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Species Determination and Quantitation in Mixtures Using MRM Mass Spectrometry of Peptides Applied to Meat Authentication
Published on: September 20, 2016
Chemometrics Assisted-Liquid Chromatography (LC)-Orbitrap High Resolution Mass Spectrometry (HRMS) Non-Targeted
Anjar Windarsih1,2, Nor Kartini Abu Bakar1, Abdul Rohman3,4
1Department of Chemistry, Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia.
Abstract:
The presence of non-halal meats in declared halal meat products is truly prohibited to be consumed, especially for Muslim consumers. The objective of this study was to identify dog meat (DM) adulteration in beef sausage (BS) using an untargeted metabolomics technique based on liquid chromatography-high resolution mass spectrometry (LC-HRMS) Orbitrap incorporated with chemometrics tools. Chemometrics of principal component analysis (PCA), partial least square-discriminant analysis (PLS-DA), PLS, and orthogonal PLS was used to manage the metabolomics data. PCA could differentiate the authentic BS and that adulterated with DM. In addition, PLS-DA successfully classified BS and BS adulterated with DM according to their classes with r2X=0.815, r2Y=0.950, and Q2=0.582, repectively. Metabolites of trans-10-heptadecenoic acid, N-stearoyltyrosine, L-gamma-glutamyl-L-leucine, 1-(beta-D-ribofuranosyl) thymine, adenosine, (3beta,24R,24'R)-fucosterol epoxide, acetyl-L-carnitine, isoleucine, diisobutyl adipate, L-tyrosine, carnosine, and DL-glutamine were found as discriminating metabolites with variable importance for projection value of >2.0 for discriminating BS from DM adulteration. In addition, orthogonal PLS using variables of discriminating metabolites was successfully used to predict DM levels in BS with r2 of 0.9995, root mean square error of estimation of 0.88%, and root mean square error of prediction of 1.63%. It can be concluded that the untargeted metabolomics approach using LC-HRMS assisted with chemometrics is potential tools to be used for the authentication of BS from DM adulteration. In the future, research on larger samples and method standardization is highly urgent to ensuring the reproducibility of this method.
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