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一种基于16S下一代测序的分子与生物信息学流程,用于识别加工肉类产品的污染和错误标签。

A 16S Next Generation Sequencing Based Molecular and Bioinformatics Pipeline to Identify Processed Meat Products Contamination and Mislabelling.

作者信息

Chaora Nyaradzo Stella, Khanyile Khulekani Sedwell, Magwedere Kudakwashe, Pierneef Rian, Tabit Frederick Tawi, Muchadeyi Farai Catherine

机构信息

Department of Life and Consumer Sciences, College of Agriculture and Environmental Sciences, University of South Africa, Rooderpoort 1709, South Africa.

Biotechnology Platform, Agricultural Research Council, Private Bag X 05, Onderstepoort, Pretoria 0110, South Africa.

出版信息

Animals (Basel). 2022 Feb 10;12(4):416. doi: 10.3390/ani12040416.

Abstract

Processed meat is a target in meat adulteration for economic gain. This study demonstrates a molecular and bioinformatics diagnostic pipeline, utilizing the mitochondrial 16S ribosomal RNA (rRNA) gene, to determine processed meat product mislabeling through Next-Generation Sequencing. Nine pure meat samples were collected and artificially mixed at different ratios to verify the specificity and sensitivity of the pipeline. Processed meat products (n = 155), namely, minced meat, biltong, burger patties, and sausages, were collected across South Africa. Sequencing was performed using the Illumina MiSeq sequencing platform. Each sample had paired-end reads with a length of ±300 bp. Quality control and filtering was performed using BBDuk (version 37.90a). Each sample had an average of 134,000 reads aligned to the mitochondrial genomes using BBMap v37.90. All species in the artificial DNA mixtures were detected. Processed meat samples had reads that mapped to the (90% and above) genus, with traces of reads mapping to and (2-5%) genus. Sausage samples showed the highest level of contamination with 46% of the samples having mixtures of beef, pork, or mutton in one sample. This method can be used to authenticate meat products, investigate, and manage any form of mislabeling.

摘要

加工肉类是肉类掺假以获取经济利益的目标对象。本研究展示了一种分子和生物信息学诊断流程,利用线粒体16S核糖体RNA(rRNA)基因,通过下一代测序来确定加工肉类产品的标签错误。收集了9个纯肉样本,并以不同比例人工混合,以验证该流程的特异性和敏感性。在南非各地收集了155种加工肉类产品,即碎肉、干肉片、汉堡肉饼和香肠。使用Illumina MiSeq测序平台进行测序。每个样本有长度约为300 bp的双端读数。使用BBDuk(版本37.90a)进行质量控制和过滤。每个样本平均有134,000个读数使用BBMap v37.90与线粒体基因组比对。人工DNA混合物中的所有物种都被检测到。加工肉类样本的读数映射到(90%及以上)属,有微量读数映射到和(2 - 5%)属。香肠样本显示出最高的污染水平,46%的样本在一个样本中含有牛肉、猪肉或羊肉的混合物。这种方法可用于验证肉类产品、调查和管理任何形式的标签错误。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/458d/8868451/30f8fb92e808/animals-12-00416-g001.jpg

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