Comparison of SNP-Based Detection Assays for Food Analysis: Coffee Authentication
Recently, DNA-based authentication methods were developed to serve as complementary approaches to analytical chemistry techniques. The single nucleotide polymorphism (SNP)-based reaction chemistries, when combined with the existing detection methods, could result in numerous analytical approaches, all with particular advantages and disadvantages. The dual aim of this study was (a) to develop SNP-based analytical assays such as the single-base primer extension (SNaPShotTM) and pyrosequencing in order to differentiate Arabica and Robusta varieties for the authentication of coffee beans and (b) to compare the performances of SNaPshot, pyrosequencing and the previously developed polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) using an Agilent 2100 Bioanalyzer on the basis of linearity (R 2) and LOD, expressed as percentage of the adulterant species, using green coffee beans (Arabica and Robusta) as a food model. The results showed that SNaPshot analysis exhibited the best LOD, whereas pyrosequencing revealed the best linearity (R 2 = 0.997). The PCR-RFLP assay using the Agilent 2100 Bioanalyzer could prove to be a very useful method for a laboratory that lacks sequencing facilities but it can be used only if a SNP creates/deletes a restriction site.
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Document Type: Research Article
Affiliations: University of Nottingham, Division of Nutritional Sciences, School of Biosciences, Sutton Bonington Campus, Loughborough, Leics LE12 5RD, UK
Publication date: 01 July 2014
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- The Journal of AOAC INTERNATIONAL publishes refereed papers and reviews in the fields of chemical, biological and toxicological analytical chemistry for the purpose of showcasing the most precise, accurate and sensitive methods for analysis of foods, food additives, supplements and contaminants, cosmetics, drugs, toxins, hazardous substances, pesticides, feeds, fertilizers and the environment available at that point in time. The scope of the Journal includes unpublished original research describing new analytical methods, techniques and applications; improved approaches to sampling, both in the field and the laboratory; better methods of preparing samples for analysis; collaborative studies substantiating the performance of a given method; statistical techniques for evaluating data. The Journal will also publish other articles of general interest to its audience, e.g., technical communications; cautionary notes; comments on techniques, apparatus, and reagents.
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