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Authentication of African green monkey cell lines using human short tandem repeat markers

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BMC BIOTECHNOLOGY
卷 11, 期 -, 页码 -

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BIOMED CENTRAL LTD
DOI: 10.1186/1472-6750-11-102

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Background: Tools for authenticating cell lines are critical for quality control in cell-based biological experiments. Currently there are methods to authenticate human cell lines using short tandem repeat (STR) markers based on the technology and procedures successfully used in the forensic community for human identification, but there are no STR based methods for authenticating nonhuman cell lines to date. There is significant homology between the human and vervet monkey genome and we utilized these similarities to design the first multiplex assay based on human STR markers for vervet cell line identification. Results: The following STR markers were incorporated into the vervet multiplex PCR assay: D17S1304, D5S1467, D19S245, D1S518, D8S1106, D4S2408, D6S1017, and DYS389. The eight markers were successful in uniquely identifying sixty-two vervet monkey DNA samples and confirmed that Vero76 cells and COS-7 cells were derived from Vero and CV-1 cells, respectively. The multiplex assay shows specificity for vervet DNA within the determined allele range for vervet monkeys; however, the primers will also amplify human DNA for each marker resulting in amplicons outside the vervet allele range in several of the loci. The STR markers showed genetic stability in over sixty-nine passages of Vero cells, suggesting low mutation rates in the targeted STR sequences in the Vero cell line. Conclusions: A functional vervet multiplex assay consisting of eight human STR markers with heterozygosity values ranging from 0.53-0.79 was successful in uniquely identifying sixty-two vervet monkey samples. The probability of a random match using these eight markers between any two vervet samples is approximately 1 in 1.9 million. While authenticating a vervet cell line, the multiplex assay may also be a useful indicator for human cell line contamination since the assay is based on human STR markers.

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