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Appl Environ Microbiol. 2009 October; 75(19): 6275–6281.
Published online 2009 August 21. doi:  10.1128/AEM.00499-09
PMCID: PMC2753054

Spatiotemporal Homogeneity of Campylobacter Subtypes from Cattle and Sheep across Northeastern and Southwestern Scotland[down-pointing small open triangle]

Abstract

Source attribution using molecular subtypes has implicated cattle and sheep as sources of human Campylobacter infection. Whether the Campylobacter subtypes associated with cattle and sheep vary spatiotemporally remains poorly known, especially at national levels. Here we describe spatiotemporal patterns of prevalence, bacterial enumeration, and subtype composition in Campylobacter isolates from cattle and sheep feces from northeastern (63 farms, 414 samples) and southwestern (71 farms, 449 samples) Scotland during 2005 to 2006. Isolates (201) were categorized as sequence type (ST), as clonal complex (CC), and as Campylobacter jejuni or Campylobacter coli using multilocus sequence typing (MLST). No significant difference in average prevalence (cattle, 22%; sheep, 25%) or average enumeration (cattle, 2.7 × 104 CFU/g; sheep, 2.0 × 105 CFU/g) was found between hosts or regions. The four most common STs (C. jejuni ST-19, ST-42, and ST-61 and C. coli ST-827) occurred in both hosts, whereas STs of the C. coli ST-828 clonal complex were more common in sheep. Neither host yielded evidence for regional differences in ST, CC, or MLST allele composition. Isolates from the two hosts combined, categorized as ST or CC, were more similar within than between farms but showed no further spatiotemporal trends up to 330 km and 50 weeks between farm samples. In contrast, both regions yielded evidence for significant differences in ST, CC, and allele composition between hosts, such that 65% of isolates could be attributed to a known host. These results suggest that cattle and sheep within the spatiotemporal scales analyzed are each capable of contributing homogeneous Campylobacter strains to human infections.

Campylobacter species are the largest cause of bacterial intestinal infection in the developed and developing world (3). Almost all reported human Campylobacter infections in the United Kingdom are caused by Campylobacter jejuni, which accounts for approximately 92% of cases, and Campylobacter coli, which accounts for most of the rest (8). Campylobacter species are carried asymptomatically in a wide range of host animals and excreted into the environment in feces (23). Humans can be infected by several routes including consumption of contaminated water (14) or food (23); indeed, case control studies indicate that consumption of poultry meat is a risk factor (11, 12, 28), but other foods including unpasteurized milk (33) and meat from cattle and sheep contaminated at the abattoir might be important (30).

Cattle and sheep on farms are major hosts of Campylobacter, with up to 89% of cattle herds (31) and up to 55% of sheep flocks (26) being infected. The prevalence of C. jejuni and C. coli combined, estimated at the level of individual animals from fecal specimens, is 23 to 54% in cattle (22, 25) and up to 20% in sheep (37). Campylobacter enumeration in feces shed from individual animals ranges from <102 to 107 CFU/g in both hosts (31), and the concentration shed varies with time. Meat products of cattle and sheep, by contrast, have generally lower levels of Campylobacter contamination. Prevalence values are 0.5 to 4.9% in surveys of retail beef (11a, 17, 36) and 6.9 to 12.6% in surveys of retail lamb and mutton (17, 35).

Clinical Campylobacter strains can be attributed to infection sources in animals by comparing subtype frequencies in clinical cases with those in different candidate sources, including cattle, sheep, pigs, and the physical environment. Campylobacter subtype data sets are most transferable when subtypes are defined as sequence type (ST) using multilocus sequence typing (MLST). Three recent MLST-based studies based in northwestern England (34), mainland Scotland (29), northeastern Scotland (32), and New Zealand (24) have used source attribution models to infer the source of human clinical infection. The results suggest that retail chicken is the source with the highest (55 to 80%) attribution while cattle and sheep combined are ranked second (20 to 40%). These attribution models require further empirical validation but appear to be showing broadly similar results.

Attribution of human Campylobacter infections to cattle and sheep raises the question of whether Campylobacter subtypes infecting farm cattle and sheep are generally homogeneous or tend to have spatiotemporal structure. Regarding spatial differences, isolates of C. jejuni from a 100-km2 study of farmland area with dairy cattle and sheep in northwestern England displayed increased genetic similarity up to 1 km apart but no further trend over distances of 1 to 14 km apart (7), and isolates from three dairy cattle farms 2 or 5 km apart in the same area demonstrated differences in the frequencies of strains of clonal complexes (CCs) ST-42 and ST-61 (15). Regarding temporal differences, isolates of C. jejuni from five dairy cattle farms in the same area demonstrated differences in the frequency of strains of CC ST-61 between the spring and summer of 2003 (15). Lastly, regarding host-associated strains, STs of CCs ST-21, ST-42, and ST-61 are associated with cattle, and the more limited data for STs from sheep also show the presence of ST-21 and ST-61 (7, 15).

The larger-scale spatiotemporal structure of Campylobacter strains from cattle and sheep is poorly known. The main aims of the present study were (i) to characterize C. jejuni and C. coli from cattle and sheep from two distinct geographical Scottish regions in terms of Campylobacter prevalence and enumeration and C. jejuni and C. coli ST composition and (ii) to estimate the extent of host association of C. jejuni and C. coli STs from cattle versus sheep.

MATERIALS AND METHODS

Farm selection and sample collection.

Fecal samples from cattle and sheep were collected from 134 farms in northeastern and southwestern Scotland between August 2005 and September 2006 (Fig. (Fig.1).1). Sheep were predominantly outdoor (>95%), while cattle were mostly beef cattle (approximately 75%) with the majority of dairy farms being in the southwestern region. The farms were chosen as follows. The postcode districts (indicated by the first four digits of the postcode) in the rural areas were tabulated, the central town or village was identified, farmers listed in the local telephone directory under that location were contacted by phone, and one willing farmer in each postcode district was randomly chosen for each collection visit. Northeastern and southwestern areas were visited concurrently. The aim on each farm visit was to collect eight fecal specimens comprising four from cattle and four from sheep; however, often only one host species was present and the availability of samples therefore varied throughout the study. Intensive collection trips focused on three or four neighboring postcode districts, and the trips continued on a monthly cycle throughout the study. In all cases, fresh fecal samples (25 g) were collected, transported to the laboratory, and chilled (4°C) for analysis within 2 h of reaching the laboratory. Median herd size was 30 (7.2% of herds contained >100 animals), while for sheep the median flock size was 40 (22.5% of flocks contained >100 animals).

FIG. 1.
Spatial distribution of cattle (a) and sheep (b) farms sampled. Maps were created using ArcView 3.3 (ESRI, Redlands, CA). (This work is based on data provided through EDINA UKBORDERS with the support of the ESCR and JISC and uses boundary material which ...

Identification and enumeration of Campylobacter.

Fecal aliquots (10 g) were homogenized (10:90 [wt:vol]) in Campylobacter enrichment broth (see below), and 0.1-ml decimal dilutions were plated directly onto modified Campylobacter blood-free selective agar base (CCDA base; catalog no. CM0739; Oxoid, United Kingdom) with CCDA selective supplement (SR 155; Oxoid, United Kingdom) for target enumeration (minimum count was therefore 100 CFU/g). The presence or absence of Campylobacter was ascertained by incubating the remaining enrichment broth microaerobically in an atmosphere of 10% CO2, 5% O2, and balance N2 in 100-ml volumes of nutrient broth base (Mast, Bootle, United Kingdom) with 5% horse blood and growth supplement (Mast Selectavial SV61); amphotericin (2 μg/ml), cefoperazone (15 μg/ml), trimethoprim (10 μg/ml), polymyxin B (2,500 IU/liter), and rifampin (rifampicin) (5 μg/ml) were added, and the broths were incubated for 2 days at 37°C (4). All antimicrobials were purchased from Sigma-Aldrich UK. Enrichment broths (0.1 ml) were plated on to mCCDA agar incubated microaerobically for 2 days at 37°C (minimum detection level was therefore 0.1 CFU/g). Colonies were presumptively identified as Campylobacter microscopically (Gram stain) and by agglutination with Microscreen latex (Microgen, Camberley, United Kingdom). Individual colonies were stored (at −80°C in nutrient broth, with glycerol added to 15% [vol/vol]) for MLST. Campylobacter presence was confirmed using isolate ST as determined by MLST.

Genotyping.

Archived isolates were plated from the frozen state onto mCCDA agar and incubated microaerobically for 48 h at 37°C. Bacterial DNA was prepared and MLST was performed, both as previously described (10). Sequences were assembled using STARS software available at http://pubmlst.org, and novel alleles and STs were submitted to the Campylobacter MLST database at this website. Values and confidence intervals (CIs) of Simpson's diversity index (D) were calculated using the online calculator V-DICE (www.hpa-bioinformatics.org.uk/cgi-bin/DICI/DICI.pl).

Analysis of prevalence.

Campylobacter prevalence was determined. Comparisons were performed between groups of categories listed in Table Table1.1. Statistical significance in prevalence between groups was performed using Fisher's exact test, with odds ratios, CIs, and P values being calculated. Odds ratios (2) were defined as the odds of a Campylobacter being found in a particular group divided by the odds of being found in a different group. An odds ratio value of >1 indicates a higher prevalence in the first source.

TABLE 1.
Campylobacter prevalence among individual animals and farms compared between hosts and regions

Analysis of bacterial enumeration.

Campylobacter enumerations were estimated for each sample collected, and averages were calculated by group (i.e., by both host species and geographical area). Briefly, the difference of the average counts for each pair of groups was calculated and tested for significance in Visual Basic Application under Excel (VBAE) by comparing this difference with a distribution of 10,000 differences obtained by randomizing the data without replacement (19).

Analysis of genetic distance between populations.

Genetic distance, d1, between pairs of groups was calculated as described by Manly (20):

equation M1

where pi and qi are the proportions of a particular genotype found in each of the animal groups under comparison. When d1 is 1, there are no genotypes in common, and when d1 is 0, the two animal groups have the same distribution of genotypes. Genetic distance was determined at the level of the CC, ST, and allele (for the allele level, the right side of the equation was modified to sum the contribution across all seven MLST alleles, which was then divided by seven). The statistical significance of the genetic distance was found using the randomization test method as described above (19).

Analysis of host association.

Structure software (27) was used to assign isolates to animal hosts by using MLST allele data. The methodology used was a modification of that described previously (21). Briefly, a nonadmixture model with uncorrelated gene frequencies between populations was used. A jackknife method (15,000 iterations of the program, implemented in C++) was used in attributing unknown MLST isolates to animal sources, and the probabilities of attribution were determined.

Spatiotemporal variation of genotypes.

A pairwise comparison was performed to determine whether isolates collected closer together in space and time were genetically more similar to each other. Cattle and sheep isolates were combined, and similarity was analyzed for isolates categorized as CC or ST. Briefly, the proportion of genetically similar pairs was determined for each element of a space-time grid. This was then plotted to visualize the spatiotemporal pattern of genetic similarity. Significance (randomization) tests were developed to determine whether the proportion of similar genotypes collected from the same farm at the same time was different from a distribution generated from isolates selected at random. All P values obtained by statistical techniques were corrected by sequential Bonferroni correction where multiple comparisons were carried out. The VBAE programs used are available by request.

RESULTS

Campylobacter prevalence and enumeration.

Campylobacter prevalence of individual cattle or sheep from northeastern or southwestern Scotland was 22 to 26%, and the percentage of farms with positive animals was 50 to 61 (Table (Table1).1). There was no evidence that the prevalence among individuals or the percentage of positive farms differed significantly either between any of these host region groups or when the data were pooled across the two regions or across hosts (Fisher's exact tests; all P values > 0.05). C. jejuni prevalence in cattle (22.9%) was significantly higher than that in sheep (14.7%) by χ2 test (P < 0.001). Conversely, C. coli prevalence in cattle (2.4%) was significantly lower than that in sheep (6.9%) by χ2 test (P < 0.01). Enumeration of Campylobacter showed that most animals were shedding low concentrations: only 4% of cattle and 11% of sheep feces contained >100 CFU/g (Fig. (Fig.2).2). Enumeration values pooled across both regions averaged 2.7 × 104 CFU/g in cattle and 2.0 × 105 CFU/g in sheep. There was no evidence that enumeration values differed significantly between hosts or between regions (randomization tests, P > 0.05 after Bonferroni correction).

FIG. 2.
Frequency distributions of the concentrations of Campylobacter in cattle (a) and sheep (b) feces from northeastern and southwestern Scotland.

Campylobacter STs.

The 201 Campylobacter isolates yielded 50 STs, of which 16 were previously unreported (see the supplemental material) and 27 were singletons (Table (Table2).2). The four most common STs overall were ST-61 (17.9%), ST-827 (12.4%), ST-42 (9.0%), and ST-19 (9.0%), and these occurred in both hosts and both regions. Campylobacter coli was significantly more common in sheep (15.4% of isolates) than in cattle (4.5%; Fisher's exact test; P = 0.004). ST diversity was high for the four host region groups (D values: cattle, northeastern = 0.885 [95% CI, 0.842 to 0.927]; cattle, southwestern = 0.920 [95% CI, 0.892 to 0.948]; sheep, northeastern = 0.899 [95% CI, 0.860 to 0.938]; sheep, southwestern = 0.892 [95% CI, 0.851 to 0.934]), but there was no evidence for significant differences between the groups.

TABLE 2.
Campylobacter genotypes by animal host and region

Genetic distances of Campylobacter subtypes between regions and hosts.

There was no evidence for any significant difference in either ST, CC, or allele composition between Campylobacter isolates from each region, either within each host or pooled between hosts (Table (Table3).3). The single possible exception (ST composition in northeastern versus southwestern Scotland regions) was not significant after Bonferroni correction. In contrast, there was evidence at all three levels of molecular resolution that Campylobacter isolates from cattle differed significantly from isolates from sheep (Table (Table3).3). Cattle and sheep isolates were also significantly different within northeastern but not southwestern Scotland.

TABLE 3.
Nei's genetic distance and attribution scores between regions and animal hosts

Levels of correct assignment to region were only marginally greater than 50%, both within each host and pooled between hosts (Table (Table3),3), consistent with the results of the genetic distance analysis. Levels of correct assignment to host were higher, particularly at allele level, where 65% of isolates were correctly assigned.

Spatiotemporal differences among Campylobacter subtypes.

Campylobacter isolates collected from the same farm on the same day showed 1.5-fold (CC)- and 2.0-fold (ST)-higher matches of identical genotypes (by pairwise comparison) than did other isolates collected at different space and/or time points (Fig. (Fig.3).3). The increased similarity within farm-day was significant for both CC (randomization tests, P < 0.0001) and ST (P < 0.0001). It was also found that cattle and sheep on the same farm had a proportion of types similar to that of cattle and sheep on different farms (approximately 8%).

FIG. 3.
Spatiotemporal variation in CC (a) and ST (b), for cattle and sheep isolates combined. The horizontal and vertical axes show the differences in space and time between isolates, respectively. The intensity of shading indicates the degree of similarity ...

DISCUSSION

The present study demonstrates the uniformity in prevalence, counts, and Campylobacter strains from both cattle and sheep across two disparate regions of Scotland. It also provides evidence for some differences in strain composition between cattle and sheep. This study found no evidence for significant differences in prevalence, enumerations, or ST composition between Campylobacter isolates from both cattle and sheep compared between northeastern and southwestern Scotland. Isolates showed increased similarity only when collected from the same farm at the same time. These results are consistent with a longitudinal study of C. jejuni isolates from cattle (16), which found ST-42 and ST-61 CC strains to be associated with particular farms, and with a farmland ecosystem study (7), which found that isolates were only genetically similar to each other when collected at distances of <1 km.

These findings are important for understanding Campylobacter transmission on small (between farms) and large (between regions) geographical scales. There does not appear to be a large-scale gradient of change in the frequency of genotypes (Fig. (Fig.3).3). Instead, the change appears to be abrupt between groups of animals either on the same farm or possibly on adjacent farms. This may occur because the large population of Campylobacter genotypes in an environment is likely to be continually reinfecting animal groups, resulting in the turnover of types of Campylobacter isolates excreted by ruminants (15). On a regional scale, it is probable that animal movements may also contribute to the homogeneity of Campylobacter diversity, but further work is required to determine the significance of this.

The most common STs found in this study were the same for both cattle and sheep. It was reported elsewhere (16) that ST-61 complex was associated with cattle but not with environmental and wildlife samples in the farming environment. In the present study, however, ST-61 complex and in particular ST-61 are common in both cattle and sheep, suggesting that this is a ruminant-associated CC. The current study also shows that C. coli is more common in sheep than in cattle, in agreement with published work (5, 26). A previous study (21) used structure to determine the degree of host attribution between cattle, sheep, and poultry. However, relatively poor discrimination was found between cattle and sheep (58%), and this result is marginally lower than that found in the present study (65%). The results are similar despite the contemporaneous, fecal-sample-only (present study) versus temporally widespread and materially diverse (21) nature of the specimens from which Campylobacter strains were isolated.

The individual animal prevalence and enumerations in cattle and sheep were similar to those described in previous studies (13, 18, 25, 37), but prevalences were lower than those reported in cattle (84 to 98%) and sheep (76%) in New Zealand (5). However, these comparisons should be treated cautiously because there is possible confounding due to different microbiological methods being used (e.g., different incubation temperatures and media). The similarity of both individual animal and group prevalences across disparate geographic regions underlines the homogeneity of the Campylobacter population in ruminants. The farm-level prevalence values reported here are probably underestimates because only four samples were collected from each herd or flock. No seasonal pattern was observed (data not presented), but this result must be treated with caution because of sample size, and it was not possible to determine whether differences existed between farm type (e.g., sheep on hill versus sheep on lowland pasture).

Inspection of the PUBMLST database showed that, for the STs found in the present study, 19 out of 32 from cattle and 23 out of 29 from sheep also occur in human clinical isolates. These STs comprise 89% of all ruminant isolates obtained in this study. Further, five of the ruminant sequence types (ST-21, ST-45, ST-48, ST-827, and ST-53) are among the 10 most frequently found in human infection during this time period (6). This provides further evidence that ruminant strains are also human pathogens, potentially causing illness by consumption of contaminated food (1) or direct contact with ruminants or their feces (9).

This is the first United Kingdom study that has collected and analyzed by MLST a representative number of sheep isolates in a spatially diverse farming environment. The results show that sheep may have a role equally as important as that of cattle in human Campylobacter infection, and there is therefore a need for longitudinal ovine studies to complement those already conducted in cattle (15) which investigated the turnover of isolates in individual animals as well as throughout the herd. The current study demonstrates the uniformity in prevalence, counts, and genetic types of Campylobacter across two geographically distinct and distant regions. It also provides evidence to suggest that there are some differences in the frequencies of genotypes between cattle and sheep. Further, it provides strong evidence that strains which are commonly found in ruminants are also found in human clinical cases.

Supplementary Material

[Supplementary material]

Acknowledgments

The Food Standards Agency, Scotland, wholly funded this work.

The Scottish Agricultural College collected rural samples from southwestern Scotland. This publication made use of the Campylobacter jejuni MLST website (http://pubmlst.org/campylobacter/) developed by Keith Jolley and Man-Suen Chan and sited at the University of Oxford.

Footnotes

[down-pointing small open triangle]Published ahead of print on 21 August 2009.

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

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