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Introduction
Farm animals represent a major reservoir of pathogens that can be transferred to milk (Arqués et al., 2015). Staphylococcus aureus, Salmonella spp., Listeria monocytogenes, Escherichia coli O157:H7 and Campylobacter are the most frequent potential pathogens associated with milk or dairy products in industrialized countries (Jakobsen et al, 2011) and are the main microbiological hazards linked to raw milk (Kousta et al, 2010; Yang et al, 2012; Claeys et al, 2013) and raw cheese (Verraes et al., 2015). In addition, as with any food matrix, dairy foods present their own inherent source of inhibitors, such as fat or lipid content, calcium concentration, and the presence of indigenous enzymes, e.g., potential inhibitors, that may have a detrimental influence on the overall integrity of an accurate and sensitive assay (Ozer and Akdemir-Evrendilek, 2014).
In natural conditions, the microbial composition of milk is influenced by different parameters, such as the microorganisms present in the teat canal, on the surface of teat skin, or in the surrounding air, as well as the animal's feed, the quality of the water supply, and equipment hygiene (Quigley et al., 2013). For this reason, the detection of pathogens in dairy products can be a challenge and is needed to ensure safety. One of the most important tasks of food safety is the elimination, or at least the reduction, of foodborne pathogens (Giacometti et al., 2013). Therefore, it is necessary to find a way to detect pathogens in their early stages of growth in different food products, which could reduce the number of foodborne outbreaks (Pinu, 2016).
Foodborne disease outbreaks related to dairy products
Because of their unique composition and properties, milk and dairy products represent excellent growth media for many spoilage and pathogenic microorganisms (Nada et al, 2012; Claeys et al, 2013). Table 1 shows a summary of outbreaks associated with the consumption of different dairy products in the world. Additionally, food derived from animals (beef and dairy products, eggs and fish) has been identified as the main vehicle for the transmission of foodborne pathogens to humans (Ahmed and Shimamoto, 2014; Arqués et al, 2015). Additionally, foodborne bacteria can contaminate food products at any point along the production chain: during slaughtering, milking, storage or packaging (Tomat et al, 2016).
Table 1 Summary of outbreaks associated with the consumption of different dairy products in the world
| Year | Country | Product involved | Pathogen | Cases | Reference | |
|---|---|---|---|---|---|---|
| North America | ||||||
| 1998 | Canada | Cheese | Salmonella enterica | 80 | Ahmed et al., 2000 | |
| 1998-2011 | United States | Cheese | Salmonella | 13 | Gould et al., 2014 | |
| (Unpasteurized milk) | Listeria monocytogenes | 4 | ||||
| Escherichia coli | 4 | |||||
| 2002 | Canada | Soft Ripened Cheese | Listeria monocytogenes | 130 | McIntyre et al., 2015 | |
| 2005 | United States | Raw milk | Escherichia coli O157:H7 | 18 | Denny et al., 2008 | |
| 2007 | United States | Pasteurized Milk | Listeria monocytogenes | 5 | MMWR, 2008 | |
| 2008 | Canada | Cheese (Pasteurized milk) | Listeria monocytogenes | 38 | Gaulin et al., 2012 | |
| 2001-2010 | United States | Raw milk | Campylobacter spp. | 407 | Robinson et al., 2014 | |
| STEC | 31 | |||||
| Salmonella spp. | 39 | |||||
| 2010 | United States | Gouda cheese (Unpasteurized milk) | Escherichia coli O157:H7 | 19 | McCollum et al., 2012 | |
| 2010-2012 | United States | Raw milk | Campylobacter spp. | 40 | Mungai et al., 2015 | |
| STEC | 8 | |||||
| 2012 | United States | Ricotta salata cheese | Listeria monocytogenes | 6 | Heiman et al., 2016 | |
| 2013 | Canada | Gouda cheese (Unpasteurized milk) | Escherichia coli O157 | 29 | Gill and Oudit, 2015 | |
| 2014 | United States | Ice cream | Listeria monocytogenes | 2 | Rietberg et al., 2016 | |
| 2015 | United States | Ice cream | Listeria monocytogenes | 4 | Pouillot et al., 2016 | |
| Europe | ||||||
| 1996-1997 | United Kingdom | Formula-dried milk | Salmonella enterica | 17 | Threlfall et al., 1998 | |
| 1997 | France | Morbier cheese (Unpasteurized milk) | Salmonella enterica | 113 | De Valk et al., 2000 | |
| 1998-1999 | Finland | Butter | Listeria monocytogenes | 25 | Lyytikäinen et al., 2000 | |
| 1997-2001 | France | Cheese (Unpasteurized milk) | Staphylococcus aureus | 70 | Kérouanton et al., 2007 | |
| 2004-2005 | France | Powdered Infant Formula | Salmonella enterica | 136 | Brouard et al., 2007 | |
| 2005-2007 | Netherlands | Raw milk | Campylobacter jejuni | 38 | Heuvelink et al., 2009 | |
| 2006 | Netherlands | Hard cheese | Salmonella Typhimurium | 38 | Van Duynhoven et al., 2009 | |
| 2006-2007 | France | Cheese (Unpasteurized milk) | Salmonella enterica | 23 | Dominguez et al., 2009 | |
| 2006-2007 | Germany | Cheese (Pasteurized milk) | Listeria monocytogenes | 34 | Koch et al., 2010 | |
| 2007 | Austria | Milk, cacao milk or vanilla milk | Staphylococcus aureus | 166 | Schmid et al., 2009 | |
| 2008 | Spain | Infant Formula | Salmonella kedougou | 21 | Rodríguez-Urrego et al., 2010 | |
| 2009 | Austria | Quargel cheese | Listeria monocytogenes | 25 | Fretz et al., 2010 | |
| 2009 | Germany | Quargel cheese | Listeria monocytogenes | 8 | Fretz et al., 2010 | |
| 2009 | Czech Republic | Quargel cheese | Listeria monocytogenes | 1 | Fretz et al., 2010 | |
| 2009 | France | Soft cheese (Unpasteurized milk) | Staphylococcus aureus | 23 | Ostyn et al., 2010 | |
| 2012 | Portugal | Cheese (Pasteurized milk) | Listeria monocytogenes | 30 | Magalhães et al., 2015 | |
| 2012 | Spain | Latin-style fresh cheese | Listeria monocytogenes | 2 | De Castro et al., 2012 | |
| (Pasteurized milk) | ||||||
| 2013 | Germany | Ice cream | Staphylococcus aureus | 13 | Fetsch et al., 2014 | |
| 2014 | Switzerland | Soft cheese (Unpasteurized milk) | Staphylococcus aureus | 14 | Johler et al., 2015 | |
| 2014 | Finland | Raw milk | Yersinia pseudotuberculosis | 43 | Pärn et al., 2015 | |
| Asia | ||||||
| 2000 | Japan | Reconstituted milk | Staphylococcus aureus | 13420 | Asao et al., 2003 | |
| South America | ||||||
| 2006 | Argentina | Cream | Staphylococcus aureus | 53 | López et al., 2008 | |
| 2007 | Paraguay | Ultrapasteurized milk | Staphylococcus aureus | 400 | Weiler et al., 2011 | |
| 2008 | Chile | Brie and Camembert cheese | Listeria monocytogenes | 165 | Montero et al., 2015 | |
†STEC: Shiga toxin-producing Escherichia coli
Several outbreaks have been associated with the consumption of dairy products, particularly cheese and other ready to-eat foods (Melo et al, 2015). Cheeses are ready-to-eat food products because they do not undergo any further treatment to ensure their safety before consumption. In addition, contamination of cheeses may occur at several stages in the production chain. Therefore, all the information about bacterial characteristics and susceptibility is necessary to prevent contamination of dairy products with pathogens (Kousta et al., 2010).
Reports from developed countries indicated that milk and dairy products are implicated in 1-6% of the total bacterial foodborne outbreaks (Ahmed and Shimamoto, 2014), with 39.1% attributed to milk, 53.1% to cheese and 7.8% to other milk products (Claeys et al, 2013). In 2013, 2.14% of foodborne outbreaks were attributed to the consumption of cheese and dairy products (11 and 7 outbreaks, respectively) in Europe (Dalzini et al, 2016).
The most common source of reported outbreaks in the USA has historically been raw (unpasteurized) milk (Taylor et al., 2013). In their study, Bianchi et al. (2013) concluded that unpasteurized milk can be a vehicle for a variety of microorganisms (Listeria spp, Salmonella, and Campylobacter) and that outbreaks related to cheeses made with unpasteurized milk are also common (Gould et al, 2014). The development of a disease after consumption of contaminated dairy products made from raw milk depends on several factors, such as the pathogenicity of the bacteria strain, the number of ingested microorganisms, the physiological state of the microorganism, and the health condition of the consumer at the moment of ingestion (Verraes et al, 2015).
Bacteria involved in dairy product contamination
Staphylococcus aureus, Salmonella spp., Listeria monocytogenes and Escherichia coli O157:H7 are the most frequent potential pathogens associated with milk or dairy products in industrialized countries (Jakobsen et al, 2011) and are therefore the main microbiological hazards linked to raw milk (Kousta et al, 2010; Yang et al, 2012; Claeys et al, 2013) and raw cheese (Verraes et al, 2015). Raw milk provides a potential growth medium for the development of bacteria that can be controlled or destroyed through the pasteurization process (Arqués et al, 2015). However, the number of people consuming unpasteurized products continues to increase all over the world due to a growing demand for natural and unprocessed foods (Fusco and Quero, 2014).
Outbreaks due to cheese made from unpasteurized milk are often caused by Salmonella (34%), Campylobacter (26%), Brucella (13%), and Shiga toxin-producing Escherichia coli (11%) (Gould et al., 2014). Listeria is killed by pasteurization, and outbreaks of this bacterial strain have rarely been associated with pasteurized dairy products, including cheese (Koch et al., 2010). These foodborne bacteria are of concern for the dairy industry because they have been identified in different dairy products and have been implicated in outbreaks (Kousta et al, 2010; Yang et al, 2012; Claeys et al, 2013; Ricci et al, 2013; Robinson et al., 2014; Tayel et al., 2015; Pouillot et al, 2016).
Listeria monocytogenes has been involved in numerous outbreaks occurring after consumption of contaminated milk and dairy products throughout the world (Wang et al., 2015; Dalzini et al, 2016). In 2015, dairy products were identified as the main sources of listeriosis (Quero et al., 2014; Jackson et al., 2016). Raw milk can be contaminated with Listeria monocytogenes from unclean equipment during milking, during storage in bulk tanks or during transport to the cheese processing plant, where hygienic control measures may not be adequate (Melo et al., 2015). Because of its high case-fatality rate, listeriosis is, after salmonellosis, the second most frequent cause of foodborne infection-related deaths in Europe (Arqués et al, 2015; Dalzini et al, 2016). However, outbreaks from Listeria monocytogenes are not common compared with those caused by pathogens such as Salmonella (Todd and Notermans, 2011).
Staphylococcus aureus is a ubiquitous pathogen; thus, the sources of this bacteria for dairy products contamination are diverse (Rosengren et al., 2010). This bacterium is commonly found in a wide variety of mammals and birds and can be transferred to food mainly by dairy animals that have mastitis and by human carriers during food processing (Hennekinne et al., 2012). Contamination of Staphylococcus aureus can have a broad occurrence in raw dairy products, with frequencies between 5 and 100% in cheeses (Verraes et al., 2015). The number of Staphylococcus aureus in raw milk or other dairy products needs to be less than 104 CFU g−1, according to the US FDA regulations (Yu et al., 2016). During the manufacture of cheese, natural staphylococcal contamination is a minor component of the total microbial population, and the initial Staphylococcus aureus contamination is usually below 103 CFU ml−1 of raw milk (Duquenne et al., 2010). Foods of animal origin with high protein contents such as milk and dairy products, meat, meat products, salads and bakery products favor the growth of bacteria, and this type of food has been frequently incriminated in Staphylococcus aureus outbreaks (Fetsch et al., 2014). This bacterium can grow in an extensive range of temperatures, pH values, sodium chloride concentrations and water activity and it can also produce staphylococcal enterotoxins, which are responsible for staphylococcal food poisoning (Schelin et al., 2011).
Staphylococcus aureus is present in raw materials and food and can be inactivated with heat treatment, but enterotoxins are heat resistant and may persist in food even after heat treatment. Staphylococcal enterotoxins are active even after boiling for 30 min and may remain stable at 121 °C for 28 min (Necidova et al., 2016). Minimum pasteurization treatments are based on European legislation, which set the heat treatment at 72 °C for 15 s or 63 °C for 30 min. High-temperature pasteurization is defined as heat treatment of milk at not less than 85 °C. In addition, in the Chilean food regulations (Reglamento Sanitario de los Alimentos), dairy products are treated at ultra-high-temperatures (UHTs) 130 °C and 145 °C for 2 or 4 s to ensure inactivation of bacteria and toxins.
Salmonella spp. is the most frequent cause of food-borne outbreaks, and human salmonellosis is the second most frequently reported zoonosis in the European Union (Wuyts et al, 2013). Milk is a food that has a high chance of contamination by Salmonella spp. (Riyaz-Ul-Hassan et al., 2013), mainly before leaving the farm, usually because of fecal contamination during the milking process (Ahmed and Shimamoto, 2014). Additionally, Salmonella spp. can be transmitted to humans via the consumption of contaminated dairy products (Vignaud et al., 2017), especially unpasteurized or insufficiently pasteurized milk and cheeses, which cause outbreaks of salmonellosis in humans (De Valk et al., 2000; Ahmed and Shimamoto, 2014). Finally, the main reservoirs of Shiga toxin-producing Escherichia coli are ruminants, contaminating milk through subclinical mastitis or feces, and the bacteria can persist in milking equipment (Arqués et al, 2015).
Foodborne bacteria detection
The detailed characterization of isolates is critical for the investigation of common outbreak sources in order to identify the source, implement control measures and/or take steps to remove the implicated food from the market place (Bopp et al, 2016).
Conventional methods
Traditional methods for the detection of bacterial pathogens in foods have been widely used because they are sensitive and inexpensive and can give both qualitative and quantitative information on the number and the nature of the microorganisms present in the food sample (Zhao et al., 2016). The conventional methods for detection of these pathogens involve identification and confirmation based on culturing on selective media along with biochemical tests and immunological assays (Quigley et al., 2013). These methods are standard methods; however, they are extremely laborious, time consuming (requiring several days), and often inconclusive (Singh et al., 2011; Chen et al., 2015; Bopp et al., 2016; Yu et al., 2016). For these reasons, there is an increasing demand for more rapid methods of foodborne pathogen detection (Zhao et al, 2014), in order to complement or replace the traditional microbial culture procedures with more advanced, sensitive, and rapid microbial detection methods.
Molecular genetic techniques
Due to their limitations, conventional methods are now giving way to molecular diagnostic methods based on DNA analysis, such as polymerase chain reaction (PCR), multiplex PCR and real-time quantitative PCR (qPCR), which have been used for rapid and reliable detection of foodborne pathogens (Chiang et al., 2012). In addition, typifying methods are also largely used for accurate genetic characterization in outbreak investigations. Table 2 shows the molecular genetic techniques applied to dairy products to detect and identify foodborne bacteria.
Table 2 Selection of molecular genetic techniques used for foodborne detection
| Bacteria | Approach | Target gene or enzyme used | Detection | Dairy product | Reference |
|---|---|---|---|---|---|
| Listeria monocytogenes | qPCR | hly | 4 log CFU mL−1 | Raw milk, pasteurized milk, kulfi, ice cream, paneer, and infant foods | Singh et al., 2011 |
| qPCR | hlyA | 3.63 log | Raw milk | Quero et al., 2013 | |
| qPCR | hlyA | CFU g−1 4.9 × 103 CFU g−1 | Milk | Paul et al., 2015 | |
| Multiplex PCR | htpG | 1 CFU mL−1 | Quargel chesse | Chiang et al., 2012 | |
| PFGE | AscI and ApaI | Nx104 CFU ml−1 | Cheese (pasteurized milk) | Schoder et al., 2014 | |
| PFGE | AscI | Cheese (pasteurized milk) | Koch et al., 2010 | ||
| PFGE | AscI and ApaI | Gaulin et al., 2012 | |||
| Salmonella | qPCR | invA | 3 log CFU mL−1 | Raw milk, pasteurized milk, kulfi, ice cream, paneer, and infant foods | Singh et al., 2011 |
| Multiplex PCR | Random DNA fragment | Nx104 CFU mL−1 | Milk | Chiang et al., 2012 | |
| qPCR | Stn | 25 to 500 cells | Milk | Riyaz-Ul-Hassan et al., 2013 | |
| MLVA | – | – | Cheese (raw milk) | Vignaud et al., 2017 | |
| PCR | Salmonella Enteritidis and Typhimurium | 3,03% of samples 1% of samples | Milk Cheese (raw milk) | Ahmed and Shimamoto, 2014 | |
| PCR | hilA | 5 bacteria ml−1 103 bacteria ml−1 | Milk Ice-cream | Marathe et al., 2012 | |
| Staphylococcus aureus | qPCR | egc | 102 to 103 CFU mL-1 | Raw milk | Fusco and Quero, 2014 |
| Multiplex PCR | hsp | Nx104 CFU ml−1 | Milk | Chiang et al., 2012 | |
| E. coli O157 | qPCR | Rfb | 1 CFU mL−1 | Raw milk | Paul et al., 2013 |
| E. coli O157: H7 | Multiplex PCR | Random DNA fragment | Nx104 CFU mL−1 | Milk | Chiang et al., 2012 |
| E. coli O157: H7 | qPCR | stx1, stx2 and stx2f | 4×106 to 40 CFU mL-1 | Milk | Derzelle et al., 2011 |
| E. coli O157:H7 | PCR | stx1, stx2 and rfb | 2,5% of samples 1,1 % of samples | Raw milk Cheese | Ahmed and Shimamoto, 2014 |
| E. coli O157 | WGS | – | – | Raw milk | Butcher et al., 2016 |
qPCR: Quantitative polymerase chain reaction
PFGE: Pulsed field gel electrophoresis
MLVA: Multiple-locus variable-number tandem repeat analysis
PCR: Polymerase chain reaction
WGS: Whole genome sequencing
Molecular techniques for pathogens are being developed for various aspects of detection, such as sensitivity, rapidity, and selectivity (Zhao et al., 2014). Studies have shown that identification systems based on molecular genetic techniques are more discriminating than phenotypic methods and often provide more accurate taxonomic information about a particular strain, which is very important in pathogen surveillance (Henri et al., 2016). Additionally, these approaches allow the detection of very low numbers of organisms in the sample and high throughput of many samples for routine analysis (Lee et al., 2015).
One of the advantages of DNA-based pathogen detection assays is the high level of specificity, as they detect specific nucleic acid sequences in the target organism by hybridizing them to a short synthetic oligonucleotide complementary to the specific nucleic acid sequence (Zhao et al, 2014). These methods have also become valuable tools for investigating foodborne outbreaks and identifying the responsible etiological agents (Riyaz-Ul-Hassan et al., 2013).
Polymerase chain reaction
PCR is a technique that amplifies a specific DNA sequence, producing thousands to millions of copies. These methods usually detect specific genes in strains of bacteria isolated from contaminated foods (Hennekinne et al., 2012). This technique has been recognized as one of the most promising rapid microbiological methods for the detection and identification of bacteria in a wide range of foods (Auvolat and Besse, 2016). It has been used to detect foodborne bacterial pathogens such as viable Escherichia coli O157:H7, Salmonella and L. monocytogenes in food (Lee et al., 2015; Wang et al., 2015). PCR is widely used to detect Staphylococcus aureus (Kim et al., 2001; Vancraeynest et al., 2007; Yang et al., 2007) because of its high sensitivity and specificity (Chen et al., 2015).
It is important to consider that PCR requires precise and expensive instruments, and macromolecules such as proteins and fat present in milk and ice cream could interfere with the PCR assay. Removal of these macromolecules is essential to prevent PCR inhibition (Marathe et al, 2012).
Real-time quantitative PCR (qPCR)
The use of qPCR has provided several advantages over conventional PCR such as quantification, real-time and in situ analyses, in addition to automation (Riyaz-Ul-Hassan et al., 2013). In this technique, the PCR products are detected as they accumulate. The amount of generated PCR product is proportional to the increase in a fluorescent signal, which is monitored during the exponential phase (Auvolat and Besse, 2016). This technique permits rapid identification and quantification of bacteria (Singh et al., 2011; Quigley et al., 2013).
Several attempts have been made to develop qPCR assays for the detection of L. monocytogenes and Salmonella spp. over a wide range of food products including beef, seafood, fresh produce, and dairy products (Singh et al., 2011). The sensitivity of qPCR when applied to a food matrix is generally quite limited when compared with other enumeration methods. Consequently, in most cases, qPCR is not suitable for the accurate enumeration of, for example, low levels of L. monocytogenes in food (Auvolat and Besse, 2016).
Multiplex PCR
Multiplex PCR involves the simultaneous detection or amplification of multiple target sequences in a single reaction by using different primers for each target. Multiplex PCR has the potential to produce considerable savings of time and effort within the laboratory without compromising test utility (Elnifro et al., 2000).
DNA microarray
In DNA arrays, specific DNA sequences are synthesized in a 2-D or 3-D array on a surface to which the DNA is covalently or non-covalently attached. The DNA array is used to probe a solution containing a mixture of labeled nucleic acids, and the binding (by hybridization) of these “targets” to the “probes” on the array allows the measurement of the relative concentrations of the nucleic acid in the sample (Bumgarner, 2013). Biochips may allow the simultaneous detection and identification of multiple microorganisms in a relatively short time, and they are being described as a powerful tool for the detection of foodborne pathogens (Chiang et al., 2012). However, the high cost associated with this approach is the main restriction limiting its application in the dairy and food industries on a routine basis (Singh et al., 2011).
Molecular subtyping methods
Molecular subtyping has been an instrumental tool for the surveillance and outbreak investigation of foodborne illness for several years (Deng et al., 2016) and has proven critical for identifying clusters that warrant further investigation (Jackson et al., 2016). These approaches are essential epidemiological tools for detecting the outbreak of foodborne diseases, and must provide strong discriminatory power and high epidemiological concordance (Liu et al., 2016). The molecular typing methods that are commonly used to detect bacterial disease outbreaks include pulsed field gel electrophoresis (PFGE), multiple-locus variable-number tandem repeat analysis (MLVA), and clustered regularly interspaced short palindromic repeat and multiple-virulence-locus sequence typing (CRISPR-MVLST) (Liu et al., 2016). Recently, these have been powered by whole-genomesequencing (WGS) technologies.
Pulsed field gel electrophoresis
PFGE has been described as the gold standard for subtyping the genus and species to provide further discrimination among bacterial pathogens (Wuyts et al., 2013; Taylor et al., 2015; Adkins et al., 2016) and is used by the National Molecular Subtyping Network for Foodborne Disease Surveillance in United States (PulseNet) (Bopp et al., 2016). Initially, PFGE was used to type Escherichia coli O157:H7 and then was developed to enable typing of various important bacteria, such as Listeria monocytogenes, Vibrio parahaemolyticus and Salmonella (Liu et al., 2016).
This is the most commonly used molecular subtyping method for surveillance and outbreak detection because of its high discriminatory power and reproducibility (Deng et al., 2016). PFGE was used for the molecular subtyping of Listeria monocytogenes isolates in a commercial cheese made from pasteurized milk that caused an outbreak in Germany from October 2006 through February 2007 (Koch et al., 2010) and in Quebec, Canada, in 2008 (Gaulin et al., 2012). Additionally, in 2010, this technique was useful in determining the genotypic diversity of Listeria monocytogenes in the acid curd cheese that caused a multinational outbreak between 2009 and 2010 (Schoder et al., 2014).
However, PFGE is time-consuming and laborious to perform (Liu et al, 2016), which makes it less suitable for typing many isolates, and it requires rigorous standardization of the protocols (Bertrand et al. 2015). PFGE also lacks the discriminatory capacity and phylogenetic basis of more advanced methods (Jackson et al., 2016).
Multiple-locus variable-number tandem repeat analysis
MLVA is a molecular subtyping method based on amplification and fragment size analysis of the number of repeats in the variable-number tandem repeats region of the bacterial genome (Bertrand et al. 2015). It is rapid and highly reproducible, and the results are easily interpreted and standardized among laboratories. Bacteria that have been typed by MLVA include Salmonella (Wuyts et al., 2013), Escherichia coli and Vibrio parahaemolyticus (Liu et al., 2016).
This method has proven very useful in investigating foodborne outbreaks because it utilizes the naturally occurring variation in the number of tandem repeat DNA sequences, and it has facilitated analysis since it requires no specific technical expertise (Vignaud et al., 2017). MLVA was applied to a raw milk cheese outbreak in France in 2012 to subtype Salmonella enterica subspecies enterica serovar Dublin, which is one of the most frequently isolated Salmonella strains in humans in that country (Vignaud et al., 2017).
Whole genome sequencing
PFGE and MLVA often do not provide sufficient resolution to differentiate between outbreaks (Taylor et al, 2015). Recently, whole genome sequencing has offered that discriminatory power with the potential to enhance epidemiological investigations and elucidate transmission pathways (Phillips et al, 2016). The use of next-generation sequencing technology for WGS allows for the sequencing of large numbers of isolates, and novel bioinformatics tools can be used for comparative genomics and analysis of the phylogeny of the isolates (Revez et al., 2014). WGS has been a very useful and powerful tool for establishing potential links between clinical, food and environmental isolates of pathogens, which could allow the identification of the source of contamination and remove contaminated foods from markets (Deng et al., 2016).
WGS has been recently used to understand outbreak sources and the transmission patterns of bacteria, including Escherichia coli, Campylobacter, Listeria spp. and Salmonella spp. (Lambert et al, 2015; Clark et al., 2016; Jackson et al., 2016; Wilson et al, 2016). Furthermore, WGS has the potential to discriminate between sporadic and outbreak isolates which may be indistinguishable by current methods of subtyping (Phillips et al., 2016). WGS usefulness in food safety is undeniable; however, this approach is expensive and is not currently in place in the majority of public health laboratories (Bopp et al, 2016). Additionally, analysis of WGS data can be difficult due to the extensive computational capacity and bioinformatics skills needed for genomic comparisons and to determine a threshold to establish relatedness (Burall et al., 2016).
General remarks
There are different examples of outbreaks associated with the consumption of dairy products, and the identification of causative bacteria is very complex. Novel molecular techniques have been crucial for accuracy in the detection of foodborne bacteria in diverse types of dairy products (including pasteurized milk), and it is probable that without these molecular approaches, the outbreaks’ etiological agents would not have been correctly identified.
On the other hand, the dairy industry requires fast, sensitive and cost-effective technology for the detection of foodborne pathogens in order to fulfill food safety requirements and to establish routine quality control testing. For example, due to the increasing demand for raw products and the conditions (i.e., transport temperature and humidity) between the processing and storing of dairy products, the application of advanced analytical methods for pathogen detection could ensure safety and prevent outbreaks due to consumption of contaminated products, reducing the economic losses related to removal of products, negative corporate images and court costs.
Molecular typifying methods are powerful tools for accurate genetic characterization of foodborne pathogens, and the dairy industry and governments might apply them extensively, implementing standard protocols for foodborne pathogens in developed and developing countries, ensuring the food safety of dairy products regardless of their origin. Molecular techniques can be used in different industries such as food and pharmaceutics; however, they require expensive equipment and reagents, and their setup requires highly technical skills. Additionally, infrastructure will be another important factor to consider, since most of these techniques require controlled environments to avoid contamination and misleading results. In the case of the dairy industry, qPCR and PCR techniques are more feasible to implement since they are quick and cost-effective and do not require much skill to perform, compared to other molecular techniques.
