Literature DB >> 24591030

Characterisation of novel α-keratin peptide markers for species identification in keratinous tissues using mass spectrometry.

Caroline Solazzo1, Marc Wadsley, Jolon M Dyer, Stefan Clerens, Matthew J Collins, Jeffrey Plowman.   

Abstract

RATIONALE: In ancient and/or damaged artefacts containing keratinous materials, the species of origin of the materials can be difficult to identify through visual examination; therefore, a minimally destructive methodology for species identification is required. While hair fibres from some species have seen substantial characterisation, others such as horn or baleen have received little or no attention, or lack protein sequences allowing formal identification using proteomics techniques.
METHODS: We used the PMF method (Peptide Mass Fingerprinting with matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF-MS)) to catalogue and identify diagnostic peptide markers up to the genus level. Sequences were checked using nanoflow liquid chromatography/electrospray ionisation tandem mass spectrometry (nanoLC/ESI-MS/MS) and unidentified peptides were searched against a theoretical database generated by substituting amino acids in keratin sequences.
RESULTS: Specific peptides were identified by m/z and sequences characterised whenever possible for a range of species belonging to Bovidae and Camelidae, and for tissues such as baleen and horn. The theoretical database allowed an increase in the number of peptides of up to 10% in species with little genetic information.
CONCLUSIONS: A proteomics approach can successfully identify specific markers for the identification of materials to the genus level, and should be considered when identification by other means is not possible. Identification by PMF is fast, reliable and inexpensive.
Copyright © 2013 John Wiley & Sons, Ltd.

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Year:  2013        PMID: 24591030     DOI: 10.1002/rcm.6730

Source DB:  PubMed          Journal:  Rapid Commun Mass Spectrom        ISSN: 0951-4198            Impact factor:   2.419


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