Technical note: A quick and more sensitive method to identify pork in processed and unprocessed food by PCR amplification of a new specific DNA fragment |
| |
| Authors: | Calvo J H Zaragoza P Osta R |
| |
| Institution: | Laboratorio de Genética Bioquímica, Facultad de Veterinaria, Zaragoza, Spain. jhcalvo@posta.unizar.es |
| |
| Abstract: | We developed and evaluated a PCR procedure to detect pork in heated and unheated meat, sausages, canned food, cured products, and patés using a faster, more specific, and more sensitive method than others previously described. Isolation of a new DNA-specific porcine repetitive element was performed by nonspecific PCR amplification. After analyzing this repetitive sequence, a pair of primers were synthesized. To confirm the effectiveness and specificity of this fragment, 55 pig blood DNA samples (from differents breeds) were tested and positive results were obtained. With 200 samples tested from other species, the specific pork amplification was not detected. Using this method, we can partially quantify degree of contamination, depending on the PCR amplification cycles, detecting up to 0.005% pork in beef and 1% pork in duck paté using 30 and 20 PCR amplification cycles, respectively. The amount of porcine DNA detected in cattle DNA was 1.25 and 250 pg when using 30 and 20 amplification cycles, respectively. Pork has been identified in both heated and unheated meat products, sausages, canned food, hamburgers, and patés. In conclusion, specific PCR amplification of a repetitive DNA element seems to be a powerful technique for the identification of pork in processed and unprocessed food, because of its simplicity, specificity, and sensitivity (with 30 amplification cycles we can detect 0.005% pork). Furthermore, it is a very fast method, because 1% pork contamination can be detected with 20 PCR cycles. The procedure is also much cheaper than other methods based on RFLP-PCR, immunodiffusion, or other techniques that need expensive equipment. |
| |
| Keywords: | |
| 本文献已被 PubMed 等数据库收录！ |
|
