Multiplex TaqMan locked nucleic acid real-time PCR for the differential identification of various meat and meat products
Introduction
As one of the most consumed protein and oil sources, meat is most prone to suffer adulteration for economic gain among the foods. Cheaper meat that has been sourced from “non-traditional” sources can be used as partial or total replacement for highly valued meats for economic benefit. Frauds in the meat industry and retail markets have become a widespread problem, especially after a European horse meat scandal that spread throughout many countries in 2013, including Sweden, Britain, France, Ireland and Romania (O'mahony, 2013). In a recent investigation performed on one thousand types of meat products, it was found that nearly 20% of the products identified were not of consistent quality (Ballin, Vogensen, & Karlsson, 2009). Otherwise, Adulteration of meat and meat products because of species substitution is also of major importance for traditional and religious foods (Costa, Mafra, Carrapatoso, & Oliveira, 2016). Therefore, the presence of certain animal species is perhaps the most concern of consumers and the responsibility of administrators, which highlighting the necessity of determining method to track meat and derived products.
Various detection methods were developed to identify specific meat sources, some of which based on species-specific proteins have been developed, such as electrophoresis, isoelectric focusing (IEF) and enzyme-linked immunosorbent assays (ELISA) (Zhang et al., 2014). However, these methods are laborious, and sometimes less sensitive for denatured proteins in products during heating, dehydration, chemical processing and pressurization. Some protein-based assays are also not sensitive to effectively differentiate closely related species (Karabasanavar, Singh, Kumar, & Shebannavar, 2014). The application of the polymerase chain reaction (PCR) is an ideal way for target identification because of its sensitivity, reliability and convenience. Various PCR-based identification methods have been developed, such as PCR-RFLP (Rahman et al., 2015), RAPD (Rastogi et al., 2007) and SSCP (Tisza et al., 2016). However, difficulties in obtaining reproducible patterns and the inappropriateness of analyzing admixed meat species make the applicability of these methods of limited scope (Fajardo, González, Rojas, García, & Martín, 2010). Recently meat detection through sensors and biosensors were developed for sensitive and fast, or even visible identification of meat sources (Ali et al., 2014, Kamruzzaman et al., 2013, Wang et al., 2015).
Real-time PCR is currently considered to be the most precise, cost-effective and applicable assay to identify meat products. Real-time PCR is performed through monitoring fluorescence signal, which allows for direct observation of results without additional steps (Chisholm et al., 2005, Tanabe et al., 2007). Multiplex real-time PCR, which can simultaneously detect different target genes in one reaction, have been validated as an effective tool for application in a number of detection fields, including food borne pathogens (Zhang et al., 2007), genetically modified organisms (Zhao, Deng, Liu, Fang, & He, 2004), and food-induced allergies (Chen & Wang, 2011), as well as meat adulteration detection (Cheng et al., 2014, Fang and Zhang, 2016, Hou et al., 2015, Köppel et al., 2013, Meira et al., 2017). Of these, TaqMan probes are the most frequently used methods to monitor fluorescence. However, high melting temperature (Tm) of TaqMan probes restricts its use because of increased competition among different probes and primers (Gašparič et al., 2010). The locked nucleic acid (LNA) adds methylene bridge linking the 2′ hydroxyl group of an RNA monomer to the 4′ carbon of the ribose ring to increase the stability of the duplex when bound to the target (Braasch and Corey, 2001, Petersen and Wengel, 2003) and have previously been used in several SNP genotyping and microRNA detection assays (Várallyay et al., 2008, Johnson et al., 2004.). Recent work has shown that when LNAs are incorporated into Taqman probes they provide increased specificity and sensitivity (Reynisson, Josefsen, Krause, & Hoorfar, 2006).
In this study, a novel multiplex TaqMan-LNA real-time PCR method (MLNA-RT-PCR) was developed to simultaneously detect four meat samples. PCR primers and TaqMan-LNA probes were designed based on the sequence of mitochondrial gene in each species, which served as the target. The specificity and sensitivity were also evaluated to determine the applicability of this assay. The reliability of this method was determined using one hundred commercial meat and meat products, which were collected from local markets.
Section snippets
Preparation of meat samples
Fresh samples of cows (Bos taurus), pigs (Sus scrofa), chicken (Gallus gallus), duck (Anas platyrhynchos), sheep (Ovis aries), horse (Equus caballus), deer (Cervus), donkey (Equus asinus), rabbit (Oryctolagus cuniculus), goose (Goose calicivirus),goat (Capra aegagrus hircus), shrimp (Penneropeanaeus Chinensis), salmon (Oncorhynchus) and maize (Zea mays L.) were purchased directly from butchers or farmers in Shantou, China, and have been confirmed by national standard method to guarantee their
Primer and probe selection
The consistency of the amplification efficiency of each primer and probe pair is the key for the application of the MLNA-RT-PCR. Mitochondrial DNA (mtDNA) accounts more copies per cell and evolves much faster than nuclear DNA, and is applied for species identification (Fajardo et al., 2010). In addition to homologous analysis through related species between primer and target, each probe was tested through RT-PCR for specificity validation (Fig. S1). Then, A four-plex MLNA-RT-PCR system was
Discussion
Chicken and duck are frequently used to be involved in processed beef and pork products for economic profit (He, Huang, & Zhang, 2012). Therefore, species identification is a major concern, due to food fraud and potential health hazards. Similar detection methods have been developed by Bai et al. (2009) and Hou et al. (2015), however, these methods require further agarose gel electrophoresis analysis. This may not be suitable for the detection of large numbers of samples under commercial or
Acknowledgements
This study was financed by the Science and Technology Project of the Guangdong Entry-Exit Inspection and Quarantine Bureau (2014GDK24), the Science and Technology Project of Guangdong Province (2015A050502030, 2016A050503031).
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