Evaluation of Several MS/MS Search Algorithms for Analysis of Spectra Derived from Electron Transfer Dissociation Experiments
ABSTRACT Electron transfer dissociation (ETD) is increasingly becoming popular for high-throughput experiments especially in the identification of the labile post-translational modifications. Most search algorithms that are currently in use for querying MS/MS data against protein databases have been optimized on the basis of matching fragment ions derived from collision induced dissociation of peptides, which are dominated by b and y ions. However, electron transfer dissociation of peptides generates completely different types of fragments: c and z ions. The goal of our study was to test the ability of different search algorithms to handle data from this fragmentation method. We compared four MS/MS search algorithms (OMSSA, Mascot, Spectrum Mill, and X!Tandem) using approximately 170,000 spectra generated from a standard protein mix, as well as from complex proteomic samples which included a large number of phosphopeptides. Our analysis revealed (1) greater differences between algorithms than has been previously reported for CID data, (2) a significant charge state bias resulting in >60-fold difference in the numbers of matched doubly charged peptides, and (3) identification of 70% more peptides by the best performing algorithm than the algorithm identifying the least number of peptides. Our results indicate that the search engines for analyzing ETD derived MS/MS spectra are still in their early days and that multiple search engines could be used to reduce individual biases of algorithms.
SourceAvailable from: Y L Ramachandra
Dataset: lavnya B
[Show abstract] [Hide abstract]
ABSTRACT: Dysregulation of protein expression is associated with most diseases including cancer. Mass spectrometry-based proteomic analysis is widely employed as a tool to study protein dysregulation in cancers. Proteins which are differentially expressed in head and neck squamous cell carcinoma (HNSCC) cell lines compared to the normal oral cell line could serve as biomarkers for patient stratification. To understand the proteomic complexity in HNSCC, we carried out iTRAQ-based mass spectrometry analysis on a panel of HNSCC cell lines in addition to a normal oral keratinocyte cell line. LC-MS/MS analysis of total proteome of the HNSCC cell lines led to the identification of 3263 proteins, of which 185 proteins were overexpressed and 190 proteins were downregulated more than 2-fold in at least two of the three HNSCC cell lines studied. Amongst the overexpressed proteins, 23 proteins were related to DNA replication and repair. These included high mobility group box 2 (HMGB2) protein, which was overexpressed in all three HNSCC lines studied. Overexpression of HMGB2 has been reported in various cancers, yet its role in HNSCC remains unclear. Immunohistochemical labeling of HMGB2 in a panel of HNSCC tumors using tissue microarrays revealed overexpression in 77% (54 of 70) of tumors. The HMGB proteins are known to bind to DNA structure resulting from cisplatin-DNA adducts and affect the chemosensitivity of cells. We observed that siRNA-mediated silencing of HMGB2 increased the sensitivity of the HNSCC cell lines to cisplatin and 5-FU. We hypothesize that targeting HMGB2 could enhance the efficacy of existing chemotherapeutic regimens for treatment of HNSCC.This article is protected by copyright. All rights reservedProteomics 10/2014; 15(2-3). DOI:10.1002/pmic.201400338 · 3.97 Impact Factor
Dataset: lavnya paper