A novel typing method for Listeria monocytogenes using high-resolution melting analysis (HRMA) of tandem repeat regions

https://doi.org/10.1016/j.ijfoodmicro.2017.04.015Get rights and content

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  • High resolution melting analysis was developed for tandem repeat regions PCR amplified from L. monocytogenes strains.

  • Developed method was evaluated by comparing with other typing methods.

  • The method has high discriminatory ability for L. monocytogenes strains.

Abstract

Listeria monocytogenes, which is responsible for causing food poisoning known as listeriosis, infects humans and animals. Widely distributed in the environment, this bacterium is known to contaminate food products after being transmitted to factories via raw materials. To minimize the contamination of products by food pathogens, it is critical to identify and eliminate factory entry routes and pathways for the causative bacteria. High resolution melting analysis (HRMA) is a method that takes advantage of differences in DNA sequences and PCR product lengths that are reflected by the disassociation temperature. Through our research, we have developed a multiple locus variable-number tandem repeat analysis (MLVA) using HRMA as a simple and rapid method to differentiate L. monocytogenes isolates. While evaluating our developed method, the ability of MLVA-HRMA, MLVA using capillary electrophoresis, and multilocus sequence typing (MLST) was compared for their ability to discriminate between strains. The MLVA-HRMA method displayed greater discriminatory ability than MLST and MLVA using capillary electrophoresis, suggesting that the variation in the number of repeat units, along with mutations within the DNA sequence, was accurately reflected by the melting curve of HRMA. Rather than relying on DNA sequence analysis or high-resolution electrophoresis, the MLVA-HRMA method employs the same process as PCR until the analysis step, suggesting a combination of speed and simplicity. The result of MLVA-HRMA method is able to be shared between different laboratories. There are high expectations that this method will be adopted for regular inspections at food processing facilities in the near future.

Introduction

Listeria monocytogenes is the causative agent of listeriosis in humans and animals (Ferreira et al., 2014, Schuchat et al., 1991). Adults with listeriosis display a fever or other influenza-like symptoms (Paolo et al., 2000). Infection in immunocompromised people, elderly people, or neonates often leads to the development of sepsis or meningitis (Ferreira et al., 2014, Schuchat et al., 1991). In pregnant women, listeriosis may lead to miscarriage, fetal death, or babies being born with listeriosis (Cartwright et al., 2013, Ferreira et al., 2014). The fatality rate for listeriosis is 20–30%, which is much higher than that of diseases caused by other food poisoning bacteria (Lomonaco et al., 2015).

Most cases of outbreaks were related to contaminated foods. This bacterium can proliferate in low temperature conditions and is highly halotolerant (Ferreira et al., 2014). For this reason, L. monocytogenes is widely distributed in the environment (Ferreira et al., 2014). It is also often detected in RTE foods such as dairy products like cheese (Barancelli et al., 2014, Gandhi and Chikindas, 2007), processed meat (Gandhi and Chikindas, 2007, Montero et al., 2015), and salads (Cartwright et al., 2013, Gandhi and Chikindas, 2007). Recently, there were outbreaks in the United States caused by ice cream (Centers for Disease Control and Prevention, 2015a) and cheese (Centers for Disease Control and Prevention, 2015b), and several cases of listeriosis occurred in the EU, caused by cheese, fruit, vegetable, and meat products (European Food Safety Authority and European Centre for Disease Prevention and Control, 2015).

Contamination of food by pathogens, including L. monocytogenes, not only increases the risk of disease outbreaks, but also results in tremendous economic losses due to recalls (Gandhi and Chikindas, 2007, Lomonaco et al., 2015). Therefore, food companies employ the utmost care in minimizing contamination of products by such bacteria. To completely prevent contamination at food production facilities, it is important to identify and eliminate reservoirs and pathways used by bacteria to contaminate the factory and products. Therefore, product and environment sampling is conducted regularly at food production facilities to isolate bacteria.

Pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), and multiple locus variable-number tandem repeat analysis (MLVA), and core genome MLST (cgMLST) are all methods widely used to discriminate bacterial isolates (Bertrand et al., 2015, Chenal-Francisque et al., 2013, Kimura et al., 2008, Lüdeke et al., 2015, Malachowa et al., 2005, Moura et al., 2016). Many cases employing these methods to trace contamination sources at food production facilities have been reported (Otero et al., 2013, Prendergast et al., 2011, Takahashi et al., 2014). Although bacteria with diverse genotypes have been isolated from food production facilities, often such bacteria are genetically related to each other (Otero et al., 2013, Prendergast et al., 2011, Takahashi et al., 2014). This relatedness depends on the source location or the time of isolation (Barancelli et al., 2014). Therefore, a typing method with greater ability to differentiate isolates is needed. However, analysis using PFGE, MLST, or MLVA is time consuming or expensive, making it difficult to employ at food companies that routinely perform numerous tests (Gasanov et al., 2005, Healy et al., 2008, Jadhav et al., 2012). Moreover MLVA needs capillary electrophoresis or sequence analysis and MLST needs sequence analysis. Thus, it is necessary for a scientist with specialized knowledge to perform the test. Hence, it has been challenging to implement PFGE, MLST, and MLVA in the food production industry as routine inspection methods. In recent years, many reports have been published on easy, fast, and inexpensive methods to differentiate isolates of food related bacteria (Cai et al., 2013, Chenal-Francisque et al., 2013, Ojima-Kato et al., 2016).

High resolution melting analysis (HRMA) is a method that detects GC content of the PCR product, variations in the product chain length, and the presence or absence of mutations in the DNA sequence, based on differences in melting temperatures of double stranded DNA samples (Gundry, 2003). An intercalating dye is added to the PCR assay and a melting step is performed after the completion of the reaction. The intercalator binds to the double-stranded DNA of the amplified PCR product and fluoresces. In the melting step, the two strands of DNA disassociate thereby quenching the fluorescence of the intercalating dye. This method continuously observes variations in fluorescence intensity, which is then used to detect differences in melting properties (e.g., length or sequence) of PCR products with real-time PCR which has highly methodological verification ability to standardize the ramping of temperatures (Gundry, 2003).

In this study, we developed a MLVA-HRMA method that utilizes HRMA to perform variable number tandem repeat (VNTR) analysis of L. monocytogenes. We also tested L. monocytogenes strains that were isolated from the raw materials of processed meat using MLVA-HRMA, MLVA, and MLST to compare the capabilities of each method to discriminate the isolates.

Section snippets

Bacterial strains

We used 48 L. monocytogenes isolates that were isolated from the raw materials of processed meats such as pork and chicken and stored in our laboratory (Table 1). These strains were classified by PFGE in previous study and were chosen with representativeness of diversity (Miya et al., 2012). The isolates were stored at − 80 °C until analysis was conducted. After inoculating the isolates in TSB medium (TSB; Becton, Dickinson and Company, Franklin Lakes, NJ), they were cultured overnight at 37 °C.

MLVA-HRMA

For the 48 L. monocytogenes isolates, we performed HRMA on 11 VNTR loci to determine the STs. Of these 48 isolates, the JLR1 locus was divided into 13 types, JLR2 into ten, Lis-TR1317 into five, Lis-TR1869 into nine, Lis-TR881 into seven, Lm11 into eight, JLR4 into eight, LM-TR4 into six, LMV1 into nine, LMV6 into seven, and LMV9 into six. After combining the allele numbers of the 11 loci, the 48 L. monocytogenes isolates were finally divided into 47 HRMA groups (Fig. 1, Supplementary Table 1).

Discussion

Many researchers have contributed to the research and development of MLVA methods for L. monocytogenes (Chenal-Francisque et al., 2013, Jadhav et al., 2012, Miya et al., 2012, Miya et al., 2008). Chenal-Francisque and colleagues comprehensively assessed MLVA methods and selected 11 valuable tandem repeat loci (Chenal-Francisque et al., 2013). Our research established the MLVA-HRMA method using those 11 loci, and developed a simple and rapid typing method highly capable of differentiating

Acknowledgement

This study was supported by Oshimo foundation. We thank the team of curators of the Institut Pasteur MLST and whole genome MLST databases for curating the data and making them publicly available at http://bigsdb.pasteur.fr/.

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