Molecular Detection, Typing, and Quantification of - Wiley Online Library

Molecular Detection, Typing, and Quantification of Campylobacter spp. in Foods of Animal Origin Beatriz da Silva Frasao, Victor Augustus Marin, and Carlos Adam Conte-Junior

Abstract: The most frequently reported zoonosis and the main bacterial foodborne disease infection in humans is caused by Campylobacter spp., and C. jejuni and C. coli are the most common types. These bacteria can be found in the intestinal tracts of cattle, dogs, cats, sheep, poultry and pigs. The isolation of this microorganism is laborious because it requires specific media and a low oxygen concentration for growth. Additionally, differentiation between species through conventional bacteriology is difficult, as there are few different biochemical characteristics among the various species. Molecular microbiological techniques have become more important and are now broadly applied to help overcome difficulties in the identification, differentiation, and quantification of this pathogen. To date, there have been advances in the development and use of molecular techniques for the identification of microorganisms in foodstuffs. Tools such as pulsed-field gel electrophoresis and multilocus sequence typing are the most commonly used for typing. For the identification and confirmation of species, polymerase chain reaction (PCR) is crucial. Quantification by real-time PCR has wide applicability. To identify strains and antimicrobial resistance genes, sequencing technologies have been applied. This review builds on the discussion about the main and most widely used molecular methods for Campylobacter, as well as methods showing better potential for the classification, identification, and quantification of this important pathogen. Keywords: foodborne pathogen, MLST, PCR, PFGE, retail meat

Introduction Previously classified as Vibrio spp., the Campylobacter genus was 1st proposed in 1963 by Sébald and Véron. Campylobacter comprises a genus of gram-negative, microaerophilic, flagellated bacteria that usually have a gull-wing shape. Coccoid forms can be observed in old or inviable cultures. These thin (0.2 to 0.5 nm) and long (0.5 to 5 nm) microorganisms are mobile due to a single polar flagellum 2 to 3 times the length of the cell itself (Nachamkin 2001; Franco and Landgraf 2008). These bacteria can be found in the intestinal tracts of cattle, dogs, cats, and sheep, with poultry and pigs being the most common reservoirs of Campylobacter jejuni and Campylobacter coli, respectively (Stern and others 2003; USDA 2013), all of which are sources of infection for humans. Transmission occurs via direct contact with feces or by food crosscontamination due to raw or undercooked meat and raw milk

CRF3-2017-0012 Submitted 1/14/2017, Accepted 5/17/2017. Authors Frasao and Conte-Junior are with Dept. of Food Technology, Fluminense Federal Univ. (UFF) 24.230-340, Niteroi, RJ, Brazil. Author Frasao is with Dept. of Epidemiology and Public Health, Federal Rural Univ. of Rio de Janeiro (UFRRJ), 23.897-000, Seropédica, RJ, Brazil. Author Marin is with Dept. of Food Science, Federal Univ. of the State of Rio de Janeiro (UNIRIO), 22.290-255, Rio de Janeiro, RJ, Brazil. Author Conte-Junior is with Natl. Inst. for Health Quality Control, Oswaldo Cruz Foundation (FIOCRUZ), 21.040-900, Rio de Janeiro, RJ, Brazil. Direct inquiries to author Conte-Junior (E-mail: [email protected]). Author disclosures: All authors declare no conflict of interest. C 2017 Institute of Food Technologists®

doi: 10.1111/1541-4337.12274

(CDC/US 2013). Campylobacteriosis is the most frequently reported zoonosis and the main bacterial foodborne disease in humans (Zendehbad and others 2015). Because poultry and pigs have a higher prevalence of this microorganism in their natural microbiota, the main foods involved in relation to public health are poultry and pork (Stern and others 2003; Gallay and others 2007). Isolation of Campylobacter is laborious, as these bacteria require enriched media and low oxygen concentrations. Additionally, differentiation between species through conventional bacteriology is difficult, as only very few biochemical characteristics differ among species (Miller and others 2010). Thus, it is easier and faster to employ molecular biology techniques such as polymerase chain reaction (PCR) and sequencing for identification purposes. In addition, tools such as pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST) are the currently the most commonly used for typing (Goering 2010; Miller and others 2010; Behringer and others 2011; Gharst and others 2013; Manfreda and others 2016; Pan and others 2016; Vidal and others 2016; Oh and others 2017; Schleihauf and others 2017; Vinueza-Burgos and others 2017; Zhang and others 2017). Within this context, the purpose of this review is to describe the main molecular techniques used for the isolation and identification of Campylobacter spp. and to recommend the fastest, most accurate, and most sensitive techniques with the best potential for typing and identifying this genus in a food matrix.

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Campylobacter molecular tools in food . . .

Characteristics of Campylobacter spp

Main considerations Public health services worldwide pay great attention to Campylobacter spp. because these microorganisms are pathogenic to humans and commonly found in the gastrointestinal tracts of cattle, dogs, cats, and sheep, though poultry and pigs are the most common reservoirs (USDA 2013). In 2009, the Campylobacter genus contained 29 species and 13 subspecies. In 2010, the number of species rose to 32, though the number of subspecies remained the same (Euzéby 2010), with no change since (Euzéby 2014). Several species of Campylobacter may compromise the health of humans and animals. In regard to foodborne disease, the most important species are the thermophilic types C. jejuni, C. coli, Campylobacter lari, and Campylobacter upsaliensis, particularly the 1st 2 (EFSA 2013). Transmission and infection involve the consumption of fecescontaminated raw or undercooked meat, especially poultry, and contaminated water. The disease begins with invasion of the host gastrointestinal tract (Nachamkin and others 2008). For humans, C. jejuni is considered the most pathogenic and is isolated more frequently than C. coli. Coinfection with C. coli may also occur (Niederer and others 2012). The number of human campylobacteriosis cases has increased worldwide, surpassing the number of cases of salmonellosis and shigellosis (Cover and others 2014). Although it is still the most reported zoonotic disease, the number of human cases of campylobacteriosis in the European Union decreased in 2012 for the 1st time in over a 5-y period (EFSA 2014b). The economic cost of the disease in developed countries in terms of days away from work and medical treatment is significant (Newell and others 2010); for example, the cost to the public health system in terms of lost productivity in the EU has been estimated at approximately 2.4 billion euros per year (EFSA 2014a). Foods involved in outbreaks and importance for public health Products improperly handled or undercooked foods, especially poultry, pork, beef, and raw milk, are primarily responsible for Campylobacter spp. infection because these species are a constituent of the natural intestinal microbiota of birds, pigs, and cows (Jayasena and Jo 2013; Frasao and Aquino 2014). In cattle, the prevalence of Campylobacter is 2.7% in carcass samples (Wieczorek and Osek 2013). C. jejuni has also been found in many other foods, such as vegetables, seafood, and animal species not intended for human consumption (FDA 2012). In Tanzania, 13.4% and 9.7% of raw milk and beef carcasses are positive for Campylobacter spp., respectively (Kashoma and others 2016). Consumption of raw vegetables and fruits can also be a risk factor, as Verhoeff-Bakkenes and others (2011) found a rate of 0.23% for the relationship between Campylobacter infection and consumption of these products. Most Campylobacter infections are associated with consumption of poultry and by-products that have been contaminated during processing (Hermans and others 2011; Wagenaar and others 2013). There are reports to date assessing the risk of Campylobacter in broiler chickens (Dong and others 2015), and raw poultry meat is considered a high-risk raw material with regard to the presence of Campylobacter spp. The evisceration stage is the most important step for preventing slaughter contamination, and Campylobacter detection may be employed to indicate microbiological safety (Jacxsens and others 2011). Rahimi and Ameri (2011) investigated Campylobacter in poultry and found a higher prevalence in chicken meat (47.0%), followed by quail (43.0%), partridge (35.3%), turkey (28.8%), and ostrich (4.8%) meats. Campylobacter is mainly found in the cecum of birds; however, these animals display no symptoms

(EFSA 2013). The most prevalent species is C. jejuni, isolated from 92.0% of samples. Although most studies describe C. jejuni as the most frequent species in broilers and laying hens (Aquino and others 2002), a survey by Miller and others (2010) in Grenada found C. coli to be the most frequent species found in these animals. Pigs are also responsible for the transmission of C. coli, as cited by various authors (Koike and others 2008; Bratz and others 2013; von Altrock and others 2013). For example, Qin and others (2011) found that 98.9% of swine tested carried C. coli. In 2013, 76.2% of the strains isolated from pigs by von Altrock and others (2013) in Lower Saxony, Germany, were found to consist of C. coli, with 21.1% being C. jejuni. A high prevalence of C. coli (42.4%) was also found on pig breeding farms in Japan (Haruna and others 2013). In the United States, campylobacteriosis outbreaks have been associated with nonpasteurized milk or with pasteurized milk failure (Taylor and others 2013). In 2011 and 2012, the Centers for Disease Control and Prevention reported that most outbreaks linked to foodborne diseases were also linked to unpasteurized (raw) milk (CDC/US 2014).

Molecular Biology and the Importance of the Use of Molecular Microbiology Molecular biology was considerably advanced in the 1970s, and it became increasingly obvious that phenotype expression is a characteristic of the genotype of an organism. Thus, it is important to study microbial diversity and differences between food matrices and to precisely identify the microorganisms responsible for a foodborne disease (Juste and others 2008). The genome is the primary “molecular identity” of the bacterial cell, and DNA sequences from phylogenetic studies are available in public databases (Olsen and others 1992; Benson and others 2004; Cole and others 2005; D’Auria and others 2006), which facilitates and expedites species identification by comparison with these sequences. Molecular methods have been applied in clinically relevant areas, including epidemiological studies, giving rise to the term “molecular epidemiology” (Siemer and others 2005; Goering 2010). Molecular tools are now available and affordable for the food industry and can be implemented for food quality control and safety. Due to the need for rapid results, molecular techniques have been developed for the identification of microorganisms in foodstuffs (Ceuppens and others 2014). Molecular techniques, especially molecular typing techniques, are used to characterize variability within a species. C. jejuni and C. coli present similar characteristics and cause similar symptoms in humans, however few studies have been diferrenciated this 2 with molecular technics applied (Behringer and others 2011). Advances in DNA techniques applied to foodborne pathogens have improved the understanding of epidemiology (Behringer and others 2011). Molecular approaches have helped scientists determine that C. jejuni and C. coli are present in commercial broiler production worldwide (He and others 2010). Moreover, rapid and direct quantification of Campylobacter spp. in complex substrates, such as stool or environmental samples, is essential to facilitate epidemiological studies on these pathogens in poultry and pig production systems (Leblanc-Maridor and others 2011). Molecular identification methods for Campylobacter spp. are rapid and specific through detection of specific segments of DNA or RNA. Additionally, sequencing provides a rapid way to detect specific DNA segments, enabling species and even subspecies determination (Gharst and others 2013). In the search for more

2 Comprehensive Reviews in Food Science and Food Safety r Vol. 00, 2017

C 2017 Institute of Food Technologists®

Campylobacter molecular tools in food . . . accurate and faster results as well as easier detection, molecular techniques have been tested and used for the detection, identification, and quantification of Campylobacter spp. in various food matrices and in foods of animal origin.

Molecular Methods Applied for Campylobacter spp Isolation and identification of Campylobacter spp. is laborious and difficult due to the particular growth demands and to the phenotypic similarity between species. Culturing requires rich media and low oxygen. Differentiation between species through conventional bacteriology is challenging, as there are no major biochemical differences among species (Miller and others 2010; Toplak and others 2012). According to Toplak and others (2012), several techniques have been proposed and tested as alternatives to classical procedures over the last 10 y. These authors mainly referred to methods based on PCR. Overall, molecular typing of strains is a tool of great importance for studying the genetic diversity of Campylobacter spp. and allows for tracking of strains that cause infections in humans (Kittl and others 2013; Duarte and others 2014). In addition to the molecular methods already described for the isolation and identification of Campylobacter, plasmid profiling, restriction endonuclease analysis, ribotyping, repetitive extragenic palindromic sequence analysis, enterobacterial repetitive intergenic consensus sequence analysis, reverse transcription-PCR, nested PCR, and PCR ribotyping represent useful methods. However, the most commonly used techniques for typing isolates of Campylobacter are based on amplification of a short segment of DNA (repetitive element sequence-based PCR), amplification and restriction of a particular gene (restriction fragment length polymorphism, RFLP-flaA), restriction and migration of large chromosomal segments (PFGE), sequencing of housekeeping fragments (MLST), PCR, and sequencing (Goering 2010; Miller and others 2010; Behringer and others 2011). Frequently employed for identification purposes, molecular biology techniques such as PCR and sequencing are easy and rapid approaches. Techniques such as PFGE and MLST are the commonly used for typing of isolates (Goering 2010; Miller and others 2010; Behringer and others 2011; Gharst and others 2013).

Molecular Tools Used for Detection of Campylobacter spp. in Food of Animal Origin Polymerase chain reaction PCR, which was described by Kary Mullis in 1980, is based on the principle of enzymatic nucleic acid replication and is applied for fast and easy amplification of DNA. This method has an irreplaceable role as one of the basic approaches for DNA analysis (Stanek 2013). This method is both rapid and specific and can be applied for detection of pathogens in food, including Campylobacter in products of animal origin (Giesendorf and others 1992; Wegmüller and others 1993; Docherty and others 1996; Jackson and others 1996; Ng and others 1997; Waage and others 1999; O’Sullivan and others 2000; Sails and others 2003; Frasao and others 2015a, b; Raja and others 2017). As the main molecule examined using these techniques, DNA can be extracted from different matrices of interest. To obtain a pure and ideal concentration of DNA, appropriate techniques for extraction should be used. Raja and others (2017) tested the efficiency of 3 types of extraction to obtain Campylobacter DNA from poultry meat: boiling, a bacterial DNA extraction kit (Qiagen), and phenol-chloroform-isoamyl alcohol (25: 24: 1) extraction. Of the methods tested, the Qiagen kit resulted in the highest purity C 2017 Institute of Food Technologists®

and DNA concentration, whereas the boiling method presented low purity. This difference can be explained by the utilization of a spin column in the Qiagen kit, allowing for better and easier removal of impurities. However, the high cost of the kit led the authors to select the phenol-chloroform-isoamyl alcohol (25: 24: 1) extraction method, which provided a good level of purity and concentration. The choice of method will depend on the relevant conditions. Some authors use the boiling method (Shams and others 2017; Zang and others 2017), others prefer the kit (Frasao and others 2015a, b; Ayaz and others 2016; Gosselin-Theberge and others 2016; Rodgers and others 2016), whereas others employ phenol-chloroform-isoamyl alcohol (25: 24: 1) extraction (Raja and others 2017). For the PCR technique, a mixture of reagents is prepared to produce a reaction buffer, including magnesium chloride, deoxynucleotide triphosphates (dNTPs, that is, guanine, adenine, thymine, and cytosine bases), oligonucleotides (primers) complementary to the gene of interest, Taq polymerase, and the DNA sample. Primers may be between 18 and 35 bp and normally amplify segments of DNA between 200 and 800 bp. This mixture is placed in a thermocycler, which is programmed for a series of cycles depending on the microorganism and the primers used. In the 1st stage, the DNA is denatured, followed by cooling for annealing of the primer to the DNA strand; the sample is then subjected to a high temperature for DNA synthesis and extension (Hue-Roye and Vege 2008). For Campylobacter, a temperature of approximately 94 °C is applied for denaturation, with annealing at 52 to 54 °C and extension at 72 °C (Frasao and others 2015a, b; Raja and others 2017; Zang and others 2017). A benefit to the food supply is achieved when PCR technology is used to detect pathogenic agents in foods, with important considerations for reducing limitations of PCR inhibition by the food matrix composition and the detection of dead cells. However, quantification is excluded (Postollec and others 2011). With PCR, specificity is enhanced by using primers specific for Campylobacter (von Altrock and others 2013; Lemos and others 2015; Han and others 2016), C. coli (Gonzalez and others 1997; von Altrock and others 2013; Fontanot and others 2014a; Frasao and others 2015a, b; Lemos and others 2015; Han and others 2016), C. jejuni (von Altrock and others 2013; Fontanot and others 2014a; Lemos and others 2015; Ayaz and others 2016; Han and others 2016; Raja and others 2017), C. lari (Fontanot and others 2014a), and C. upsaliensis (Fontanot and others 2014a) (Table 1). In addition to these specific primers, it is possible to amplify to different sizes (bp) by using a primer linked to the 16S-23S ITS sequence, as this region has a variable size and is interspersed within wellconserved regions, allowing differentiation between C. jejuni and C. coli (Fontanot and others 2014b). Virulence and toxin genes, such as cadF and cdtB, are also examined (Lemos and others 2015) to verify the importance of strains to public health. After amplification, the products are separated by gel electrophoresis, and the timeframe required for gel analysis as well as the inability to verify large numbers of strains are major impediments to this approach. In addition, although ethidium bromide is a relatively inexpensive reagent for DNA gel staining, it poses human and environmental safety concerns (Barletta and others 2013). Despite the limitations regarding this technique, PCR does allow for verification of the presence of a unique species in an amplification reaction and requires more time than multiplex PCR (mPCR), which enables determination of the presence of more than one species in a single reaction (Gharst and others 2013; Stanek 2013).


Campylobacter spp.

Simple PCR


Campylobacter coli

Campylobacter jejuni

Campylobacter

TOOLS

Ayaz and others (2016)

Turkey meat

Fontanot and others (2014a)

Ayaz and others (2016)

Turkey meat

Chicken and turkey meat

Zang and others (2017)

Geese and chickens

Lemos and others (2015)

Raja and others (2017)

Chicken meat

Poultry

Fontanot and others (2014b)

Poultry




Poultry


Poultry

von Altrock and others (2013)


Poultry

Pigs

von Altrock and others (2013)

Pigs


Poultry

Reference matrix von Altrock and others (2013)

Pigs

Matrix

ColiF: 5’-TGGTTGGGATGCAACTCTT-3’ ColiR: 5’-GCCTACACGAACTGTTTCGTTG-3’

VAT2: 5’-GTTAAAATCCCTGCTATCAACCA-3’ WMI-R: 5’-GTTGGCACTTGGAATTTGCAAGGC-3’

CC18F: 5’-GGTATGATTTCTACAAAGCGAG-3’ CC519R: 5’-ATAAAAGACTATCGTCGCGTG-3’

COL1: 5’-ATGAAAAAATATTTAGTTTTTGCA-3’ COL2: 5’-ATTTTATTATTTGTAGCAGCG-3’

Hip 400 F: 5’-GAA GAG GGT TTG GGT GGT-3’ Hip 1134 R: 5’-AGC TAG CTT CGC ATA ATA ACT TG-3’

Jej 1: 5’- CCT GCT ACG GTG AAA GTT TTG C-3’ Jej 2: 5’-GAT CTT TTT GTT TTG TGC TGC-3’

cjaA-F3: 5’-TCTAAGTGTTTTAACGGC-3’ cjaA-B3: 5’-AGTTCTTTTGCTATGCGT-3’

C-F: 5’-GGCGTTCATTTGGCGAATTTGAA-3’ C-R: 5’-CCGCTGTATTGCTCATAGGGA-3’

CampyForw: 5’-CTGATAAGGGTGAGGTCACAAGT-3’ CampyRev: 5’-CTTGCTTGTGACTCTTAACAATG-3’

JejuniF: 5’-TTCAGCAGCTAACGCTACT-3’ JeiuniR: 5’-AGCGATTACACTTGTAGCA-3’

F2B: 5’-TGGAGGGTAATTTAGAATATG-3’ R1B: 5’-CTAATACCTAAAGTTGAAAC-3’

CCCJ609F: 5’-AATCTAATGGCTTAACCATTA3’ CCCJ1442R: 5’-GTAACTAGTTTAGTATTCCGG3’

CAH16S 1a: 5’-AATACATGCAAGTCGAACGA-3’ CAH16S 1b: 5’-TTAACCCAACATCTCACGAC-3’

HIP400F: 5’-GAAGAGGGTTTGGGTGGTG-3’ HIP1134R: 5’-AGCTAGCTTCGCATAATAACTTG-3’

GTP1.1: 5’-GCCAAATGTTGGiAARTC-3’ GTP2.1: 5’-CATCAAGCCCTCCACTATC-3’ GTP 2.2: 5’-ATCiAGiCCTSSiCTRTC-3’

Primer

porA gene

cdtB virulence gene

CCCH gene

ceuA gene

hipO

ceuE

cjaA

Hyp gene

16S-23S ITS

porA gene

cadF virulence gene

rrs gene

16S rRNA

hip gene

GTPase gene

Sequence amplified

(Continued)


Ripabelli and others (2010)

Linton and others (1997)

Gonzalez and others (1997)



Zang and others (2017)

Raja and others (2017)



Ripabelli and others (2010)


Marshall and others (1999)


van Doorn and others (1998)

Reference primer

Table 1–Primers used in previous studies for the detection (PCR or multiplex PCR) and quantification (qRT-PCR or multiplex qRT-PCR) of Campylobacter spp. in foods of animal origin and the respective sequence amplified




qRT-PCR

Multiplex PCR

TOOLS

Broiler flocks

Bacterial strains of species

Campylobacter jejuni Campylobacter coli Campylobacter lari Campylobacter upsaliensis

Campylobacter spp.

Broilers

Broilers

de Boer and others (2015)

Girgis and others (2014)

Han and others (2016)

Zendehbad and others (2015)

Bratz and others (2013)

Pigs

Campylobacter spp. Campylobacter jejuni Campylobacter coli

Campylobacter spp. Campylobacter jejuni Campylobacter coli

Ansari-Lari and others (2011)



Broilers


Campylobacter upsaliensis

Campylobacter jejuni Campylobacter coli


Frasao and others (2015b)

Chickens

Reference matrix Fontanot and others (2014b)

Matrix

Poultry

Campylobacter lari

Campylobacter

Table 1–Continued. Primer

Sequence amplified

mapA ceuE

MDJEGF: 5 -CTATTTTATTTTTGAGTGCTTGTG-3 MDJEGR: 5 -GCTTTATTTGCCATTTGTTTTATT-3 , COLF: 5 -AATTGAAAATTGCTCCAACTATG-3 COLR: 5 -TGATTTTATTATTTGTAGCAGCG-3

16S-CampyF1: 5’-CACGTGCTACAATGGCATATACAA-3’ 16S-CampyR1: 5’-CCGAACTGGGACATATTTTATAGA TTT -3’ 16S-CampyP1 5’-FAM-AGACGCAATACCGTGAG GT-MGB-3’

C-1: 5’-CAAATAAAGTTAGAGGTAGAATGT-3’ C-3: 5’-CCATAAGCACTAGCTAGCTGAT-3’ CC18F: 5’GGTATGATTTCTACAAAGCGAG-3’ CC519R: 5’-ATAAAAGACTATCGTCGCGTG-3’ CLF: 5’-TAGAGAGATAGCAAAAGAGA-3’ CLR: 5’-TACACATAATAATCCCACCC-3’ CU61F: 5’-CGATGATGTGCAAATTGAAGC-3’ CU146R: 5’-TTCTAGCCCCTTGCTTGATG-3’

F: TCTAATGGCTTAACCATTAAAC R: GGACGGTAACTAGTTTAGTATT F: TGATGGCTTCTTCGGATAG R: CTAGCTTCGCATAATAACTTG F: ATTGAAAATTGCTCCAACTATG R: GATTTTATTATTTGTAGCAGCG

Fa: 5’-ATCTAATGGCTTAACCATTAAAC-3’ Ra: 5’-GGACGGTAACTAGTTTAGTATT-3’ F: 5’-CTATTTTATTTTTGAGTGCTTGTG-3’ R: 5’-GCTTTATTTGCCATTTGTTTTATTA-3’ F: 5’-AATTGAAAATTGCTCCAACTATG-3’ R: 5’-TGATTTTATTATTTGTAGCAGCG-3’

16S rDNA

cj0414§ askD glyA lpxA

16S rRNA hipO ceuE

16S rRNA mapA ceuA

hipO glyA

porA gene

UpsF: 5 -TGGAATGGCTTTGACGCT-3’ UpsR: 5’-GGTATAACCAGCAGTTAGG-3’

CJF: 5’-ACTTCTTTATTGCTTGCTGC3’ CJR: 5’-GCCACAACAAGTAAAGAAGC-3’ CCF: 5’-GTAAAACCAAAGCTTATCGTG-3’ CCR: 5’-TCCAGCAATGTGTGCAATG-3’

porA gene

ceuA gene

16S-23S ITS sequence

LariF: 5’-CAATACTTAGGAAATAGCTTAGAC-3’ LariR: 5’-GCTTGTTTAGATTTACCACCGA-3’

COL1: 5’-ATGAAAAAATATTTAGTTTTTGCA-3’ COL2: 5’-ATTTTATTATTTGTAGCAGCG-3’

CampyForw: 5’-CTGATAAGGGTGAGGTCACAAGT-3’ CampyRev: 5’-CTTGCTTGTGACTCTTAACAATG-3’

Reference primer

(Continued)

Lund and others (2004)

Wang and others (1992) Linton and others (1997) Wang and others (2002) Yamazaki-Matsune and others (2007)

Denis and others (1999) Han and others (2016) Denis and others (1999)

Zendehbad and others (2015)

Wang and others (2002)

Denis and others (1999)








Multiplex qRT-PCR

TOOLS

Campylobacter spp. Campylobacter jejuni

Campylobacter coli

Campylobacter jejuni

Campylobacter

Table 1–Continued.

Frasao and others (2015b)


Broiler flocks

Chickens

Toplak and others (2012)

Chickens

C412F: 5 -GGATGACACTTTTCGGAGC-3 C1288R: 5"-CATTGTAGCACGTGTGTC-3 . C-1: 5 -CAAATAAAGTTAGAGGTAGAATGT-3 C-4: 3 -TAGTCGATCGATCACGAATAGGG-5’

Ccoli-F2: 5’-CATATTGTAAAACCAAAGCTTATC-3’ Ccoli-R: 5’-AGTCCAGCAATGTGTGCAATG-3’ Ccoli probe: 5’-VIC-TAAGCTCCAACTTCATCCGCAATCTCT CTAAATTT-TAMRA-3’

CC_cadF_F: 5’-GAGAAATTTTATTTTTATGGTTTAGCTGGT-3’ CC_cadF_R: 5’-ACCTGCTCCATAATGGCCAA-3’ CC_cadF_probe YakimaYellow-5’CCTCCACTTTTATTATCAAAAGCGCCTTTAGAAABHQ1-3’

Cj-F2: 5’- ATGAAGCTGTGGATTTTGCTAGTG-3’ Cj-R3: 5’-AAATCCAAAATCCTCACTTGCCA-3’ Cj probe 5’-FAM-TTGTGAATTTAATCATCGTCC-MGB-3’


16S rRNA oxidoreductase gene

glyA

cadF

hipO

rpoB

Cj_rpoB1: 5 -GAGTAAGCTTGGTAAGATTAAAG-3 Cjs_rpoB2: 5 - AAGAAGTTTTAGAGTTTCTCC-3

hipO

Rantsiou and others (2010)

Bacterial strains of species Broiler flocks

Sequence amplified ccoN

ORF-C sequence

Sails and others (2003)

Food

CJ_hipO_F: 5-‘AATGCACAAATTTGCCTTATAAAAGC -3’ CJ_hipO_R: 5-‘TNCCATTAAAATTCTGACTTGCTAAATA-3’ CJ_hipO_probe: 5-‘FAM-ACATACTACTTCTTTATTGCTTG-MGB-3’

CJ_ccoN_F: 5’-TGGTCTAAGTCTTGAAAAAGTGGCA -3’ CJ_ccoN_R: 5-‘ACTCTTATAGCTTTTCAAATGGCATATCC-3’ CJ_ccoN_probe: 5’FAM-CTCCTGCTAAATAATTTAA-MGB-3’

Primer

CJTP2_F: TTGGTATGGCTATAGGAACTCTTATAGCT CJTP2_R: CACACCTGAAGTATGAAGTGGTCTAAGT CJTP2 probe:TGGCATATCCTAATTTAAATTATTTACCAGGAC


Chickens

Reference matrix Toplak and others (2012)

Matrix

Chickens

Reference primer

(Continued)

Linton and others (1996) Winters and Slavik (1995)

LaGier and others (2004)



Rantsiou and others (2010)

Sails and others (2003)





TOOLS



Shigella boydii Campylobacter jejuni Mycobacterium bovis Enterobacter sakazaki Clostridium perfringens

Campylobacter jejuni, Campylobacter coli, Campylobacter lari

Seafood

Chickens

Campylobacter spp. Salmonella spp. Shigella spp.

Campylobacter jejuni Campylobacter coli

Matrix


Campylobacter

Table 1–Continued. Reference matrix

Karus and others (2017)

Taminiau and others (2014)

He and others (2010)

Barletta and others (2013)

Primer

ipaH2_F: 5’-GATACCGTCTCTGCACGCAAT -3’ ipaH2_R: 5’-GCCATGCAGCGACCTGTT-3’ CadF_F: 5’-GTGGCAAAAAGGAAAAAGCTGTA -3’ CadF_R: 5’-CATTTTGCTTGTGGAGTTGCA-3’ Hsp_F: 5’-GGGTCAAGCTCGACGTTGA-3’ Hsp_R: 5’-CGGTGGTCCGTTTGGAACT-3’ AY748357_F: 5’-GCGCGGTGTGTCAGAGTCT -3’ AY748357_R: 5’-AACCTCACAACCCGAAGAAGTC-3’ α toxin _F: 5’-GCATGAGTCATAGTTGGGATGATT-3’ α toxin_R: 5’-TGCTGTTCCTTTTTGAGAGTTAGCT-3’

50S-F: 5’-GCGGGTTCAACAAGAACTAACG-3’ 50S-R: 5’-GTAGTTTCTTTCATTTGTTGGACCAA-3’ 50S-probe: 5’-[VIC]-TGGGTAGGCGGTGCGGTTGC-[NFQ-MGB]-3’ VS1-F: 5’-GTAGTTTCTTTCATTTGTTGGACCAA-3’ VS1-R: 5’-GCGGGTTCAACAAGAACTAACG-3’ VS1-probe: 5’-[FAM]AAGAATTAGAATATCGTGGCTATG-[NFQ-MGB]-3’

Cj For: 5’-TCCAAAATCCTCACTTGCCATT-3’ Cj Rev: 5’-TGCACCAGTGACTATGAATAACGA-3’ Cj Probe: 5’-T TGCAACCTCACTAGCAAAATCCACAGCT-3’ Cc For: 5’-TGTCAAACAAAAAACACCAAGCTT-3’ Cc Rev: 5’-CCTTTGACGGCATTATCTCCTT -3’ Cc Probe: 5’-AAAATTTCCCGCCATACCACTTGTCCC-3’ Cl For: 5’-TTAGATTGTTGTGAAATAGGCGAGTT-3’ Cl Rev: 5’-TGAGCTGATTTGCCTATAAATTCG-3’ Cl Probe: 5’-TGAAAATTGGAACGCAGGTG-3’

F: 5’-GGATGACACTTTTCGGAGC-3’ R:5’- CATTGTAGCACGTGTGTC-3’ F: 5’-CATTTCTATGTTCGTCATTCCATTACC-3’ R: 5’-AGGAAACGTTGAAAAACTGAGGATTCT-3’ F: 5’-CGCGACGGACAACAGAATACACTCCATC -3’ R: 5’-ATGTTCAAAAGCATGCCATATCTGTG-3’

Sequence amplified

ipaH2 cadF hsp AY748357 α toxin gene

50S gene VS1

hipO cdtA pepT

16S rRNA invA ipaH

Reference primer

Karus and others (2017)

Taminiau and others (2014)

He and others (2010)

Logan and others (2001) Pusterla and others (2010) Barletta and others (2013)



Campylobacter molecular tools in food . . . Multiplex PCR MPCR, allowing detection of 2 or more species in the same sample, has been developed in recent years (Gharst and others 2013). In experiments in which there is a need to identify different species of Campylobacter, or different genera, application of mPCR has great potential. However, this technique has some limiting factors, such as identifying or obtaining primers that have similar annealing temperatures (El-Adawy and others 2012). This methodology can readily be applied to Campylobacter spp. and C jejuni (Frasao and others 2015b) as well as C. coli, as has been described by various authors (Bratz and others 2013; Zendehbad and others 2015; Kashoma and others 2016; Rodgers and others 2016; Shams and others 2017); C. jejuni, C. coli, C. lari, and C. upsaliensis can also be identified using this method (Girgis and others 2014) (Table 1). In addition, Raja and Rao (2016) used the technique to detect 2 different pathogens, C. jejuni and Listeria monocytogenes, in chicken meat during processing. Nonetheless, complex sample preparation methods and manipulation of amplification products, that is, gel electrophoresis detection methods, are required, which hampers the routine use of these methods in food microbiology laboratories (Sails and others 2003). Accordingly, other faster PCR techniques have been developed, such as real-time PCR (qPCR).

The application of qPCR to the food industry supports the detection of pathogens; the approach is recognized and trusted (Boyer and Combrisson 2013), and it has been used to detect different species of Campylobacter (Postollec and others 2011; Vencia and others 2014). For detection of the Campylobacter genus, the primers used are specific for 16 rRNA genes (Garcia and others 2013; de Boer and others 2015; Gosselin-Theberge and others 2016). However, for detection of C. jejuni, the primers can be specific for the hipO gene (de Boer and others 2015), the ccoN or the hypO gene (Toplak and others 2012), the rpoB gene (Rantsiou and others 2010), or open reading frame (ORF) C (Sails and others 2003). For detection of C. coli, primers specific for the cadF gene (Toplak and others 2012) or the glyA gene (de Boer and others 2015) have been used. A significant number of studies report using qPCR for detection of Campylobacter spp. However, due to some difficulties, there are few reports of the use of this methodology for quantification of Campylobacter in food; for example, all Campylobacter bacteria present in the sample, including dead cells, are detected (Josefsen and others 2010; Melero and others 2011). Thus, RNA can be extracted to evaluate only viable strains (Josefsen and others 2010). Similarly, conventional PCR and multiplex real-time PCR (qRT-PCR) allow evaluation of the presence of different species or genera in the same reaction.

Real-time PCR Among the molecular methods based on PCR, qPCR offers speed, robustness, and high sensitivity and specificity for analysis. Accurate quantification of DNA and RNA can be performed. As this method enables online detection of the PCR product (Juste and others 2008), eliminating the need to manipulate PCR products after amplification, the risk of false-positive results through cross-contamination between amplification products and subsequent test samples is reduced (Sails and others 2003; McKillip and Drake 2004). Quantitative PCR methods with endpoint detection utilize an internal or external control with known concentrations that are amplified in parallel with the tested samples, and the results for a sample are provided from control data (Reischl and Kochanowski 1995). However, this methodology has limitations in its accuracy because the final quantity of the product that is accumulated in the final PCR process is very susceptible to small variations. The TaqMan 5 nuclease PCR method utilizes a fluorogenically labeled probe, which when hybridized and cleaved allows detection of the PCR product accumulated during the amplification reaction (Livak and others 1995). The fluorescence emitted is the direct result of the specific PCR product incorporating that probe. This increase can be monitored in real time, allowing accurate quantification of the DNA or RNA sequence (Gibson and others 1996). This method has the ability to quantify target organisms in complex matrices and is therefore a promising tool for improving the safety and quality of food. Indeed, food scientists employ using qPCR for security management and food quality (Mart´ınez and others 2011). Compared to conventional PCR, the possible rapid and reliable detection as well as quantification of specific pathogens is highly desirable (Josefsen and others 2010), and there is a reduced risk of contamination because the presence of labeled DNA is indicated by an increase in fluorescence. Additionally, it is possible to quantify specific microorganisms (Dolan and others 2010). This methodology is attractive because it is fast and robust, as there is no need for processing to detect the amplified product (Barletta and others 2013).

Multiplex real-time PCR Segments of DNA can be amplified in a simple multiple reaction to simultaneously detect and differentiate various species and strains of bacteria. Several studies have been conducted for discriminating among different species of Campylobacter, especially C. jejuni and C. coli, C. jejuni, C. coli, and C. lari, or C. jejuni, C. coli, and C. upsaliensis, and for detection of different genera, such as Campylobacter, Salmonella, and Shigella (He and others 2010; Barletta and others 2013), C. coli, C. jejuni, Escherichia coli O157:H7, and Salmonella spp. (Taminiau and others 2014), or C. jejuni, Mycobacterium bovis, Enterobacter sakazaki, Shigella boydii, and Clostridium perfringens (Karus and others 2017) (Table 1). For simultaneous detection of C. jejuni and C. coli, primers for amplifying the hypo gene (amidohydrolase benzoylglycine) and the glyA gene (serine hydroxymethyltransferase) are used. The hypO gene is responsible for the hippurate activity found exclusively in C. jejuni, and the glyA gene is found in a unique sequence in C. coli (Leblanc-Maridor and others 2011). A combination of primers for amplifying the ccoN gene was reported to be specific for C. jejuni, and the addition of primers specific for C. coli cadF has been used for simultaneous detection of both species (Toplak and others 2012). Amplification of the hypO gene (C. jejuni) and cadF gene (C. coli) has also been employed (Toplak and others 2012). Simultaneous detection of thermophilic species using the bipA gene was validated for C. upsaliensis and C. lari, and the cje0832 gene as used for C. jejuni and C. coli (Bonjoch and others 2010). For simultaneous detection of C. jejuni, C. coli, C. lari, C. upsaliensis, and Campylobacter fetus subsp. fetus, primers specific for the hypo for the 1st, sapB2 for the last, and glyA for others were utilized (Wang and others 2002). Primers amplifying the 16S RNA gene detect the efflux pump, which characterizes cmeABC resistance, and the hypo gene is used to detect C. jejuni; the cdtA gene is used to detect C. coli and the peptidyl gene is used to detect C. lari and allow simultaneous detection of the presence of the efflux pump for identifying the C. jejuni, C. coli, and C. lari (He and others 2010). Additionally, a commercial qPCR-based method kit for detecting C. jejuni, C. coli, and C. lari in foods, fruit and vegetable-based



Campylobacter molecular tools in food . . . products, and dairy products was validated by Vencia and others (2014). However, PCR techniques, including PCR, mPCR, q-PCR, and q-RT-PCR, do not allow for the molecular characterization of Campylobacter. Conversely, PFGE and MLST are efficient tools for this purpose.

Molecular Tools Used for Typing Campylobacter spp. in Foods of Animal Origin Pulsed-field gel electrophoresis In 1980, an electrophoretic “alternative” was developed based on the principle of periodic reorientation of the electric field (migration and DNA) relative to the direction of the gel. As smaller DNA molecules require less time than larger molecules to redirect after application of a gradual increase in electrophoretic pulse time, the observed different directions allow for separation of DNA fragments of different sizes, from kb to Mb. Electrophoresis separates molecules according to their electric charge, with the formation of strips or bands grouping similar fragments (Goering 2010). PFGE is based on gel electrophoresis of restriction-digested genomic DNA (Noormohamed and Fakhr 2014). The principle of PFGE is that DNA molecules, including Mbsize fragments, can be separated by applying a periodic pulse to the electric field in different directions. Fragments hundreds of kb in length migrate proportional to their sizes and the pulse time (Goering 2010). In this case, the pattern of the bands determines the relatedness of the isolates (Noormohamed and Fakhr 2014). Due to its efficiency, PFGE prevents compacting of the fragments and allows for separation of intact chromosomes of yeast and molds. However, as mammalian chromosomes are too large, special restriction enzymes that 1st cleave DNA fragments of 40 kb to 2 Mb are required (Mawer and Leach 2014). This methodology is widely used for typing to obtain a clear comparison of genomic relationships among bacterial isolates, with the ability to correlate isolated microorganisms from different sites and samples. This technique is classified as a 3rd-generation technique that uses molecular interaction and is considered the “gold standard” for evaluating interrelationships between isolates, including foodborne pathogens (Goering 2010; Chung and others 2012; Noormohamed and Fakhr 2014). Additionally, a network project, called Campynet, to standardize subtyping methods for Campylobacter in the European Union was created in 1998. Three protocols were validated: fla-PCR RFLP, PFGE, and amplified fragment length polymorphism (www.svs.dk/campynet). In addition, outbreaks of foodborne illness can be detected and examined using data obtained and “fingerprinting” patterns in PulseNet, a network of national and international laboratories for foodborne disease. As PFGE is the molecular subtyping method of choice for PulseNet laboratories, it is possible to detect thousands of food outbreaks (CDC/US 2013). Typing of Campylobacter strains isolated from pigs, poultry, turkey, sheep, and lambs by PFGE has been described, mainly in outbreak investigations for correlating the isolates from sick patients with those from animal products (Silva and others 2016; Lahti and others 2017a). In many cases, the sample must be digested with the restriction enzymes SmaI and KpnI for efficiency (Abley and others 2012; Melero and others 2012; Garcia and others 2013; Abay and others 2014). A 1st digestion with the SmaI enzyme and a 2nd digestion with the SmalI enzyme were also introduced (Postollec and others 2011). However, only SmaI was C 2017 Institute of Food Technologists®

applied by Oyarzabal and others (2013), Silva and others (2016), and Lahti and others (2017a, b). In New Zealand, the most frequently isolated PFGE genotypes of Campylobacter spp. from sheep were typically natural strains in ovine feces and those observed to cause disease in humans (Gilpin and others 2013). Silva and others (2016) found that Campylobacter clones belong to poultry flocks to indicate endemic strains with horizontal transmission among birds. In addition, the genetic profile associated with different farms suggested different sources of contamination. Lahti and others (2017b) determined that human and cattle C. jejuni isolates belong to same cluster; thus, cattle were considered the source of microorganisms at that particular dairy farm. However, patterns not distinguishable after multiple attempts were excluded. In one study, isolates from chicken rectal swabs presented high similarity (100%), with the lowest being 26%; such similarity indicates a level of homogeneity and identical genotypes. Nonetheless, other authors identified differences in resistance profiles, including multidrug-resistant strains (Bakhshi and others 2016). The presence of 6 genotypes indistinguishable from human clinical isolates suggests that the survival data generated by this study are applicable to zoonotic Campylobacter strains (Chung and others 2012). In addition, because of the potential to identify and determine groups of bacteria or food outbreaks, this methodology can be applied for assessing gene location, such as gentamicin-resistant genes on a plasmid or the chromosome (Yao and others 2017). PFGE is widely used as a genotyping method for bacteria, including foodborne pathogens, enabling determination of the genetic proximity of these microorganisms. However, several factors can influence gel resolution and quality of the results, including variations in voltage, pulse time, gel concentration, temperature, buffer solution, angle between the alternating fields, sample preparation, and choice of restriction enzyme. Moreover, its disadvantages include the requirement of expensive equipment and complex protocols, without standardized methods for result interpretation, which makes it difficult to compare with data from other researchers (Noormohamed and Fakhr 2014). Another method of genotyping is MLST, which can confirm small differences in strains that are considered identical in PFGE and allows for a better comparison between results obtained by different scientists.

Multilocus sequence typing In 1998, MLST was proposed as a universal and definitive method for characterizing bacteria (Maiden and others 1998). This technique is used for the characterization of bacterial isolates based on the sequences of internal fragments of 7 housekeeping genes that are fairly conserved. Each recorded sequence of each gene is given a number (Noormohamed and Fakhr 2014). MLST can be used for epidemiological investigations, studies of population biology, and the pathogenic evolution of bacteria (Urwin and Maiden 2003; Maiden 2006; Strachan and others 2012; Noormohamed and Fakhr 2014). Unlike most techniques used for typing, which compare the sizes of DNA fragments on gels, the allelic profiles obtained by MLST can be compared with those found in databases, and the results are unambiguous (Maiden and others 1998). A series of 7 integers represents the alleles of 7 housekeeping loci. The alleles at each of the 7 loci define the sequence type (ST) of each isolate, and the different sequences found within bacterial species are assigned to distinct alleles for each housekeeping gene. The sequences are indicated by different numbers of alleles, despite


Campylobacter molecular tools in food . . . differences in nucleotides between alleles and the fact that such differences can be found at a single nucleotide site or at many sites (Maiden and others 1998). In MLST, gene fragments are amplified from chromosomal DNA using PCR. For each gene fragment, sequences are compared, and the sequence of identical isolates receives the same number assigned to an allele. The number of alleles at each of the 7 loci is assigned by comparing the sequences of each fragment with all sequences previously identified including at that locus. For each strain, the combination of the 7 allele numbers defines the allelic profile of the strain, and a multilocus ST is assigned to each different allelic profile. The relationship between each multilocus ST is illustrated in a dendrogram (Maiden and others 1998). Due to variation, MLST tool can detect more alleles per locus than other molecular typing methods and data can be compared between laboratories and stored in electronic databases for wide access, thus supporting global epidemiology and comparison (Dingle and others 2001). The MLST patterns for C. jejuni and C. coli have been determined and available (Dingle and others 2002; Jolley and Maiden 2010; PubMLST.org 2016). This technique can be applied to almost all species of bacteria and other haploid organisms, including those difficult to culture, and for characterizing hypervariable genomes, such as that of Campylobacter spp. (Maiden and others 1998; Dingle and others 2001; Behringer and others 2011; Noormohamed and Fakhr 2014; Wei and others 2014). MLST requires PCR amplification of the 7 MLST loci: aspA (aspartase), glnA (glutamine synthetase), gltA (citrate synthase), glyA (serine hydroxy methyl transferase), tkt (transketolase), pgm (phospho glucomutase), and uncA (ATP synthase alpha subunit). This technique is described in several studies of isolated Campylobacter spp. strains from ducks, milk, chickens, pork, and beef (Strachan and others 2012; Stone and others 2013; Bianchini and others 2014; Carrique-Mas and others 2014; Noormohamed and Fakhr 2014; Revez and others 2014; Wei and others 2014). This tool is commonly used to determine the STs of Campylobacter isolates as well as genotypes and genetic diversity (Strachan and others 2012; Stone and others 2013; Bianchini and others 2014; Revez and others 2014; Wei and others 2014; Vidal and others 2016) and for typing (Behringer and others 2011; Abley and others 2012; Egger and others 2012; Manfreda and others 2016; Pan and others 2016; Vinueza-Burgos and others 2017). MLST can be applied to determine macrolide and quinolone resistance based on partial sequences of 23S rRNA and gyrA genes (Jonas and others 2015). It can also detect the level of genetic diversity of species and predict interspecies transmission, as reported for experiments on pig and poultry farms (Ceuppens and others 2014), and to determine genetic relatedness between C. jejuni and C. coli isolates from retail meat sources (Noormohamed and Fakhr 2014) and Campylobacter isolates from chicken flocks on 2 farms (Zhang and others 2017). MLST has also been used in reports of outbreaks and for determining public health cases (Schleihauf and others 2017) and epidemiological relationships of C. jejuni strains from chickens and humans (Oh and others 2017). In all these studies, STs and clonal complexes were assigned using the C. jejuni or C. coli PubMLST database. This technology is of great importance for the genotyping of Campylobacter and is an important tool for elucidating the diversity of animal hosts for Campylobacter isolates. In addition, this technique can be used in the epidemiological investigation of outbreaks and related diseases. MLST provides not only information on transmission routes to humans, but also on host-specific emer-

gence of antibiotic-resistant clones and their persistence within the animal host and environment (Stone and others 2013). However, it is not possible to examine the bacterial genome or determine codons mutated when testing antimicrobial resistance.

Conclusions Current molecular methodologies constitute breakthroughs in detecting and typing microorganisms responsible for foodborne illness. PCR is an important technique for the differentiation of species within Campylobacter and can be used for confirmation of strains assessed using conventional microbiology. Although quantification is not possible using this technique, it was and still is widely used to confirm and identify species, virulence genes, and even plasmids responsible for antimicrobial resistance. To lower the cost of technology, mPCR is an important tool for simultaneous detection of certain species and even genera such as C. coli and C. jejuni, C. coli, C. jejuni, and C. lari, as well as Salmonella, Shigella, and Campylobacter. Allowing for bacterial quantification, qPCR has been applied for the identification and quantification of Campylobacter spp. The application of mPCR in real time allows not only simultaneous identification of different species, but also quantification of each species in one analysis or reaction. With regard to species difficult to quantify, isolate, or distinguish, such as Campylobacter spp., PFGE is an important technique enabling research on the entire food supply chain as well as the tracing and estimation of the same strain responsible for contamination, from the raising of the animal to the foodborne illness in a human. In addition, MLST is of great importance for the genotyping of Campylobacter spp., as well as elucidating the diversity of animal hosts of Campylobacter isolates. With this tool, detection of host-specific emergence of antibiotic-resistant clones and their persistence within the animal host, the environment, and food can be achieved. Moreover, PCR should be used when the research aim is to detect the presence or absence of Campylobacter and specific species in food. Another application is the determination of particular characteristics, such as antibiotic resistance and virulence genes. MPCR should be performed when the goal is identification of a microorganism at the species level or a different species. However, when quantification is the objective, qPCR should be applied. PFGE can be used to correlate strains isolated from different sites in an effort to determine the level of relationship between strains. The MLST approach is also able to detect the level of genetic diversity of species and predict interspecies transmission. PFGE and MLST can be used to type and determine the relationship between contaminated products and human cases in outbreaks. In view of these state-of-the-art techniques, current molecular tools are both promising and important for the identification and differentiation of Campylobacter spp., as well as for the quantification and determination of characteristics of different strains.

Acknowledgments The authors thank the Research Foundation of the State of Rio de Janeiro (grants E-26/201.185/2014 and E26/010.001911/2015, FAPERJ, Brazil) and the Natl. Council of Technological and Scientific Development (grant 311361/20137, CNPq, Brazil) for financial support. B.S. Frasao was supported by the Coordination of Enhancement of People of a Superior Level (grant 125, 15/2014, CAPES/EMBRAPA, Brazil) graduate scholarship.




Author Contributions

and tools for high-throughput rRNA analysis. Nucleic Acids Res

Frasao interpreted and compiled the data and drafted the 33:D294–6. manuscript. Marin researched prior studies. Conte-Junior super- Cover KE, Ruiz SA, Chapman AS. 2014. Reported gastrointestinal infections in the U.S. Air Force, 2000–2012. MSMR 21:2–7. vised and reviewed the writing of the manuscript.

D’Auria G, Pushker R, Rodriguez-Valera F. 2006. IWoCS: analyzing ribosomal intergenic transcribed spacers configuration and taxonomic relationships. Bioinformatics 22:527–31. de Boer P, Rahaoui H, Leer RJ, Montijn RC, van der Vossen JM. 2015. References Real-time PCR detection of Campylobacter spp.: a comparison to classic Abay S, Kayman T, Otlu B, Hizlisoy H, Aydin F, Ertas N. 2014. Genetic culturing and enrichment. Food Microbiol 51:96–100. diversity and antibiotic resistance profiles of Campylobacter jejuni isolates from Denis M, Soumet C, Rivoal K, Ermel G, Blivet D, Salvat G, Colin P. 1999. poultry and humans in Turkey. Intl J Food Microbiol 178:29–38. Development of a m-PCR assay for simultaneous identification of Abley MJ, Wittum TE, Funk JA, Gebreyes WA. 2012. Antimicrobial Campylobacter jejuni and C. coli. Lett Appl Microbiol 29:406–10. susceptibility, pulsed-field gel electrophoresis, and multi-locus sequence Dingle KE, Colles FM, Wareing DR, Ure R, Fox AJ, Bolton FE, Bootsma typing of Campylobacter coli in swine before, during, and after the slaughter HJ, Willems RJ, Urwin R, Maiden MC. 2001. Multilocus sequence typing process. Foodborne Pathog Dis 9:506–12. system for Campylobacter jejuni. J Clin Microbiol 39:14–23. Ansari-Lari M, Hosseinzadeh S, Shekarforoush SS, Abdollahi M, Berizi E. Dingle KE, Colles FM, Wareing DR, Ure R, Wagenaar JA, Duim B, Bolton 2011. Prevalence and risk factors associated with Campylobacter infections in FJ, Fox AJ, Wareing DR, Maiden MC. 2002. Molecular characterization of broiler flocks in Shiraz, southern Iran. Intl J Food Microbiol 144(3):475–9. Campylobacter jejuni clones: a basis for epidemiologic investigation. Emerg Aquino MH, Filgueiras AL, Ferreira MC, Oliveira SS, Bastos MC, Tibana A. Infect Dis 8:949–55. 2002. Antimicrobial resistance and plasmid profiles of Campylobacter jejuni Docherty L, Adams MR, Patel P, McFadden J. 1996. The magnetic and Campylobacter coli from human and animal sources. Lett Appl Microbiol immuno-polymerase chain reaction assay for the detection of Campylobacter 34:149–53. in milk and poultry. Lett Appl Microbiol 22:288–92. Ayaz N, Goncuoglu M, Cakmak O, Erol I. 2016. Comparison of hipO and Dolan A, Burgess CM, Fanning S, Duffy G. 2010. Application of quantitative ceuE gene based PCR assays for the detection of Campylobacter jejuni. J Clin reverse-transcription PCR (qRT-PCR) for the determination of the total Microbiol Biochem Technol 8:6–8. viable count (TVC) on meat samples. J Appl Microbiol 109:91–8. Bakhshi B, Kalantar M, Rastegar-Lari A, Fallah F. 2016. PFGE genotyping Dong QL, Barker GC, Gorris LG, Tian MS, Song XY, Malakar PK. 2015. and molecular characterization of Campylobacter spp. isolated from chicken Status and future of quantitative microbiological risk assessment in China. meat. Iran J Vet Res 17:177–83. Trends Food Sci Technol 42:70–80. Barletta F, Mercado EH, Lluque A, Ruiz J, Cleary TG, Ochoa TJ. 2013. Duarte A, Santos A, Manageiro V, Martins A, Fraqueza MJ, Canica M, Multiplex real-time PCR for detection of Campylobacter, Salmonella, and Domingues FC, Oleastro M. 2014. Human, food and animal Campylobacter Shigella. J Clin Microbiol 51:2822–9. spp. isolated in Portugal: high genetic diversity and antibiotic resistance Behringer M, Miller WG, Oyarzabal OA. 2011. Typing of Campylobacter rates. Intl J Antimicrob Agents 44:306–13. jejuni and Campylobacter coli isolated from live broilers and retail broiler meat EFSA (European Food Safety Authority). 2013. Panel on biological hazards. by flaA-RFLP, MLST, PFGE and REP-PCR. J Microbiol Methods Scientific opinion on the evaluation of molecular typing methods for major 84:194–201. food-borne microbiological hazards and their use for attribution modelling, Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL. 2004. outbreak investigation and scanning surveillance: part 1 (evaluation of GenBank: update. Nucleic Acids Res 32:D23–6. methods and applications). EFSA J 11:3502. Bianchini V, Borella L, Benedetti V, Parisi A, Miccolupo A, Santoro E, EFSA (European Food Safety Authority). 2014a. Campylobacter. Available Recordati C, Luini M. 2014. Prevalence in bulk tank milk and from: https://www.efsa.europa.eu/en/topics/topic/campylobacter.htm. epidemiology of Campylobacter jejuni in dairy herds in Northern Italy. Appl Accessed 2016 June 1. Environ Microbiol 80:1832–7. EFSA (European Food Safety Authority). 2014b. Campylobacter decreases Bonjoch X, Calvó L, Soler M, Ruiz-Rueda O, Garcia-Gil LJ. 2010. A new slightly, Salmonella down, Listeria up-EFSA and ECDC say. Available from: multiplexed real-time PCR assay to detect Campylobacter jejuni, C. coli, C. https://www.efsa.europa.eu/en/press/news/140219.htm. Accessed 2016 lari, and C. upsaliensis. Food Anal Methods 3:40–6. May 28. Boyer M, Combrisson J. 2013. Analytical opportunities of quantitative Egger R, Korczak BM, Niederer L, Overesch G, Kuhnert P. 2012. polymerase chain reaction in dairy microbiology. Intl Dairy J 30:45–52. Genotypes and antibiotic resistance of Campylobacter coli in fattening pigs. Vet Microbiol 155:272–8. Bratz K, Bucker R, Golz G, Zakrzewski SS, Janczyk P, Nockler K, Alter T. 2013. Experimental infection of weaned piglets with Campylobacter El-Adawy H, Hotzel H, Tomaso H, Neubauer H, Hafez HM. 2012. coli-excretion and translocation in a pig colonisation trial. Vet Microbiol Elucidation of colonization time and prevalence of thermophilic 162:136–43. Campylobacter species during turkey rearing using multiplex polymerase chain reaction. Poult Sci 91:454–9. Carrique-Mas JJ, Bryant JE, Cuong NV, Hoang NV, Campbell J, Hoang NV, Dung TT, Duy DT, Hoa NT, Thompson C, Hien VV, Phat VV, Euzéby JP. 2010. List of prokaryotic names with standing in nomenclature: Farrar J, Baker S. 2014. An epidemiological investigation of Campylobacter in genus Campylobacter. Available from: pig and poultry farms in the Mekong delta of Vietnam. Epidemiol Infect https://www.bacterio.net/campylobacter.html. Accessed 2016 December 142:1425–36. 20. CDC/US (Centers for Disease Control and Prevention). 2013. Euzéby JP. 2014. List of prokaryotic names with standing in nomenclature: Campylobacter. Available from: genus Campylobacter. Available from: https://www.cdc.gov/nczved/divisions/dfbmd/diseases/campylobacter/. https://www.bacterio.net/campylobacter.html. Accessed 2016 December Accessed 2013 November 12. 23. CDC/US (Center for Disease Control and Prevention). 2014. New CDC FDA (Food and Drug Administration). 2012. Bad bug book, foodborne data on foodborne disease outbreaks. Available from: pathogenic microorganisms and natural toxins-Campylobacter jejuni. 2nd ed. https://www.cdc.gov/features/foodborne-diseases-data/?s_cid = cdc_ Egypt, FDA. p 14–7. Available from: homepage_feature_002. Accessed 2014 June 25. http://pdf.usaid.gov/pdf_docs/Pnado152.pdf. Accessed 2016 December 15. Ceuppens S, Li D, Uyttendaele M, Renault P, Ross P, Ranst MV, Cocolin Fontanot M, Iacumin L, Cecchini F, Comi G, Manzano M. 2014a. Rapid L, Donaghy J. 2014. Molecular methods in food safety microbiology: detection and differentiation of important Campylobacter spp. in poultry interpretation and implications of nucleic acid detection. Compr Rev Food samples by dot blot and PCR. Food Microbiol 43:28–34. Sci Food Saf 13:551–77. Fontanot M, Iacumin L, Cecchini F, Comi G, Manzano M. 2014b. PorA Chung S, Yi J, Jang MH, Joo SI, Ra EK, Kim SY, Chang CL, Park SS, specific primers for the identification of Campylobacter species in food and Kim EC. 2012. Comparison of modified multiple-locus variable-number clinical samples. LWT-Food Sci Technol 58:86–92. tandem-repeat fingerprinting with pulsed-field gel electrophoresis for Franco BDGM, Landgraf M. 2008. Microrganismos patogênicos de typing clinical isolates of Staphylococcus aureus. Ann Lab Med 32:50–6. importância em alimentos. In: Microbiologia dos alimentos. São Paulo: Cole JR, Chai B, Farris RJ, Wang Q, Kulam SA, McGarrell DM, Garrity Atheneu. p 33–81. GM, Tiedje JM. 2005. The ribosomal database project (RDP-II): sequences



Campylobacter molecular tools in food . . . Frasao BS, Aquino MHC. 2014. Campylobacter spp. em aves (Gallus gallus domesticus) e su´ınos (Sus domesticus): resistência a antimicrobianos e importância na saúde coletiva. Enciclopédia Biosfera 10:745–58. Frasao BS, Cortes LR, Nascimento ER, Cunha NC, Almeida VL, Aquino MHC. 2015a. Detecça˜ o de resistência a` s fluoroquinolonas em Campylobacter isolados de frangos de criaça˜ o orgânica. Pesq Vet Bras 35:613–9. Frasao BS, Medeiros V, Barbosa AV, de Aguiar WS, dos Santos FF, Abreu DLDC, Clementino MM, de Aquino MHC. 2015b. Detection of fluoroquinolone resistance by mutation in gyrA gene of Campylobacter spp. isolates from broiler and laying (Gallus gallus domesticus) hens, from Rio de Janeiro State, Brazil. Cienc Rural 45:2013–8. Gallay A, Prouzet-Mauléon V, Kempf I, Lehours P, Labadi L, Camou C, Denis M, de Valk H, Desenclos J-C, Mégraud F. 2007. Campylobacter antimicrobial drug resistance among humans, broiler chickens, and pigs, France. Emerg Infect Dis 13:259–66. Garcia AB, Kamara JN, Vigre H, Hoorfar J, Josefsen MH. 2013. Direct quantification of Campylobacter jejuni in chicken fecal samples using real-time PCR: evaluation of six rapid DNA extraction methods. Food Anal Methods 6:1728–38. Gharst G, Oyarzabal OA, Hussain SK. 2013. Review of current methodologies to isolate and identify Campylobacter spp. from foods. J Microbiol Methods 95:84–92. Gibson UE, Heid CA, Williams PM. 1996. A novel method for real time quantitative RT-PCR. Genome Res 6:995–1001. Giesendorf BA, Quint WG, Henkens MH, Stegeman H, Huf FA, Niesters HG. 1992. Rapid and sensitive detection of Campylobacter spp. in chicken products by using the polymerase chain reaction. Appl Environ Microbiol 58:3804–8. Gilpin BJ, Walshe G, On SL, Smith D, Marshall JC, French NP. 2013. Application of molecular epidemiology to understanding campylobacteriosis in the Canterbury region of New Zealand. Epidemiol Infect 141:1253–66. Girgis SA, Rashad SS, Othman HB, Bassim HH, Kassem NN, El-Sayed FM. 2014. Multiplex PCR for identification and differentiation of Campylobacter species and their antimicrobial susceptibility pattern in Egyptian patients. Intl J Curr Microbiol App Sci 3:861–75. Goering RV. 2010. Pulsed field gel electrophoresis: a review of application and interpretation in the molecular epidemiology of infectious disease. Infect Genet Evol 10:866–75. Gonzalez I, Grant KA, Richardson PT, Park SF, Collins MD. 1997. Specific identification of the enteropathogens Campylobacter jejuni and Campylobacter coli by using a PCR test based on the ceuE gene encoding a putative virulence determinant. J Clin Microbiol 35:759–63. Gosselin-Theberge M, Taboada E, Guy RA. 2016. Evaluation of real-time PCR assays and standard curve optimisation for enhanced accuracy in quantification of Campylobacter environmental water isolates. J Microbiol Methods 129:70–7. Han X, Zhu D, Lai H, Zeng H, Zhou K, Zou L, Wu C, Han G, Liu S. 2016. Prevalence, antimicrobial resistance profiling and genetic diversity of Campylobacter jejuni and Campylobacter coli isolated from broilers at slaughter in China. Food Control 69:160–70. Haruna M, Sasaki Y, Murakami M, Mori T, Asai T, Ito K, Yamada Y. 2013. Prevalence and antimicrobial resistance of Campylobacter isolates from beef cattle and pigs in Japan. J Vet Med Sci 75:625–8. He Y, Yao X, Gunther NW, Xie Y, Tu S-I, Shi X. 2010. Simultaneous detection and differentiation of Campylobacter jejuni, C. coli, and C. lari in chickens using a multiplex real-time PCR assay. Food Anal Methods 3:321–9. Hermans D, van Deun K, Messens W, Martel A, van Immerseel F, Haesebrouck F, Rasschaert G, Heyndrickx M, Pasmans F. 2011. Campylobacter control in poultry by current intervention measures ineffective: urgent need for intensified fundamental research. Vet Microbiol 152:219–28. Hue-Roye K, Vege S. 2008. Principles of PCR-based assays. Immunohematology 24:170–5. Jackson CJ, Fox AJ, Jones DM. 1996. A novel polymerase chain reaction assay for the detection and speciation of thermophilic Campylobacter spp. J Appl Bacteriol 81:467–73. Jacxsens L, Luning PA, Marcelis WJ, van Boekel T, Rovira J, Oses S, Kousta M, Drosinos E, Jasson V, Uyttendaele M. 2011. Tools for the performance assessment and improvement of food safety management systems. Trends Food Sci Technol 22:S80–9. Jayasena DD, Jo C. 2013. Essential oils as potential antimicrobial agents in meat and meat products: a review. Trends Food Sci Technol 34:96–108.

Jolley KA, Maiden MC. 2010. BIGSdb: scalable analysis of bacterial genome variation at the population level. BMC Bioinformatics 11:595–605. Jonas R, Kittl S, Overesch G, Kuhnert P. 2015. Genotypes and antibiotic resistance of bovine Campylobacter and their contribution to human campylobacteriosis. Epidemiol Infect 143:2373–80. Josefsen MH, Lofstrom C, Hansen TB, Christensen LS, Olsen JE, Hoorfar J. 2010. Rapid quantification of viable Campylobacter bacteria on chicken carcasses, using real-time PCR and propidium monoazide treatment, as a tool for quantitative risk assessment. Appl Environ Microbiol 76:5097– 104. Juste A, Thomma BP, Lievens B. 2008. Recent advances in molecular techniques to study microbial communities in food-associated matrices and processes. Food Microbiol 25:745–61. Karus A, Ceciliani F, Bonastre AS, Karus V. 2017. Development of simple multiplex real-time PCR assays for foodborne pathogens detection and identification on lightcycler. Maced Vet Rev 40:53–8. Kashoma IP, Kassem, II, John J, Kessy BM, Gebreyes W, Kazwala RR, Rajashekara G. 2016. Prevalence and antimicrobial resistance of Campylobacter isolated from dressed beef carcasses and raw milk in Tanzania. Microb Drug Resist 22:40–52. Kittl S, Heckel G, Korczak BM, Kuhnert P. 2013. Source attribution of human Campylobacter isolates by MLST and Fla-typing and association of genotypes with quinolone resistance. PLoS One 8:e81796. Koike R, Asai T, Ozawa M, Ishikawa H. 2008. The use of therapeutic antimicrobials for food-producing animals. Annual Report Nat Vet Assay Lab 45: 30–3. LaGier MJ, Joseph LA, Passaretti TV, Musser KA, Cirino NM. 2004. A real-time multiplexed PCR assay for rapid detection and differentiation of Campylobacter jejuni and Campylobacter coli. Mol Cell Probes 18:275–82. Lahti E, Lofdahl M, Agren J, Hansson I, Engvall EO. 2017a. Confirmation of a campylobacteriosis outbreak associated with chicken liver pate using PFGE and WGS. Zoonoses Public Health 64:14–20. Lahti E, Rehn M, Ockborn G, Hansson I, Agren J, Engvall EO, Jernberg C. 2017b. Outbreak of campylobacteriosis following a dairy farm visit: confirmation by genotyping. Foodborne Pathog Dis ahead of print. https://doi.org/10.1089/fpd.2016.2257. Leblanc-Maridor M, Beaudeau F, Seegers H, Denis M, Belloc C. 2011. Rapid identification and quantification of Campylobacter coli and Campylobacter jejuni by real-time PCR in pure cultures and in complex samples. BMC Microbiol 11:113–28. Lemos A, Morais L, Fontes MDC, Pires I, Vieira-Pinto M. 2015. Campylobacter spp. isolation from infected poultry livers with and without necrotic lesions. Food Control 50:236–42. Linton D, Lawson AJ, Owen RJ, Stanley J. 1997. PCR detection, identification to species level, and fingerprinting of Campylobacter jejuni and Campylobacter coli direct from diarrheic samples. J Clin Microbiol 35:2568–72. Linton D, Owen RJ, Stanley J. 1996. Rapid identification by PCR of the genus Campylobacter and of five Campylobacter species enteropathogenic for man and animals. Res Microbiol 147:707–18. Livak KJ, Flood SJ, Marmaro J, Giusti W, Deetz K. 1995. Oligonucleotides with fluorescent dyes at opposite ends provide a quenched probe system useful for detecting PCR product and nucleic acid hybridization. PCR Methods Appl 4:357–62. Logan JM, Edwards KJ, Saunders NA, Stanley J. 2001. Rapid identification of Campylobacter spp. by melting peak analysis of biprobes in real-time PCR. J Clin Microbiol 39:2227–32. Lund M, Nordentoft S, Pedersen K, Madsen M. 2004. Detection of Campylobacter spp. in chicken fecal samples by real-time PCR. J Clin Microbiol 42:5125–32. Maiden MC. 2006. Multilocus sequence typing of bacteria. Annu Rev Microbiol 60:561–88. Maiden MC, Bygraves JA, Feil E, Morelli G, Russell JE, Urwin R, Zhang Q, Zhou J, Zurth K, Caugant DA, Feavers IM, Achtman M, Spratt BG. 1998. Multilocus sequence typing: a portable approach to the identification of clones within populations of pathogenic microorganisms. Proc Natl Acad Sci USA 95:3140–5. Manfreda G, Parisi A, De Cesare A, Mion D, Piva S, Zanoni RG. 2016. Typing of Campylobacter jejuni isolated from Turkey by genotypic methods, antimicrobial susceptibility, and virulence gene patterns: a retrospective study. Foodborne Pathog Dis 13:93–100. Marshall SM, Melito PL, Woodward DL, Johnson WM, Rodgers FG, Mulvey MR. 1999. Rapid identification of Campylobacter, Arcobacter, and



Campylobacter molecular tools in food . . . Helicobacter isolates by PCR-restriction fragment length polymorphism analysis of the 16S rRNA gene. J Clin Microbiol 37:4158–60. Mart´ınez N, Mart´ın MC, Herrero A, Fernández M, Alvarez MA, Ladero V. 2011. qPCR as a powerful tool for microbial food spoilage quantification: significance for food quality. Trends Food Sci Technol 22:367–76. Mawer JSP, Leach DRF. 2014. Branch migration prevents DNA loss during double-strand break repair. PLoS Genet 10(8):e1004485. McKillip JL, Drake M. 2004. Real-time nucleic acid-based detection methods for pathogenic bacteria in food. J Food Prot 67:823–32. Melero B, Cocolin L, Rantsiou K, Jaime I, Rovira J. 2011. Comparison between conventional and qPCR methods for enumerating Campylobacter jejuni in a poultry processing plant. Food Microbiol 28:1353–8. Melero B, Juntunen P, Hanninen ML, Jaime I, Rovira J. 2012. Tracing Campylobacter jejuni strains along the poultry meat production chain from farm to retail by pulsed-field gel electrophoresis, and the antimicrobial resistance of isolates. Food Microbiol 32:124–8. Miller RS, Miller WG, Behringer M, Hariharan H, Matthew V, Oyarzabal OA. 2010. DNA identification and characterization of Campylobacter jejuni and Campylobacter coli isolated from caecal samples of chickens in Grenada. J Appl Microbiol 108:1041–9. Nachamkin I. 2001. Campylobacter jejuni. Food microbiology: fundamentals and frontiers. Wash., D.C.: ASM Press. Nachamkin I, Szymanski CM, Blaser MJ. 2008. Campylobacter. Wash., D.C.: ASM Press. Available from: https://www.cabdirect.org/abstracts/20083230307.html. Accessed 2013 October 11. Newell DG, Koopmans M, Verhoef L, Duizer E, Aidara-Kane A, Sprong H, Opsteegh M, Langelaar M, Threfall J, Scheutz F, van der Giessen J, Kruse H. 2010. Food-borne diseases—the challenges of 20 years ago still persist while new ones continue to emerge. Intl J Food Microbiol 139(Suppl. 1):S3–15. Ng LK, Kingombe CI, Yan W, Taylor DE, Hiratsuka K, Malik N, Garcia MM. 1997. Specific detection and confirmation of Campylobacter jejuni by DNA hybridization and PCR. Appl Environ Microbiol 63:4558–63. Niederer L, Kuhnert P, Egger R, Buttner S, Hachler H, Korczak BM. 2012. Genotypes and antibiotic resistances of Campylobacter jejuni and Campylobacter coli isolates from domestic and travel-associated human cases. Appl Environ Microbiol 78:288–91. Noormohamed A, Fakhr MK. 2014. Molecular typing of Campylobacter jejuni and Campylobacter coli isolated from various retail meats by MLST and PFGE. Foods 3:82–93. O’Sullivan N, Fallon R, Carroll C, Smith T, Maher M. 2000. Detection and differentiation of Campylobacter jejuni and Campylobacter coli in broiler chicken samples using a PCR/DNA probe membrane based colorimetric detection assay. Mol Cell Probes 14(1):7–16. https://doi.org/10.1006/mcpr.1999.0274. Oh JY, Kwon YK, Wei B, Jang HK, Lim SK, Kim CH, Jung SC, Kang MS. 2017. Epidemiological relationships of Campylobacter jejuni strains isolated from humans and chickens in South Korea. J Microbiol 55:13–20. Olsen GJ, Overbeek R, Larsen N, Marsh TL, McCaughey MJ, Maciukenas MA, Kuan WM, Macke TJ, Xing Y, Woese CR. 1992. The ribosomal database project. Nucleic Acids Res 20:2199–200. Oyarzabal OA, Williams A, Zhou P, Samadpour M. 2013. Improved protocol for isolation of Campylobacter spp. from retail broiler meat and use of pulsed field gel electrophoresis for the typing of isolates. J Microbiol Methods 95:76–83. Pan H, Ge Y, Xu H, Zhang J, Kuang D, Yang X, Su X, Huang Z, Shi X, Xu X, Meng J. 2016. Molecular characterization, antimicrobial resistance and Caco-2 Cell invasion potential of Campylobacter jejuni/coli from young children with diarrhea. Pediatr Infect Dis J 35:330–4. Postollec F, Falentin H, Pavan S, Combrisson J, Sohier D. 2011. Recent advances in quantitative PCR (qPCR) applications in food microbiology. Food Microbiol 28:848–61. PubMLST.org. 2016. Campylobacter MLST home page. Available from: PubMLST.org. Accessed 2017 April 5. Pusterla N, Byrne BA, Hodzic E, Mapes S, Jang SS, Magdesian KG. 2010. Use of quantitative real-time PCR for the detection of Salmonella spp. in fecal samples from horses at a veterinary teaching hospital. Vet J 186:252–5. Qin SS, Wu CM, Wang Y, Jeon B, Shen ZQ, Wang Y, Zhang Q, Shen JZ. 2011. Antimicrobial resistance in Campylobacter coli isolated from pigs in two provinces of China. Intl J Food Microbiol 146:94–8.


Rahimi E, Ameri M. 2011. Antimicrobial resistance patterns of Campylobacter spp. isolated from raw chicken, turkey, quail, partridge, and ostrich meat in Iran. Food Control 22:1165–70. Raja SS, Rao VA. 2016. Screening of chicken meat in Chennai for emerging food pathogens by multiplex PCR. Intl J Care Coord 5:80–1. Raja SS, Rao VA, Babu RN, Raja A, Abraham RJJ, Thamizhannal M. 2017. Detection of Campylobacter jejuni in chicken meat by polymerase chain reaction. Indian Vet J 94:25–8. Rantsiou K, Lamberti C, Cocolin L. 2010. Survey of Campylobacter jejuni in retail chicken meat products by application of a quantitative PCR protocol. Intl J Food Microbiol 141:S75–9. Reischl U, Kochanowski B. 1995. Quantitative PCR. Mol Biotechnol 3:55–71. Revez J, Zhang J, Schott T, Kivisto R, Rossi M, Hanninen ML. 2014. Genomic variation between Campylobacter jejuni isolates associated with milk-borne-disease outbreaks. J Clin Microbiol 52:2782–6. Ripabelli G, Tamburro M, Minelli F, Leone A, Sammarco ML. 2010. Prevalence of virulence-associated genes and cytolethal distending toxin production in Campylobacter spp. isolated in Italy. Comp Immunol Microbiol Infect Dis 33:355–64. Rodgers JD, Simpkin E, Lee R, Clifton-Hadley FA, Vidal AB. 2016. Sensitivity of direct culture, enrichment and PCR for detection of Campylobacter jejuni and C. coli in broiler flocks at slaughter. Zoonoses Public Health 64(4):262–71. https://doi.org/10.1111/zph.12306. Sails AD, Fox AJ, Bolton FJ, Wareing DRA, Greenway DLA. 2003. A real-time PCR assay for the detection of Campylobacter jejuni in foods after enrichment culture. Appl Environ Microbiol 69:1383–90. Schleihauf E, Mutschall S, Billard B, Taboada EN, Haldane D. 2017. Comparative genomic fingerprinting of Campylobacter: application in routine public health surveillance and epidemiological investigations. Epidemiol Infect 145:299–309. Shams S, Ghorbanalizadgan M, Mahmmodi SH, Piccirillo A. 2017. Evaluation of a multiplex PCR assay for the identification of Campylobacter jejuni and Campylobacter coli. Infect Epidemiol Med 3:6–8. Siemer BL, Nielsen EM, On SL. 2005. Identification and molecular epidemiology of Campylobacter coli isolates from human gastroenteritis, food, and animal sources by amplified fragment length polymorphism analysis and Penner serotyping. Appl Environ Microbiol 71:1953–8. Silva DT, Tejada TS, Blum-Menezes D, Dias PA, Timm CD. 2016. Campylobacter species isolated from poultry and humans, and their analysis using PFGE in southern Brazil. Intl J Food Microbiol 217: 189–94. Stanek L. 2013. Polymerase chain reaction: basic principles and applications in molecular pathology. Cesk Patol 49:119–21. Stern NJ, Hiett KL, Alfredsson GA, Kristinsson KG, Reiersen J, Hardardottir H, Briem H, Gunnarsson E, Georgsson F, Lowman R, Berndtson E, Lammerding AM, Paoli GM, Musgrove MT. 2003. Campylobacter spp. in Icelandic poultry operations and human disease. Epidemiol Infect 130:23–32. Stone D, Davis M, Baker K, Besser T, Roopnarine R, Sharma R. 2013. MLST genotypes and antibiotic resistance of Campylobacter spp. isolated from poultry in Grenada. Biomed Res Intl 2013:794643–52. Strachan NJ, MacRae M, Thomson A, Rotariu O, Ogden ID, Forbes KJ. 2012. Source attribution, prevalence and enumeration of Campylobacter spp. from retail liver. Intl J Food Microbiol 153:234–6. Taminiau B, Korsak N, Lemaire C, Delcenserie V, Daube G. 2014. Validation of real-time PCR for detection of six major pathogens in seafood products. Food Control 44:130–7. Taylor EV, Herman KM, Ailes EC, Fitzgerald C, Yoder JS, Mahon BE, Tauxe RV. 2013. Common source outbreaks of Campylobacter infection in the USA, 1997–2008. Epidemiol Infect 141:987–96. Toplak N, Kovac M, Piskernik S, Mozina SS, Jersek B. 2012. Detection and quantification of Campylobacter jejuni and Campylobacter coli using real-time multiplex PCR. J Appl Microbiol 112:752–64. Urwin R, Maiden MC. 2003. Multi-locus sequence typing: a tool for global epidemiology. Trends Microbiol 11:479–87. USDA (United States Department of Agriculture). 2013. Food safety and inspection service: Campylobacter questions and answers. Available from: https://www.fsis.usda.gov/wps/portal/fsis/topics/food-safety-education/ get-answers/food-safety-fact-sheets/foodborne-illness-and-disease/ campylobacter-questions-and-answers/CT_Index/. Accessed 2016 May 24.


Campylobacter molecular tools in food . . . van Doorn LJ, Verschuuren-Van Haperen A, Van Belkum A, Endtz HP, Vliegenthart JS, Vandamme P, Quint WG. 1998. Rapid identification of diverse Campylobacter lari strains isolated from mussels and oysters using a reverse hybridization line probe assay. J Appl Microbiol 84:545–50. Vencia W, Nogarol C, Bianchi DM, Gallina S, Zuccon F, Adriano D, Gramaglia M, Decastelli L. 2014. Validation according to ISO 16140:2003 of a commercial real-time PCR-based method for detecting Campylobacter jejuni, C. coli, and C. lari in foods. Intl J Food Microbiol 177:78–80. Verhoeff-Bakkenes L, Jansen HA, in t Veld PH, Beumer RR, Zwietering MH, van Leusden FM. 2011. Consumption of raw vegetables and fruits: a risk factor for Campylobacter infections. Intl J Food Microbiol 144:406–12. Vidal AB, Colles FM, Rodgers JD, McCarthy ND, Davies RH, Maiden MC, Clifton-Hadley FA. 2016. Genetic diversity of Campylobacter jejuni and Campylobacter coli isolates from conventional broiler flocks and the impacts of sampling strategy and laboratory method. Appl Environ Microbiol 82:2347–55. Vinueza-Burgos C, Wautier M, Martiny D, Cisneros M, Van Damme I, De Zutter L. 2017. Prevalence, antimicrobial resistance and genetic diversity of Campylobacter coli and Campylobacter jejuni in Ecuadorian broilers at slaughter age. Poult Sci 0:1–9. https://doi.org/10.3382/ps/pew487. von Altrock A, Hamedy A, Merle R, Waldmann KH. 2013. Campylobacter spp.—prevalence on pig livers and antimicrobial susceptibility. Prev Vet Med 109:152–7. Waage AS, Vardund T, Lund V, Kapperud G. 1999. Detection of small numbers of Campylobacter jejuni and Campylobacter coli cells in environmental water, sewage, and food samples by a seminested PCR assay. Appl Environ Microbiol 65:1636–43. Wagenaar JA, French NP, Havelaar AH. 2013. Preventing Campylobacter at the source: why is it so difficult? Clin Infect Dis 57:1600–6. Wang G, Clark CG, Taylor TM, Pucknell C, Barton C, Price L, Woodward DL, Rodgers FG. 2002. Colony multiplex PCR assay for identification and differentiation of Campylobacter jejuni, C. coli, C. lari, C. upsaliensis, and C. fetus subsp. fetus. J Clin Microbiol 40:4744–7. Wang R-F, Slavik MF, Cao W-W. 1992. A rapid PCR method for direct detection of low numbers of Campylobacter jejuni. J Rapid Methods Autom Microbiol 1:101–8.

Wegmüller B, Lüthy J, Candrian U. 1993. Direct polymerase chain reaction detection of Campylobacter jejuni and Campylobacter coli in raw milk and dairy products. Appl Environ Microbiol 59:2161–5. Wei B, Cha SY, Kang M, Roh JH, Seo HS, Yoon RH, Jang HK. 2014. Antimicrobial susceptibility profiles and molecular typing of Campylobacter jejuni and Campylobacter coli isolates from ducks in South Korea. Appl Environ Microbiol 80:7604–10. Wieczorek K, Osek J. 2013. Antimicrobial resistance mechanisms among Campylobacter. Biomed Res Intl 2013:1–12. Article ID 340605. https://doi:10.1155/2013/340605. Winters DK, Slavik MF. 1995. Evaluation of a PCR based assay for specific detection of Campylobacter jejuni in chicken washes. Mol Cell Probes 9:307–10. Yamazaki-Matsune W, Taguchi M, Seto K, Kawahara R, Kawatsu K, Kumeda Y, Kitazato M, Nukina M, Misawa N, Tsukamoto T. 2007. Development of a multiplex PCR assay for identification of Campylobacter coli, Campylobacter fetus, Campylobacter hyointestinalis subsp. hyointestinalis, Campylobacter jejuni, Campylobacter lari and Campylobacter upsaliensis. J Med Microbiol 56:1467–73. Yao H, Liu D, Wang Y, Zhang Q, Shen Z. 2017. High prevalence and predominance of the aph(2 )-If gene conferring aminoglycoside resistance in Campylobacter. Antimicrob Agents Chemother 61:e00112–17. https://doi.org/10.1128/AAC.00112-17. Zang X, Tang H, Jiao X, Huang J. 2017. Can a visual loop-mediated isothermal amplification assay stand out in different detection methods when monitoring Campylobacter jejuni from diverse sources of samples? Food Control 75:220–7. Zendehbad B, Khayatzadeh J, Alipour A. 2015. Prevalence, seasonality and antibiotic susceptibility of Campylobacter spp. isolates of retail broiler meat in Iran. Food Control 53:41–5. Zhang X, Yin T, Du X, Yang W, Huang J, Jiao X. 2017. Occurrence and genotypes of Campylobacter species in broilers during the rearing period. Avian Pathol 46:215–23.

