scholarly journals AA_stat enables extensive characterization of artefact and post-translational modifications in bottom-up proteomics

2020 ◽  
Author(s):  
Lev I. Levitsky ◽  
Julia A. Bubis ◽  
Mikhail V. Gorshkov ◽  
Irina A. Tarasova
Keyword(s):  
Amino Acid ◽  
Mass Spectra ◽  
Large Scale ◽  
Proteomics Data ◽  
Post Translational Modifications ◽  
Tandem Mass Spectra ◽  
Command Line Tool ◽  
Mass Shifts ◽  
Bioinformatic Approach

ABSTRACTWe report on AA_stat, a bioinformatic approach for panoramic profiling of artificial and post-translational modifications and their localization sites in large-scale proteomics data. Presented version of AA_stat provides validation of ultra-tolerant (open) search results followed by interpretation of the observed mass shifts and recommendation of the optimized sets of fixed and variable modifications for subsequent regular searches. Localization of modification sites is based on relative amino acid frequencies and analysis of tandem mass spectra. AA_stat determines groups of peptide identifications with mass shifts from the validated results of the open search and then scores each possible mass shift location by matching the MS/MS spectrum across the theoretical peptide isoforms. Here we demonstrate the utility of AA_stat for blind scanning of abundant and rare amino acid modifications of both artificial and biological origins and analyze advantages and limitations of open search strategies. AA_stat is implemented as an open-source command line tool available at https://github.com/SimpleNumber/aa_stat.

scholarly journals Statistical Characterization of Ion Trap Tandem Mass Spectra from Doubly Charged Tryptic Peptides

2003 ◽  
Vol 75 (5) ◽  
pp. 1155-1163 ◽  
Author(s):  
David L. Tabb ◽  
Lori L. Smith ◽  
Linda A. Breci ◽  
Vicki H. Wysocki ◽  
Dayin Lin ◽  
...  
Keyword(s):  
Mass Spectra ◽  
Ion Trap ◽  
Tandem Mass ◽  
Tryptic Peptides ◽  
Statistical Characterization ◽  
Tandem Mass Spectra ◽  
Doubly Charged

scholarly journals FLEXIQuant-LF to quantify protein modification extent in label-free proteomics data

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Christoph N Schlaffner ◽  
Konstantin Kahnert ◽  
Jan Muntel ◽  
Ruchi Chauhan ◽  
Bernhard Y Renard ◽  
...  
Keyword(s):  
Protein Modification ◽  
Large Scale ◽  
Software Tool ◽  
Label Free ◽  
Anaphase Promoting Complex ◽  
Proteomics Data ◽  
Single Experiment ◽  
Post Translational Modifications ◽  
Data Independent Acquisition ◽  
Modified Peptides

Improvements in LC-MS/MS methods and technology have enabled the identification of thousands of modified peptides in a single experiment. However, protein regulation by post-translational modifications (PTMs) is not binary, making methods to quantify the modification extent crucial to understanding the role of PTMs. Here, we introduce FLEXIQuant-LF, a software tool for large-scale identification of differentially modified peptides and quantification of their modification extent without knowledge of the types of modifications involved. We developed FLEXIQuant-LF using label-free quantification of unmodified peptides and robust linear regression to quantify the modification extent of peptides. As proof of concept, we applied FLEXIQuant-LF to data-independent-acquisition (DIA) data of the anaphase promoting complex/cyclosome (APC/C) during mitosis. The unbiased FLEXIQuant-LF approach to assess the modification extent in quantitative proteomics data provides a better understanding of the function and regulation of PTMs. The software is available at https://github.com/SteenOmicsLab/FLEXIQuantLF.

scholarly journals Understanding the limit of open search in the identification of peptides with post-translational modifications — A simulation-based study

2018 ◽  
Author(s):  
Jiaan Dai ◽  
Fengchao Yu ◽  
Ning Li ◽  
Weichuan Yu
Keyword(s):  
Analytical Model ◽  
Mass Spectra ◽  
Mass Spectrometry Data ◽  
Supplementary Information ◽  
Necessary Condition ◽  
Tandem Mass ◽  
Search Methods ◽  
Post Translational Modifications ◽  
Tandem Mass Spectra ◽  
The Relationship

AbstractMotivationAnalyzing tandem mass spectrometry data to recognize peptides in a sample is the fundamental task in computational proteomics. Traditional peptide identification algorithms perform well when identifying unmodified peptides. However, when peptides have post-translational modifications (PTMs), these methods cannot provide satisfactory results. Recently, Chick et al., 2015 and Yu et al., 2016 proposed the spectrum-based and tag-based open search methods, respectively, to identify peptides with PTMs. While the performance of these two methods is promising, the identification results vary greatly with respect to the quality of tandem mass spectra and the number of PTMs in peptides. This motivates us to systematically study the relationship between the performance of open search methods and quality parameters of tandem mass spectrum data, as well as the number of PTMs in peptides.ResultsThrough large-scale simulations, we obtain the performance trend when simulated tandem mass spectra are of different quality. We propose an analytical model to describe the relationship between the probability of obtaining correct identifications and the spectrum quality as well as the number of PTMs. Based on the analytical model, we can quantitatively describe the necessary condition to effectively apply open search methods.AvailabilitySource codes of the simulation are available at http://bioinformatics.ust.hk/[email protected] or [email protected] informationSupplementary data are available at Bioinformatics online.

Method to Correlate Tandem Mass Spectra of Modified Peptides to Amino Acid Sequences in the Protein Database

1995 ◽  
Vol 67 (8) ◽  
pp. 1426-1436 ◽  
Author(s):  
John R. Yates ◽  
Jimmy K. Eng ◽  
Ashley L. McCormack ◽  
David. Schieltz
Keyword(s):  
Amino Acid ◽  
Mass Spectra ◽  
Amino Acid Sequences ◽  
Tandem Mass ◽  
Protein Database ◽  
Tandem Mass Spectra ◽  
Modified Peptides
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