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 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.

Mass Spectrometry Techniques: Principles and Practices for Quantitative Proteomics

2020 ◽  
Vol 21 ◽  
Author(s):  
Rocco J. Rotello ◽  
Timothy D. Veenstra
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Protein Identification ◽  
Dynamic Nature ◽  
Complete Coverage ◽  
The Past ◽  
Proteome Level ◽  
A Cell ◽  
Quantitative Changes ◽  
Made In

: In the current omics-age of research, major developments have been made in technologies that attempt to survey the entire repertoire of genes, transcripts, proteins, and metabolites present within a cell. While genomics has led to a dramatic increase in our understanding of such things as disease morphology and how organisms respond to medications, it is critical to obtain information at the proteome level since proteins carry out most of the functions within the cell. The primary tool for obtaining proteome-wide information on proteins within the cell is mass spectrometry (MS). While it has historically been associated with the protein identification, developments over the past couple of decades have made MS a robust technology for protein quantitation as well. Identifying quantitative changes in proteomes is complicated by its dynamic nature and the inability of any technique to guarantee complete coverage of every protein within a proteome sample. Fortunately, the combined development of sample preparation and MS methods have made it capable to quantitatively compare many thousands of proteins obtained from cells and organisms.

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 NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses

2020 ◽  
Vol 48 (14) ◽  
pp. e83-e83 ◽  
Author(s):  
Shisheng Wang ◽  
Wenxue Li ◽  
Liqiang Hu ◽  
Jingqiu Cheng ◽  
Hao Yang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Missing Values ◽  
Protein Complexes ◽  
Label Free ◽  
Missing Value ◽  
Imputation Methods ◽  
Data Independent Acquisition ◽  
Low Performance ◽  
User Friendly

Abstract Mass spectrometry (MS)-based quantitative proteomics experiments frequently generate data with missing values, which may profoundly affect downstream analyses. A wide variety of imputation methods have been established to deal with the missing-value issue. To date, however, there is a scarcity of efficient, systematic, and easy-to-handle tools that are tailored for proteomics community. Herein, we developed a user-friendly and powerful stand-alone software, NAguideR, to enable implementation and evaluation of different missing value methods offered by 23 widely used missing-value imputation algorithms. NAguideR further evaluates data imputation results through classic computational criteria and, unprecedentedly, proteomic empirical criteria, such as quantitative consistency between different charge-states of the same peptide, different peptides belonging to the same proteins, and individual proteins participating protein complexes and functional interactions. We applied NAguideR into three label-free proteomic datasets featuring peptide-level, protein-level, and phosphoproteomic variables respectively, all generated by data independent acquisition mass spectrometry (DIA-MS) with substantial biological replicates. The results indicate that NAguideR is able to discriminate the optimal imputation methods that are facilitating DIA-MS experiments over those sub-optimal and low-performance algorithms. NAguideR further provides downloadable tables and figures supporting flexible data analysis and interpretation. NAguideR is freely available at http://www.omicsolution.org/wukong/NAguideR/ and the source code: https://github.com/wangshisheng/NAguideR/.

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 Sensitive Quantitative Proteomics of Human Hematopoietic Stem and Progenitor Cells by Data-independent Acquisition Mass Spectrometry

2019 ◽  
Vol 18 (7) ◽  
pp. 1454-1467 ◽  
Author(s):  
Sabine Amon ◽  
Fabienne Meier-Abt ◽  
Ludovic C. Gillet ◽  
Slavica Dimitrieva ◽  
Alexandre P. A. Theocharides ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Progenitor Cells ◽  
Quantitative Proteomics ◽  
Hematopoietic Stem ◽  
Data Independent Acquisition ◽  
Stem And Progenitor Cells

scholarly journals Ultrafast and Reproducible Proteomics from Small Amounts of Heart Tissue Enabled by Azo and timsTOF Pro

2021 ◽  
Author(s):  
Timothy J Aballo ◽  
David S Roberts ◽  
Jake A Melby ◽  
Kevin M Buck ◽  
Kyle A Brown ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Large Scale ◽  
Protein Identification ◽  
Heart Tissue ◽  
Tryptic Digestion ◽  
Bottom Up ◽  
Preparation Methods ◽  
Liquid Chromatography Tandem Mass ◽  
And Function ◽  
Identification And Quantification

Global bottom-up mass spectrometry (MS)-based proteomics is widely used for protein identification and quantification to achieve a comprehensive understanding of the composition, structure, and function of the proteome. However, traditional sample preparation methods are time-consuming, typically including overnight tryptic digestion, extensive sample clean-up to remove MS-incompatible surfactants, and offline sample fractionation to reduce proteome complexity prior to online liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. Thus, there is a need for a fast, robust, and reproducible method for protein identification and quantification from complex proteomes. Herein, we developed an ultrafast bottom-up proteomics method enabled by Azo, a photocleavable, MS-compatible surfactant that effectively solubilizes proteins and promotes rapid tryptic digestion, combined with the Bruker timsTOF Pro, which enables deeper proteome coverage through trapped ion mobility spectrometry (TIMS) and parallel accumulation-serial fragmentation (PASEF) of peptides. We applied this method to analyze the complex human cardiac proteome and identified nearly 4,000 protein groups from as little as 1 mg of human heart tissue in a single one-dimensional LC-TIMS-MS/MS run with high reproducibility. Overall, we anticipate this ultrafast, robust, and reproducible bottom-up method empowered by both Azo and the timsTOF Pro will be generally applicable and greatly accelerate the throughput of large-scale quantitative proteomic studies. Raw data are available via the MassIVE repository with identifier MSV000087476.

Shotgun Protein Identification and Quantification by Mass Spectrometry in Neuroproteomics

2009 ◽  
pp. 229-259 ◽  
Author(s):  
Bingwen Lu ◽  
Tao Xu ◽  
Sung Kyu Park ◽  
Daniel B. McClatchy ◽  
Lujian Liao ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Identification ◽  
Identification And Quantification
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