scholarly journals Matrix-matched calibration curves for assessing analytical figures of merit in quantitative proteomics

2019 ◽  
Author(s):  
Lindsay K Pino ◽  
Han-Yin Yang ◽  
William Stafford Noble ◽  
Brian C Searle ◽  
Andrew N Hoofnagle ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Sample Preparation ◽  
Quantitative Proteomics ◽  
Protein Abundance ◽  
Complex Samples ◽  
Figures Of Merit ◽  
Data Independent Acquisition ◽  
Proteomics Experiment ◽  
Series Of Experiments ◽  
Analytical Figures Of Merit

AbstractMass spectrometry is a powerful tool for quantifying protein abundance in complex samples. Advances in sample preparation and the development of data independent acquisition (DIA) mass spectrometry approaches have increased the number of peptides and proteins measured per sample. Here we present a series of experiments demonstrating how to assess whether a peptide measurement is quantitative by mass spectrometry. Our results demonstrate that increasing the number of detected peptides in a proteomics experiment does not necessarily result in increased numbers of peptides that can be measured quantitatively.

scholarly journals Comparison of TIMS-PASEF quantitative proteomics data-analysis workflows using FragPipe, DIA-NN, and Spectronaut from a user's perspective

2021 ◽  
Author(s):  
Alejandro Fernandez-Vega ◽  
Federica Farabegoli ◽  
Maria Mercedes Alonso-Martinez ◽  
Ignacio Ortea
Keyword(s):  
Data Analysis ◽  
Quantitative Proteomics ◽  
Real Life ◽  
Analysis Tool ◽  
Proteomics Data ◽  
Mass Spectrometers ◽  
Data Independent Acquisition ◽  
Proteomics Experiment ◽  
Under Sampling ◽  
The One

Data-independent acquisition (DIA) methods have gained great popularity in bottom-up quantitative proteomics, as they overcome the irreproducibility and under-sampling limitations of data-dependent acquisition (DDA). diaPASEF, recently developed for the timsTOF Pro mass spectrometers, has brought improvements to DIA, providing additional ion separation (in the ion mobility dimension) and increasing sensitivity. Several studies have benchmarked different workflows for DIA quantitative proteomics, but mostly using instruments from Sciex and Thermo, and therefore, the results are not extrapolable to diaPASEF data. In this work, using a real-life sample set like the one that can be found in any proteomics experiment, we compared the results of analyzing PASEF data with different combinations of library-based and library-free analysis, combining the tools of the FragPipe suite, DIA-NN and including MS1-level LFQ with DDA-PASEF data, and also comparing with the workflows possible in Spectronaut. We verified that library-independent workflows, not so efficient not so long ago, have greatly improved in the recent versions of the software tools, and now perform as well or even better than library-based ones. We report here information so that the user who is going to conduct a relative quantitative proteomics study using a timsTOF Pro mass spectrometer can make an informed decision on how to acquire (diaPASEF for DIA analysis, or DDA-PASEF for MS1-level LFQ) the samples, and what can be expected depending on the data analysis tool used, among the different alternatives offered by the recently optimized tools for TIMS-PASEF data 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 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 Data-independent acquisition mass spectrometry enables reproducible characterization of microbiota function

2018 ◽  
Author(s):  
Juhani Aakko ◽  
Sami Pietilä ◽  
Tomi Suomi ◽  
Mehrad Mahmoudian ◽  
Raine Toivonen ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Dynamic Range ◽  
Functional Characterization ◽  
Research Area ◽  
Microbial Composition ◽  
Complex Samples ◽  
Data Independent Acquisition ◽  
Novel Approach ◽  
Open Source Software Package

AbstractMetaproteomics is an emerging research area which aims to reveal the functionality of microbial communities – unlike the increasingly popular metagenomics providing insights only on the functional potential. So far, the common approach in metaproteomics has been data-dependent acquisition mass spectrometry (DDA). However, DDA is known to have limited reproducibility and dynamic range with samples of complex microbial composition. To overcome these limitations, we introduce here a novel approach utilizing data-independent acquisition (DIA) mass spectrometry, which has not been applied in metaproteomics of complex samples before. For robust analysis of the data, we introduce an open-source software package diatools, which is freely available at Docker Hub and runs on various operating systems. Our highly reproducible results on laboratory-assembled microbial mixtures and human fecal samples support the utility of our approach for functional characterization of complex microbiota. Hence, the approach is expected to dramatically improve our understanding on the role of microbiota in health and disease.

84 Quantifying pharmacodynamic biomarker changes in immuno-oncology by mass spectrometry

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A92-A93
Author(s):  
Joseph Eckenrode ◽  
Omar Laterza ◽  
Michael Lassman
Keyword(s):  
Mass Spectrometry ◽  
Cell Membrane ◽  
Membrane Protein ◽  
Sample Preparation ◽  
Whole Blood ◽  
Quantitative Proteomics ◽  
Tryptic Digestion ◽  
Signal To Noise ◽  
Pharmacodynamic Biomarkers ◽  
T Cell Membrane

BackgroundQuantifying pharmacodynamic biomarker changes enables decision making and clinical trials in drug development. Pharmacodynamic biomarkers are used to determine the effects of treatment on disease. Mass spectrometry offers a quantitative, selective, and multiplex platform for pharmacodynamic protein biomarker analysis in clinical samples (e.g. blood and tumor) that is feasible across multiple sample conditions (e.g. fresh, frozen and formalin-fixed paraffin-embedded (FFPE)). To date, however, methodologies for targeted protein analysis by mass spectrometry (i.e. quantitative proteomics) are underdeveloped for application in immuno-oncology.MethodsTo address this, we sought to extract the immuno-oncology-associated T cell membrane proteins CD3, CD4 and CD8 from peripheral blood mononucleate cells (PBMC) and develop a multiplexed mass spectrometry method to quantify their expression. PBMC were isolated from whole blood and using detergent-based lysis buffers fractionated into a cytosolic and membrane protein lysate (figure 1). Analytical methods were then developed to detect proteotypic peptides of all three proteins (table 1 and figure 6) from the lysates by mass spectrometry.ResultsCD3, CD4 and CD8 were detected in the membrane protein fraction but not in the cytosolic protein fraction after whole-proteome tryptic digestion using a filter-aided sample preparation (or FASP) technique but with a signal-to-noise ratio of ≤ 2.0 (figure 2). Applying an additional immunoaffinity (IA) enrichment step with antibody-conjugated magnetic beads, prior to digestion, dramatically improved the analyte signal-to-noise ratios to > 100 (figure 3). Reverse-phase nanoflow liquid chromatography (LC) was used to separate all three analytes in multiplex over a 12-minute run prior to tandem mass analysis (MS/MS) (figure 4). Together, this IA-LC-MS/MS method resulted in detection of endogenous CD3, CD4 and CD8 proteins from small volumes of whole blood (< 0.1 mL) and the analyte responses were linear over at least two orders of magnitude (figure 5).Abstract 84 Figure 1Detergent-based protein extraction and fractionation of PBMCAbstract 84 Table 1Surrogate peptides for selective protein analysis by MS/MS after tryptic digestionAbstract 84 Figure 2Filter-aided sample preparation (FASP) for whole-proteome analysisAbstract 84 Figure 3Immunoaffinity enrichment of proteins from PBMC lysatesAbstract 84 Figure 4Representative multiplex analysis from 1mL of whole bloodAbstract 84 Figure 5Multiplex analysis of endogenous CD3, CD4, and CD8Abstract 84 Figure 6Optimization of tryptic digestion conditionsConclusionsThis method was developed specifically to quantitate pharmacodynamic changes in CD4 and CD8 T cell membrane expressions from clinically feasible samples (i.e. PBMC). This work, however, provides a foundation for developing methodologies to conduct quantitative proteomics applicable to immuno-oncology, which may be used to interrogate additional pharmacodynamic biomarkers.

scholarly journals Time-resolved in vivo ubiquitinome profiling by DIA-MS reveals USP7 targets on a proteome-wide scale

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Martin Steger ◽  
Vadim Demichev ◽  
Mattias Backman ◽  
Uli Ohmayer ◽  
Phillip Ihmor ◽  
...  
Keyword(s):  
Neural Network ◽  
Mass Spectrometry ◽  
Sample Preparation ◽  
Mode Of Action ◽  
System Level ◽  
High Temporal Resolution ◽  
Time Resolved ◽  
Data Independent Acquisition ◽  
Wide Scale

AbstractMass spectrometry (MS)-based ubiquitinomics provides system-level understanding of ubiquitin signaling. Here we present a scalable workflow for deep and precise in vivo ubiquitinome profiling, coupling an improved sample preparation protocol with data-independent acquisition (DIA)-MS and neural network-based data processing specifically optimized for ubiquitinomics. Compared to data-dependent acquisition (DDA), our method more than triples identification numbers to 70,000 ubiquitinated peptides in single MS runs, while significantly improving robustness and quantification precision. Upon inhibition of the oncology target USP7, we simultaneously record ubiquitination and consequent changes in abundance of more than 8,000 proteins at high temporal resolution. While ubiquitination of hundreds of proteins increases within minutes of USP7 inhibition, we find that only a small fraction of those are ever degraded, thereby dissecting the scope of USP7 action. Our method enables rapid mode-of-action profiling of candidate drugs targeting DUBs or ubiquitin ligases at high precision and throughput.

scholarly journals Current Status and Advances in Quantitative Proteomic Mass Spectrometry

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Valerie C. Wasinger ◽  
Ming Zeng ◽  
Yunki Yau
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Biomarker Discovery ◽  
Current Status ◽  
Label Free ◽  
Stable Isotope Labelling ◽  
Complex Samples ◽  
Bioinformatic Tools ◽  
Critical Overview ◽  
Proteins And Peptides

The accurate quantitation of proteins and peptides in complex biological systems is one of the most challenging areas of proteomics. Mass spectrometry-based approaches have forged significant in-roads allowing accurate and sensitive quantitation and the ability to multiplex vastly complex samples through the application of robust bioinformatic tools. These relative and absolute quantitative measures using label-free, tags, or stable isotope labelling have their own strengths and limitations. The continuous development of these methods is vital for increasing reproducibility in the rapidly expanding application of quantitative proteomics in biomarker discovery and validation. This paper provides a critical overview of the primary mass spectrometry-based quantitative approaches and the current status of quantitative proteomics in biomedical research.

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