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Improved methods for the enrichment and analysis of glycated peptides.

ABSTRACT: Nonenzymatic glycation of tissue proteins has important implications in the development of complications of diabetes mellitus. Herein we report improved methods for the enrichment and analysis of glycated peptides using boronate affinity chromatography and electron-transfer dissociation mass spectrometry, respectively. The enrichment of glycated peptides was improved by replacing an off-line desalting step with an online wash of column-bound glycated peptides using 50 mM ammonium acetate, followed by elution with 100 mM acetic acid. The analysis of glycated peptides by MS/MS was improved by considering only higher charged (> or = 3) precursor ions during data-dependent acquisition, which increased the number of glycated peptide identifications. Similarly, the use of supplemental collisional activation after electron transfer (ETcaD) resulted in more glycated peptide identifications when the MS survey scan was acquired with enhanced resolution. Acquiring ETD-MS/MS data at a normal MS survey scan rate, in conjunction with the rejection of both 1+ and 2+ precursor ions, increased the number of identified glycated peptides relative to ETcaD or the enhanced MS survey scan rate. Finally, an evaluation of trypsin, Arg-C, and Lys-C showed that tryptic digestion of glycated proteins was comparable to digestion with Lys-C and that both were better than Arg-C in terms of the number of glycated peptides and corresponding glycated proteins identified by LC-MS/MS.

SUBMITTER: Zhang Q

PROVIDER: S-EPMC2752342 | biostudies-literature | 2008 Dec

REPOSITORIES: biostudies-literature

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Improved methods for the enrichment and analysis of glycated peptides.

Zhang Qibin Q Schepmoes Athena A AA Brock Jonathan W C JW Wu Si S Moore Ronald J RJ Purvine Samuel O SO Baynes John W JW Smith Richard D RD Metz Thomas O TO

Analytical chemistry 20081201 24

Nonenzymatic glycation of tissue proteins has important implications in the development of complications of diabetes mellitus. Herein we report improved methods for the enrichment and analysis of glycated peptides using boronate affinity chromatography and electron-transfer dissociation mass spectrometry, respectively. The enrichment of glycated peptides was improved by replacing an off-line desalting step with an online wash of column-bound glycated peptides using 50 mM ammonium acetate, follow ...[more]

PMID: 18989935

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Project description:BACKGROUND:Pathway enrichment extensively used in the analysis of Omics data for gaining biological insights into the functional roles of pre-defined subsets of genes, proteins and metabolites. A large number of methods have been proposed in the literature for this task. The vast majority of these methods use as input expression levels of the biomolecules under study together with their membership in pathways of interest. The latest generation of pathway enrichment methods also leverages information on the topology of the underlying pathways, which as evidence from their evaluation reveals, lead to improved sensitivity and specificity. Nevertheless, a systematic empirical comparison of such methods is still lacking, making selection of the most suitable method for a specific experimental setting challenging. This comparative study of nine network-based methods for pathway enrichment analysis aims to provide a systematic evaluation of their performance based on three real data sets with different number of features (genes/metabolites) and number of samples. RESULTS:The findings highlight both methodological and empirical differences across the nine methods. In particular, certain methods assess pathway enrichment due to differences both across expression levels and in the strength of the interconnectedness of the members of the pathway, while others only leverage differential expression levels. In the more challenging setting involving a metabolomics data set, the results show that methods that utilize both pieces of information (with NetGSA being a prototypical one) exhibit superior statistical power in detecting pathway enrichment. CONCLUSION:The analysis reveals that a number of methods perform equally well when testing large size pathways, which is the case with genomic data. On the other hand, NetGSA that takes into consideration both differential expression of the biomolecules in the pathway, as well as changes in the topology exhibits a superior performance when testing small size pathways, which is usually the case for metabolomics data.

Dataset Information

Improved methods for the enrichment and analysis of glycated peptides.

Publications

Improved methods for the enrichment and analysis of glycated peptides.

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