scholarly journals N-Linked Glycopeptide Identification Based on Open Mass Spectral Library Search

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Zhiwu An ◽  
Qingbo Shu ◽  
Hao Lv ◽  
Lian Shu ◽  
Jifeng Wang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Human Cancer ◽  
Cancer Cell Line ◽  
Peptide Identification ◽  
High Energy ◽  
Mass Spectral Library ◽  
Spectral Library ◽  
Data Set ◽  
Library Search ◽  
Mass Spectral

Confident characterization of intact glycopeptides is a challenging task in mass spectrometry-based glycoproteomics due to microheterogeneity of glycosylation, complexity of glycans, and insufficient fragmentation of peptide bones. Open mass spectral library search is a promising computational approach to peptide identification, but its potential in the identification of glycopeptides has not been fully explored. Here we present pMatchGlyco, a new spectral library search tool for intact N-linked glycopeptide identification using high-energy collisional dissociation (HCD) tandem mass spectrometry (MS/MS) data. In pMatchGlyco, (1) MS/MS spectra of deglycopeptides are used to create spectral library, (2) MS/MS spectra of glycopeptides are matched to the spectra in library in an open (precursor tolerant) manner and the glycans are inferred, and (3) a false discovery rate is estimated for top-scored matches above a threshold. The efficiency and reliability of pMatchGlyco were demonstrated on a data set of mixture sample of six standard glycoproteins and a complex glycoprotein data set generated from human cancer cell line OVCAR3.

scholarly journals Identification of Leishmania by Matrix-Assisted Laser Desorption Ionization–Time of Flight (MALDI-TOF) Mass Spectrometry Using a Free Web-Based Application and a Dedicated Mass-Spectral Library

2017 ◽  
Vol 55 (10) ◽  
pp. 2924-2933 ◽  
Author(s):  
Laurence Lachaud ◽  
Anna Fernández-Arévalo ◽  
Anne-Cécile Normand ◽  
Patrick Lami ◽  
Cécile Nabet ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Leishmania Donovani ◽  
Identification System ◽  
Enzyme Electrophoresis ◽  
Mass Spectral Library ◽  
Spectral Library ◽  
Web Based ◽  
Content Type ◽  
Mass Spectral ◽  
Scalable Database

ABSTRACT Human leishmaniases are widespread diseases with different clinical forms caused by about 20 species within the Leishmania genus. Leishmania species identification is relevant for therapeutic management and prognosis, especially for cutaneous and mucocutaneous forms. Several methods are available to identify Leishmania species from culture, but they have not been standardized for the majority of the currently described species, with the exception of multilocus enzyme electrophoresis. Moreover, these techniques are expensive, time-consuming, and not available in all laboratories. Within the last decade, mass spectrometry (MS) has been adapted for the identification of microorganisms, including Leishmania . However, no commercial reference mass-spectral database is available. In this study, a reference mass-spectral library (MSL) for Leishmania isolates, accessible through a free Web-based application (mass-spectral identification [MSI]), was constructed and tested. It includes mass-spectral data for 33 different Leishmania species, including species that infect humans, animals, and phlebotomine vectors. Four laboratories on two continents evaluated the performance of MSI using 268 samples, 231 of which were Leishmania strains. All Leishmania strains, but one, were correctly identified at least to the complex level. A risk of species misidentification within the Leishmania donovani , L. guyanensis , and L. braziliensis complexes was observed, as previously reported for other techniques. The tested application was reliable, with identification results being comparable to those obtained with reference methods but with a more favorable cost-efficiency ratio. This free online identification system relies on a scalable database and can be implemented directly in users' computers.

Evaluation of mass spectral library search algorithms implemented in commercial software

2015 ◽  
Vol 50 (6) ◽  
pp. 820-825 ◽  
Author(s):  
Andrey Samokhin ◽  
Ksenia Sotnezova ◽  
Vitaly Lashin ◽  
Igor Revelsky
Keyword(s):  
Search Algorithms ◽  
Mass Spectral Library ◽  
Spectral Library ◽  
Commercial Software ◽  
Library Search ◽  
Mass Spectral

False Discovery Rate Estimation for Hybrid Mass Spectral Library Search Identifications in Bottom-up Proteomics

2019 ◽  
Vol 18 (9) ◽  
pp. 3223-3234 ◽  
Author(s):  
Meghan C. Burke ◽  
Zheng Zhang ◽  
Yuri A. Mirokhin ◽  
Dmitrii V. Tchekovskoi ◽  
Yuxue Liang ◽  
...  
Keyword(s):  
False Discovery Rate ◽  
Mass Spectral Library ◽  
Spectral Library ◽  
Bottom Up ◽  
Library Search ◽  
Mass Spectral ◽  
Rate Estimation ◽  
False Discovery ◽  
False Discovery Rate Estimation

The Hybrid Search: A Mass Spectral Library Search Method for Discovery of Modifications in Proteomics

2017 ◽  
Vol 16 (5) ◽  
pp. 1924-1935 ◽  
Author(s):  
Meghan C. Burke ◽  
Yuri A. Mirokhin ◽  
Dmitrii V. Tchekhovskoi ◽  
Sanford P. Markey ◽  
Jenny Heidbrink Thompson ◽  
...  
Keyword(s):  
Search Method ◽  
Mass Spectral Library ◽  
Spectral Library ◽  
Hybrid Search ◽  
Library Search ◽  
Mass Spectral
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