Fingerprinting of Campylobacter jejuni by using resolution-optimized binary gene targets derived from comparative genome hybridization studies

An Improved Multiplex Real-Time SYBR Green PCR Assay for Analysis of 24 Target Genes from 16 Bacterial Species in Fecal DNA Samples from Patients with Foodborne Illnesses

Here, we developed a new version of our original screening system (Rapid Foodborne Bacterial Screening 24; RFBS24), which can simultaneously detect 24 genes of foodborne pathogens in fecal DNA samples. This new version (RFBS24 ver. 5) detected all known stx2 subtypes, enterotoxigenic Escherichia coli (STh genotype), and Vibrio parahaemolyticus (trh2), which were not detected by the original RFBS24 assay. The detection limits of RFBS24 ver. 5 were approximately 5.6 × 10(-2)-5.6 × 10(-5) (ng DNA)/reaction, significantly lower (10- to 100-fold) than those of the original RFBS24 for the 22 target genes analyzed here. We also tested the new assay on fecal DNA samples from patients infected with Salmonella, Campylobacter, or enterohemorrhagic E. coli. The number of bacterial target genes detected by RFBS24 ver. 5 was greater than that detected by RFBS24. RFBS24 ver. 5 combined with an Ultra Clean Fecal DNA Isolation Kit showed adequate performance (sensitivity and specificity 89% and 100%, respectively, for Salmonella spp. and 100% and 83%, respectively, for Campylobacter jejuni) in terms of rapid detection of a causative pathogen during foodborne-illness outbreaks. Thus, RFBS24 ver. 5 is more useful than the previous assay system for detection of foodborne pathogens and offers quick simultaneous analysis of many targets and thus facilitates rapid dissemination of information to public health officials.

Current methods for molecular typing of Campylobacter species

Campylobacter remains one of the most common bacterial causes of gastroenteritis worldwide. Tracking sources of this organism is challenging due to the large numbers of human cases, and the prevalence of this organism throughout the environment due to growth in a wide range of animal species. Many molecular subtyping methods have been developed to characterize Campylobacter species, but only a few are commonly used in molecular epidemiology studies. This review examines the applicability of these methods, as well as the role that emerging whole genome sequencing technologies will play in tracking sources of Campylobacter spp. infection.

Development and validation of a comparative genomic fingerprinting method for high-resolution genotyping of Campylobacter jejuni

Campylobacter spp. are a leading cause of bacterial gastroenteritis worldwide. The need for molecular subtyping methods with enhanced discrimination in the context of surveillance- and outbreak-based epidemiologic investigations of Campylobacter spp. is critical to our understanding of sources and routes of transmission and the development of mitigation strategies to reduce the incidence of campylobacteriosis. We describe the development and validation of a rapid and high-resolution comparative genomic fingerprinting (CGF) method for C. jejuni. A total of 412 isolates from agricultural, environmental, retail, and human clinical sources obtained from the Canadian national integrated enteric pathogen surveillance program (C-EnterNet) were analyzed using a 40-gene assay (CGF40) and multilocus sequence typing (MLST). The significantly higher Simpson's index of diversity (ID) obtained with CGF40 (ID = 0.994) suggests that it has a higher discriminatory power than MLST at both the level of clonal complex (ID = 0.873) and sequence type (ID = 0.935). High Wallace coefficients obtained when CGF40 was used as the primary typing method suggest that CGF and MLST are highly concordant, and we show that isolates with identical MLST profiles are comprised of isolates with distinct but highly similar CGF profiles. The high concordance with MLST coupled with the ability to discriminate between closely related isolates suggests that CFG40 is useful in differentiating highly prevalent sequence types, such as ST21 and ST45. CGF40 is a high-resolution comparative genomics-based method for C. jejuni subtyping with high discriminatory power that is also rapid, low cost, and easily deployable for routine epidemiologic surveillance and outbreak investigations.

Differential decay of human faecal Bacteroides in marine and freshwater

Genetic markers from Bacteroides and other faecal bacteria are being tested for inclusion in regulations to quantify aquatic faecal contamination and estimate public health risk. For the method to be used quantitatively across environments, persistence and decay of markers must be understood. We measured concentrations of contaminant molecular markers targeting Enterococcus and Bacteroides spp. in marine and freshwater microcosms spiked with human sewage and exposed to either sunlight or dark treatments. We used Bayesian statistics with a delayed Chick-Watson model to estimate kinetic parameters for target decay. DNA- and RNA-based targets decayed at approximately the same rate. Molecular markers persisted (could be detected) longer in marine water. Sunlight increased the decay rates of cultured indicators more than those of molecular markers; sunlight also limited persistence of molecular markers. Within each treatment, Bacteroides markers had similar decay profiles, but some Bacteroides markers significantly differed in decay rates. The role of extracellular DNA in persistence appeared unimportant in the microcosms. Because conditions were controlled, microcosms allowed the effects of specific environmental variables on marker persistence and decay to be measured. While marker decay profiles in more complex environments would be expected to vary from those observed here, the differences we measured suggest that water matrix is an important factor affecting quantitative source tracking and microbial risk assessment applications.

Everything at once: comparative analysis of the genomes of bacterial pathogens

The sum of unique genes in all genomes of a bacterial species is referred to as the pan-genome and is comprised of variably absent or present accessory genes and universally present core genes. The accessory genome is an important source of genetic variability in bacterial populations, allowing sub-populations of bacteria to better adapt to specific niches. Such subgroups may themselves have a relatively stable core genome that may influence host preference, virulence, or an association with specific disease syndromes. The core genome provides a useful means of phylogenetic reconstruction as well as contributing to phenotypic heterogeneity. Variation within the pan-genome forms the basis of comparative genotyping techniques, which have evolved alongside technology. Current high-throughput sequencing platforms have created an unprecedented opportunity for comparisons among multiple, closely related genomes. The computer algorithms and software for such comparisons continue to evolve and promise exciting advances in the world of bacterial comparative genomics. We review genotyping techniques based upon phenotypic traits, both core and accessory genomes, and look at some of the software programs currently available to perform whole-genome comparative analyses.

Simultaneous Screening of 24 Target Genes of Foodborne Pathogens in 35 Foodborne Outbreaks Using Multiplex Real-Time SYBR Green PCR Analysis

A set of 8 multiplex real-time SYBR Green PCR (SG-PCR) assays including 3 target primers and an internal amplification control (IAC) primer was simultaneously evaluated in 3 h or less with regard to detection of 24 target genes of 23 foodborne pathogens in 7 stool specimens of foodborne outbreak using a 96-well reaction plate. This assay, combined with DNA extraction (QIAamp DNA Stool Mini kit), offered detection of greater than 10(3)-10(4) foodborne pathogens per g in stool specimens. The products formed were identified using melting point temperature (Tm) curve analysis. This assay was evaluated for the detection of foodborne pathogens in 33 out of 35 cases of foodborne outbreak, using 4 different PCR instruments in 5 different laboratories. No interference from the multiplex real-time SG-PCR assay, including IAC, was observed in stool specimens in any analysis. We found multiplex real-time SG-PCR assay for simultaneous detection of 24 target genes of foodborne pathogens to be comprehensive, rapid, inexpensive, accurate, of high selectivity, and good for screening probability.

Human and bovine adenoviruses for the detection of source-specific fecal pollution in coastal waters in Australia

In this study, the host-specificity and -sensitivity of human- and bovine-specific adenoviruses (HS-AVs and BS-AVs) were evaluated by testing wastewater/fecal samples from various animal species in Southeast, Queensland, Australia. The overall specificity and sensitivity of the HS-AVs marker were 1.0 and 0.78, respectively. These figures for the BS-AVs were 1.0 and 0.73, respectively. Twenty environmental water samples were collected during wet conditions and 20 samples were colleted during dry conditions from the Maroochy Coastal River and tested for the presence of fecal indicator bacteria (FIB), host-specific viral markers, zoonotic bacterial and protozoan pathogens using PCR/qPCR. The concentrations of FIB in water samples collected after wet conditions were generally higher compared to dry conditions. HS-AVs was detected in 20% water samples collected during wet conditions and whereas BS-AVs was detected in both wet (i.e., 10%) and dry (i.e., 10%) conditions. Both Campylobacter jejuni mapA and Salmonella invA genes detected in 10% samples collected during dry conditions. The concentrations of Salmonella invA ranged between 3.5 × 10(2) and 4.3 × 10(2) genomic copies per 500 ml of water Giardia lamblia β-giardin gene was detected only in one sample (5%) collected during the dry conditions. Weak or significant correlations were observed between FIB with viral markers and zoonotic pathogens. However, during dry conditions, no significant correlations were observed between FIB concentrations with viral markers and zoonotic pathogens. The prevalence of HS-AVs in samples collected from the study river suggests that the quality of water is affected by human fecal pollution and as well as bovine fecal pollution. The results suggest that HS-AVs and BS-AVs detection using PCR could be a useful tool for the identification of human sourced fecal pollution in coastal waters.

Implications of faecal indicator bacteria for the microbiological assessment of roof-harvested rainwater quality in southeast Queensland, Australia

The study aimed to evaluate the suitability of Escherichia coli , enterococci, and Clostridium perfringens for assessing the microbiological quality of roof-harvested rainwater and assessing whether the concentrations of these faecal indicators can be used to predict the presence or absence of specific zoonotic bacterial or protozoan pathogens. From a total of 100 samples tested, 58%, 83%, and 46% of samples were found to be positive for, respectively, E. coli, enterococci, and Clostridium perfringens spores, as determined by traditional culture-based methods. Additionally, in the samples tested, 7%, 19%, 1%, 8%, 17%, and 15% were PCR positive for Aeromonas hydrophila lip, Campylobacter coli ceuE, Campylobacter jejuni mapA, Legionella pneumophila mip, Salmonella invA, and Giardia lamblia β-giardin genes, respectively. However, none of the samples was positive for E. coli O157 lipopolysaccharide, verocytotoxin 1, and verocytotoxin 2 and Cryptosporidium parvum oocyst wall protein genes. The presence or absence of these potential pathogens did not correlate with any of the faecal indicator bacterial concentrations as determined by a binary logistic regression model. The roof-harvested rainwater samples tested in this study appeared to be of poor microbiological quality, and no significant correlation was found between the concentration of faecal indicators and pathogenic microorganisms. The use of faecal indicator bacteria raises questions regarding their reliability in assessing the microbiological quality of water and particularly their poor correlation with pathogenic microorganisms. The presence of one or more zoonotic pathogens suggests that the microbiological analysis of water should be performed and that appropriate treatment measures should be undertaken, especially in tanks where the water is used for drinking.

Highly discriminatory single-nucleotide polymorphism interrogation of Escherichia coli by use of allele-specific real-time PCR and eBURST analysis

In total, 782 Escherichia coli strains originating from various host sources have been analyzed in this study by using a highly discriminatory single-nucleotide polymorphism (SNP) approach. A set of eight SNPs, with a discrimination value (Simpson's index of diversity [D]) of 0.96, was determined using the Minimum SNPs software, based on sequences of housekeeping genes from the E. coli multilocus sequence typing (MLST) database. Allele-specific real-time PCR was used to screen 114 E. coli isolates from various fecal sources in Southeast Queensland (SEQ). The combined analysis of both the MLST database and SEQ E. coli isolates using eight high-D SNPs resolved the isolates into 74 SNP profiles. The data obtained suggest that SNP typing is a promising approach for the discrimination of host-specific groups and allows for the identification of human-specific E. coli in environmental samples. However, a more diverse E. coli collection is required to determine animal- and environment-specific E. coli SNP profiles due to the abundance of human E. coli strains (56%) in the MLST database.

Comparison of PCR binary typing (P-BIT), a new approach to epidemiological subtyping of Campylobacter jejuni, with serotyping, pulsed-field gel electrophoresis, and multilocus sequence typing methods

To overcome some of the deficiencies with current molecular typing schema for Campylobacter spp., we developed a prototype PCR binary typing (P-BIT) approach. We investigated the distribution of 68 gene targets in 58 Campylobacter jejuni strains, one Campylobacter lari strain, and two Campylobacter coli strains for this purpose. Gene targets were selected on the basis of distribution in multiple genomes or plasmids, and known or putative status as an epidemicity factor. Strains were examined with Penner serotyping, pulsed-field gel electrophoresis (PFGE; using SmaI and KpnI enzymes), and multilocus sequence typing (MLST) approaches for comparison. P-BIT provided 100% typeability for strains and gave a diversity index of 98.5%, compared with 97.0% for SmaI PFGE, 99.4% for KpnI PFGE, 96.1% for MLST, and 92.8% for serotyping. Numerical analysis of the P-BIT data clearly distinguished strains of the three Campylobacter species examined and correlated somewhat with MLST clonal complex assignations and with previous classifications of "high" and "low" risk. We identified 18 gene targets that conferred the same level of discrimination as the 68 initially examined. We conclude that P-BIT is a useful approach for subtyping, offering advantages of speed, cost, and potential for strain risk ranking unavailable from current molecular typing schema for Campylobacter spp.

Campylobacter jejuni and Campylobacter coli genotyping by high-resolution melting analysis of a flaA fragment

The highly variable flagellin-encoding flaA gene has long been used for genotyping Campylobacter jejuni and Campylobacter coli. High-resolution melting (HRM) analysis is emerging as an efficient and robust method for discriminating DNA sequence variants. The objective of this study was to apply HRM analysis to flaA-based genotyping. The initial aim was to identify a suitable flaA fragment. It was found that the PCR primers commonly used to amplify the flaA short variable repeat (SVR) yielded a mixed PCR product unsuitable for HRM analysis. However, a PCR primer set composed of the upstream primer used to amplify the fragment used for flaA restriction fragment length polymorphism (RFLP) analysis and the downstream primer used for flaA SVR amplification generated a very pure PCR product, and this primer set was used for the remainder of the study. Eighty-seven C. jejuni and 15 C. coli isolates were analyzed by flaA HRM and also partial flaA sequencing. There were 47 flaA sequence variants, and all were resolved by HRM analysis. The isolates used had previously also been genotyped using single-nucleotide polymorphisms (SNPs), binary markers, CRISPR HRM, and flaA RFLP. flaA HRM analysis provided resolving power multiplicative to the SNPs, binary markers, and CRISPR HRM and largely concordant with the flaA RFLP. It was concluded that HRM analysis is a promising approach to genotyping based on highly variable genes.

Binary genomotyping using lipooligosaccharide biosynthesis genes distinguishes between Campylobacter jejuni isolates within poultry-associated multilocus sequence types

Campylobacter jejuni is a leading cause of human bacterial gastroenteritis throughout the industrialized world. We investigated whether or not differences in gene complement at the lipooligosaccharide (LOS) biosynthesis locus can identify epidemiologically useful binary genomotypes in 87 C. jejuni isolates from poultry-associated multilocus sequence types (STs) collected during the course of a sentinel surveillance study. Using a PCR-based approach, we correlated assignment of both isolate LOS locus class and binary genomotype with ST. We found that isolates within STs 45, 190, 354 and 474 displayed mosaicism in gene complement at the intra-ST level. For example, based upon their binary genomotypes, we assigned individual ST-45 isolates from human clinical cases as probably originating from either a poultry or wild-bird source. However, intra-ST mosaicism in gene complement was observed alongside broader patterns of congruence in LOS locus class and gene complement that distinguished between isolates from different STs.

Characterisation of chicken Campylobacter jejuni isolates using resolution optimised single nucleotide polymorphisms and binary gene markers

The principal objective of this study was to determine if Campylobacter jejuni genotyping methods based upon resolution optimised sets of single nucleotide polymorphisms (SNPs) and binary genetic markers were capable of identifying epidemiologically linked clusters of chicken-derived isolates. Eighty-eight C. jejuni isolates of known flaA RFLP type were included in the study. They encompassed three groups of ten isolates that were obtained at the same time and place and possessed the same flaA type. These were regarded as being epidemiologically linked. Twenty-six unlinked C. jejuni flaA type I isolates were included to test the ability of SNP and binary typing to resolve isolates that were not resolved by flaA RFLP. The remaining isolates were of different flaA types. All isolates were typed by real-time PCR interrogation of the resolution optimised sets of SNPs and binary markers. According to each typing method, the three epidemiologically linked clusters were three different clones that were well resolved from the other isolates. The 26 unlinked C. jejuni flaA type I isolates were resolved into 14 SNP-binary types, indicating that flaA typing can be unreliable for revealing epidemiological linkage. Comparison of the data with data from a fully typed set of isolates associated with human infection revealed that abundant lineages in the chicken isolates that were also found in the human isolates belonged to clonal complex (CC) -21 and CC-353, with the usually rare C-353 member ST-524 being especially abundant in the chicken collection. The chicken isolates selected to be diverse according to flaA were also diverse according to SNP and binary typing. It was observed that CC-48 was absent in the chicken isolates, despite being very common in Australian human infection isolates, indicating that this may be a major cause of human disease that is not chicken associated.

Assignment of Streptococcus agalactiae isolates to clonal complexes using a small set of single nucleotide polymorphisms

BACKGROUND

Streptococcus agalactiae (Group B Streptococcus (GBS)) is an important human pathogen, particularly of newborns. Emerging evidence for a relationship between genotype and virulence has accentuated the need for efficient and well-defined typing methods. The objective of this study was to develop a single nucleotide polymorphism (SNP) based method for assigning GBS isolates to multilocus sequence typing (MLST)-defined clonal complexes.

RESULTS

It was found that a SNP set derived from the MLST database on the basis of maximization of Simpsons Index of Diversity provided poor resolution and did not define groups concordant with the population structure as defined by eBURST analysis of the MLST database. This was interpreted as being a consequence of low diversity and high frequency horizontal gene transfer. Accordingly, a different approach to SNP identification was developed. This entailed use of the "Not-N" bioinformatic algorithm that identifies SNPs diagnostic for groups of known sequence variants, together with an empirical process of SNP testing. This yielded a four member SNP set that divides GBS into 10 groups that are concordant with the population structure. A fifth SNP was identified that increased the sensitivity for the clinically significant clonal complex 17 to 100%. Kinetic PCR methods for the interrogation of these SNPs were developed, and used to genotype 116 well characterized isolates.

CONCLUSION

A five SNP method for dividing GBS into biologically valid groups has been developed. These SNPs are ideal for high throughput surveillance activities, and combining with more rapidly evolving loci when additional resolution is required.

Real-time PCR detection of pathogenic microorganisms in roof-harvested rainwater in Southeast Queensland, Australia

In this study, the microbiological quality of roof-harvested rainwater was assessed by monitoring the concentrations of Escherichia coli, enterococci, Clostridium perfringens, and Bacteroides spp. in rainwater obtained from tanks in Southeast Queensland, Australia. Samples were also tested using real-time PCR (with SYBR Green I dye) for the presence of potential pathogenic microorganisms. Of the 27 rainwater samples tested, 17 (63%), 21 (78%), 13 (48%), and 24 (89%) were positive for E. coli, enterococci, C. perfringens, and Bacteroides spp., respectively. Of the 27 samples, 11 (41%), 7 (26%), 4 (15%), 3 (11%), and 1 (4%) were PCR positive for the Campylobacter coli ceuE gene, the Legionella pneumophila mip gene, the Aeromonas hydrophila lip gene, the Salmonella invA gene, and the Campylobacter jejuni mapA gene. Of the 21 samples tested, 4 (19%) were positive for the Giardia lamblia beta-giardin gene. The binary logistic regression model indicated a positive correlation (P < 0.02) between the presence/absence of enterococci and A. hydrophila. In contrast, the presence/absence of the remaining potential pathogens did not correlate with traditional fecal indicators. The poor correlation between fecal indicators and potential pathogens suggested that fecal indicators may not be adequate to assess the microbiological quality of rainwater and consequent health risk.

Genomic differences between Campylobacter jejuni isolates identify surface membrane and flagellar function gene products potentially important for colonizing the chicken intestine

Campylobacter spp. are one of the leading bacterial etiologic agents of acute human gastroenteritis among industrialized countries. Poultry are implicated as a major source of the organism for human illness; however, the factors involved with colonization of poultry gastrointestinal systems remain unclear. Genomics and proteomics analyses were used to identify differences between poor- versus robust-colonizing Campylobacter jejuni isolates, 11168(GS) and A74/C, respectively. Sequence analyses of subtracted DNA resulted in A74/C-specifc genes similar to a dimethyl sulfoxide reductase, a serine protease, polysaccharide modification proteins, and restriction modification proteins. DNA microarray analyses were performed for comparison of A74/C to the complete genome sequences published for two C. jejuni. A total of 114 genes (7.1%) were determined absent from A74/C relative to those genomes. Additionally, proteomics was completed on both soluble and membrane protein extracts from 11168(GS) and A74/C. Variation in protein expression and physical characteristics such as pI was detected between the two isolates that included the major outer membrane protein, flagella, and aconitate hydratase. Several proteins including cysteine synthase and a Ni/Fe hydrogenase were determined to be differentially present between the two isolates. Finally, DNA hybridization analyses of 19 C. jejuni isolates recovered from chickens and humans worldwide over the past 20 years were performed to determine the distribution of a subset of differentially identified gene sequences.

Performance of a 70-mer oligonucleotide microarray for genotyping of Campylobacter jejuni

BACKGROUND

Campylobacter jejuni is widespread in the environment and is the major cause of bacterial gastroenteritis in humans. In the present study we use microarray-based comparative genomic hybridizations (CGH), pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST) to analyze closely related C. jejuni isolates from chicken and human infection.

RESULTS

With the exception of one isolate, the microarray data clusters the isolates according to the five groups determined by PFGE. In contrast, MLST defines only three genotypes among the isolates, indicating a lower resolution. All methods show that there is no inherit difference between isolates infecting humans and chicken, suggesting a common underlying population of C. jejuni. We further identify regions that frequently differ between isolates, including both previously described and novel regions. Finally, we show that genes that belong to certain functional groups differ between isolates more often than expected by chance.

CONCLUSION

In this study we demonstrated the utility of 70-mer oligonucleotide microarrays for genotyping of Campylobacter jejuni isolates, with resolution outperforming MLST.

Computer-aided identification of polymorphism sets diagnostic for groups of bacterial and viral genetic variants

BACKGROUND

Single nucleotide polymorphisms (SNPs) and genes that exhibit presence/absence variation have provided informative marker sets for bacterial and viral genotyping. Identification of marker sets optimised for these purposes has been based on maximal generalized discriminatory power as measured by Simpson's Index of Diversity, or on the ability to identify specific variants. Here we describe the Not-N algorithm, which is designed to identify small sets of genetic markers diagnostic for user-specified subsets of known genetic variants. The algorithm does not treat the user-specified subset and the remaining genetic variants equally. Rather Not-N analysis is designed to underpin assays that provide 0% false negatives, which is very important for e.g. diagnostic procedures for clinically significant subgroups within microbial species.

RESULTS

The Not-N algorithm has been incorporated into the "Minimum SNPs" computer program and used to derive genetic markers diagnostic for multilocus sequence typing-defined clonal complexes, hepatitis C virus (HCV) subtypes, and phylogenetic clades defined by comparative genome hybridization (CGH) data for Campylobacter jejuni, Yersinia enterocolitica and Clostridium difficile.

CONCLUSION

Not-N analysis is effective for identifying small sets of genetic markers diagnostic for microbial sub-groups. The best results to date have been obtained with CGH data from several bacterial species, and HCV sequence data.

Systematic derivation of marker sets for staphylococcal cassette chromosome mec typing

The aim of this study was to identify optimized sets of genotyping targets for the staphylococcal cassette chromosome mec (SCCmec). We analyzed the gene contents of 46 SCCmec variants in order to identify minimal subsets of targets that provide useful resolution. This was achieved by firstly identifying and characterizing each available SCCmec element based on the presence or absence of 34 binary targets. This information was used as input for the software "Minimum SNPs," which identifies the minimum number of targets required to differentiate a set of genotypes up to a predefined Simpson's index of diversity (D) value. It was determined that 22 of the 34 targets were required to genotype the 46 SCCmec variants to a D of 1. The first 6, 9, 12, and 15 targets were found to define 21, 29, 35, and 39 SCCmec variants, respectively. The genotypes defined by these marker subsets were largely consistent with the relationships between SCCmec variants and the accepted nomenclature. Consistency was made virtually complete by forcing the computer program to include ccr1 and ccr5 in the target set. An alternative target set biased towards discriminating abundant SCCmec variants was derived by analyzing an input file in which common SCCmec variants were repeated, thus ensuring that markers that discriminate abundant variants had a large effect on D. Finally, it was determined that mecA single nucleotide polymorphisms (SNPs) can increase the overall genotyping resolution, as different mecA alleles were found in otherwise identical SCCmec variants.

High-resolution DNA melt curve analysis of the clustered, regularly interspaced short-palindromic-repeat locus of Campylobacter jejuni

A novel method for genotyping the clustered, regularly interspaced short-palindromic-repeat (CRISPR) locus of Campylobacter jejuni is described. Following real-time PCR, CRISPR products were subjected to high-resolution melt (HRM) analysis, a new technology that allows precise melt profile determination of amplicons. This investigation shows that the CRISPR HRM assay provides a powerful addition to existing C. jejuni genotyping methods and emphasizes the potential of HRM for genotyping short sequence repeats in other species.