Evaluation of chemical labeling methods for identifying functional arginine residues of proteins by mass spectrometry

Arginine residues undergo several kinds of post-translational modifications (PTMs). These PTMs are associated with several inflammatory diseases, such as rheumatoid arthritis, atherosclerosis, and diabetes. Mass spectrometric studies of arginine modified proteins and peptides are very important, not only to identify the reactive arginine residues but also to understand the tandem mass spectrometry behavior of these peptides for assigning the sequences unambiguously. Herein, we utilize tandem mass spectrometry to report the performance of two widely used arginine labeling reagents, 1,2-cyclohexanedione (CHD) and phenylglyoxal (PG) with several arginine containing peptides and proteins. Time course labeling studies were performed to demonstrate the selectivity of the reagents in proteins or protein digests. Structural studies on the proteins were also explored to better understand the reaction sites and position of arginine residues. We found CHD showed better labeling efficiencies compared to phenylglyoxal. Reactive arginine profiling on a purified albumin protein clearly pointed out the cellular glycation modification site for this protein with high confidence.     

XRF to support food traceability studies: Classification of Sri Lankan tea based on their region of origin

Food fraud is a concern for the producers of high‐quality food products as it causes brand damage and loss of profit. Tea (Camellia sinensis L.) is one of the major agricultural products of Sri Lanka and accounts for more than 300 million of kilograms per year, roughly 2% of the national GDP. Trace metals and stable isotope ratios in tea samples originating from various regions in Sri Lanka were determined by using X‐ray fluorescence analysis and isotope‐ratio mass spectrometry to explore the possibility of classifying the tea according to its origin. In total, 13 elements (Mg, P, S, Cl, K, Ca, Mn, Fe, Cu, Zn, Br, Rb and Sr) were determined in 58 tea samples originating from four production districts in Sri Lanka (Hantana, Thalawakelle, Passara and Ratnapura). Two multivariate analysis techniques, namely principal component analysis and canonical discriminant analysis, were applied to explore the differences in elemental contents among the tea produced in these regions and to find a method for compositional classification. This study, although limited by the number of samples available, clearly shows that the differentiation and classification of tea samples according to the four regions of origin is possible by using the elemental contents and applying canonical discriminant analysis. Copyright © 2017 John Wiley & Sons, Ltd.