Articles by Yvonne Gunning in JoVE
Species Determination and Quantitation in Mixtures Using MRM Mass Spectrometry of Peptides Applied to Meat Authentication Yvonne Gunning1, Andrew D. Watson1, Neil M. Rigby2, Mark Philo1, Joshua K. Peazer1,3, E. Kate Kemsley1 1Analytical Sciences Unit, Institute of Food Research, 2Institute of Food Research, 3School of Chemistry, University of East Anglia We present a protocol for identifying and quantifying the components in mixtures of species possessing similar proteins. Mass spectrometry detects peptides for identification, and gives relative quantitation by ratios of peak areas. As a tool food for fraud detection, the method can detect 1% horse in beef.
Other articles by Yvonne Gunning on PubMed
NMR and HPLC-UV Profiling of Potatoes with Genetic Modifications to Metabolic Pathways Journal of Agricultural and Food Chemistry. Oct, 2004 | Pubmed ID: 15453669 Metabolite profiling has been carried out to assess the compositional changes occurring in potato tubers after genetic modifications have been made to different metabolic pathways. Most major features in the (1)H NMR and HPLC-UV profiles of tuber extracts have been assigned. About 40 GM lines and controls belonging to 4 groups of samples (derived from cv. Record or cv. Desirée and modified in primary carbon metabolism, starch synthesis, glycoprotein processing, or polyamine/ethylene metabolism) were analyzed. Differences were assessed at the level of whole profiles (by PCA) or individual compounds (by ANOVA). The most obvious differences seen in both NMR and HPLC-UV profiles were between the two varieties. There were also significant differences between two of the four Desirée GM lines with modified polyamine metabolism and their controls. Compounds notably affected were proline, trigonelline, and numerous phenolics. However, that modification gave rise to a very abnormal phenotype. Certain lines from the other groups had several compounds present in significantly higher or lower amounts compared to the control, but the differences in mean values amounted to no more than a 2-3-fold change: in the context of variability in the whole data set, such changes did not appear to be important.
Meat Authentication Via Multiple Reaction Monitoring Mass Spectrometry of Myoglobin Peptides Analytical Chemistry. Oct, 2015 | Pubmed ID: 26366801 A rapid multiple reaction monitoring (MRM) mass spectrometric method for the detection and relative quantitation of the adulteration of meat with that of an undeclared species is presented. Our approach uses corresponding proteins from the different species under investigation and corresponding peptides from those proteins, or CPCP. Selected peptide markers can be used for species detection. The use of ratios of MRM transition peak areas for corresponding peptides is proposed for relative quantitation. The approach is introduced by use of myoglobin from four meats: beef, pork, horse and lamb. Focusing in the present work on species identification, by use of predictive tools, we determine peptide markers that allow the identification of all four meats and detection of one meat added to another at levels of 1% (w/w). Candidate corresponding peptide pairs to be used for the relative quantification of one meat added to another have been observed. Preliminary quantitation data presented here are encouraging.
Low-field (1)H NMR Spectroscopy for Distinguishing Between Arabica and Robusta Ground Roast Coffees Food Chemistry. Feb, 2017 | Pubmed ID: 27596398 This work reports a new screening protocol for addressing issues of coffee authenticity using low-field (60MHz) bench-top (1)H NMR spectroscopy. Using a simple chloroform-based extraction, useful spectra were obtained from the lipophilic fraction of ground roast coffees. It was found that 16-O-methylcafestol (16-OMC, a recognized marker compound for robusta beans) gives rise to an isolated peak in the 60MHz spectrum, which can be used as an indicator of the presence of robusta beans in the sample. A total of 81 extracts from authenticated coffees and mixtures were analysed, from which the detection limit of robusta in arabica was estimated to be between 10% and 20% w/w. Using the established protocol, a surveillance exercise was conducted of 27 retail samples of ground roast coffees which were labelled as "100% arabica". None were found to contain undeclared robusta content above the estimated detection limit.