Genetically modified (GM) cotton lines have been approved for commercialization and widely cultivated in many countries, especially in China. As a step towards the development of reliable qualitative and quantitative PCR methods for detecting GM cottons, we report here the validation of the cotton (Gossypium hirsutum) endogenous reference control gene, Sad1, using conventional and real-time (RT)-PCR methods. Both methods were tested on 15 different G. hirsutum cultivars, and identical amplicons were obtained with all of them. No amplicons were observed when DNA samples from three species of genus Gossypium, Arabidopsis thaliana, maize, and soybean and others were used as amplified templates, demonstrating that these two systems are specific for the identification and quantification of G. hirsutum. The results of Southern blot analysis also showed that the Sad1 gene was two copies in these 15 different G. hirsutum cultivars. Furthermore, one multiplex RT-quantitative PCR employing this gene as an endogenous reference gene was designed to quantify the Cry1A(c) gene modified from Bacillus thuringiensis (Bt) in the insect-resistant cottons, such as Mon531 and GK19. The quantification detection limit of the Cry1A(c) and Sad1 genes was as low as 10 pg of genomic DNA. These results indicate that the Sad1 gene can be used as an endogenous reference gene for both qualitative and quantitative PCR detection of GM cottons.
We describe the development of a novel combined approach for high-throughput analysis of multiple DNA targets based on multiplex Microdroplet PCR Implemented Capillary gel electrophoresis (MPIC), a two-step PCR amplification strategy. In the first step, the multiple target DNAs are preamplified using bipartite primers attached with universal tail sequences on their 5'-ends. Then, the preamplified templates are compartmentalized individually in the microdroplet of the PCR system, and multiple targets can be amplified in parallel, employing primers targeting their universal sequences. Subsequently, the resulting multiple products are analyzed by capillary gel electrophoresis (CGE). Using genetically modified organism (GMO) analysis as a model, 24 DNA targets can be simultaneously detected with a relative limit of detection of 0.1% (w/w) and absolute limit of detection of 39 target DNA copies. The described system provides a promising alternative for high-throughput analysis of multiple DNA targets.
In this project, a highly precise quantitative method based on the digital polymerase chain reaction (dPCR) technique was developed to determine the weight of pork and chicken in meat products. Real-time quantitative polymerase chain reaction (qPCR) is currently used for quantitative molecular analysis of the presence of species-specific DNAs in meat products. However, it is limited in amplification efficiency and relies on standard curves based Ct values, detecting and quantifying low copy number target DNA, as in some complex mixture meat products. By using the dPCR method, we find the relationships between the raw meat weight and DNA weight and between the DNA weight and DNA copy number were both close to linear. This enabled us to establish formulae to calculate the raw meat weight based on the DNA copy number. The accuracy and applicability of this method were tested and verified using samples of pork and chicken powder mixed in known proportions. Quantitative analysis indicated that dPCR is highly precise in quantifying pork and chicken in meat products and therefore has the potential to be used in routine analysis by government regulators and quality control departments of commercial food and feed enterprises.
Meat products often consist of meat from multiple animal species, and inaccurate food product adulteration and mislabeling can negatively affect consumers. Therefore, a cost-effective and reliable method for identification and quantification of animal species in meat products is required. In this study, we developed a duplex droplet digital PCR (dddPCR) detection and quantification system to simultaneously identify and quantify the source of meat in samples containing a mixture of beef (Bos taurus) and pork (Sus scrofa) in a single digital PCR reaction tube. Mixed meat samples of known composition were used to test the accuracy and applicability of this method. The limit of detection (LOD) and the limit of quantification (LOQ) of this detection and quantification system were also identified. We conclude that our dddPCR detection and quantification system is suitable for quality control and routine analyses of meat products.
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