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Appl Environ Microbiol. May 2009; 75(10): 3055–3061.
Published online Mar 20, 2009. doi:  10.1128/AEM.00101-09
PMCID: PMC2681665

Development of cpn60-Based Real-Time Quantitative PCR Assays for the Detection of 14 Campylobacter Species and Application to Screening of Canine Fecal Samples[down-pointing small open triangle]

Abstract

Campylobacter species are important organisms in both human and animal health. The identification of Campylobacter currently requires the growth of organisms from complex samples and biochemical identification. In many cases, the condition of the sample being tested and/or the fastidious nature of many Campylobacter species has limited the detection of campylobacters in a laboratory setting. To address this, we have designed a set of real-time quantitative PCR (qPCR) assays to detect and quantify 14 Campylobacter species, C. coli, C. concisus, C. curvus, C. fetus, C. gracilis, C. helveticus, C. hyointestinalis, C. jejuni, C. lari, C. mucosalis, C. rectus, C. showae, C. sputorum, and C. upsaliensis, directly from DNA extracted from feces. By use of a region of the cpn60 (also known as hsp60 or groEL) gene, which encodes the universally conserved 60-kDa chaperonin, species-specific assays were designed and validated. These assays were then employed to determine the prevalence of Campylobacter species in fecal samples from dogs. Fecal samples were found to contain detectable and quantifiable levels of C. fetus, C. gracilis, C. helveticus, C. jejuni, C. showae, and C. upsaliensis, with the majority of samples containing multiple Campylobacter species. This study represents the first report of C. fetus, C. gracilis, C. mucosalis, and C. showae detection in dogs and implicates dogs as a reservoir for these species. The qPCR assays described offer investigators a new tool to study many Campylobacter species in a culture-independent manner.

Campylobacter species are important in both the medical and veterinary arenas. Currently, of the 19 Campylobacter species that have been classified (8; http://www.bacterio.cict.fr/), 10 or 11 species/subspecies have well-established associations with animal or human diseases, respectively (4, 20). Of significance is the role campylobacters play as the most common cause of enteric disease worldwide (34). Although most enteric disease is attributed to Campylobacter jejuni and C. coli, advances in cultivation techniques have revealed that other “unusual” campylobacters, such as C. upsaliensis, C. concisus, C. lari, and C. hyointestinalis, may be more commonly associated with gastrointestinal (GI) disease than was previously recognized (6, 17, 21, 27). Beyond being associated with enteric disease, C. rectus and C. gracilis have been directly associated with periodontal disease (24, 31, 32), and of note regarding livestock, C. fetus is an important venereal disease (2). Furthermore, a number of Campylobacter species appear to be part of the normal microbiota of healthy animals; for example, C. jejuni, C. coli, C. helveticus, C. upsaliensis, and C. lari are part of the normal microbiota of domestic dogs and cats (11, 15, 30).

Quick and reliable identification and discrimination of Campylobacter species remain challenging. Culture from clinical specimens is often very sensitive but limited by several factors. While a number of different selective media have been specifically designed for Campylobacter species isolation, the fastidious nature and varied requirements of members of this genus mean that there is no single growth condition that is optimal for all species. Transport time from sampling to processing is also an important consideration, especially when sampling is done at some distance from the laboratory or a large number of samples are collected simultaneously. Prolonged time between sample collection and processing can reduce the success of Campylobacter isolation. Processing times as short as 4 h from the time of sample collection may be required for isolation of multiple Campylobacter species (15, 16).

Routine identification of cultured Campylobacter species is based on biochemical profiling (29). This, however, has become increasingly problematic, as phenotypic profiles used to distinguish species, such as the hippurate hydrolysis assay to discriminate C. jejuni and C. coli, have become varied within species (29). There are also cases where multiple species share the same basic biochemical characteristics (such as C. mucosalis and C. concisus), leading to disputes over the definitive identities of isolated Campylobacter strains (9, 18, 19). The similar phenotypic and biochemical profiles of other closely related gram-negative curved rods, such as Arcobacter and Helicobacter spp., may further complicate the identification of Campylobacter isolates.

To circumvent some of the limitations of biochemical profiling, various DNA-based identification methods have been developed. Methods with high discrimination potential for Campylobacter strains, like macrorestriction analysis of the whole genome by pulsed-field gel electrophoresis or of certain loci by restriction fragment length polymorphism, amplified fragment length polymorphism, and multilocus sequence typing, are available (20). However, these identification techniques are best suited for short- and long-term epidemiological studies in which the identity of an individual strain is of interest for source tracking or population phylogenies. These techniques also require considerable operator skill to generate reproducible patterns for comparison or the sequencing of multiple regions for identification. For targeted identification, a number of PCR strategies, both conventional and quantitative, based on the 16S rRNA gene or unspecified species- or subspecies-specific regions, have been designed (3, 22, 23, 26, 28). Unfortunately, strategies to date have focused on the detection of a single species or subspecies (26, 28), the genus as a whole (3), or a subset of species to the exclusion of others (22, 23). At the present, there is simply no way to quickly and reliably detect and identify many Campylobacter species.

We have designed a set of real-time quantitative PCR (qPCR) assays to identify and quantify 14 Campylobacter species, C. coli, C. concisus, C. curvus, C. fetus, C. gracilis, C. helveticus, C. hyointestinalis, C. jejuni, C. lari, C. mucosalis, C. rectus, C. showae, C. sputorum, and C. upsaliensis, directly from DNA extracted from feces. These assays are based on the cpn60 gene, which encodes the universal 60-kDa chaperonin (also known as HSP60 or GroEL). The utility of this target has been demonstrated through its ability to identify and differentiate Campylobacter species from each other and from Helicobacter and Arcobacter species (12). This target is also supported by the reference database cpnDB (13; http://cpndb.cbr.nrc.ca), a curated collection of cpn60 sequences from thousands of type strains, reference strains, and clinical isolates. To validate and test our qPCR assays, we applied them in a survey of fecal samples from a population of dogs from a rural community of northern Saskatchewan, Canada.

MATERIALS AND METHODS

Cloning of cpn60 UT regions from Campylobacter species.

The cpn60 universal target (UT) region from 14 species of Campylobacter, corresponding to nucleotides 274 to 828 of the Escherichia coli cpn60 gene (10), were amplified from genomic DNA (Table (Table1)1) by using the degenerate, universal cpn60 PCR primers H279 and H280 as previously described (12). The 555-bp UT product from each species was ligated into pGEM-T Easy (Invitrogen) and used to transform E. coli JM109 cells (Invitrogen). Single transformants were isolated, and the resulting vectors were sequenced to confirm their identities.

TABLE 1.
Targets and primers used in this study

Design of species-specific qPCR primer sets.

SignatureOligo (LifeIntel Inc., Port Moody, British Columbia, Canada) was used to identify regions within the cpn60 UT unique to each Campylobacter species (12). The specificities of the PCR primers were initially verified by comparison to all of the reference strain and clinical isolate sequences in cpnDB by using BLASTn (1) configured for short, nearly exact matches. Regions that allowed PCR products from 100 to 200 bp, with no secondary structure elements, were selected as suitable primer binding sites. PCR primers were synthesized by Invitrogen (Burlington, Ontario, Canada) or Integrated DNA Technologies (Toronto, Ontario, Canada).

Conventional PCR.

For initial qPCR primer optimization and specificity testing (see below), conventional PCR was used. Conventional PCR consisted of 1× PCR buffer [10 mM KCl, 10 mM (NH4)2SO4, 20 mM Tris-HCl (pH 8.75), 0.1% Triton X-100, 0.1 mg/ml bovine serum albumin], 2.0 mM MgSO4, 200 μM deoxynucleoside triphosphate, a 400 nM concentration of each primer, 2.5 U high-purity Taq DNA polymerase (UBI Life Sciences, Saskatoon, Saskatchewan, Canada), and 2 μl template and was carried out in a final volume of 50 μl. An Eppendorf Mastercycler thermal cycler was used with an initial denaturing at 95°C for 5 min, followed by 40 cycles of 30 s at 94°C, 30 s at the appropriate annealing temperature (Table (Table1),1), and 30 s at 72°C and a final extension at 72°C for 10 min. Products were visualized on an agarose gel by using standard techniques.

Real-time qPCR.

Each reaction mixture consisted of 1× iQ SYBR green supermix (Bio-Rad), 400 nM concentrations of the appropriate primers (with the exception of the JH0087/JH0088 primer set, each primer of which was used at a final concentration of 200 nM; Table Table1),1), and 2 μl of template DNA in a final volume of 25 μl. A MyiQ thermocycler (Bio-Rad) was used for all reactions with the following program: 95°C for 3 min, followed by 40 cycles of 15 s at 95°C, 15 s at the appropriate annealing temperature (Table (Table1),1), and 15 s at 72°C. A final melt at 95°C for 1 min was done prior to a melt curve analysis (55°C to 95°C in 0.5°C steps for 10-s increments). All reactions were performed in duplicate. Fluorescence signals were measured every cycle at the end of the annealing step and continuously during the melt curve analysis. The resulting data were analyzed using iQ5 optical system software (Bio-Rad).

Canine fecal sample collection and DNA extraction.

For assay validation purposes, fecal samples were collected from two urban pet dogs from different households, a 1.5-year-old purebred Boxer and a 4-year-old Shetland sheepdog, and designated healthy dog samples (HDS) 1 and 2, respectively. Both dogs were considered healthy by their owners and had no history of antibiotic treatment for at least 6 months. Fresh feces was kept at refrigerated temperatures for transport (less than 12 h) and stored at −80°C until processed.

A survey collection of canine fecal samples was undertaken in a rural northern Saskatchewan community with a large population of free-ranging dogs. Fecal samples were collected from the ground in three distinct neighborhoods. No attempt was made to establish the age or specific source of each sample. Samples were chilled for transport and stored at −80°C until processed.

Total bacterial DNA was extracted from 0.19 to 0.22 g of thawed feces by using the QIAamp DNA stool minikit (Qiagen) per the manufacturer's instructions. DNA was eluted into a final volume of 200 μl.

Determination of qPCR assay specificity.

In order to evaluate whether each species-specific primer pair would amplify only the Campylobacter species of interest, a conventional PCR was conducted with each primer pair with three test templates. The positive-control template for each primer set was the cloned cpn60 UT from the appropriate Campylobacter species. The second template was a pool of all 14 E. coli strains containing the cpn60 UT plasmid constructs from each Campylobacter species. This mixture is referred to as the “All Campy” panel. For both the positive-control panel and the All Campy panel, PCR was performed directly on E. coli cell lysates. The third template set was made up of genomic DNA or plasmid containing cloned cpn60 UT regions from 23 GI bacteria, including C. jejuni (Table (Table2)2) (5). This mixture was designed to simulate a complex fecal bacterial DNA extract and is referred to as the GI mixed panel.

TABLE 2.
Panel of GI tract organisms for primer validation

Determination of qPCR assay sensitivity.

To determine what effect any inhibitors would have on the sensitivities of our assays, plasmids containing cpn60 UT were spiked into neat, 1:10, and 1:100 dilutions of HDS1 and HDS2 fecal DNA extracts, and qPCR detection values were compared to those obtained for the plasmid target in water. Comparisons were corrected for any assay with detectable Campylobacter levels in HDS1 and HDS2 before spiking to account for background Campylobacter spp. present.

RESULTS

Optimization of qPCR conditions.

To establish the optimal conditions for each qPCR assay, a series of tests were performed with each primer set using the assay's corresponding positive-control plasmid in water as the template. The optimal annealing temperature for each assay was determined by conventional gradient PCR. The highest temperature that generated significant specific product, as visualized on an agarose gel, was selected as the annealing temperature for the assay; these values are listed in Table Table1.1. A qPCR standard curve was then generated for each assay to confirm that linear amplification could be achieved through 101 to 108 copies/reaction. The melt curve from each standard curve product was examined to ensure that the obtained PCR product's melting temperature was within 0.5°C of the predicted PCR product melting temperature (Table (Table1).1). In the case of the JH0087/JH0088 primer set (for C. fetus detection), a significant primer dimer melt peak was observed (data not shown). The concentration of these primers was reduced from 400 nM to 200 nM to reduce this phenomenon and resulted in cleaner melt curves with no loss in assay detection range. The qPCR standard curve products were also visualized on an agarose gel to confirm that they were the correct size (Table (Table1)1) and sequenced to confirm their identities.

Determination of qPCR assay specificity.

Conventional PCR with three test templates was done to evaluate the specificity of each assay. The goal was to determine if each primer set would amplify only its target species from a complex template mixture comprised of either E. coli cells containing the positive-control plasmids from all 14 Campylobacter species being tested (All Campy panel) or DNA that contained the cpn60 target regions from a wide range of common GI microorganisms, including C. jejuni (GI mixed panel; Table Table2).2). For each primer pair, a single PCR product was generated from both the positive-control plasmid and the All Campy panel. The PCR product sizes, determined from an agarose gel, were the same for both templates and consistent with the size expected in each case (Table (Table1;1; data not shown). The All Campy panel product was sequenced and confirmed to be an unambiguous sequence from the target species only for each assay (data not shown). When each primer pair was tested against the GI mixed panel, as expected, the only primer pair that generated a PCR product was JH0039/JH0040. The identity of the product was confirmed by sequencing to be the C. jejuni cpn60 target region (data not shown).

Determination of qPCR assay sensitivity.

It has been established that fecal DNA extracts often contain PCR inhibitors that can reduce the sensitivity of qPCR (25). To determine what effect an actual fecal DNA extract would have on the sensitivity of our assays, the positive-control plasmid for each assay was spiked into the fecal DNA extracts from HDS1 and HDS2. Since HDS1 and HDS2 were actual dog samples, expected to contain Campylobacter DNA, if any assay detected a target in the HDS sample alone (unspiked), that value was mathematically subtracted from all sensitivity calculations.

Standard curves for C. coli (JH0041/JH0042), C. jejuni (JH0039/JH0040), and C. lari (JH0015/JH0016) were generated by calculating the copies of plasmid detected per reaction in water and compared to the same number of copies of plasmid detected per reaction in a spiked fecal background. Figure S1 in the supplemental material illustrates that the addition of a fecal extract background resulted in detection of 101 to 105 fewer copies/reaction of plasmid than in a water background. To establish if dilution of the neat fecal DNA extract would improve assay sensitivity, 1:10 and 1:100 dilutions of HDS1 and HDS2 were made and spiked with known copy numbers of plasmid. When the standard curves for C. coli, C. jejuni, and C. lari were retested, a maximum loss of 103 copies/reaction was seen, with the vast majority of detection loss being within 101 copies/reaction of the value for the plasmid in water (see Fig. S1 in the supplemental material). There was no significant improvement in detection between the 1:10 and 1:100 dilutions. Therefore, the sensitivities of the remaining 11 assays were determined by spiking the appropriate positive-control plasmids into 1:10 HDS1 and 1:10 HDS2 only.

For each assay, a standard curve for the plasmid in water was generated, and the percentage of the known copy number/reaction of plasmid in a 1:10 HDS background detected was determined (Fig. (Fig.1)1) . Given that a known number of targets were spiked into each reaction mixture, no qPCR inhibition corresponds to 100% detection of that target. At the lowest levels, a total of 102 copies/reaction was undetectable (0%) for C. coli, C. concisus, C. helveticus, C. hyointestinalis, C. jejuni, C. mucosalis, C. rectus, and C. showae assays with 1:10 HDS1 and C. coli, C. helveticus, C. hyointestinalis, C. lari, C. mucosalis, and C. rectus assays with 1:10 HDS2. The remaining assays detected 79% to 114% of the spiked target in 1:10 HDS1 and 89% to 150% in 1:10 HDS2. At 103 copies/reaction, only C. helveticus and C. rectus assays were unable to detect anything (0%) in 1:10 HDS1, while C. coli, C. helveticus, C. rectus, and C. sputorum assays had 0% detection in 1:10 HDS2. The remaining assays were able to detect 64% to 98% of the spiked target in 1:10 HDS1 and 76% to 113% in 1:10 HDS2. By 104 copies/reaction, all 14 assays could detect 85 to 115% of the spiked target, with the exception of C. coli in 1:10 HDS2 (77% quantifiable detection), and at 105 to 107 copies/reaction, all assays had quantifiable detection within 10% of 100% detection (Fig. (Fig.11).

FIG. 1.
Detection sensitivity of each qPCR Campylobacter assay in a 1:10 HDS1 (A) or 1:10 HDS2 (B) fecal DNA extract background. Each point represents the known number of copies/reaction of positive-control plasmid spiked into background and the percentage of ...

Campylobacter species detected in healthy city canine fecal samples.

As part of the sensitivity assay validation process, HDS1 and HDS2 were tested with all 14 Campylobacter qPCR assays. Figure Figure22 illustrates the species and quantities of Campylobacter DNA detected per reaction. Within HDS1, six species were detected (C. gracilis, C. helveticus, C. hyointestinalis, C. jejuni, C. mucosalis, and C. showae), at a range of 3.33 × 100 to 2.73 × 102 copies/reaction. For HDS2, five species were detected (C. helveticus, C. jejuni, C. mucosalis, C. showae, and C. upsaliensis), at a range of 5.13 × 101 to 6.94 × 103 copies/reaction. Given the volume of template used (2 μl of a 1:10 dilution of a stock derived from ~0.2 g of feces), this translates into a range of 1.66 × 104 to 3.47 × 107 copies/g of feces for an individual Campylobacter species present in either of these two dogs.

FIG. 2.
Campylobacter spp. detected in HDS1 and HDS2. Asterisks indicate species previously reported to be found in dogs. The given copies detected/reaction are averages for duplicate reactions.

Campylobacter species detected in rural northern Saskatchewan canine fecal samples.

The second study group consisted of a population of free-ranging domestic dogs from a rural community in northern Saskatchewan, Canada. The diet on which these dogs subsist is difficult to determine but likely includes both human waste products and meat/organs from hunted game. To investigate the Campylobacter species present in feces from these animals, 60 fecal samples were collected from three distinct neighborhoods in the community. Due to the fact that feces was collected from the ground, it was not possible to determine the age and origin of the samples or the environmental conditions to which they were exposed prior to collection.

Initially, all 60 samples were tested with the assays for C. jejuni, C. upsaliensis, and C. helveticus (previously found in dogs [7, 14, 30]), as well as C. rectus (not reported or anticipated to be found in dogs), to determine if any Campylobacter DNA could be detected and, if so, if there were equal distributions of results across the three neighborhoods. Assay results were divided into three categories: qPCR values that reproducibly fell within the linear quantifiable range of the standard curve run with each assay were considered quantifiable (numbers of copies/reaction were recorded), qPCR values that were reproducibly above zero but below the linear range of the standard curve were recorded as detectable but not quantifiable (D/Q), and qPCR values that were not reproducibly above zero were deemed undetectable. C. jejuni, C. upsaliensis, and C. helveticus were each detectable (both quantifiable and D/Q) from all three neighborhoods, while C. rectus was D/Q in only one sample analyzed (see Table S1 in the supplemental material; summarized in Table Table3).3). As there were equal distributions of positive samples between neighborhoods (see Table S1 in the supplemental material), the remaining 10 assays were prescreened against neighborhood 1 (20 samples). Any assay that obtained a quantifiable positive sample or more than one D/Q positive sample was expanded to include all 60 samples. In total, seven assays were tested against the entire sample set (additional assays were for C. fetus, C. gracilis, and C. showae), and the complete results are shown in Table S1 in the supplemental material and summarized in Table Table33.

TABLE 3.
Summary of Campylobacter spp. detected in rural northern Saskatchewan canine fecal samples

DISCUSSION

The first objective of this study was to design and validate a set of real-time qPCR assays to detect and quantify 14 Campylobacter species. We chose these 14 since they are the well-established species in the genus, and many of these species are associated with disease in humans and other animals. The second objective was to use these assays to survey the Campylobacter species present in canine fecal samples collected from a rural community in northern Saskatchewan, Canada. This type of survey is a prime example of a situation in which conventional Campylobacter detection has limitations. For Campylobacter detection in a diagnostic laboratory, fecal samples are usually examined by direct microscopy and cultured for Campylobacter growth on selective media. While gram-negative curved rods might be visualized by microscopy, their presence is not diagnostic, and there is no way to distinguish or identify to the species level Campylobacter, Helicobacter, and Arcobacter bacteria visually. Also, the time between sample collection and processing, as well as the conditions under which the samples were during transport to the laboratory, can have a significant impact on the likelihood that viable organisms will be cultivated. Even once a fecal sample is plated, campylobacters other than C. coli, C. jejuni, and C. lari are often too sensitive to the antibiotics in most conventional selective media to be isolated in routine laboratories (6). In addition, species such as C. concisus, C. curvus, C. rectus, and C. sputorum and some strains of C. hyointestinalis and C. upsaliensis also need incubation in a hydrogen-enriched microaerobic atmosphere to enable recovery (6, 21). Thus, it is often the case that gram-negative curved rods can be seen in a fecal sample by microscopy, while culturing of the sample yields nothing viable (Musangu Ngeleka, personal communication). The likelihood of isolating Campylobacter from our canine fecal samples, which were exposed to the environment for unknown lengths of time prior to collection and were expected to contain several non-C. jejuni species of Campylobacter, necessitated a detection technique that did not require growth of the organism for identification.

To carry out culture-free identification and species identification of Campylobacter, we chose to utilize real-time qPCR based on SYBR green detection. The SYBR green system was chosen as the qPCR detection system over probe-based technologies because SYBR assays require fewer reagents and allowed the assays to be run as either real-time or conventional PCR (increasing their utility as either quantitative or present/absent testing, respectively). Given our goal to create a set of research laboratory tools, we designed and validated these assays with practical research standards and not diagnostic laboratory standards. As well, multiplexing of our 14 assays was considered, but given the practical necessity of limiting multiplex reactions to three or four targets, it was deemed better to have each assay optimized individually. With this foundation, it would be straightforward to multiplex a group of assays for future applications that focus on a subset of Campylobacter species.

The 14 qPCR assays described in this report offer a number of advantages over culture identification. Each assay was specific for its target Campylobacter species, having no cross-reactivity with the other 13 Campylobacter species tested or with a wide range of common intestinal microorganisms (Table (Table2).2). As well, each Campylobacter assay targets a single species independently, which is of particular utility when multiple Campylobacter species are suspected to be present in a sample. For multiple species to be identified by culture, individual colonies must be biochemically profiled. If two species differ in prevalence by a single log, at least 10 colonies would have to be typed to hopefully detect one colony from the second species present. With culture studies that have specifically looked for multiple species of Campylobacter in a single sample typing anywhere from 2 to 33 isolates (average of 12 isolates) per sample (15, 16), the presence of multiple Campylobacter species could have been overlooked. From our analysis, canine fecal sample no. 128 was found to contain 2.6 × 103 copies/reaction of C. upsaliensis, 6.6 × 102 copies/reaction of C. gracilis, and D/Q levels of both C. helveticus and C. jejuni (see Table S1 in the supplemental material). Given this range, even under ideal conditions, it is unlikely that C. helveticus or C. jejuni would have been isolated and identified by culture. Finally, the time it takes to perform an assay, from DNA extraction of the sample to qPCR analysis, could easily be carried out in a single workday, which represents a significant reduction in processing time compared to the amount of time needed for culture.

Unfortunately, the limitation of the assays is in their sensitivity. As with any PCR-based technique, only a very small proportion of the original sample ends up in each reaction. For our methodology, the equivalent of 0.2 mg of feces is tested per reaction. This means that the theoretical detection limit (1 copy of target DNA/reaction) is 5 × 103 copies/g of feces. However, given the inherent inhibitory nature of fecal extracts, most reactions need at least 102 to 103 copies of target DNA/reaction for reliable detection (Fig. (Fig.1).1). This pushes the practical detection limit of these assays into the range of 105 to 106 copies/g. Although this seems like a large number, bacterial counts in feces can reach levels of 1011 organisms/g (33). As well, there is a general lack of understanding of the relationship between Campylobacter counts and pathogenesis/disease that merits further investigation. Regardless, multiple Campylobacter species were still detected from most of the fecal samples tested (Fig. (Fig.33).

FIG. 3.
Distribution of multiple Campylobacter species per sample.

A number of novel observations can be made from the analysis of the canine fecal samples in this study. First, to our knowledge, C. fetus, C. gracilis, C. mucosalis, and C. showae have not been previously reported to be found in dogs. This is significant, as C. gracilis is a known human pathogen and was the most prevalent Campylobacter species isolated from the rural northern dog samples (65% of samples were positive) and quantifiable in one of the two city dogs (HDS1). Whether this prevalence of C. gracilis is specific to Saskatchewan or this organism has simply not been cultured in previous studies (preventing detection) remains to be determined. As well, C. fetus also had a reasonable detection rate (17% of samples positive) in the rural northern dog samples, implicating dogs as a possible reservoir for this livestock pathogen. Alternatively, C. coli and C. lari have been found at low levels in European dogs (7, 14) but were completely undetectable in our samples.

When Campylobacter was detected, the majority of samples contained multiple species (Fig. (Fig.3).3). Out of 60 rural northern dog samples, only 15 samples had no detectable levels of any Campylobacter sp., and there were 9 samples that contained one species, 15 samples that contained 2 species, and 21 samples with 3 or more species (Fig. (Fig.3).3). This was consistent with the case for the two city dog samples, in which HDS1 and HDS2 contained six and five detectable species of Campylobacter, respectively. These findings reinforce previous work showing that multiple species of Campylobacter are quite common in dogs (15) and expand the number and diversity of species detected substantially. In addition, these findings represent the first attempt at quantification of these Campylobacter populations and set the stage for further study into the differences in Campylobacter population profiles between healthy and diarrheic animals. Finally, this collection of Campylobacter qPCR assays allows for new research opportunities when investigating possible Campylobacter reservoirs.

Supplementary Material

[Supplemental material]

Acknowledgments

We gratefully acknowledge Swee Han Goh for providing genomic DNA samples from Campylobacter type strains and Tim Dumonceaux for the GI mixed panel DNA. As well, the assistance of the veterinary students from the Western College of Veterinary Medicine for canine fecal collection was greatly appreciated.

B.C. was supported by a Saskatchewan Health Research Foundation (SHRF) Research Fellowship. K.M.M. was supported by the Merck-Merial Veterinary Scholar Program. This work was supported by SHRF Establishment and Equipment grants (to J.E.H.).

Footnotes

[down-pointing small open triangle]Published ahead of print on 20 March 2009.

Supplemental material for this article may be found at http://aem.asm.org/.

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