Simplified 2-D CE-MS mapping: analysis of proteolytic digests.
ABSTRACT 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.
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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.Electrophoresis 12/2007; 28(22):4192-201. · 3.26 Impact Factor
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ABSTRACT: Abstract In metabolomics, the rapid identification of quantitative differences between multiple biological samples remains a majorMetabolomics. 01/2010;
Article: Serum proteomics for gastric cancer.[Show abstract] [Hide abstract]
ABSTRACT: According to the World Health Organization, 800,000 cancer-related deaths are caused by gastric cancer each year globally, hence making it the second leading cause of cancer-related deaths in the world. Gastric cancer is often either asymptomatic or causing only nonspecific symptoms in its early stages. By the time the symptoms occur, the cancer has usually reached an advanced stage, which is one of the main reasons for its relatively poor prognosis. Therefore, early diagnosis and early treatment are very crucial. The differential analysis of serum protein between cancer patients and healthy controls can be performed using proteomics techniques and can hence be adopted as tumor biomarkers for the early diagnosis of cancer. So far, several serum tumor biomarkers have been identified for gastric cancer. However due to their poor specificity and sensitivity, they have proven to be insufficient for the reliable diagnosis of gastric cancer. Thus, using modern advanced proteomic techniques to find some new and reliable serum tumor biomarkers for earlier and reliable diagnosis of gastric cancer is a must. Nowadays, proteomics-based techniques, such as SELDI and HCLP, are available to discover biomarkers in gastric cancer. Numerous novel serum tumor biomarkers such as SAA, plasminogen and C9c, have been discovered through serological proteomics strategies. This review mainly focuses on the serum proteomics techniques and their application in the research of gastric cancer.Clinica chimica acta; international journal of clinical chemistry 02/2014; · 2.54 Impact Factor