It has been demonstrated that CE-MS is a very useful hyphenated technique for proteomic studies. However, the huge amount of data stored in a single CE-MS run makes it necessary to account with procedures able to extract all the relevant information made available by CE-MS. In this work, we present a new and easy approach capable of generating a simplified 2-D map from CE-MS raw data. This new approach provides the automatic detection and characterization of the most abundant ions from the CE-MS data including their mass-to-charge (m/z) values, ion intensities and analysis times. It is demonstrated that visualization of CE-MS data in this simplified 2-D format allows: (i) an easy and simultaneous visual inspection of large datasets, (ii) an immediate perception of relevant differences in closely related samples, (iii) a rapid monitoring of data quality levels in different samples, and (iv) a fast discrimination between comigrating polypeptides and ESI-MS fragmentation ions. The strategy proposed in this work does not rely on an excellent mass accuracy for peak detection and filtering, since MS values obtained from an IT analyzer are used. Moreover, the methodology developed works directly with the CE-MS raw data, without interference by the user, giving simultaneously a simplified 2-D map and a much easier and more complete data evaluation. Besides, this procedure can easily be implemented in any CE-MS laboratory. The usefulness of this approach is validated by studying the very similar trypsin digests from bovine, rabbit and horse cytochrome c. It is demonstrated that this simplified 2-D approach allows specific markers for each species to be obtained in a fast and simple way.
[Show abstract][Hide abstract] ABSTRACT: In metabolomics, the rapid identification of quantitative differences between multiple biological samples remains a major challenge. While capillary electrophoresis-mass spectrometry (CE-MS) is a powerful tool to simultaneously quantify charged metabolites, reliable and easy-to-use software that is well suited to analyze CE-MS metabolic profiles is still lacking. Optimized software tools for CE-MS are needed because of the sometimes large variation in migration time between runs and the wider variety of peak shapes in CE-MS data compared with LC-MS or GC-MS. Therefore, we implemented a stand-alone application named JDAMP (Java application for Differential Analysis of Metabolite Profiles), which allows users to identify the metabolites that vary between two groups. The main features include fast calculation modules and a file converter using an original compact file format, baseline subtraction, dataset normalization and alignment, visualization on 2D plots (m/z and time axis) with matching metabolite standards, and the detection of significant differences between metabolite profiles. Moreover, it features an easy-to-use graphical user interface that requires only a few mouse-actions to complete the analysis. The interface also enables the analyst to evaluate the semiautomatic processes and interactively tune options and parameters depending on the input datasets. The confirmation of findings is available as a list of overlaid electropherograms, which is ranked using a novel difference-evaluation function that accounts for peak size and distortion as well as statistical criteria for accurate difference-detection. Overall, the JDAMP software complements other metabolomics data processing tools and permits easy and rapid detection of significant differences between multiple complex CE-MS profiles.
[Show abstract][Hide abstract] ABSTRACT: Zein proteins are a complex mixture of polypetides that belong to the alcohol-soluble storage proteins group (prolamines) in corn. These proteins constitute about 50-60% of the total endosperm protein and are classified in different groups on the basis of differences in their solubility and sequence. Among them, zein proteins are considered the majority group showing a high tendency to aggregate what makes their analysis by any analytical method very difficult. Thus, CZE of these proteins requires the use of very complex BGEs noncompatible with online ESI-MS analysis. The aim of this work was to find a new BGE for the CZE separation of zein protein fully compatible with ESI-MS while providing further light on the complex CZE separation of aggregatable proteins. Thus, it is demonstrated in this work that efficient and reproducible CZE separations of zein proteins can be achieved by using a BGE composed of water, ACN, formic acid and ammonium hydroxide. Besides, it is shown that zein analysis is significantly improved by including the effect of an ammonium gradient during their separation. It is experimentally verified that the ammonium gradient can easily be achieved in CZE by either working with a sample zone with a low concentration of ammonium and a BGE with a high concentration, or conversely, working with a sample zone with high ammonium concentration and a BGE with low concentration of ammonium, giving rise in both cases to a significant improvement in the CZE separation of these proteins. It is demonstrated that this procedure can give rise to efficiency improvements of up to 20-fold in the CZE separation of zein proteins. Under optimized conditions, 20 proteins could be separated with average efficiencies higher than 400 000 theoretical plates/m. Some possible explanations of this effect are discussed including stacking, protein-capillary wall adsorption, protein solubility and protein-salt interactions.
[Show abstract][Hide abstract] ABSTRACT: In this work, an original CE-MS method has been developed to analyze the complex zein protein fractions from maize. A thorough optimization of: (i) zein protein extraction, (ii) CE separation, and (iii) electrospray-MS (ESI-MS) detection is carried out in order to obtain highly informative CE-MS profiles of this fraction. The developed CE-MS method provides good separation of multiple zein proteins based on their electrophoretic mobilities as well as adequate characterization of these proteins based on their M(r). Zein proteins with small M(r) differences (below 100 Da) were easily separated and successfully analyzed by CE-MS. Thus, apart of the so-called 15-kDa-beta-zein and 16-kDa-gamma-zein, which are demonstrated to be formed by a heterogeneous group of proteins, numerous alpha-zeins belonging to the 19- and 22-kDa fraction were also identified for the first time in this work. The usefulness of this CE-MS method was corroborated by comparing the zein-protein fingerprints of various maize lines including transgenic and their corresponding nontransgenic isogenic lines cultivated under the same conditions.
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