Evaluation of stable isotope labelling strategies for the quantitation of CP4 EPSPS in genetically modified soya
Centre for Chemical and Bioanalytical Sciences, Royal Holloway, University of London, Egham TW20 0EX, UK.Analytica chimica acta (Impact Factor: 4.51). 03/2009; 634(1):75-82. DOI: 10.1016/j.aca.2008.11.071
The introduction of genetically modified (GM) crops into the market has raised a general alertness relating to the control and safety of foods. The applicability of protein separation hyphenated to mass spectrometry to identify the bacterial enolpyruvylshikimate-3-phosphate synthase (CP4 EPSPS) protein expressed in GM crops has been previously reported [M.F. Ocana, P.D. Fraser, R.K.P. Patel, J.M. Halket, P.M. Bramley, Rapid Commun. Mass Spectrom. 21 (2007) 319.]. Herein, we investigate the suitability of two strategies that employ heavy stable isotopes, i.e. AQUA and iTRAQ, to quantify different levels of CP4 EPSPS in up to four GM preparations. Both quantification strategies showed potential to determine whether the presence of GM material is above the limits established by the European Union. The AQUA quantification procedure involved protein solubilisation/fractionation and subsequent separation using SDS-PAGE. A segment of the gel in which the protein of interest was located was excised, the stable isotope labeled peptide added at a known concentration and proteolytic digestion initiated. Following recovery of the peptides, on-line separation and detection using LC-MS was carried out. A similar approach was used for the iTRAQ workflow with the exception that proteins were digested in solution and generated tryptic peptides were chemically tagged. Both procedures demonstrated the potential for quantitative detection at 0.5% (w/w) GM soya which is a level below the current European Union's threshold for food-labelling. In this context, a comparison between the two procedures is provided within the present study.
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ABSTRACT: A CE-TOF MS proteomic approach was applied for the analysis of hydrolyzates from complex soybean protein mixtures. After CE-TOF MS method development, the new approach provided the simultaneous analysis of more than 150 peptides from the soybean protein fraction soluble in ACN-water (80/20 v/v). The method is fast (about 30 min of analysis per sample) and is characterized by a relatively low running cost. The approach was used to study the substantial equivalence between a genetically modified variety of soybean compared with its traditional counterpart. No significant differences were found between the two studied soybeans based on the protein fraction studied. The capacity of the CE-TOF MS method to analyze complex mixtures of peptides in short times opens interesting possibilities in the growing Foodomics area.Electrophoresis 04/2010; 31(7):1175-83. DOI:10.1002/elps.200900448 · 3.03 Impact Factor
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ABSTRACT: A proteomic-based method has been developed for the detection of chicken meat within mixed meat preparations. The procedure is robust and simple, comprising the extraction of myofibrillar proteins, enrichment of target proteins using OFFGEL isoelectric focusing, in-solution trypsin digestion of myosin light chain 3, and analysis of the generated peptides by liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS). Using this approach, it was possible for example to detect 0.5% contaminating chicken in pork meat with high confidence. Quantitative detection of chicken meat was done by using AQUA stable isotope peptides made from the sequence of previously selected species-specific peptide biomarkers. Linearity was observed between the amount of the peptide biomarker and the amount of chicken present in the mixture; further independent replication is required now to validate the method. Apart from its simplicity, this approach has the advantage that it can be used effectively for the detection of both raw and cooked meat. The method is robust, reliable, and sensitive, representing a serious alternative to methods currently in use for these purposes. It is amenable to highly processed foods which can be particularly problematic, as the tertiary protein structure is often affected in processed food precluding immunoassays. In addition, this proteomic analysis will permit the determination of definitive discriminatory sequence, unlike the DNA PCR based methods used presently. The present article also demonstrates the translation of the technology to routine mass spectrometry equipment, making the methodology suitable for public analysts.Journal of Proteome Research 07/2010; 9(7):3374-83. DOI:10.1021/pr9008942 · 4.25 Impact Factor
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ABSTRACT: Mass spectrometry (MS) has become an essential technology for proteomics applications in biological sciences. Advances in this technique have been possible owing to improvements in MS instrumentation, new experimental strategies in sample preparation, and development of bioinformatics tools for data analyses. In recent years, complementary strategies to the classical two-dimensional gel electrophoresis approaches (2-DE) have been developed. These techniques are based on multidimensional peptide separation coupled to tandem MS (also referred as “second generation proteomics”), enabling protein expression analysis and high throughput protein identification studies. New methods such as Multidimensional Protein Identification Technology (MudPIT) and stable isotope labeling of protein/peptide samples (either by chemical, metabolic, or enzymatic methods), among others, are powerful tools for large-scale studies on characterization and expression of proteins in complex biological systems. Hence, these techniques can be very useful in the study of plant-pathogen interactions, aiding to detect and characterize both plant proteins concerned in defense reactions and pathogen proteins involved in pathogenicity and/or virulence. But these techniques have been implemented in these biological systems just recently. We will examine here how MS-based proteomics approaches are helping to better understand the multifaceted phenomena underlying plant-pathogen interactions.Current Proteomics 11/2010; 7(4):234-243. DOI:10.2174/157016410793611738 · 0.64 Impact Factor
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