Species identification of the Northern shrimp (Pandalus borealis) by polymerase chain reaction-restriction fragment length polymorphism and proteomic analysis

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• 作者：Ananias Pascoal^a ; ¹ ; Ignacio Ortea^b ; ¹ ; José ; M. Gallardo^b ; Benito Cañ ; as^c ; Jorge Barros-Velá ; zquez^a ; Pilar Calo-Mata^a ; ^{p.calo.mata@usc.es}
• 关键词：Northern prawns ; Pandalus borealis ; Species identification ; PCR&ndash ; RFLP ; Crustacean ; Decapoda ; Proteomics
• 刊名：Analytical Biochemistry
• 出版年：2012
• 出版时间：1 February 2012
• 年：2012
• 卷：421
• 期：1
• 页码：56-67
• 全文大小：949 K

文摘

Genomic and proteomic techniques for species identification of meat and seafood products are being widely used. In this study, a genomic approach was used to differentiate Pandalus borealis (the Northern shrimp), which belongs to the superfamily Pandaloidea, from 30 crustaceans consisting of 19 commercially relevant prawns/shrimps species that belong to the superfamily Penaeoidea, which include the families Penaeidae and Solenoceridae, and 11 other crustacean species, including prawns, shrimps, lobsters, and crabs. For this purpose, a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method was designed based on the amplification of the 16S rRNA/tRNA^Val/12S rRNA mitochondrial regions using the primers 16S-CruF and 16S-CruR. The 966-bp PCR products were produced and cleaved with the restriction enzymes AluI, TaqI, and HinfI, which provided species-specific restriction patterns. In addition, a proteomic approach, based on matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) and electrospray ionization-ion trap (ESI-IT) mass spectrometry, was used to identify and characterize new P. borealis-specific peptides that could be useful as potential markers of this species in protein-based detection methods. To our knowledge, this is the first time a molecular method has been successfully applied to identify a wide range of prawn and shrimp species, including P. borealis, for either whole individuals or processed products. However, validation of the methods proposed here is required by applying them to a larger sample of individuals from different populations and geographic origins in order to avoid mainly false-negative results.