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A digital PCR method for identifying and quantifying adulteration of meat species in raw and processed food

Meat adulteration is a worldwide concern. In this paper, a new droplet digital PCR (ddPCR) method was developed for the quantitative determination of the presence of chicken in sheep and goat meat products. Meanwhile, a constant (multiplication factor) was introduced to transform the ratio of copy n...

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Detalles Bibliográficos
Autores principales: Ren, Junan, Deng, Tingting, Huang, Wensheng, Chen, Ying, Ge, Yiqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5358868/
https://www.ncbi.nlm.nih.gov/pubmed/28319152
http://dx.doi.org/10.1371/journal.pone.0173567
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author Ren, Junan
Deng, Tingting
Huang, Wensheng
Chen, Ying
Ge, Yiqiang
author_facet Ren, Junan
Deng, Tingting
Huang, Wensheng
Chen, Ying
Ge, Yiqiang
author_sort Ren, Junan
collection PubMed
description Meat adulteration is a worldwide concern. In this paper, a new droplet digital PCR (ddPCR) method was developed for the quantitative determination of the presence of chicken in sheep and goat meat products. Meanwhile, a constant (multiplication factor) was introduced to transform the ratio of copy numbers to the proportion of meats. The presented ddPCR method was also proved to be more accurate (showing bias of less than 9% in the range from 5% to 80%) than real-time PCR, which has been widely used in this determination. The method exhibited good repeatability and stability in different thermal treatments and at ultra-high pressure. The relative standard deviation (RSD) values of 5% chicken content was less than 5.4% for ultra-high pressure or heat treatment. Moreover, we confirmed that different parts of meat had no effect on quantification accuracy of the ddPCR method. In contrast to real-time PCR, we examined the performance of ddPCR as a more precise, sensitive and stable analytical strategy to overcome potential problems of discrepancies in amplification efficiency discrepancy and to obtain the copy numbers directly without standard curves. The method and strategy developed in this study can be applied to quantify the presence and to confirm the absence of adulterants not only to sheep but also to other kinds of meat and meat products.
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spelling pubmed-53588682017-04-06 A digital PCR method for identifying and quantifying adulteration of meat species in raw and processed food Ren, Junan Deng, Tingting Huang, Wensheng Chen, Ying Ge, Yiqiang PLoS One Research Article Meat adulteration is a worldwide concern. In this paper, a new droplet digital PCR (ddPCR) method was developed for the quantitative determination of the presence of chicken in sheep and goat meat products. Meanwhile, a constant (multiplication factor) was introduced to transform the ratio of copy numbers to the proportion of meats. The presented ddPCR method was also proved to be more accurate (showing bias of less than 9% in the range from 5% to 80%) than real-time PCR, which has been widely used in this determination. The method exhibited good repeatability and stability in different thermal treatments and at ultra-high pressure. The relative standard deviation (RSD) values of 5% chicken content was less than 5.4% for ultra-high pressure or heat treatment. Moreover, we confirmed that different parts of meat had no effect on quantification accuracy of the ddPCR method. In contrast to real-time PCR, we examined the performance of ddPCR as a more precise, sensitive and stable analytical strategy to overcome potential problems of discrepancies in amplification efficiency discrepancy and to obtain the copy numbers directly without standard curves. The method and strategy developed in this study can be applied to quantify the presence and to confirm the absence of adulterants not only to sheep but also to other kinds of meat and meat products. Public Library of Science 2017-03-20 /pmc/articles/PMC5358868/ /pubmed/28319152 http://dx.doi.org/10.1371/journal.pone.0173567 Text en © 2017 Ren et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ren, Junan
Deng, Tingting
Huang, Wensheng
Chen, Ying
Ge, Yiqiang
A digital PCR method for identifying and quantifying adulteration of meat species in raw and processed food
title A digital PCR method for identifying and quantifying adulteration of meat species in raw and processed food
title_full A digital PCR method for identifying and quantifying adulteration of meat species in raw and processed food
title_fullStr A digital PCR method for identifying and quantifying adulteration of meat species in raw and processed food
title_full_unstemmed A digital PCR method for identifying and quantifying adulteration of meat species in raw and processed food
title_short A digital PCR method for identifying and quantifying adulteration of meat species in raw and processed food
title_sort digital pcr method for identifying and quantifying adulteration of meat species in raw and processed food
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5358868/
https://www.ncbi.nlm.nih.gov/pubmed/28319152
http://dx.doi.org/10.1371/journal.pone.0173567
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