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 Data-Independent Acquisition for the Quantification and Identification of Metabolites in Plasma

Metabolites ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 514
Author(s):  
Tom van der Laan ◽  
Isabelle Boom ◽  
Joshua Maliepaard ◽  
Anne-Charlotte Dubbelman ◽  
Amy C. Harms ◽  
...  
Keyword(s):  
Mass Spectra ◽  
Mass Range ◽  
Correct Identification ◽  
Hydrophilic Interaction ◽  
Specific Mass ◽  
Structural Isomers ◽  
Data Independent Acquisition ◽  
Targeted Analysis ◽  
Theoretical Mass ◽  
Accurate Quantification

A popular fragmentation technique for non-targeted analysis is called data-independent acquisition (DIA), because it provides fragmentation data for all analytes in a specific mass range. In this work, we demonstrated the strengths and weaknesses of DIA. Two types of chromatography (fractionation/3 min and hydrophilic interaction liquid chromatography (HILIC)/18 min) and three DIA protocols (variable sequential window acquisition of all theoretical mass spectra (SWATH), fixed SWATH and MSALL) were used to evaluate the performance of DIA. Our results show that fast chromatography and MSALL often results in product ion overlap and complex MS/MS spectra, which reduces the quantitative and qualitative power of these DIA protocols. The combination of SWATH and HILIC allowed for the correct identification of 20 metabolites using the NIST library. After SWATH window customization (i.e., variable SWATH), we were able to quantify ten structural isomers with a mean accuracy of 103% (91–113%). The robustness of the variable SWATH and HILIC method was demonstrated by the accurate quantification of these structural isomers in 10 highly diverse blood samples. Since the combination of variable SWATH and HILIC results in good quantitative and qualitative fragmentation data, it is promising for both targeted and untargeted platforms. This should decrease the number of platforms needed in metabolomics and increase the value of a single analysis.

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 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 A European proposal for quality control and quality assurance of tandem mass spectral libraries

2020 ◽  
Vol 32 (1) ◽  
Author(s):  
Herbert Oberacher ◽  
Michael Sasse ◽  
Jean-Philippe Antignac ◽  
Yann Guitton ◽  
Laurent Debrauwer ◽  
...  
Keyword(s):  
Quality Control ◽  
Quality Assurance ◽  
Tandem Mass ◽  
Mass Spectral ◽  
Spectral Libraries ◽  
Mass Spectral Libraries

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 Narrow Precursor Mass Range for DIA-MS Enhances Protein Identification and Quantification

2021 ◽  
Author(s):  
Huoming Zhang ◽  
Dalila Bensaddek
Keyword(s):  
Mass Spectrometry ◽  
Total Protein ◽  
Quantitative Proteomics ◽  
Protein Identification ◽  
Mass Range ◽  
Systematic Evaluation ◽  
Data Independent Acquisition ◽  
Subsequent Application ◽  
Accurate Quantification ◽  
Identification And Quantification

Data independent acquisition - mass spectrometry (DIA-MS) is becoming widely utilised for robust and accurate quantification of samples in quantitative proteomics. Here, we describe the systematic evaluation of the effects of DIA precursor mass range on total protein identification and quantification. We show that a narrow mass range of precursors (~250 m/z) for DIA-MS enables a higher number of protein identifications. Subsequent application of DIA with narrow precursor range (from 400 to 650 m/z) on Arabidopsis sample with spike-in of known proteins identified 34.7% more proteins than in conventional DIA (cDIA) with a wide precursor range of 400-1200 m/z. When combining several DIA-MS analyses with narrow precursor ranges (i.e., 400-650, 650-900 and 900-1200 m/z), we were able to quantify 10,099 protein groups with a median coefficient of variation of <6%. These findings represent a 59.4% increase in the number of proteins quantified than with cDIA analysis. This is particularly important for low abundance proteins, as exemplified by the 6-protein mix spike-in. In cDIA only 5 out of the 6-protein mix were quantified while our approach allowed accurate quantitation of all six proteins.

scholarly journals Streamlined single-cell proteomics by an integrated microfluidic chip and data-independent acquisition mass spectrometry

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Sofani Tafesse Gebreyesus ◽  
Asad Ali Siyal ◽  
Reta Birhanu Kitata ◽  
Eric Sheng-Wen Chen ◽  
Bayarmaa Enkhbayar ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Single Cell ◽  
Mammalian Cells ◽  
Missing Values ◽  
Dynamic Range ◽  
Analytical Sensitivity ◽  
Microfluidic Chips ◽  
Mass Spectral ◽  
Data Independent Acquisition ◽  
Spectral Libraries

AbstractSingle-cell proteomics can reveal cellular phenotypic heterogeneity and cell-specific functional networks underlying biological processes. Here, we present a streamlined workflow combining microfluidic chips for all-in-one proteomic sample preparation and data-independent acquisition (DIA) mass spectrometry (MS) for proteomic analysis down to the single-cell level. The proteomics chips enable multiplexed and automated cell isolation/counting/imaging and sample processing in a single device. Combining chip-based sample handling with DIA-MS using project-specific mass spectral libraries, we profile on average ~1,500 protein groups across 20 single mammalian cells. Applying the chip-DIA workflow to profile the proteomes of adherent and non-adherent malignant cells, we cover a dynamic range of 5 orders of magnitude with good reproducibility and <16% missing values between runs. Taken together, the chip-DIA workflow offers all-in-one cell characterization, analytical sensitivity and robustness, and the option to add additional functionalities in the future, thus providing a basis for advanced single-cell proteomics applications.

scholarly journals Narrow Precursor Mass Range for DIA–MS Enhances Protein Identification and Quantification in Arabidopsis

Life ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 982
Author(s):  
Huoming Zhang ◽  
Dalila Bensaddek
Keyword(s):  
Mass Spectrometry ◽  
Total Protein ◽  
Quantitative Proteomics ◽  
Protein Identification ◽  
Mass Range ◽  
Systematic Evaluation ◽  
Data Independent Acquisition ◽  
Subsequent Application ◽  
Accurate Quantification ◽  
Identification And Quantification

Data independent acquisition–mass spectrometry (DIA–MS) is becoming widely utilised for robust and accurate quantification of samples in quantitative proteomics. Here, we describe the systematic evaluation of the effects of DIA precursor mass range on total protein identification and quantification. We show that a narrow mass range of precursors (~250 m/z) for DIA–MS enables a higher number of protein identifications. Subsequent application of DIA with narrow precursor range (from 400 to 650 m/z) on an Arabidopsis sample with spike-in known proteins identified 34.7% more proteins than in conventional DIA (cDIA) with a wide precursor range of 400–1200 m/z. When combining several DIA–MS analyses with narrow precursor ranges (i.e., 400–650, 650–900 and 900–1200 m/z), we were able to quantify 10,099 protein groups with a median coefficient of variation of <6%. These findings represent a 54.7% increase in the number of proteins quantified than with cDIA analysis. This is particularly important for low abundance proteins, as exemplified by the six-protein mix spike-in. In cDIA only five out of the six-protein mix were quantified while our approach allowed accurate quantitation of all six proteins.

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.

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