食品科学 ›› 2017, Vol. 38 ›› Issue (11): 318-327.doi: 10.7506/spkx1002-6630-201711049

• 专题论述 • 上一篇    

基于核酸分子学方法的肉类成分鉴别技术研究进展

王金斌,李 文,白 蓝,刘 华,蒋 玮,吴 潇,王荣谈,唐雪明   

  1. 1.上海市农业科学院,上海 201106;2.上海海洋大学食品学院,上海 200090;3.上海市农业遗传育种重点实验室,上海 201106;4.上海瑞丰农业科技有限公司,上海 201106
  • 出版日期:2017-06-15 发布日期:2017-06-19

A Review of Current DNA-Based Methodologies for Meat Authentication

WANG Jinbin, LI Wen, BAI Lan, LIU Hua, JIANG Wei, WU Xiao, WANG Rongtan, TANG Xueming   

  1. 1. Shanghai Academy of Agricultural Sciences, Shanghai 201106, China; 2. College of Food Science and Technology, Shanghai Ocean University, Shanghai 200090, China; 3. Key Laboratory of Agricultural Genetics and Breeding, Shanghai 201106, China; 4. Shanghai Ruifeng Agricultural Sci-Tech Company Ltd., Shanghai 201106, China
  • Online:2017-06-15 Published:2017-06-19

摘要: 近年来,肉类掺假问题频繁发生。基于核酸的分子生物学肉类成分鉴别技术已成为研究热点,其具有灵敏度高、特异性强、检测时间短以及成本低的优点。本文综述了基于核酸分子学的肉类成分种属鉴别技术在肉类掺假检验中的应用,着重于量化各种方法的检测限,并重点对实时荧光定量聚合酶链式反应(polymerase chainreaction,PCR)和数字PCR技术在动物成分鉴别定量分析的研究现状与前景做介绍。探讨不同来源的靶基因(核DNA和线粒体DNA)在动物成分鉴别中,定性和定量检测灵敏度与特异性的区别。

关键词: 掺假, 肉类制品, 数字PCR, 物种测定

Abstract: In recent years, the problem of meat adulteration has occurred frequently. Full attention has been paid to DNAbased methodologies for meat species identification because of their high sensitivity and specificity, as well as rapid processing time and low cost. This article presents an overview of the commonly used DNA-based methodologies to verify the authenticity of meat and meat products with focus on their detection limits. Moreover, this review highlights the current applications and future prospects of real-time fluorescence quantitative polymerase chain reaction (PCR) and digital PCR in the identification of animal origin ingredients. Finally, target genes from different sources (nuclear DNA and mitochondrial DNA) are compared in terms of their characteristics and their influence on the sensitivity and specificity of species identification and quantification.

Key words: adulteration, meat products, digital PCR, species determination

中图分类号: