Identification of Adulterated Animal-derived Ingredients in Edible Animal Viscera Based on Capillary Gel Electrophoresis and DNA Barcoding Techniques
-
摘要: 建立并优化了使用基于DNA条形码技术对可食用内脏制品中包括猪、牛、羊、鸡、鸭、鹅、兔7种常见动物源成分进行掺假鉴别的方法。用生理盐水清洗和真空冷冻干燥预处理后的内脏样品,经DNA提取扩增后,扩增产物经毛细管凝胶电泳分析系统进行确认,克隆测序结果提交本地数据库Viscera进行比对,同时筛选出适合7种动物源内脏DNA扩增的通用引物COI-A,优化DNA模板量和退火温度,验证考察了19个可食用内脏掺假模型的最低掺假比例。7种动物的5类内脏的PCR扩增效率均为100%,最佳的DNA模板量和退火温度为2 μL和53 ℃,掺假成分的最低检出比例为5%。本方法灵敏度高,可靠性好,可作为常见可食用动物内脏掺假的有效检测方法。
-
关键词:
- 毛细管凝胶电泳 /
- DNA条形码 /
- 内脏 /
- 细胞色素C氧化酶亚基Ⅰ /
- 掺假
Abstract: A DNA barcoding method with cytochrome C oxidase subunit I sequence (COI) was developed to identify 7 adulterated animal-derived components (including pig, cattle, sheep, chicken, duck, goose and rabbit) in edible viscera products. Samples were cleaned with physiological saline and pretreated by vacuum freeze drying before DNA extraction and amplification. PCR products were confirmed by capillary gel electrophoresis analysis system, and the cloned sequencing results were submitted to the local database (Viscera) for comparison. The universal primer set COI-A was used for the amplification, and the amount of DNA template and annealing temperature were optimized. Meanwhile, the minimum adulteration percentage of 19 edible viscera adulteration models was validated and examined. Results showed that the 5 viscera sources from 7 animal species can be completely amplified under the above conditions, the optimal DNA template volume and annealing temperature are 2 μL and 53 ℃ respectively, and the minimum detection percentage of adulterated components was 5%. The method is sensitive and reliable, which can be used for the identification of adulterated 7 animal-derived components in the edible viscera products.-
Key words:
- capillary gel electrophoresi /
- DNA barcoding /
- viscera /
- cytochrome coxidase subunit I /
- adulteration
-
表 1 基因引物序列
Table 1. Primer sequence of genes
引物 上游引物(F-Primer 5′-3′) 下游引物(R-Primer 5′-3′) COI-A[27] TGTAAAACGACGGCCAGTTCTCAACCAACCACAARGAYATYGG CAGGAAACAGCTATGACTAGACTTCTGGGTGGCCRAARAAYCA COI-B[26] TGTAAAACGACGGCCAGTICTCAACCAACCACAAAGACATIGG CAGGAAACAGCTATGACTAGACTTCTGGGTGGCCAAAGAATCA COI-C[26] TGTAAAACGACGGCCAGTTCTCAACCAACCAIAAIGALATIGG CAGGAAACAGCTATGACTAGACTTCTGGGTGICCIAAIAAICA 表 2 7种动物源内脏的DNA条形码检测结果
Table 2. DNA barcoding results for 7 samples found to contain one species
序号(NO.) 内脏来源 基因相似度 物种匹配结果 1 猪 99% Sus scrofa(野猪) 2 牛 98% Bos primigenius(原始牛) 3 羊 99% Capra hircus(山羊) 4 鸭 98% Anas platyrhynchos(绿头鸭) 5 鸡 100% Gallus gallus(普通家鸡) 6 鹅 98% Anser(鹅属) 7 兔 100% Oryctolagus cuniculus(家兔) 表 3 可食用内脏掺假模型
Table 3. Animal viscera adulteration model
模型编号 高经济价值内脏 掺假内脏 灵敏度(%) 1 牛肝 猪肝 5 2 羊肝 猪肝 5 3 兔肝 猪肝 5 4 鹅肝
鹅肝鸭肝 5 5 鸡肝 5 6 牛胃 猪胃 5 7 羊胃 猪胃 5 8 鹅胃
鹅胃鸡胃 5 9 鸭胃 5 10 牛肠 猪肠 5 11 羊肠 猪肠 5 12 鹅肠
鹅肠鸡肠 5 13 鸭肠 5 14 牛肾 猪肾 5 15 羊肾 猪肾 5 16 鹅肾
鹅肾鸡肾 5 17 鸭肾 5 18 牛肺 猪肺 5 19 羊肺 猪肺 5 表 4 实际样品检测结果
Table 4. Actual sample test results
序号
(NO.)样品名称 DNA条形
码鉴定结果基因相似
度(%)判断
结果实时荧光定
性PCR法结果1 牛肝a 牛源性成分 98 符合 牛源性成分 2 牛肝b 牛源性成分 98 符合 牛源性成分 3 牛肝c 牛源性成分 98 符合 牛源性成分 4 羊肝a 羊源性成分 99 符合 羊源性成分 5 羊肝b 羊源性成分 99 符合 羊源性成分 6 鹅肝a 鹅源性成分 99 符合 鹅源性成分 7 鹅肝b 鹅源性成分 99 符合 鹅源性成分 8 鹅肝c 鹅源性成分 99 符合 鹅源性成分 9 鹅肝d 鸭源性成分 98 掺假 鸭源性成分 10 鹅肝e 鹅源性成分 99 符合 鹅源性成分 11 牛百叶a 牛源性成分 98 符合 牛源性成分 12 牛百叶b 牛源性成分 98 符合 牛源性成分 13 牛百叶c 牛源性成分 98 符合 牛源性成分 14 牛百叶d 猪源性成分 97 掺假 猪源性成分 15 牛百叶e 牛源性成分 98 符合 牛源性成分 16 牛百叶f 猪源性成分 97 掺假 猪源性成分 17 牛肠a 牛源性成分 98 符合 牛源性成分 18 牛肠b 牛源性成分 98 符合 牛源性成分 19 鹅肠a 鹅源性成分 99 符合 鹅源性成分 20 鹅肠b 鹅源性成分 99 符合 鹅源性成分 21 鹅肠c 鸭源性成分 99 掺假 鸭源性成分 22 鹅肠d 鹅源性成分 99 符合 鹅源性成分 23 牛肺 牛源性成分 98 符合 牛源性成分 24 羊肺a 羊源性成分 99 符合 羊源性成分 25 羊肺b 羊源性成分 99 符合 羊源性成分 -
[1] 王学平. 畜禽产品加工的综合利用发展趋势[J]. 肉类研究,2008(11):11−14. [WANG X P. The comprehensive utilization of the livestock and poultry products processing[J]. Meat Research,2008(11):11−14. doi: 10.3969/j.issn.1001-8123.2008.11.006WANG X P. The comprehensive utilization of the livestock and poultry products processing[J]. Meat Research, 2008, (11): 11-14. doi: 10.3969/j.issn.1001-8123.2008.11.006 [2] 王晓雄. 吃动物内脏的好与坏[J]. 安全与健康,2017(12):51. [WANG X X. The benefits and disadvantages of eating animal viscera[J]. Safety & Health,2017(12):51.WANG X X. The benefits and disadvantages of eating animal viscera[J]. Safety & Health, 2017, (12): 51. [3] 张文文, 梅娜娜, 钤莉妍, 等. 驴肝与猪肝、鸡肝和鹅肝之间的营养成分比较[J]. 食品安全质量检测学报,2018,9(16):4435−4439. [ZHANG W W, MEI N N, QIAN L Y, et al. Comparison of nutrients between donkey liver and pig liver, chicken liver and goose liver[J]. Journal of Food Safety & Quality,2018,9(16):4435−4439. doi: 10.3969/j.issn.2095-0381.2018.16.041ZHANG W W, MEI N N, QIAN L Y, et al. Comparison of nutrients between donkey liver and pig liver, chicken liver and goose liver [J]. Journal of Food Safety & Quality, 2018, 9(16): 4435-4439. doi: 10.3969/j.issn.2095-0381.2018.16.041 [4] 李珮斯, 苏永祺, 郭新东, 等. 微波消解-电感耦合等离子体质谱法测定动物内脏中金属元素含量[J]. 安徽农业科学,2013,41(21):8915−8917. [LI P S, SU Y Q, GUO X D, et al. Content determination of metal elements in animal viscera by microwave digestion-inductively coupled plasma mass spectrometry[J]. Journal of Anhui Agricultural Sciences,2013,41(21):8915−8917. doi: 10.3969/j.issn.0517-6611.2013.21.037LI P S, SU Y Q, GUO X D, et al. Content determination of metal elements in animal viscera by microwave digestion-inductively coupled plasma mass spectrometry [J]. Journal of Anhui Agricultural Sciences, 2013, 41(21): 8915-8917. doi: 10.3969/j.issn.0517-6611.2013.21.037 [5] 林竹光, 孙若男, 张莉莉, 等. 气相色谱-质谱法同时测定动物内脏中的14种酞酸酯类环境激素残留[J]. 色谱,2008(3):280−284. [LIN Z G, SUN R N, ZHANG L L, et al. Simultaneous determination of 14 phthalate ester residues in animal innards by gas chromatography-mass spectrometry with electron impact ionization[J]. Chinese Journal of Chromatography,2008(3):280−284. doi: 10.3321/j.issn:1000-8713.2008.03.003LIN Z G, SUN R N, ZHANG L L, et al. Simultaneous determination of 14 phthalate ester residues in animal innards by gas chromatography-mass spectrometry with electron impact ionization [J]. Chinese Journal of Chromatography, 2008, (3): 280-284. doi: 10.3321/j.issn:1000-8713.2008.03.003 [6] 魏法山, 巩阿娜, 谢文佳, 等. 我国畜禽内脏食用安全指标检测分析[J]. 食品安全质量检测学报,2017,8(9):3667−3673. [WEI F S, GONG A N, XIE W J, et al. Detection and analysis of edible safety of livestock and poultry viscera in China[J]. Journal of Food Safety & Quality,2017,8(9):3667−3673. doi: 10.3969/j.issn.2095-0381.2017.09.066WEI F S, GONG A N, XIE W J, et al. Detection and analysis of edible safety of livestock and poultry viscera in China [J]. Journal of Food Safety & Quality, 2017, 8(9): 3667-3673. doi: 10.3969/j.issn.2095-0381.2017.09.066 [7] ERBAN T, SHCHERBACHENKO E, TALACKO P, et al. A single honey proteome dataset for identifying adulteration by foreign amylases and mining various protein markers natural to honey[J]. Journal of Proteomics,2021,239:104157. doi: 10.1016/j.jprot.2021.104157 [8] KRITIKOU A S, AALIZADEH R, DAMALAS D E, et al. MALDI-TOF-MS integrated workflow for food authenticity investigations: An untargeted protein-based approach for rapid detection of PDO feta cheese adulteration[J]. Food Chemistry,2022,370:131057. doi: 10.1016/j.foodchem.2021.131057 [9] MONTOWSKA M, FORNAL E. Absolute quantification of targeted meat and allergenic protein additive peptide markers in meat products[J]. Food Chemistry,2019,274:857−864. doi: 10.1016/j.foodchem.2018.08.131 [10] LECRENIER M C, MARIEN A, VEYS P, et al. Inter-laboratory study on the detection of bovine processed animal protein in feed by LC-MS/MS-based proteomics[J]. Food Control,2021,125:107944. doi: 10.1016/j.foodcont.2021.107944 [11] FORNAL E, MONTOWSKA M. Species-specific peptide-based liquid chromatography–mass spectrometry monitoring of three poultry species in processed meat products[J]. Food Chemistry,2019,285:489−498. [12] HAO X K, FU L L, SHAO L L, et al. Quantification of major milk proteins using ultra-performance liquid chromatography tandem triple quadrupole mass spectrometry and its application in milk authenticity analysis[J]. Food Control,2022,131:108455. doi: 10.1016/j.foodcont.2021.108455 [13] COTTENET G, BLANCPAIN C, CHUAH P F, et al. Evaluation and application of a next generation sequencing approach for meat species identification[J]. Food Control,2020,110:107003. doi: 10.1016/j.foodcont.2019.107003 [14] GALAL-KHALLAF A. Multiplex PCR and 12S rRNA gene sequencing for detection of meat adulteration: A case study in the Egyptian markets[J]. Gene,2021,764:145062. doi: 10.1016/j.gene.2020.145062 [15] WANG N, XING R R, ZHOU M Y, et al. Application of DNA barcoding and metabarcoding for species identification in salmon products[J]. Food Additives & Contaminants,2021,38(5):754−768. [16] CAOBY H, ZHENG K Z, JIANG J F, et al. A novel method to detect meat adulteration by recombinase polymerase amplification and SYBR green I[J]. Food Chemistry,2018,266:73−78. doi: 10.1016/j.foodchem.2018.05.115 [17] KANG T S, TANAKA T. Comparison of quantitative methods based on SYBR Green real-time qPCR to estimate pork meat adulteration in processed beef products[J]. Food Chemistry,2018,269:549−558. doi: 10.1016/j.foodchem.2018.06.141 [18] QUINTO C A, TINOCO R, HELLBERG R S. DNA barcoding reveals mislabeling of game meat species on the U. S. commercial market[J]. Food Control,2016,59:386−392. doi: 10.1016/j.foodcont.2015.05.043 [19] ZIA Q, ALAWAMI M, MOKHTAR N F, et al. Current analytical methods for porcine identification in meat and meat products[J]. Food Chemistry,2020,324:126664. doi: 10.1016/j.foodchem.2020.126664 [20] XING R R, HU R R, HAN J X, et al. DNA barcoding and mini-barcoding in authenticating processed animal-derived food: A case study involving the Chinese market[J]. Food Chemistry,2020,309:125653. doi: 10.1016/j.foodchem.2019.125653 [21] AHMED N, SANGALE D, TIKNAIK A, et al. Authentication of origin of meat species processed under various Indian culinary procedures using DNA barcoding[J]. Food Control, 2018, 90: 259−265. [22] KANE D E, HELLBERG R S. Identification of species in ground meat products sold on the U. S. commercial market using DNA-based methods[J]. Food Control,2016,59:158−163. doi: 10.1016/j.foodcont.2015.05.020 [23] BARAKAT H, EI-GARHY H A S, MOUSTAFA M M A. Detection of pork adulteration in processed meat by species-specific PCR-QIAxcel procedure based on D-loop and cytb genes[J]. Applied Microbiology and Biotechnology,2014,98:9805−9816. doi: 10.1007/s00253-014-6084-x [24] SEN F, UNCU A O, UNCU A T, et al. The trnL (UAA)-trnF (GAA) intergenic spacer is a robust marker of green pea (Pisum sativum L.) adulteration in economically valuable pistachio nuts (Pistacia vera L.)[J]. Journal of the Science of Food and Agriculture,2020,100(7):3056−3061. doi: 10.1002/jsfa.10336 [25] ELSAYED M S A E. A first insight into the application of high discriminatory MIRU-VNTR typing using QIAxcel technology for genotyping Mycobacterium bovis isolated from the Delta area in Egypt[J]. Infection, Genetics and Evolution,2019,71:211−214. doi: 10.1016/j.meegid.2019.04.004 [26] HAJIBABAEI M, SINGER G A C, HEBERT P D N, et al. DNA barcoding: How it complements taxonomy, molecular phylogenetics and population genetics[J]. Trends in Genetics,2007,23(4):167−172. doi: 10.1016/j.tig.2007.02.001 [27] IVANOVA N V, DEWAARD J R, HEBERT P D N. An inexpensive automation-friendly protocol for recovering high-quality DNA[J]. Molecular Ecology Notes,2006,6:998−1002. doi: 10.1111/j.1471-8286.2006.01428.x [28] RAO M S, CHAKRABORTY G, MURTHY K S. Market drivers and discovering technologies in meat species identification[J]. Food Analytical Methods,2019,12:2416−2429. doi: 10.1007/s12161-019-01591-8 [29] KUMAR A, RODRIGUES V, BASKARAN K, et al. DNA barcode based species-specific marker for Ocimum tenuiflorum and its applicability in quantification of adulteration in herbal formulations using qPCR[J]. Journal of Herbal Medicine,2020,23:100376. doi: 10.1016/j.hermed.2020.100376 [30] DAI Z Y, QIAO J, YANG S R, et al. Species authentication of common meat based on PCR analysis of the mitochondrial COI Gene[J]. Applied Biochemistry and Biotechnology,2015,176:1770−1780. doi: 10.1007/s12010-015-1715-y [31] LIU W W, TAO J, XUE M, et al. A multiplex PCR method mediated by universal primers for the identification of eight meat ingredients in food products[J]. European Food Research and Technology,2019,245:2385−2392. doi: 10.1007/s00217-019-03350-9 [32] DUNHAM-CHEATHAM S M, KLINGLER K B, ESTRADA M V, et al. Using a next-generation sequencing approach to DNA metabarcoding for identification of adulteration and potential sources of mercury in commercial cat and dog foods[J]. Science of The Total Environment,2021,778:146102. doi: 10.1016/j.scitotenv.2021.146102 [33] COTTENET G, SONNARD V, BLANCPAIN C, et al. A DNA macro-array to simultaneously identify 32 meat species in food samples[J]. Food Control,2016,67:135−143. doi: 10.1016/j.foodcont.2016.02.042 [34] SWETHA V P, SHEEJA T E, SASIKUMAR B. DNA barcoding as an authentication tool for food and agricultural commodities[J]. Current Trends in Biotechnology & Pharmacy,2016,10(4):384−402. [35] HELLBERG R S, HERNANDEZ B C, HERNANDEZ E L. Identification of meat and poultry species in food products using DNA barcoding[J]. Food Controll,2017,80:23−28. doi: 10.1016/j.foodcont.2017.04.025 [36] 励炯, 吴琼, 扈明洁, 等. 基于细胞色素C氧化酶亚基Ⅰ序列的DNA微条形码技术鉴别11种生鲜肉制品掺假的研究[J]. 浙江大学学报(农业与生命科学版),2021,47(1):52−59. [LI J, WU Q, HU M J, et al. Identification of adulteration in 11 fresh meat products by DNA mini-barcoding methods based on cytochrome C oxidase subunit Ⅰ (COⅠ) sequence[J]. Journal of Zhejiang University (Agriculture and Life Sciences),2021,47(1):52−59. doi: 10.3785/j.issn.1008-9209.2020.04.291LI J, WU Q, HU M J, et al. Identification of adulteration in 11 fresh meat products by DNA mini-barcoding methods based on cytochrome C oxidase subunit Ⅰ (COⅠ) sequence[J]. Journal of Zhejiang University(Agriculture and Life Sciences), 2021, 47(1): 52-59. doi: 10.3785/j.issn.1008-9209.2020.04.291 [37] 郜星晨, 姜伟. 三峡库区常见鱼类DNA条形码本地BLAST数据库的构建和应用[J]. 基因组学与应用生物学,2021,40(5):1952−1964. [HAO X C, JIANG W. The construction and application of BLAST database of DNA barcode for common fish in the three gorges reservoir[J]. Genomics and Applied Biology,2021,40(5):1952−1964. doi: 10.13417/j.gab.040.001952HAO X C, JIANG W. The construction and application of BLAST database of DNA barcode for common fish in the three gorges reservoir [J]. Genomics and Applied Biology, 2021, 40(5): 1952-1964. doi: 10.13417/j.gab.040.001952 -