scholarly journals DIA-Pipe: Identification and Quantification of Post-Translational Modifications using exclusively Data-Independent Acquisition

2017 ◽  
Author(s):  
Jesse G. Meyer ◽  
Sushanth Mukkamalla ◽  
Alexandria K. D’Souza ◽  
Alexey I. Nesvizhskii ◽  
Bradford W. Gibson ◽  
...  
Keyword(s):  
Peptide Identification ◽  
Software Tool ◽  
Label Free ◽  
Spectral Library ◽  
Automated Identification ◽  
Post Translational Modifications ◽  
Data Independent Acquisition ◽  
Sample Amount ◽  
Using Data ◽  
Identification And Quantification

Label-free quantification using data-independent acquisition (DIA) is a robust method for deep and accurate proteome quantification1,2. However, when lacking a pre-existing spectral library, as is often the case with studies of novel post-translational modifications (PTMs), samples are typically analyzed several times: one or more data dependent acquisitions (DDA) are used to generate a spectral library followed by DIA for quantification. This type of multi-injection analysis results in significant cost with regard to sample consumption and instrument time for each new PTM study, and may not be possible when sample amount is limiting and/or studies require a large number of biological replicates. Recently developed software (e.g. DIA-Umpire) has enabled combined peptide identification and quantification from a data-independent acquisition without any pre-existing spectral library3,4. Still, these tools are designed for protein level quantification. Here we demonstrate a software tool and workflow that extends DIA-Umpire to allow automated identification and quantification of PTM peptides from DIA. We accomplish this using a custom, open-source graphical user interface DIA-Pipe (https://github.com/jgmeyerucsd/PIQEDia/releases/tag/v0.1.2) (figure 1a).

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 DIALib-QC an assessment tool for spectral libraries in data-independent acquisition proteomics

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Mukul K. Midha ◽  
David S. Campbell ◽  
Charu Kapil ◽  
Ulrike Kusebauch ◽  
Michael R. Hoopmann ◽  
...  
Keyword(s):  
Quality Control ◽  
Assessment Tool ◽  
Software Tool ◽  
Mass Range ◽  
Systematic Evaluation ◽  
Label Free ◽  
Mass Spectral ◽  
Data Independent Acquisition ◽  
Theoretical Mass ◽  
Spectral Libraries

Abstract Data-independent acquisition (DIA) mass spectrometry, also known as Sequential Window Acquisition of all Theoretical Mass Spectra (SWATH), is a popular label-free proteomics strategy to comprehensively quantify peptides/proteins utilizing mass spectral libraries to decipher inherently multiplexed spectra collected linearly across a mass range. Although there are many spectral libraries produced worldwide, the quality control of these libraries is lacking. We present the DIALib-QC (DIA library quality control) software tool for the systematic evaluation of a library’s characteristics, completeness and correctness across 62 parameters of compliance, and further provide the option to improve its quality. We demonstrate its utility in assessing and repairing spectral libraries for correctness, accuracy and sensitivity.

scholarly journals Quantification and Identification of Post-Translational Modifications Using Modern Proteomics

2021 ◽  
pp. 225-235
Author(s):  
Anja Holtz ◽  
Nathan Basisty ◽  
Birgit Schilling
Keyword(s):  
Mass Spectrometry ◽  
High Resolution ◽  
High Throughput ◽  
High Resolution Mass Spectrometry ◽  
Label Free ◽  
Post Translational Modifications ◽  
Data Independent Acquisition ◽  
Lysine Residues ◽  
Detailed Protocol ◽  
Resolution Mass

AbstractPost-translational modifications (PTMs) occur dynamically, allowing cells to quickly respond to changes in the environment. Lysine residues can be targeted by several modifications including acylations (acetylation, succinylation, malonylation, glutarylation, and others), methylation, ubiquitination, and other modifications. One of the most efficient methods for the identification of post-translational modifications is utilizing immunoaffinity enrichment followed by high-resolution mass spectrometry. This workflow can be coupled with comprehensive data-independent acquisition (DIA) mass spectrometry to be a high-throughput, label-free PTM quantification approach. Below we describe a detailed protocol to process tissue by homogenization and proteolytically digest proteins, followed by immunoaffinity enrichment of lysine-acetylated peptides to identify and quantify relative changes of acetylation comparing different conditions.

scholarly journals Specter: linear deconvolution as a new paradigm for targeted analysis of data-independent acquisition mass spectrometry proteomics

2017 ◽  
Author(s):  
Ryan Peckner ◽  
Samuel A Myers ◽  
Jarrett D Egertson ◽  
Richard S Johnson ◽  
Jennifer G. Abelin ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Open Source Software ◽  
Software Tool ◽  
Nucleotide Polymorphisms ◽  
Spectral Library ◽  
New Paradigm ◽  
Single Nucleotide ◽  
Data Independent Acquisition ◽  
Targeted Analysis ◽  
Peptide Precursors

AbstractMass spectrometry with data-independent acquisition (DIA) has emerged as a promising method to greatly improve the comprehensiveness and reproducibility of targeted and discovery proteomics, in theory systematically measuring all peptide precursors within a biological sample. Despite the technical maturity of DIA, the analytical challenges involved in discriminating between peptides with similar sequences in convoluted spectra have limited its applicability in important cases, such as the detection of single-nucleotide polymorphisms and alternative site localizations in phosphoproteomics data. We have developed Specter, an open-source software tool that uses linear algebra to deconvolute DIA mixture spectra directly in terms of a spectral library, circumventing the problems associated with typical fragment correlation-based approaches. We validate the sensitivity of Specter and its performance relative to other methods by means of several complex datasets, and show that Specter is able to successfully analyze cases involving highly similar peptides that are typically challenging for DIA analysis methods.

scholarly journals DIA-NN: Deep neural networks substantially improve the identification performance of Data-independent acquisition (DIA) in proteomics

2018 ◽  
Author(s):  
Vadim Demichev ◽  
Christoph B. Messner ◽  
Kathryn S. Lilley ◽  
Markus Ralser
Keyword(s):  
Software Tool ◽  
Protein Quantification ◽  
Neural Nets ◽  
Label Free ◽  
Software Analysis ◽  
Data Independent Acquisition ◽  
Typical Data ◽  
Computational Reconstruction ◽  
Selection Of ◽  
Precursor Ions

AbstractData-independent acquisition (DIA-MS) strategies, like SWATH-MS, have been developed to increase consistency, quantification precision and proteomic depth in label-free proteomic experiments. They aim to overcome stochasticity in the selection of precursor ions by utilising (mass-) windowed acquisition that is followed by computational reconstruction of the chromatograms. While DIA methods increasingly outperform typical data-dependent methods in identification consistency and precision specifically on large sample series, possibilities remain for further improvements. At present, only a fraction of the information recorded in the complex DIA spectra is extracted by the software analysis pipelines. Here we present a software tool (DIA-NN) that introduces artificial neural nets and a new quantification strategy to enhance signal processing in DIA-data. DIA-NN greatly improves identification of precursor ions and, as a consequence, protein quantification accuracy. The performance of DIA-NN demonstrates that deep learning provides opportunities to boost the analysis of data-independent acquisition workflows in proteomics.

scholarly journals Optimization of Spectral Library Size Improves DIA-MS Proteome Coverage

2020 ◽  
Author(s):  
Weigang Ge ◽  
Xiao Liang ◽  
Fangfei Zhang ◽  
Luang Xu ◽  
Nan Xiang ◽  
...  
Keyword(s):  
Protein Identification ◽  
A Priori ◽  
Peptide Identification ◽  
Colorectal Tumor ◽  
Spectral Library ◽  
Library Size ◽  
Test Dataset ◽  
Proteome Coverage ◽  
Data Independent Acquisition ◽  
Computational Strategy

AbstractEfficient peptide and protein identification from data-independent acquisition mass spectrometric (DIA-MS) data typically rely on an experiment-specific spectral library with a suitable size. Here, we report a computational strategy for optimizing the spectral library for a specific DIA dataset based on a comprehensive spectral library, which is accomplished by a priori analysis of the DIA dataset. This strategy achieved up to 44.7% increase in peptide identification and 38.1% increase in protein identification in the test dataset of six colorectal tumor samples compared with the comprehensive pan-human library strategy. We further applied this strategy to 389 carcinoma samples from 15 tumor datasets and observed up to 39.2% increase in peptide identification and 19.0% increase in protein identification. In summary, we present a computational strategy for spectral library size optimization to achieve deeper proteome coverage of DIA-MS data.

scholarly journals The role of Data-Independent Acquisition for Glycoproteomics

2020 ◽  
pp. mcp.R120.002204
Author(s):  
Zilu Ye ◽  
Sergey Y Vakhrushev
Keyword(s):  
Early Stage ◽  
Label Free ◽  
Basic Principles ◽  
Post Translational Modifications ◽  
Full Characterization ◽  
Data Independent Acquisition ◽  
Stage Of Development ◽  
Free Quantification

Data independent acquisition (DIA) is now an emerging method in bottom-up proteomics and capable of achieving deep proteome coverage and accurate label-free quantification. However, for post-translational modifications (PTM), such as glycosylation, DIA methodology is still in the early stage of development. The full characterization of glycoproteins requires site specific glycan identification as well as subsequent quantification of glycan structures at each site. The tremendous complexity of glycosylation represents a significant analytical challenge in glycoproteomics. This review focuses on the development and perspectives of DIA methodology for N- and O- glycoproteomics and posits that DIA-based glycoproteomics could be a method of choice to address some of the challenging aspects of glycoproteomics. First, the current challenges in glycoproteomics and the basic principles of DIA is briefly introduced. DIA based glycoproteomics is then summarized and described into four aspects based on the actual samples. Lastly, we discussed the important challenges and future perspectives in the field. We believe that DIA can significantly facilitate glycoproteomic studies and contribute to the development of future advanced tools and approaches in the field of glycoproteomics.

scholarly journals Rapid and site-specific deep phosphoproteome profiling by data-independent acquisition (DIA) without the need for spectral libraries

2019 ◽  
Author(s):  
Dorte B. Bekker-Jensen ◽  
Oliver M. Bernhardt ◽  
Alexander Hogrebe ◽  
Ana Martinez del Val ◽  
Lynn Verbeke ◽  
...  
Keyword(s):  
Kinase Inhibitors ◽  
Dynamic Range ◽  
Phosphorylation Site ◽  
Software Tool ◽  
Single Shot ◽  
Data Independent Acquisition ◽  
Order Of Magnitude ◽  
Site Localization ◽  
Using Data ◽  
Spectral Libraries

ABSTRACTQuantitative phosphoproteomics has in recent years revolutionized understanding of cell signaling, but it remains a challenge to scale the technology for high-throughput analyses. Here we present a rapid and reproducible phosphoproteomics approach to systematically analyze hundreds of samples by fast liquid chromatography tandem mass spectrometry using data independent acquisition (DIA). To overcome the inherent issue of positional phosphopeptide isomers in DIA-based phosphoproteomics, we developed and employed an accurate site localization scoring algorithm, which is incorporated into the Spectronaut software tool. Using a library of synthetic phosphopeptides spiked-in to a yeast phosphoproteome in different ratios we show that it is on par with the top site localization score for data-dependent acquisition (DDA) based phosphoproteomics. Single-shot DIA-based phosphoproteomics achieved an order of magnitude broader dynamic range, higher reproducibility of identification and improved sensitivity and accuracy of quantification compared to state-of-the-art DDA-based phosphoproteomics. Importantly, direct DIA without the need of spectral libraries performed almost on par with analyses using specific project-specific libraries. Moreover, we implemented and benchmarked an algorithm for globally determining phosphorylation site stoichiometry in DIA. Finally, we demonstrate the scalability of the DIA approach by systematically analyzing the effects of thirty different kinase inhibitors in context of epidermal growth factor (EGF) signaling showing that a large proportion of EGF-dependent phospho-regulation is mediated by a specific set of protein kinases.

scholarly journals DIAmeter: Matching peptides to data-independent acquisition mass spectrometry data

2021 ◽  
Author(s):  
Yang Young Lu ◽  
Jeff Bilmes ◽  
Ricard A Rodriguez-Mias ◽  
Judit Villén ◽  
William Stafford Noble
Keyword(s):  
Mass Spectrometry ◽  
Complex Structure ◽  
Mass Spectrometry Data ◽  
Peptide Sequence ◽  
Sequence Database ◽  
Post Translational Modifications ◽  
Data Independent Acquisition ◽  
Using Data ◽  
Tandem Mass Spectrometry Data ◽  
Analyze Data

AbstractTandem mass spectrometry data acquired using data independent acquisition (DIA) is challenging to interpret because the data exhibits complex structure along both the mass-to-charge (m/z) and time axes. The most common approach to analyzing this type of data makes use of a library of previously observed DIA data patterns (a “spectral library”), but this approach is expensive because the libraries do not typically generalize well across laboratories. Here we propose DIAmeter, a search engine that detects peptides in DIA data using only a peptide sequence database. Unlike other library-free DIA analysis methods, DIAmeter supports data generated using both wide and narrow isolation windows, can readily detect peptides containing post-translational modifications, can analyze data from a variety of instrument platforms, and is capable of detecting peptides even in the absence of detectable signal in the survey (MS1) scan.

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