analyzed by the regression method of Collins
et al. [58]. Euclidean distances between
microbial communities at different time points were calculated using utilities
made available online by John Brzustowski at http://www2.biology.ualberta.ca/jbrzusto/cluster.php;
regression analysis was performed using SigmaStat 3.1 (Systat Software, Point Richmond, Calif, USA).


### 2.7. Quantitative Real-Time PCR Method and Analyses

DNA extracted from feces (as
previously described) was used as the template in species-specific Q-PCR assays.Bacteroides/Prevotella/Porphyromonas and Clostridium groups I and XIVa assays were performed using the primer
sequences from Rinttilä et al. [51]. Escherichia coli Q-PCR assays were performed using primer sequences
from Khan et al. [52]; Enterococcus faecalis and Enterococcus faecium Q-PCR assays were performed using primer
sequences from Firmesse et al. [53]. In all assays, 25 μL reactions
were performed in triplicate for each sample with iQ SYBR Green Supermix (Bio-Rad,
Hercules, Calif, USA) and 250 ng of
fecal DNA. The following cycling protocol was used for Clostridium group
I, Clostridium group XIVa, Bacteroides, and E. coli: 95°C
for 3 minutes and 40 repeats of 95°C for 10 seconds, specific annealing
temperature for 30 seconds. Cycling parameters for E. faecium were 95°C,
3 minutes; 40 cycles of 63°C for 10 seconds. Cycling parameters for E.
faecalis were 95°C, 3 minutes; 40 cycles of 64.5°C for 10 seconds. Each
species-specific assay was optimized for primer concentration and annealing
temperature. Bacteroides species
assay used 6.25 pm of each primer per reaction with an annealing temperature of
65°C. E. coli assays used 6.25 pm of
each primer per reaction and an annealing temperature of 63.3°C. Clostridium Groups I and XIVa used 7.5 pm
of each primer per reaction with annealing temperatures of 58.9°C and 57°C,
respectively. All Q-PCR assays included a 6-point standard curve in triplicate (R2>0.90) and three no-template controls containing all other reaction
components on a Bio-Rad iQ5 Real-Time PCR Detection System (Bio-Rad, Hercules, Calif, USA). Three DNA
preparations were purchased for the standard curves: Clostridium
perfringens for Clostridium group I (Sigma Aldrich, St. Louis,
Mo, USA), Ruminococcus productus VPI 4299 for Clostridium group XIVa, and Bacteroides fragilis VPI 2553 (DNA purchased from American Type Culture
Collection, Manassas, Va, USA). Three DNA preparations for the standard curves were prepared in our laboratory
by the CTAB method of Ausubel et al.
[59] from strains E. coli DH5-α, Enterococcus faecalis 19433, and Enterococcus faecium 19434.Bio-Rad iQ5 PCR detection system software (Bio-Rad, Hercules, Calif, USA)
was used to calculate the Ct value for each reaction, the mean Ct value for
each set of triplicates, and the amount of target DNA using values derived from
the standard curves. The statistic PV, which quantifies variability in
population abundance over time, was calculated for each of the organisms
assayed using the Q-PCR data [60].


## 2.1. Enrollment of Study Dogs and Experimental Design

We established a standard operating procedure for
sample collection and processing that was approved by the Michigan State
University Institutional Animal Care and Use Committee (2-16-2006). The study
also followed all guidelines and standard protocols of the Michigan State
University (MSU) Veterinary Teaching Hospital (VTH). Information on all animals
included in the study is given in Table1. A panel of eight household pet dogs was enrolled in the study over one
year. These eight dogs included two pets from a single household (Pets 1 and 2
in Table 1; Pet 1 suffered one episode of diarrhea), a single pet from a second
household (Pet 3 in Table 1; this pet suffered two episodes of diarrhea which
were treated at the MSU VTH), a single healthy pet from a third household
(Pet 4 in Table 1), two healthy pets from a fourth household (Pets 5 and 6 in
Table 1), and two pets from different households presenting to the MSU VTH with
diarrhea (Pets 7 and 8 in Table 1). Five
control dogs from an extended genetically related family were enrolled that
were housed in an MSU-closed research colony, were fed the same food daily, and
were exercised indoors to prevent infections. Feces were collected from these
dogs to assess repeatability and technical quality of our protocols and to
provide comparisons to diarrhea cases.Table 1
Characteristics of dogs enrolled in the study.
BreedSexAgeDiet (%)CommentsproteinfatfiberPet 1Beagle × schnauzer; related to research colony dogsF4 years21.513.03.0Time series; one diarrheic samples (dietary indiscretion; no treatment),
three normal samplesPet 2Labrador retriever puppy; same household as Pet 1M9 weeks26.08.53.0Time series; six normal samplesPet 3Golden retrieverM12 years25.06.0–8.012.0Time series with normal and diarrheic samples (dietary indiscretion;
metronidazole treatment)Pet 4Golden RetrieverM6 years22.012.05.0One normal samplePet 5DachshundM7 years22.013.03.0Normal samplePet 6American Eskimo mixM3 years22.013.03.0Normal samplePet 7Retriever mixF2 yearsNDNDNDDiarrheic samplePet 8Mixed breedF12 yearsNDNDNDDiarrheic sampleResearch 1Beagle × SchnauzerF4 years25.09.05.0Normal sampleResearch 2Beagle × SchnauzerF6 years25.09.05.0Normal sampleResearch 3Beagle × SchnauzerM4 years25.09.05.0Normal sampleResearch 4Beagle × SchnauzerF6 years25.09.05.0Normal sampleResearch 5Beagle × SchnauzerF4 years25.09.05.0Normal sampleAll diagnostic tests (except for an ELISA test
forGiardia) and T-RFLP analyses were conducted on DNA isolated from
fecal samples. DNA of sufficient quality for T-RFLP analysis could not be
isolated from one of two samples from Pet 4 or from Pets 5, 6, 7, or 8.
Diagnostic PCR results are presented for all thirteen dogs: T-RFLP results are
presented for the five research colony dogs and four household pet dogs (Pets
1, 2, 3, and 4). For T-RFLP analysis of fecal microbiota over time, we
collected repeated fecal samples from three household pet dogs to assess
variability of the microbiota based on housing and feeding regimes. As
mentioned above, two of these three dogs experienced diarrhea, one of them
twice. Therefore, we collected samples from these dogs during and after treatment,
if any, with the prescribed antibiotic.


## 2.2. History and Clinical Examination

The overall strategy for sampling of dogs is shown in Figure1. The case definition for a dog with diarrhea was a
dog that presented with acute diarrhea. If dogs presented to the MSU VTH with
diarrhea, we instituted resampling three to five days after completion of
treatment. For one of the two diarrheic household pets studied (Pet 3 in Table 1), two original samples were taken before antibiotic treatment and further
samples were taken during and after antibiotic treatment; for Pet 1 in Table 1,
the initial sample was diarrheic and subsequent samples were taken after resolution of disease, which was not treated.Figure 1
Scheme for sample processing.With cases presenting with signs of acute large bowel diarrhea, the typical MSU small
animal clinic protocol includes a fecal flotation,Giardia test, and
fecal cytology. Treatment usually comprises a short course of metronidazole (10–50 mg/kg BID) and
institution of a low-residue diet. In this study, our protocol involved taking
a history, performing a physical examination, and initiating diagnostic tests
according to standard methods currently employed in the MSU VTH.


## 2.3. Sample Handling and DNA Isolation

Preliminary studies were conducted to define the best
method of handling fecal samples to optimize T-RFLP analysis. Using clean
gloves for each animal, samples from research colony dogs and Pets 1 and 2 were
taken as free catch or rectal samples; samples from other dogs were taken from
the ground immediately after defecation taking care to avoid taking any part of
the sample that touched the ground. Subsamples were taken from the interior of
the fecal mass for analysis. The feces was placed into tryptose soy broth with
15% glycerol, mixed well, aliquoted into at least 4-5 identical
subsamples; three were frozen back at −80 and one had DNA extracted that day.
Samples were subjected to one of the following treatments: holding on ice only
long enough for transport to the laboratory, holding at room temperature for 24
hours prior to DNA extraction, holding on ice for 24 hours prior to DNA
extraction, refrigeration for 24 hours prior to DNA extraction, and freezing
for 24 hours prior to DNA extraction. These conditions were intended to mimic
the possible fates of clinical specimens prior to submission to the
laboratory. DNA could be recovered in
quantities sufficient for diagnostic PCR and T-RFLP analysis from samples
subjected to all treatments, although yields were greater when samples were
held on ice only long enough for transport to the laboratory. Freezing was
preferred when samples could not be processed immediately in order to avoid
changes in microbiota that have been documented in samples held at room or
refrigeration temperatures [36–38].Bacterial
populations were recovered from 200 mg of feces by suspending samples in 300 mM
sucrose solution followed by two low-speed centrifugations as described [39]. Bacteria were then
collected by high-speed centrifugation and the pellets resuspended in 200
microliters 10 mM Tris 1 mM EDTA, pH 8.0. Klijn et al. [39]
reported that this method results in the recovery of over 80% of
aerobic/facultatively anaerobic bacteria able to grow on Columbia blood agar
medium (they did not assay obligately anaerobic bacteria). Similar differential
centrifugation methods have been used to isolate bacterial DNA for microbial
community analysis from digesta from chicken gastrointestinal tracts [40, 41], rat cecal digesta [42], and human feces [43]. Community DNA was isolated from the
harvested bacterial cells using
QIAgen DNeasy Tissue Kit (QIAgen, Valencia, Calif, USA) according to the
manufacturer's instructions for Gram-positive bacteria, including digestion
first with 20 mg/mL lysozyme for one hour at 37°C followed by proteinase K (20 mg/mL) overnight at 55°C; DNA was then purified from the lysates using QIAgen
spin columns.


## 2.4. Screening for Common Pathogens in Normal and Diarrheic Dogs

Fecal samples were screened for parasites by the Cornell-Wisconsin saturated sucrose
flotation technique [44]. Giardia tests were
performed using the ProSpect Giardia-ELISA-microplate assay (Remel, Lenexa, Kan, USA) according to the
manufacturer's instructions. DNA preparations were screened for
the presence of DNA from the following bacterial pathogens by standard
polymerase chain reaction assays using published primer pairs and cycling
conditions: Clostridium perfringens [45], Campylobacter spp. [5], Enterococcus spp. [46], Enterococcus faecium [47], Helicobacter spp. [48], Salmonella spp. [49], and  Brachyspira (Serpulina) spp. [50]. Purified DNA samples from
cultured known bacterial species were used as positive controls for the PCR
assays. In addition, quantitative PCR assays (Q-PCR) were performed using
primers and cycling conditions developed by Rinttilä et al. [51] for Bacteroides spp.
and related organisms, Clostridium group I, and Clostridium group
XIVa. However, Q-PCR assays for Escherichia coli were performed as
published [52]; Q-PCR assays for Enterococcus faecium, and Enterococcus faecalis were performed as described below [53].


## 2.5. T-RFLP Analysis

Terminal restriction fragment polymorphism analysis was conducted using the 516f and
1510r primers, PCR reaction mixture, PCR cycling conditions, and restriction
enzyme digestion conditions described by Nagashima et al. [31], except that reactions were
carried out using 50 ng template DNA in a total volume of 100 μL. The forward primer carried a 6-FAM
fluorescent probe. The PCR products were purified using QIAquick PCR
purification columns (QIAgen; Valencia, Calif, USA) according to the
manufacture's protocol prior to digestion with BslI (New England
Biolabs, Inc., Ipswich, Mass, USA); the resulting fragments were separated by
electrophoresis on an automated DNA sequencer (ABI
Prism 3100) at the MSU Genomic Technology Support Facility. An internal
lane standard (MapMarker1000; BioVentures, Murfreesboro, Tenn, USA) was added to every sample, and
the standard peak sizes were used by the GeneScan Analysis software to compute
peak sizes. Electropherograms were
stored as computer files for later analysis.


## 2.6. T-RFLP Data Analysis

Analysis of T-RFLPBslI peak patterns was conducted as follows. Only peaks
corresponding to DNA fragment lengths between 100 and 990 bp in length, having
a height of at least 25 fluorescent units, and contributing at least 1% of the
total area under the electropherogram were considered; electropherograms having
a total area less than 5000 fluorescence units were not analyzed. Likely
identities of the phylogenetic groups of bacteria detected were determined
manually by comparing peak fragment sizes to fragment sizes assigned to various
bacterial groups by Nagashima et al. [31], allowing for an error of ±1 bp. Peaks that did not fall into the size classes defined by Nagashima et al. [31] were combined to form an
“unknown” class. The identities of the bacterial groups and the range of peak
sizes that contributed to each group are shown in Table 2. The community
profile consisted of a list of the bacterial groups present or absent in a
sample and the % area under the electropherogram contributed by each group.Table 2
Assignment of T-RFLP fragment size classes to bacterial taxa based on data
of Nagashima et al. [31].
Fragment class according to Nagashima et al.[31]Fragment size range (bp)Predominant genusOther genera includedBslI 110110–115NoneClostridium, Eubacterium, Lactobacillus, VeillonellaBslI 124125–128BifidobacteriumNoneBslI 317316–319PrevotellaLactobacillusBslI 332326–338StreptococcusBifidobacterium, Clostridium, Eubacterium, Lactobacillus, PrevotellaBslI 370364–378ClostridiumBacteroides, Bifidobacterium, Eubacterium, Lactobacillus, PrevotellaBslI 469464–473BacteroidesClostridium, Eubacterium, PrevotellaBslI 494487–502ClostridiumEubacterium, Ruminococcus, StreptococcusBslI 520513–519EnterococcusClostridium, Eubacterium, LactobacillusBslI 657655–665Lactobacillus; StreptococcusBacteroides, Clostridium, Enterococcus, Eubacterium, RuminococcusBslI 749748–757ClostridiumEubacterium, Fusobacterium, RuminococcusBslI 853848–854BacteroidesBacteroidesBslI 919911–921RuminococcusEnterococcus, EubacteriumBslI 940935–941EscherichiaClostridium, Eubacterium, Fusobacterium, RuminococcusBslI 955955–960NoneClostridium, Eubacterium, RuminococcusFor cluster
analysis, the % area data were fourth-root transformed, and single linkage cluster
analysis using the Bray-Curtis similarity index was performed on the
transformed data [54]; a dendrogram was
constructed, and its stability was evaluated using the jackknife procedure [55]. These calculations were
performed using utilities made available online by John Brzustowski at http://www2.biology.ualberta.ca/jbrzusto/cluster.php.
The Bray-Curtis similarity index is widely used in community ecology studies
because it is less affected than other indices by differences involving rare,
low abundance organisms and it is thought to perform better with datasets
containing widely differing sets of communities [55, 56]. This index takes into
account both the presence and absence of peaks and differences in the
areas under same-sized peaks in the electropherograms, which indicate
differences in the proportions of a particular organism in two
populations.We also
calculated the descriptive microbial community parameters developed
specifically for molecular ecological fingerprinting by Marzorati et al. [57]; the community parameters
summarize community richness (R0), functional organization (Fo,
evenness), and dynamics (% change and Δt). These parameters were calculated
and interpreted for T-RFLP profiles generated in this study as described in
Marzorati et al. [57], except that the Bray-Curtis
similarity index was used in the calculation of the % change parameter instead
of the similarity index used by Marzorati et al. [57]. Finally, patterns of variability in T-RFLP
profiles for Pet 3 over time were analyzed by the regression method of Collins
et al. [58]. Euclidean distances between
microbial communities at different time points were calculated using utilities
made available online by John Brzustowski at http://www2.biology.ualberta.ca/jbrzusto/cluster.php;
regression analysis was performed using SigmaStat 3.1 (Systat Software, Point Richmond, Calif, USA).


## 2.7. Quantitative Real-Time PCR Method and Analyses

DNA extracted from feces (as
previously described) was used as the template in species-specific Q-PCR assays.Bacteroides/Prevotella/Porphyromonas and Clostridium groups I and XIVa assays were performed using the primer
sequences from Rinttilä et al. [51]. Escherichia coli Q-PCR assays were performed using primer sequences
from Khan et al. [52]; Enterococcus faecalis and Enterococcus faecium Q-PCR assays were performed using primer
sequences from Firmesse et al. [53]. In all assays, 25 μL reactions
were performed in triplicate for each sample with iQ SYBR Green Supermix (Bio-Rad,
Hercules, Calif, USA) and 250 ng of
fecal DNA. The following cycling protocol was used for Clostridium group
I, Clostridium group XIVa, Bacteroides, and E. coli: 95°C
for 3 minutes and 40 repeats of 95°C for 10 seconds, specific annealing
temperature for 30 seconds. Cycling parameters for E. faecium were 95°C,
3 minutes; 40 cycles of 63°C for 10 seconds. Cycling parameters for E.
faecalis were 95°C, 3 minutes; 40 cycles of 64.5°C for 10 seconds. Each
species-specific assay was optimized for primer concentration and annealing
temperature. Bacteroides species
assay used 6.25 pm of each primer per reaction with an annealing temperature of
65°C. E. coli assays used 6.25 pm of
each primer per reaction and an annealing temperature of 63.3°C. Clostridium Groups I and XIVa used 7.5 pm
of each primer per reaction with annealing temperatures of 58.9°C and 57°C,
respectively. All Q-PCR assays included a 6-point standard curve in triplicate (R2>0.90) and three no-template controls containing all other reaction
components on a Bio-Rad iQ5 Real-Time PCR Detection System (Bio-Rad, Hercules, Calif, USA). Three DNA
preparations were purchased for the standard curves: Clostridium
perfringens for Clostridium group I (Sigma Aldrich, St. Louis,
Mo, USA), Ruminococcus productus VPI 4299 for Clostridium group XIVa, and Bacteroides fragilis VPI 2553 (DNA purchased from American Type Culture
Collection, Manassas, Va, USA). Three DNA preparations for the standard curves were prepared in our laboratory
by the CTAB method of Ausubel et al.
[59] from strains E. coli DH5-α, Enterococcus faecalis 19433, and Enterococcus faecium 19434.Bio-Rad iQ5 PCR detection system software (Bio-Rad, Hercules, Calif, USA)
was used to calculate the Ct value for each reaction, the mean Ct value for
each set of triplicates, and the amount of target DNA using values derived from
the standard curves. The statistic PV, which quantifies variability in
population abundance over time, was calculated for each of the organisms
assayed using the Q-PCR data [60].


## 3. Results

### 3.1. Dogs Enrolled in Study

Information on
sex, age, breed, and diet of all dogs enrolled in the study is given in Table1. Five
control dogs were identified that lived in MSU colonies, were fed the same food
daily, and were exercised indoors. These dogs were from a family developed to
study an inherited disorder unrelated to the GI tract. As such, dogs were full
or half siblings, or their parents. We also collected feces from four normal
dogs living in households to assess variability of the microbiota based on
housing and feeding regimes. Of the household pets, two were supervised outside
(e.g., walked on leash), one was allowed to roam freely in a suburban
environment, and one was allowed to roam freely in a rural environment. In
addition, two of the four dogs living in households experienced diarrhea, one
of them twice, after collection of the normal samples. We, therefore, collected
samples from these dogs during and after treatment, if any, with the prescribed
antibiotic.Fecal samples
were screened forGiardia by ELISA. One of two dogs (Pet 8 in Table 1) presenting to the MSU Small Animal
Clinic with diarrhea was positive for Giardia; all others were negative.
Fecal samples were screened for other parasites by fecal flotation; all were
negative. DNA was extracted from each fecal sample and characterized using PCR
for seven known enteric pathogens. Two of the five research colony dogs carried Enterococcus faecium, Campylobacter spp., and Helicobacter spp.
(Research dogs 1 and 5). Two others of the five carried Enterococcus spp. and, Helicobacter spp. (Research dogs 2 and 4). The fifth research
colony dog carried only Enterococcus faecium (Research dog 3).
Diagnostic PCR assays performed on fecal DNA obtained from the seven Giardia-negative
household pets showed that five (Pets 1, 2, 3, 4, and 5) had at least one
sample positive for Enterococcus spp., Helicobacter spp., and Campylobacter spp. during the sampling period; all three organisms were detected
simultaneously in many samples. Pet 6 was positive for Campylobacter spp. and Enterococcus spp. but not Helicobacter spp. Pet 7, which
presented to the MSU Small Animal Clinic with diarrhea, was positive for both Enterococcus spp. and Helicobacter spp. All thirteen dogs were negative for Salmonella spp. and Brachyspira spp.


### 3.2. Bacterial Communities in Research Colony Dogs

Results of T-RFLP analysis of fecal samples from research colony dogs are shown in Figure2. Community composition is shown in Panel (a); for this figure, % areas of peaks
corresponding to the bacterial groups assigned by Nagashima et al. [31] were combined at the taxonomic level of order
as follows: Bifidobacteriales (peak BslI 124), Bacillales (peaks BslI
322, 520, and 657), Bacteroidales (peaks BslI 317, 469, and 853), Clostridiales (peaks BslI 370, 494, 749, 919, and 955), Enterobacteriales (peak BslI 940), and Unknown (all peaks not
classified in one of the previous groups). While a number of the BslI peaks defined by Nagashima et al. [31] contain organisms from more than one order,
inspection of Table 1 in their
publication shows that members of a single genus do dominate almost all peaks.
The taxonomic level of order also captures some aspects of the physiology of
intestinal bacteria that may be important in determining colonic health.T-RFLP analysis of fecal samples from
research colony dogs. Panel (a) community
composition expressed as % area of peaks under the T-RFLP electropherogram;
bacterial groups were combined at the taxonomic level of order. Panel (b) dendrogram
based on Bray-Curtis similarities of community composition among the five dogs;
numbers at nodes indicate percentage of trees having an equivalent node in
jackknife analysis. Panel (c) community richness parameter, Rr. Panel (d)
community functional organization, Fo.
(a)(b)(c)(d)The fecal bacterial community composition of the genetically related research colony dogs
was similar in four of five dogs (Figure2, panels (a) and (b)). Dogs 1, 3, and 5
are housed in the same room and are the three research animals that were
PCR-positive for Enterococcus faecium.
The values of the community richness measure Rr for these communities are shown in Figure 2, Panel (c). These values
were calculated using all peaks in each profile, not the combined order level
data shown in Panel (a); values were comparable to those reported by Marzorati et al. [57] for microbially rich environments such as
soils and sediments. Values of the community functional organization parameter (Fo reflects the “evenness” of
the pattern of the relative abundances of the organisms) are shown in Figure 2,
Panel (d); values ranged from 0.42 to 0.60. Marzorati et al. [57] have characterized Rr values >30 as indicating environments capable of sustaining
large, diverse communities. Fo values
for the research colony dog fecal communities fall around 0.45, a value which
Marzorati et al. [57] have characterized as indicating a balanced
community able to continue functioning properly during perturbations.


### 3.3. Household Pet Dogs

Results of
T-RFLP analysis of fecal communities from two pet dogs (Pets 1 and 2) living in
the same household and followed over time are shown in Figure3. These dogs
were genetically different and were fed different dry diets: an adult diet and
a puppy diet from the same manufacturer. The adult dog (Pet 1) was allowed to
roam freely in a rural environment, while the puppy (Pet 2) was exercised
outdoors under the owners' supervision. The episode of diarrhea in Pet 1 on day
1 was due to dietary indiscretion and resolved by the next day; it was
characterized by a “bloom” of BslI
940 (E. coli). Community compositions
of fecal samples from the two dogs were dissimilar and exhibited considerable
variation over time (Figure 3, Panel (a)). Nevertheless, five of six community
composition patterns for Pet 2 did cluster together in the dendrogram shown in
Figure 3, Panel (b). Values of the richness parameter Rr for Pet 1 ranged from 25 to 50; values of Rr for Pet 2 ranged from 11 to 147 (Figure 3, Panel (c)). These Rr values were generally lower than those obtained for the
research colony dogs. Fo values
ranged from 0.30 to 0.77 for Pet 1 and from 0.39 to 0.53
for Pet 2 (Figure 3, Panel (d)). Fo values for both dogs were more constant than either community composition or Rr values. The community dynamics %
change parameter was calculated for sequential samples (Figure 3, Panel (e));
because the time intervals between samples were not equal, we did not calculate
the rate of change parameter Δt.
Values for Pet 1 ranged from 0.40 to 0.75 and for Pet 2 from 0.45 to 0.86. These % change values are much higher than those reported for other kinds
of microbial communities by Marzorati et
al. [57].T-RFLP analysis of
fecal samples from two pets in a single household. Panel (a) community composition expressed
as % area of peaks under the T-RFLP electropherogram; bacterial groups were
combined at the taxonomic level of order. Panel (b) dendrogram based on
Bray-Curtis similarities of community composition among the samples from the
two dogs; numbers at nodes indicate percentage of trees having an equivalent
node in jackknife analysis. Panel (c) community richness parameter, Rr.
Panel (d) community functional organization, Fo. Panel (e) % change
parameter for community dynamics.
(a)(b)(c)(d)(e)One
T-RFLP profile was obtained from another household pet (Pet 4); this animal was
fed a commercial adult diet and occasional table scraps and allowed to roam
freely in a suburban environment; bothRr and Fo values were low:
6.0 and 0.31, respectively.


### 3.4. Household Pet Dog with Repeated Diarrhea

Results of T-RFLP analysis of fecal samples from a household pet dog (Pet 3) experiencing
two separate episodes of diarrhea are shown in Figure4. This animal was fed a
commercial weight control dry diet two to four times higher in fiber than the
diets of the other dogs in the study, and was consistently supervised by the
owner when outdoors in a suburban environment. At the time of enrollment in the
study, this pet was being treated for osteoarthritis with carprofen at 1.0 mg/kg BID; on day 121 after enrollment, the dosage was increased to 2.0 mg/kg
BID. Moderate anorexia developed on day 151, and the owner began supplementing
the diet in various ways to stimulate appetite; this supplementation continued
throughout the rest of the study. After
the second episode of diarrhea on day 168, treatment with carprofen was discontinued
and treatment with tramadol (2.7 mg/kg TID) was instituted. Tramadol was
discontinued due to vomiting on day 219 and deracoxib (1.4 mg/kg SID) was
initiated; this drug was also not well tolerated and was discontinued on day
233. No further analgesics were given during the study.T-RFLP analysis of
fecal samples from a single pet with two diarrheic episodes. Panel (a) community composition expressed
as % area of peaks under the T-RFLP electropherogram; bacterial groups were
combined at the taxonomic level of order. Panel (b) dendrogram based on
Bray-Curtis similarities of community composition among the samples from this
dog; numbers at nodes indicate percentage of trees having an equivalent node in
jackknife analysis. Panel (c) community richness parameter, Rr. However, Rr is not reported when there was only a single peak ≥1% of
the area under the electropherogram (days 168 and 198); the value of Rr was 0.12 on day 172 and 1.5 on day 221. Panel (d) community functional
organization, Fo. However, Fo is not reported when there was only
a single peak ≥1% of the area under the electropherogram
(days 168 and 198). Panel (e) % change parameter for community dynamics. Panel (f) time lag analysis. Arrows below the X-axis indicate the day of onset of an
episode of diarrhea.
(a)(b)(c)(d)(e)(f)Results of
pathogen-specific PCR assays for this animal are shown in Table3. Campylobacter and Helicobacter spp. were detected by PCR assay in 11 of 15 samples; the Campylobacter spp. PCR assay was positive in two samples taken on the day of onset of the
first episode of diarrhea. Enterococcus faecalis and E. faecium assays were positive following the onset of the first episode of diarrhea. E. faecalis was not detected
subsequently by this assay, while E. faecium levels were below the limit
of detection until the onset of the second episode of diarrhea when the dog
became positive over a course of 30 days.Table 3
Detection of potential pathogens in pet dog with
two diarrheic episodes by standard PCR assay*.
DayStatus**EnterococcusEnterococcusCampylobacterHelicobacterClostridiumfaecalisfaeciumspp.spp.perfringens1N−−++−16N−−−+−61D−−+++67D, M++−−+70N, M++−−−77N−−−−+84N−−−++112N−±−+−133N−−−+−168D−+−−+172D, M−+−++180N−+−++198N−±−++221N−−−++252N−−−++* “−”: negative; “+”: positive; “±”: weak positive. All
fecal flotation and Giardia tests were negative.**N:
normal; D: diarrhea: M: metronidazole treatment.Community composition was similar in the normal samples taken on days 1, 17, 70, 78, 85,
113, and 134. Episodes of diarrhea occurred beginning on days 61 and 168; both
episodes were treated with metronidazole (1st treatment starting on day
65 (14.0 mg/kg BID, for 10 days) and 2nd treatment starting on day 172 (14.0 mg/kg BID for 6 days)), and a brief period on a low-residue diet. Because the
second episode of diarrhea occurred 107 days after the first and the microbiota
returned to its starting composition during the interval, the second episode
was probably not an antibiotic-associated diarrhea. Community composition
returned to its starting composition after the first episode of diarrhea but
not after the second; the two episodes were also different in character, the
first being dominated byEnterobacteriales and Clostridiales and the second by Bacillales. Simple fecal cytology
performed by MSU VTH staff at the onset of the second episode of diarrhea was
read out as bacterial overgrowth. The community did not begin to return to its
previous composition for an extended period after the second episode of
diarrhea. On the last day of sampling, representatives of all the orders
previously present were detected, but their proportions were altered from those
in the normal samples. The dendrogram showing the similarities of the
communities at different times (Figure 4, Panel (b)) also demonstrates this
pattern: most of the samples taken prior to day 168 cluster together and away
from the diarrheic samples and the normal samples taken after the second
episode of diarrhea.Changes in
community richness parameterRr values
are shown in Figure 4, Panel (c). Community richness dropped to a value of 11.2
following institution of metronidazole treatment for the first episode of
diarrhea but rebounded to a high level (460) and then
declined slowly over the next month. Richness was severely reduced during the
second episode of diarrhea and did not return to even moderate levels; repeated changes in medications and diet were made during the
period after the second episode of diarrhea. Changes in Fo values (Figure 4, Panel (d)) were less
pronounced but consistently somewhat lower after the second episode of
diarrhea.Changes
in the community dynamics parameter % change also reflect the events described
above (Figure4, Panel (e)). Large values (0.85 to 0.99) are associated with the
two episodes of diarrhea. Prior to the first episode of diarrhea and after
recovery from it, the % change values ranged from 0.09 to 0.38 and were comparable to those
reported for other kinds of communities by Marzorati et al. [57]. Marzorati et al. characterized %
change values around 0.10 as indicating that the community is stable; new organisms
are able to become established but do not interfere with community function.
Very high % change values were associated with the diarrheic episodes in Pet 3,
and after the second episode, the % change values continued to fluctuate,
indicating that the community did not return to stability. This period of instability coincided with the
period of repeated changes in medications and diet.Temporal
variability in the T-RFLP data was also analyzed using the regression method of
Collins et al. [58] (Figure 4, panel (f)); the period
when diet and medication were constant and the period when both varied were
analyzed separately. The period when
diet and medications were constant, which included the first episode of
diarrhea, exhibited a phase with a positive slope followed by a phase with a
negative slope. This pattern can be interpreted as showing a directional change
in community composition after a perturbation followed by a return to the
starting condition [58]. The period when diet and medications were varied did not yield a
significant regression; according to Collins et al. [58], this result indicates fluctuating
changes in community composition over time.


### 3.5. Q-PCR Analysis of Fecal Samples from a Household Pet Dog Experiencing Repeated Episodes of Diarrhea

To explore further the results for Pet 3
obtained from T-RFLP analysis, we performed quantitative real-time PCR on the same DNA
samples used for T-RFLP. Q-PCR
results are shown in Figure5, Panels (a) to (f). Population variability (PV)
values were high (range: 0.768–0.915) for all
organisms assayed. Clostridium groups I and XIVa were analyzed
separately; group I contains the potential enteric pathogen C. perfringens.
(C. difficile is a member of Clostridium group XI and would not
be detected by these assays.) Both groups were detected by Q-PCR throughout the
sampling period. Clostridium group I levels were relatively constant,
except for an 880-fold increase coincident with the first episode of diarrhea
(day 61); the Clostridiales peaks
comprised 55% of the total area under the electropherogram for that sample in
the T-RFLP analysis (Figure 4(a)), and the BslI 749 peak
comprised 40% of the total area under the electropherogram (data not shown).
The BslI 749 peak is included in the Clostridiales portion of the
bar in Figure 4(a). The expected BslI peak size for Clostridium perfringens
is approximately 750 bp. Once this result was obtained, we performed a specific PCR assay for Clostridium
perfringens [45]. That assay was negative prior to the
first episode of diarrhea, it became strongly positive in the first diarrheic
sample (Table 3), and remained so in all but one sample for about three weeks.
Four weeks after the last positive sample, the assay was negative and remained
so until the onset of the second episode of diarrhea, when it became strongly
positive again. It remained positive throughout the second metronidazole
treatment and was still positive twelve weeks later.Q-PCR analysis of
bacterial groups in fecal samples from a single pet with two diarrheic
episodes. Panel (a) Clostridium group I; Panel (b) Clostridium group XIVa; Panel (c) Bacteroides spp.; Panel (d) E. coli;
Panel (e) E. faecium; Panel (f) E. faecalis. R2 values
for the standard curves were 0.995, 0.986, 0.956, 0.958, 0.980, and 0.998,
respectively. Error bars indicate the standard deviation of triplicate samples.
Lack of a bar indicates that no product was detected in 40 cycles. The sample
for day 252 was exhausted before Q-PCR for E. faecium, E. faecalis, and E.
coli was performed. Population variability (PV) values are shown at the
upper right of each panel.
(a)(b)(c)(d)(e)(f)Clostridium group XIVa levels were more variable and
did not exhibit any pattern with respect to either episode of diarrhea. Levels
of E. coli exhibited a peak on day 112 but also did not exhibit any
pattern with respect to either episode of diarrhea.Levels ofE. faecium and E.
faecalis both rose after the initiation of metronidazole treatment during
both episodes of diarrhea. E. faecium rose 4000-fold between the onset of the first episode of diarrhea (day 61) and
day 77 and 77-fold between the onset of the second episode of diarrhea (day
168) and day 180. E. faecalis rose 7000-fold between the onset of the first episode of diarrhea (day 61) and
day 70 and 1500-fold between the onset of the second episode of diarrhea (day
168) and day 180.Q-PCR assay detectedBacteroides in all samples. Levels of Bacteroides spp. were highest in normal
samples taken during the period when diet and medications were constant. Bacteroides spp. decreased approximately 105-fold during and following the first
episode of diarrhea but returned to the original levels. Levels decreased
approximately 104-fold during the second episode of diarrhea and
fluctuated thereafter. This result
is in marked contrast to the T-RFLP assay, which seldom detected Bacteroides at levels exceeding 1% of the total area under the electropherogram.


## 3.1. Dogs Enrolled in Study

Information on
sex, age, breed, and diet of all dogs enrolled in the study is given in Table1. Five
control dogs were identified that lived in MSU colonies, were fed the same food
daily, and were exercised indoors. These dogs were from a family developed to
study an inherited disorder unrelated to the GI tract. As such, dogs were full
or half siblings, or their parents. We also collected feces from four normal
dogs living in households to assess variability of the microbiota based on
housing and feeding regimes. Of the household pets, two were supervised outside
(e.g., walked on leash), one was allowed to roam freely in a suburban
environment, and one was allowed to roam freely in a rural environment. In
addition, two of the four dogs living in households experienced diarrhea, one
of them twice, after collection of the normal samples. We, therefore, collected
samples from these dogs during and after treatment, if any, with the prescribed
antibiotic.Fecal samples
were screened forGiardia by ELISA. One of two dogs (Pet 8 in Table 1) presenting to the MSU Small Animal
Clinic with diarrhea was positive for Giardia; all others were negative.
Fecal samples were screened for other parasites by fecal flotation; all were
negative. DNA was extracted from each fecal sample and characterized using PCR
for seven known enteric pathogens. Two of the five research colony dogs carried Enterococcus faecium, Campylobacter spp., and Helicobacter spp.
(Research dogs 1 and 5). Two others of the five carried Enterococcus spp. and, Helicobacter spp. (Research dogs 2 and 4). The fifth research
colony dog carried only Enterococcus faecium (Research dog 3).
Diagnostic PCR assays performed on fecal DNA obtained from the seven Giardia-negative
household pets showed that five (Pets 1, 2, 3, 4, and 5) had at least one
sample positive for Enterococcus spp., Helicobacter spp., and Campylobacter spp. during the sampling period; all three organisms were detected
simultaneously in many samples. Pet 6 was positive for Campylobacter spp. and Enterococcus spp. but not Helicobacter spp. Pet 7, which
presented to the MSU Small Animal Clinic with diarrhea, was positive for both Enterococcus spp. and Helicobacter spp. All thirteen dogs were negative for Salmonella spp. and Brachyspira spp.


## 3.2. Bacterial Communities in Research Colony Dogs

Results of T-RFLP analysis of fecal samples from research colony dogs are shown in Figure2. Community composition is shown in Panel (a); for this figure, % areas of peaks
corresponding to the bacterial groups assigned by Nagashima et al. [31] were combined at the taxonomic level of order
as follows: Bifidobacteriales (peak BslI 124), Bacillales (peaks BslI
322, 520, and 657), Bacteroidales (peaks BslI 317, 469, and 853), Clostridiales (peaks BslI 370, 494, 749, 919, and 955), Enterobacteriales (peak BslI 940), and Unknown (all peaks not
classified in one of the previous groups). While a number of the BslI peaks defined by Nagashima et al. [31] contain organisms from more than one order,
inspection of Table 1 in their
publication shows that members of a single genus do dominate almost all peaks.
The taxonomic level of order also captures some aspects of the physiology of
intestinal bacteria that may be important in determining colonic health.T-RFLP analysis of fecal samples from
research colony dogs. Panel (a) community
composition expressed as % area of peaks under the T-RFLP electropherogram;
bacterial groups were combined at the taxonomic level of order. Panel (b) dendrogram
based on Bray-Curtis similarities of community composition among the five dogs;
numbers at nodes indicate percentage of trees having an equivalent node in
jackknife analysis. Panel (c) community richness parameter, Rr. Panel (d)
community functional organization, Fo.
(a)(b)(c)(d)The fecal bacterial community composition of the genetically related research colony dogs
was similar in four of five dogs (Figure2, panels (a) and (b)). Dogs 1, 3, and 5
are housed in the same room and are the three research animals that were
PCR-positive for Enterococcus faecium.
The values of the community richness measure Rr for these communities are shown in Figure 2, Panel (c). These values
were calculated using all peaks in each profile, not the combined order level
data shown in Panel (a); values were comparable to those reported by Marzorati et al. [57] for microbially rich environments such as
soils and sediments. Values of the community functional organization parameter (Fo reflects the “evenness” of
the pattern of the relative abundances of the organisms) are shown in Figure 2,
Panel (d); values ranged from 0.42 to 0.60. Marzorati et al. [57] have characterized Rr values >30 as indicating environments capable of sustaining
large, diverse communities. Fo values
for the research colony dog fecal communities fall around 0.45, a value which
Marzorati et al. [57] have characterized as indicating a balanced
community able to continue functioning properly during perturbations.


## 3.3. Household Pet Dogs

Results of
T-RFLP analysis of fecal communities from two pet dogs (Pets 1 and 2) living in
the same household and followed over time are shown in Figure3. These dogs
were genetically different and were fed different dry diets: an adult diet and
a puppy diet from the same manufacturer. The adult dog (Pet 1) was allowed to
roam freely in a rural environment, while the puppy (Pet 2) was exercised
outdoors under the owners' supervision. The episode of diarrhea in Pet 1 on day
1 was due to dietary indiscretion and resolved by the next day; it was
characterized by a “bloom” of BslI
940 (E. coli). Community compositions
of fecal samples from the two dogs were dissimilar and exhibited considerable
variation over time (Figure 3, Panel (a)). Nevertheless, five of six community
composition patterns for Pet 2 did cluster together in the dendrogram shown in
Figure 3, Panel (b). Values of the richness parameter Rr for Pet 1 ranged from 25 to 50; values of Rr for Pet 2 ranged from 11 to 147 (Figure 3, Panel (c)). These Rr values were generally lower than those obtained for the
research colony dogs. Fo values
ranged from 0.30 to 0.77 for Pet 1 and from 0.39 to 0.53
for Pet 2 (Figure 3, Panel (d)). Fo values for both dogs were more constant than either community composition or Rr values. The community dynamics %
change parameter was calculated for sequential samples (Figure 3, Panel (e));
because the time intervals between samples were not equal, we did not calculate
the rate of change parameter Δt.
Values for Pet 1 ranged from 0.40 to 0.75 and for Pet 2 from 0.45 to 0.86. These % change values are much higher than those reported for other kinds
of microbial communities by Marzorati et
al. [57].T-RFLP analysis of
fecal samples from two pets in a single household. Panel (a) community composition expressed
as % area of peaks under the T-RFLP electropherogram; bacterial groups were
combined at the taxonomic level of order. Panel (b) dendrogram based on
Bray-Curtis similarities of community composition among the samples from the
two dogs; numbers at nodes indicate percentage of trees having an equivalent
node in jackknife analysis. Panel (c) community richness parameter, Rr.
Panel (d) community functional organization, Fo. Panel (e) % change
parameter for community dynamics.
(a)(b)(c)(d)(e)One
T-RFLP profile was obtained from another household pet (Pet 4); this animal was
fed a commercial adult diet and occasional table scraps and allowed to roam
freely in a suburban environment; bothRr and Fo values were low:
6.0 and 0.31, respectively.


## 3.4. Household Pet Dog with Repeated Diarrhea

Results of T-RFLP analysis of fecal samples from a household pet dog (Pet 3) experiencing
two separate episodes of diarrhea are shown in Figure4. This animal was fed a
commercial weight control dry diet two to four times higher in fiber than the
diets of the other dogs in the study, and was consistently supervised by the
owner when outdoors in a suburban environment. At the time of enrollment in the
study, this pet was being treated for osteoarthritis with carprofen at 1.0 mg/kg BID; on day 121 after enrollment, the dosage was increased to 2.0 mg/kg
BID. Moderate anorexia developed on day 151, and the owner began supplementing
the diet in various ways to stimulate appetite; this supplementation continued
throughout the rest of the study. After
the second episode of diarrhea on day 168, treatment with carprofen was discontinued
and treatment with tramadol (2.7 mg/kg TID) was instituted. Tramadol was
discontinued due to vomiting on day 219 and deracoxib (1.4 mg/kg SID) was
initiated; this drug was also not well tolerated and was discontinued on day
233. No further analgesics were given during the study.T-RFLP analysis of
fecal samples from a single pet with two diarrheic episodes. Panel (a) community composition expressed
as % area of peaks under the T-RFLP electropherogram; bacterial groups were
combined at the taxonomic level of order. Panel (b) dendrogram based on
Bray-Curtis similarities of community composition among the samples from this
dog; numbers at nodes indicate percentage of trees having an equivalent node in
jackknife analysis. Panel (c) community richness parameter, Rr. However, Rr is not reported when there was only a single peak ≥1% of
the area under the electropherogram (days 168 and 198); the value of Rr was 0.12 on day 172 and 1.5 on day 221. Panel (d) community functional
organization, Fo. However, Fo is not reported when there was only
a single peak ≥1% of the area under the electropherogram
(days 168 and 198). Panel (e) % change parameter for community dynamics. Panel (f) time lag analysis. Arrows below the X-axis indicate the day of onset of an
episode of diarrhea.
(a)(b)(c)(d)(e)(f)Results of
pathogen-specific PCR assays for this animal are shown in Table3. Campylobacter and Helicobacter spp. were detected by PCR assay in 11 of 15 samples; the Campylobacter spp. PCR assay was positive in two samples taken on the day of onset of the
first episode of diarrhea. Enterococcus faecalis and E. faecium assays were positive following the onset of the first episode of diarrhea. E. faecalis was not detected
subsequently by this assay, while E. faecium levels were below the limit
of detection until the onset of the second episode of diarrhea when the dog
became positive over a course of 30 days.Table 3
Detection of potential pathogens in pet dog with
two diarrheic episodes by standard PCR assay*.
DayStatus**EnterococcusEnterococcusCampylobacterHelicobacterClostridiumfaecalisfaeciumspp.spp.perfringens1N−−++−16N−−−+−61D−−+++67D, M++−−+70N, M++−−−77N−−−−+84N−−−++112N−±−+−133N−−−+−168D−+−−+172D, M−+−++180N−+−++198N−±−++221N−−−++252N−−−++* “−”: negative; “+”: positive; “±”: weak positive. All
fecal flotation and Giardia tests were negative.**N:
normal; D: diarrhea: M: metronidazole treatment.Community composition was similar in the normal samples taken on days 1, 17, 70, 78, 85,
113, and 134. Episodes of diarrhea occurred beginning on days 61 and 168; both
episodes were treated with metronidazole (1st treatment starting on day
65 (14.0 mg/kg BID, for 10 days) and 2nd treatment starting on day 172 (14.0 mg/kg BID for 6 days)), and a brief period on a low-residue diet. Because the
second episode of diarrhea occurred 107 days after the first and the microbiota
returned to its starting composition during the interval, the second episode
was probably not an antibiotic-associated diarrhea. Community composition
returned to its starting composition after the first episode of diarrhea but
not after the second; the two episodes were also different in character, the
first being dominated byEnterobacteriales and Clostridiales and the second by Bacillales. Simple fecal cytology
performed by MSU VTH staff at the onset of the second episode of diarrhea was
read out as bacterial overgrowth. The community did not begin to return to its
previous composition for an extended period after the second episode of
diarrhea. On the last day of sampling, representatives of all the orders
previously present were detected, but their proportions were altered from those
in the normal samples. The dendrogram showing the similarities of the
communities at different times (Figure 4, Panel (b)) also demonstrates this
pattern: most of the samples taken prior to day 168 cluster together and away
from the diarrheic samples and the normal samples taken after the second
episode of diarrhea.Changes in
community richness parameterRr values
are shown in Figure 4, Panel (c). Community richness dropped to a value of 11.2
following institution of metronidazole treatment for the first episode of
diarrhea but rebounded to a high level (460) and then
declined slowly over the next month. Richness was severely reduced during the
second episode of diarrhea and did not return to even moderate levels; repeated changes in medications and diet were made during the
period after the second episode of diarrhea. Changes in Fo values (Figure 4, Panel (d)) were less
pronounced but consistently somewhat lower after the second episode of
diarrhea.Changes
in the community dynamics parameter % change also reflect the events described
above (Figure4, Panel (e)). Large values (0.85 to 0.99) are associated with the
two episodes of diarrhea. Prior to the first episode of diarrhea and after
recovery from it, the % change values ranged from 0.09 to 0.38 and were comparable to those
reported for other kinds of communities by Marzorati et al. [57]. Marzorati et al. characterized %
change values around 0.10 as indicating that the community is stable; new organisms
are able to become established but do not interfere with community function.
Very high % change values were associated with the diarrheic episodes in Pet 3,
and after the second episode, the % change values continued to fluctuate,
indicating that the community did not return to stability. This period of instability coincided with the
period of repeated changes in medications and diet.Temporal
variability in the T-RFLP data was also analyzed using the regression method of
Collins et al. [58] (Figure 4, panel (f)); the period
when diet and medication were constant and the period when both varied were
analyzed separately. The period when
diet and medications were constant, which included the first episode of
diarrhea, exhibited a phase with a positive slope followed by a phase with a
negative slope. This pattern can be interpreted as showing a directional change
in community composition after a perturbation followed by a return to the
starting condition [58]. The period when diet and medications were varied did not yield a
significant regression; according to Collins et al. [58], this result indicates fluctuating
changes in community composition over time.


## 3.5. Q-PCR Analysis of Fecal Samples from a Household Pet Dog Experiencing Repeated Episodes of Diarrhea

To explore further the results for Pet 3
obtained from T-RFLP analysis, we performed quantitative real-time PCR on the same DNA
samples used for T-RFLP. Q-PCR
results are shown in Figure5, Panels (a) to (f). Population variability (PV)
values were high (range: 0.768–0.915) for all
organisms assayed. Clostridium groups I and XIVa were analyzed
separately; group I contains the potential enteric pathogen C. perfringens.
(C. difficile is a member of Clostridium group XI and would not
be detected by these assays.) Both groups were detected by Q-PCR throughout the
sampling period. Clostridium group I levels were relatively constant,
except for an 880-fold increase coincident with the first episode of diarrhea
(day 61); the Clostridiales peaks
comprised 55% of the total area under the electropherogram for that sample in
the T-RFLP analysis (Figure 4(a)), and the BslI 749 peak
comprised 40% of the total area under the electropherogram (data not shown).
The BslI 749 peak is included in the Clostridiales portion of the
bar in Figure 4(a). The expected BslI peak size for Clostridium perfringens
is approximately 750 bp. Once this result was obtained, we performed a specific PCR assay for Clostridium
perfringens [45]. That assay was negative prior to the
first episode of diarrhea, it became strongly positive in the first diarrheic
sample (Table 3), and remained so in all but one sample for about three weeks.
Four weeks after the last positive sample, the assay was negative and remained
so until the onset of the second episode of diarrhea, when it became strongly
positive again. It remained positive throughout the second metronidazole
treatment and was still positive twelve weeks later.Q-PCR analysis of
bacterial groups in fecal samples from a single pet with two diarrheic
episodes. Panel (a) Clostridium group I; Panel (b) Clostridium group XIVa; Panel (c) Bacteroides spp.; Panel (d) E. coli;
Panel (e) E. faecium; Panel (f) E. faecalis. R2 values
for the standard curves were 0.995, 0.986, 0.956, 0.958, 0.980, and 0.998,
respectively. Error bars indicate the standard deviation of triplicate samples.
Lack of a bar indicates that no product was detected in 40 cycles. The sample
for day 252 was exhausted before Q-PCR for E. faecium, E. faecalis, and E.
coli was performed. Population variability (PV) values are shown at the
upper right of each panel.
(a)(b)(c)(d)(e)(f)Clostridium group XIVa levels were more variable and
did not exhibit any pattern with respect to either episode of diarrhea. Levels
of E. coli exhibited a peak on day 112 but also did not exhibit any
pattern with respect to either episode of diarrhea.Levels ofE. faecium and E.
faecalis both rose after the initiation of metronidazole treatment during
both episodes of diarrhea. E. faecium rose 4000-fold between the onset of the first episode of diarrhea (day 61) and
day 77 and 77-fold between the onset of the second episode of diarrhea (day
168) and day 180. E. faecalis rose 7000-fold between the onset of the first episode of diarrhea (day 61) and
day 70 and 1500-fold between the onset of the second episode of diarrhea (day
168) and day 180.Q-PCR assay detectedBacteroides in all samples. Levels of Bacteroides spp. were highest in normal
samples taken during the period when diet and medications were constant. Bacteroides spp. decreased approximately 105-fold during and following the first
episode of diarrhea but returned to the original levels. Levels decreased
approximately 104-fold during the second episode of diarrhea and
fluctuated thereafter. This result
is in marked contrast to the T-RFLP assay, which seldom detected Bacteroides at levels exceeding 1% of the total area under the electropherogram.


## 4. Discussion

Screening for specific pathogens by PCR revealed that most animals carried one or more
potential enteric pathogens in their fecal microbiota even when they had no
clinical signs. Thus, many cases of “spontaneous” diarrhea in dogs—and by extension,
sporadic diarrhea in humans—may be caused by
organisms already present in the GI tract following perturbation of the
microbiota by an environmental factor rather than by a pathogen acquired from
another source [6, 61]. The hypothesis that
alterations in the microbiota may inhibit or facilitate disease processes has
been invoked in the context of chronic inflammatory bowel diseases; our results
support the idea that there may be a significant role for the microbiota in
acute infectious disease processes. Other clinical and experimental studies
suggest that the relative balance of aggressive and protective bacterial
species is altered in inflammatory diseases such as Crohn's disease (CD),
ulcerative colitis (UC), and pouchitis. In a review
of current work in this area, it was postulated that overly aggressive
immune responses to a subset of commensal (nonpathogenic) enteric bacteria in
genetically predisposed individuals result in disease [62]. Recently, Frank et al.
showed that CD patients, UC patients, and noninflamed controls had
statistically significantly different microbiotas based on culture-independent
rRNA sequence analysis of cloned libraries [63]. Because it was based on
surgical samples of colon, this study provided a survey of gut-wall associated
microbiota relevant to Inflammatory Bowel Disease. Here, as in all studies
using methods based on SSU rRNA, bacterial “numbers” were recognized to be
relative estimates reflecting gene copy numbers and not indicative of
causation. However, microbiota surveys can provide candidates for hypothesis
testing of causation. In our study, fecal samples could be argued to best
represent “diagnostic” samples that would be taken from a host presenting with
acute diarrhea. It is acknowledged that further work will be needed to document
the ability of readily available fecal samples to represent different locations
within the colon to document the etiologies of these diarrheas [64].The influence of diet and medication on the intestinal microbiota has been studied directly
in animals and humans [17, 18, 21, 29, 62]. Although it was not our
intent to study such effects, our results confirm that the composition of the
intestinal microbiota is quite sensitive to changes in environmental factors
such as changes in diet and/or medications as well as exposure to the
microbiotas of other animals. The relatively consistent microbiotas of the
research colony dogs are in marked contrast to the fluctuations observed in Pet
1, which roamed freely in a rural environment. The microbiotas of Pets 2 and 3,
which were more closely supervised when out of doors, showed less variability
than that observed in Pet 1 but more than in the research colony dogs. Finally, fluctuations in the microbiota of
Pet 3 became much more pronounced when diet and medication were changed.Comparison of results from T-RFLP and Q-PCR results for Pet
3 showed that both methods can detect variation in the microbiota associated
with events such as diarrheal episodes and changes in diet and medication. The
extensive variability in the abundances of the different groups of organisms
evident in the T-RFLP data was also evident in the Q-PCR results for individual
groups and organisms; population variability (PV) values for all organisms
assayed by Q-PCR were high. This result is not surprising given the wide range
of target DNA concentrations detected by this assay (lowest detected level,3.6×10−6 ng for E. faecalis;
highest detected level, 1.8×102 ng for Bacteroides).The T-RFLP analysis indicated that there was a large
increase inClostridiales, including the BslI 749 bp peak defined
by Nagashima et al. [31], on day 61, the day of onset of the first episode of diarrhea. Q-PCR
analysis indicated an increase in Clostridium group I, of
which C. perfringens is a member, which coincided with the onset of the first
episode of diarrhea. Diagnostic PCR assays for C. perfringens showed
that this organism was temporally associated with the onset of both episodes of
diarrhea. But because the time intervals that elapsed between samples were
long, we cannot determine whether the increases in Clostridium group I
or the detection of C. perfringens reflected causes or consequences of the episodes of diarrhea. The data thus
suggest but do not prove that the illness was caused by a member of Clostridium group I, possibly C. perfringens. However, C. perfringens remained at detectable levels during the period when
diet and medications varied. This result suggests that the instability of the
microbial community during this period facilitated the growth of this potential
pathogen.T-RFLP analysis also indicated large increases inBacillales; which includes lactobacilli, streptococci, and enterococci; subsequent to metronidazole treatment. In Q-PCR analysis, both E. faecium and E. faecalis exhibited repeated substantial increases after the
initiation of metronidazole treatment, and after the second episode of
diarrhea, E. faecium levels did not return to those seen at the
beginning of the study. These results suggest that, in view of the potential of
both E. faecium and E. faecalis to have deleterious effects on
the GI tract, the use of metronidazole as a first-line treatment for canine
diarrhea should be re-evaluated.Perturbations inBacteroides spp. levels associated with the two episodes of diarrhea were also apparent;
levels of these organisms decreased during both episodes of diarrhea and became
unstable during the period when diet and medication were varied. Since Bacteroides spp. are major components of
the colon microbial community and essential to its function, such fluctuations
might be expected to have repercussions for colon health.The discrepancy
between the two methods in detecting the genusBacteroides in this
animal would be most simply explained as a relative inability of the universal
eubacterial 16S primers used to bind to the 16S rDNA sequences of the
particular Bacteroides spp. predominating in that dog compared to the
more specific primers used in the Q-PCR assay. However, members of the Bacteroidales were detected by the primers used in T-RFLP analysis in four of the five
research colony dogs and in Pets 1 and 2. BLAST searches
indicated that the region of homology between the Nagashima et al. [31] reverse primer to the 16S
rDNA sequence of (1) some but not all strains of Bacteroides eggerthii,
(2) some but not all strains of B. stercoris, and (3) some but not all
strains of B. caccae consists only of the seven bases from nucleotide 11
to nucleotide 17 of the 19-base primer. This limited homology was even present
in the 16S rDNA sequences of the type strains of B. stercoris and B.
caccae. No PCR product would be obtained from DNA of these strains. Also, BLAST
searches indicated that the 16S primers used for the Q-PCR studies [51] would be expected to amplify
rDNA of all strains of these three species. However, B. eggerthii, B. stercoris, and B. caccae are
found in humans; in a cloned library study, sequences closely related to B.
stercoris were obtained from dogs [20]. Of the Bacteroides spp. sequences obtained from dogs in the latter study, one was very similar to
that of B. stercoris, three were similar to that of B. vulgatus, and
four were not similar to those of any of the published Bacteroides spp.
used in the analysis. The same study also indicated that the Bacteroides spp. sequences from the fecal microbial communities of humans, dogs, cats, and
gulls clustered together and separately from those of cattle and elk.We applied the
community characterization schema proposed by Marzorati et al. [57] to the dog fecal bacterial
communities studied here and related them to what we know about the management
and clinical presentation of the dogs. The research colony dog communities were
characterized by high richness and intermediate “balanced” levels of functional organization.
Because of the constancy of the environment of these dogs, we predict that
their communities would experience low-to-medium dynamics similar to those
observed in normal samples from Pet 3. The communities of Pets 1, 2, and 4 were
generally characterized by lower richness, balanced functional organization,
and high levels of dynamic change for Pets 1 and 2.The normal
communities of Pet 3 prior to and following the first episode of diarrhea were
characterized by high richness, medium levels of dynamic change, and balanced
functional organization, while the diarrheic samples were characterized by low
richness, high levels of dynamic change, and low levels of functional
organization. Communities in the normal samples taken following the second
episode of diarrhea were characterized by continued low richness, fluctuating
levels of dynamic change, and somewhat lower levels of functional organization
than previous normal samples. The fluctuating levels of dynamic change were
temporally correlated with changes in diet and medication. Time lag analysis
indicated that samples taken when diet and medication were constant—the initial
samples, samples taken during the first episode of diarrhea, and samples taken
prior to the second episode of diarrhea—showed a
recognizable pattern of disturbance followed by a return to the initial
condition. Samples taken when diet and medications were varied—beginning with
the onset of the second episode diarrhea and continuing to the end of the study—did not exhibit
any directional changes but instead showed random fluctuation. The general
agreement between these complementary analyses suggests that concepts from
macroecology will be useful in interpreting data from microbial communities.According to
Marzorati et al. [57], the level of the community
richness parameter Rr is indicative of the carrying capacity of the
environment; diet is one obvious environmental variable that might affect the
carrying capacity in the GI tract. The similar values of Rr obtained for
research colony dogs fed and housed under controlled conditions supports this
idea. However, Pet 2 was genetically related to the research colony dogs and
was fed a similar diet, but exhibited lower community richness. This free-roaming dog probably had a much
more variable intake than the research colony dogs, so values for apparent
carrying capacity might have been influenced by the highly dynamic nature of
the microbial community in this animal. A similar effect can be seen in the richness parameter values for Pet 3; Rr varied widely subsequent to perturbation and periods of dynamic
change in the community due to episodes of diarrhea.The level of dynamic change also varied considerably in Pets 1, 2, and 4, and was
correlated with environmental factors in that Pets 1 and 2 experienced both
more environmental variation and consistently higher levels of change in
community composition than did Pet 3 during healthy periods. The community functional organization
parameterFo is held by Marzorati et al. [57] to reflect the resistance of the community
structure to perturbation. If Fo values do predict community resiliency, then such resiliency may explain why
both Pet 1 and Pet 2, which had relatively robust Fo values, were mainly
non-diarrheic in spite of having high levels of dynamic change and
substantially shifting community compositions. In the case of Pet 1, the latter
phenomena may have been due to varied intake of substances from the
environment; in the case of Pet 2, a puppy, these phenomena may have been due
to maturation processes in the GI tract. In addition, after the second episode of diarrhea in Pet 3, Fo values declined and the community appeared to become less stable under the
influence of changing diet and medication regimes; this observation further
supports the connection between functional organization and resiliency.Studies with larger sample sizes are required to substantiate these apparent
correlations in a rigorous way. Also, more
work is clearly needed to delineate the variability of the microbiota of the
healthy GI tract before embarking on detailed studies of disease states.
However, based on these observations, we would predict that if the normal or
background variability is substantial, it may prove exceedingly difficult to
detect relevant changes in heterogeneous populations such as individuals
enrolled in clinical trials.


## 5. Conclusions

We hypothesized
that dogs have a stable composition of the colon microbial community and that
episodes of diarrhea lead to long lasting changes in community composition
and/or function; furthermore, treatment for specific
pathogens can compound these effects. Outbred
monogastric animals like dogs can serve as easily manipulable models to address
approaches for problems of the human GI tract. Thus, the microbiota of dogs was
studied during diarrheic episodes and compared to those of healthy control dogs
to make a preliminary assessment of the contribution of members of the
microbiota to acute diarrheal disease processes. We found that (1) four of five
dogs living in an environment expected to provide the least exposure to factors
that might alter the GI tract microbiota had similar microbiotas, (2) the
microbiotas of dogs kept in more variable environments were correspondingly
more variable, (3) acute episodes of diarrhea resulted in large-scale changes
in the GI tract microbiota, and (4) when the diet and medications of a dog
having a previously stable microbiota were changed repeatedly, the GI tract
microbiota also changed repeatedly, ultimately reducing richness. The high
levels of variability we encountered in the pet dogs indicate that descriptive
population-based microbiota studies may be so fraught with variation within and
between individuals that meaningful patterns and changes may be hard to
distinguish from the “noise.” Either
longitudinal studies of individuals under relatively constant environmental regimes
(Pet 3) or model-based studies of groups of individuals under strictly
controlled environments (research colony dogs) with planned experimental
interventions could be expected to yield interpretable results. The
consistency of the microbial communities in the research colony dogs and the
changes we were able to observe in Pet 3 indicate that it is possible to
establish baseline starting conditions and that the methods employed in these
studies can be used to
detect and delineate changes in fecal microbial communities. We expect
these considerations derived from this useful animal model to apply with equal
force to studies in humans.



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*Source: 149694-2009-01-13.xml*