scholarly journals Selection of Features with Consistent Profiles Improves Relative Protein Quantification in Mass Spectrometry Experiments

2020 ◽  
Vol 19 (6) ◽  
pp. 944-959 ◽  
Author(s):  
Tsung-Heng Tsai ◽  
Meena Choi ◽  
Balazs Banfai ◽  
Yansheng Liu ◽  
Brendan X. MacLean ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Profile ◽  
Protein Quantification ◽  
Selected Reaction Monitoring ◽  
Estimation Accuracy ◽  
Spectral Features ◽  
Data Set ◽  
Post Translational Modifications ◽  
Data Independent Acquisition ◽  
Manual Curation

In bottom-up mass spectrometry-based proteomics, relative protein quantification is often achieved with data-dependent acquisition (DDA), data-independent acquisition (DIA), or selected reaction monitoring (SRM). These workflows quantify proteins by summarizing the abundances of all the spectral features of the protein (e.g. precursor ions, transitions or fragments) in a single value per protein per run. When abundances of some features are inconsistent with the overall protein profile (for technological reasons such as interferences, or for biological reasons such as post-translational modifications), the protein-level summaries and the downstream conclusions are undermined. We propose a statistical approach that automatically detects spectral features with such inconsistent patterns. The detected features can be separately investigated, and if necessary, removed from the data set. We evaluated the proposed approach on a series of benchmark-controlled mixtures and biological investigations with DDA, DIA and SRM data acquisitions. The results demonstrated that it could facilitate and complement manual curation of the data. Moreover, it can improve the estimation accuracy, sensitivity and specificity of detecting differentially abundant proteins, and reproducibility of conclusions across different data processing tools. The approach is implemented as an option in the open-source R-based software MSstats.

scholarly journals Emerging mass spectrometry-based proteomics methodologies for novel biomedical applications

2020 ◽  
Vol 48 (5) ◽  
pp. 1953-1966
Author(s):  
Lindsay K. Pino ◽  
Jacob Rose ◽  
Amy O'Broin ◽  
Samah Shah ◽  
Birgit Schilling
Keyword(s):  
Mass Spectrometry ◽  
Human Health ◽  
Protein Complexes ◽  
Protein Quantification ◽  
Intact Protein ◽  
Protein Signaling ◽  
Post Translational Modifications ◽  
Protein Protein Interaction ◽  
Health And Disease ◽  
Proteomics Research

Research into the basic biology of human health and disease, as well as translational human research and clinical applications, all benefit from the growing accessibility and versatility of mass spectrometry (MS)-based proteomics. Although once limited in throughput and sensitivity, proteomic studies have quickly grown in scope and scale over the last decade due to significant advances in instrumentation, computational approaches, and bio-sample preparation. Here, we review these latest developments in MS and highlight how these techniques are used to study the mechanisms, diagnosis, and treatment of human diseases. We first describe recent groundbreaking technological advancements for MS-based proteomics, including novel data acquisition techniques and protein quantification approaches. Next, we describe innovations that enable the unprecedented depth of coverage in protein signaling and spatiotemporal protein distributions, including studies of post-translational modifications, protein turnover, and single-cell proteomics. Finally, we explore new workflows to investigate protein complexes and structures, and we present new approaches for protein–protein interaction studies and intact protein or top-down MS. While these approaches are only recently incipient, we anticipate that their use in biomedical MS proteomics research will offer actionable discoveries for the improvement of human health.

scholarly journals OPTIMIZING RADIOMETRIC PROCESSING AND FEATURE EXTRACTION OF DRONE BASED HYPERSPECTRAL FRAME FORMAT IMAGERY FOR ESTIMATION OF YIELD QUANTITY AND QUALITY OF A GRASS SWARD

2018 ◽  
Vol XLII-3 ◽  
pp. 1305-1310 ◽  
Author(s):  
R. Näsi ◽  
N. Viljanen ◽  
R. Oliveira ◽  
J. Kaivosoja ◽  
O. Niemeläinen ◽  
...  
Keyword(s):  
Feature Extraction ◽  
3D Structure ◽  
Point Clouds ◽  
Estimation Accuracy ◽  
Spectral Features ◽  
Data Set ◽  
Area Of Interest ◽  
Evaluation Task ◽  
Corrected Data ◽  
Grass Sward

Light-weight 2D format hyperspectral imagers operable from unmanned aerial vehicles (UAV) have become common in various remote sensing tasks in recent years. Using these technologies, the area of interest is covered by multiple overlapping hypercubes, in other words multiview hyperspectral photogrammetric imagery, and each object point appears in many, even tens of individual hypercubes. The common practice is to calculate hyperspectral orthomosaics utilizing only the most nadir areas of the images. However, the redundancy of the data gives potential for much more versatile and thorough feature extraction. We investigated various options of extracting spectral features in the grass sward quantity evaluation task. In addition to the various sets of spectral features, we used photogrammetry-based ultra-high density point clouds to extract features describing the canopy 3D structure. Machine learning technique based on the Random Forest algorithm was used to estimate the fresh biomass. Results showed high accuracies for all investigated features sets. The estimation results using multiview data provided approximately 10 % better results than the most nadir orthophotos. The utilization of the photogrammetric 3D features improved estimation accuracy by approximately 40 % compared to approaches where only spectral features were applied. The best estimation RMSE of 239 kg/ha (6.0 %) was obtained with multiview anisotropy corrected data set and the 3D features.

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 Optimization of Data-Independent Acquisition Mass Spectrometry for Deep and Highly Sensitive Proteomic Analysis

2019 ◽  
Vol 20 (23) ◽  
pp. 5932 ◽  
Author(s):  
Yusuke Kawashima ◽  
Eiichiro Watanabe ◽  
Taichi Umeyama ◽  
Daisuke Nakajima ◽  
Masahira Hattori ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Proteomic Analysis ◽  
Protein Quantification ◽  
Single Shot ◽  
Human Embryonic Kidney Cells ◽  
Practical Applications ◽  
Data Independent Acquisition ◽  
Highly Sensitive ◽  
Specific Pathogen ◽  
Sequence Database Search

Data-independent acquisition (DIA)-mass spectrometry (MS)-based proteomic analysis overtop the existing data-dependent acquisition (DDA)-MS-based proteomic analysis to enable deep proteome coverage and precise relative quantitative analysis in single-shot liquid chromatography (LC)-MS/MS. However, DIA-MS-based proteomic analysis has not yet been optimized in terms of system robustness and throughput, particularly for its practical applications. We established a single-shot LC-MS/MS system with an MS measurement time of 90 min for a highly sensitive and deep proteomic analysis by optimizing the conditions of DIA and nanoLC. We identified 7020 and 4068 proteins from 200 ng and 10 ng, respectively, of tryptic floating human embryonic kidney cells 293 (HEK293F) cell digest by performing the constructed LC-MS method with a protein sequence database search. The numbers of identified proteins from 200 ng and 10 ng of tryptic HEK293F increased to 8509 and 5706, respectively, by searching the chromatogram library created by gas-phase fractionated DIA. Moreover, DIA protein quantification was highly reproducible, with median coefficients of variation of 4.3% in eight replicate analyses. We could demonstrate the power of this system by applying the proteomic analysis to detect subtle changes in protein profiles between cerebrums in germ-free and specific pathogen-free mice, which successfully showed that >40 proteins were differentially produced between the cerebrums in the presence or absence of bacteria.

scholarly journals Label-Free Quantitation and Mapping of the ErbB2 Tumor Receptor by Multiple Protease Digestion with Data-Dependent (MS1) and Data-Independent (MS2) Acquisitions

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Jason M. Held ◽  
Birgit Schilling ◽  
Alexandria K. D'Souza ◽  
Tara Srinivasan ◽  
Jessica B. Behring ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Resolution ◽  
Posttranslational Modifications ◽  
Development Time ◽  
Assay Development ◽  
Selected Reaction Monitoring ◽  
Label Free ◽  
Data Independent Acquisition ◽  
Key Indicator ◽  
Biomarker Quantitation

The receptor tyrosine kinase ErbB2 is a breast cancer biomarker whose posttranslational modifications (PTMs) are a key indicator of its activation. Quantifying the expression and PTMs of biomarkers such as ErbB2 by selected reaction monitoring (SRM) mass spectrometry has several limitations, including minimal coverage and extensive assay development time. Therefore, we assessed the utility of two high resolution, full scan mass spectrometry approaches, MS1 Filtering and SWATH MS2, for targeted ErbB2 proteomics. Endogenous ErbB2 immunoprecipitated from SK-BR-3 cells was in-gel digested with trypsin, chymotrypsin, Asp-N, or trypsin plus Asp-N in triplicate. Data-dependent acquisition with an AB SCIEX TripleTOF 5600 and MS1 Filtering data processing was used to assess peptide and PTM coverage as well as the reproducibility of enzyme digestion. Data-independent acquisition (SWATH) was also performed for MS2 quantitation. MS1 Filtering and SWATH MS2 allow quantitation of all detected analytes after acquisition, enabling the use of multiple proteases for quantitative assessment of target proteins. Combining high resolution proteomics with multiprotease digestion enabled quantitative mapping of ErbB2 with excellent reproducibility, improved amino acid sequence and PTM coverage, and decreased assay development time compared to typical SRM assays. These results demonstrate that high resolution quantitative proteomic approaches are an effective tool for targeted biomarker quantitation.

scholarly journals A repository of assays to quantify 10,000 human proteins by SWATH-MS

2014 ◽  
Vol 1 (1) ◽  
Author(s):  
George Rosenberger ◽  
Ching Chiek Koh ◽  
Tiannan Guo ◽  
Hannes L. Röst ◽  
Petri Kouvonen ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
A Priori ◽  
Selected Reaction Monitoring ◽  
Spectrometric Method ◽  
Mass Spectrometric Method ◽  
Data Independent Acquisition ◽  
Targeted Analysis ◽  
Human Proteins ◽  
The One ◽  
Multiple Samples

Abstract Mass spectrometry is the method of choice for deep and reliable exploration of the (human) proteome. Targeted mass spectrometry reliably detects and quantifies pre-determined sets of proteins in a complex biological matrix and is used in studies that rely on the quantitatively accurate and reproducible measurement of proteins across multiple samples. It requires the one-time, a priori generation of a specific measurement assay for each targeted protein. SWATH-MS is a mass spectrometric method that combines data-independent acquisition (DIA) and targeted data analysis and vastly extends the throughput of proteins that can be targeted in a sample compared to selected reaction monitoring (SRM). Here we present a compendium of highly specific assays covering more than 10,000 human proteins and enabling their targeted analysis in SWATH-MS datasets acquired from research or clinical specimens. This resource supports the confident detection and quantification of 50.9% of all human proteins annotated by UniProtKB/Swiss-Prot and is therefore expected to find wide application in basic and clinical research. Data are available via ProteomeXchange (PXD000953-954) and SWATHAtlas (SAL00016-35).

scholarly journals Ultra-streamlined single cell proteomics by all-in-one chip and data-independent-acquisition mass spectrometry

2021 ◽  
Author(s):  
Hsiung-Lin Tu ◽  
Sofani Gebreyesus ◽  
Asad Ali Siyal ◽  
Reta Birhanu Kitata ◽  
Eric Sheng-Wen Chen ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Single Cell ◽  
Missing Values ◽  
Protein Quantification ◽  
Single Cell Level ◽  
Cell Level ◽  
Proteome Coverage ◽  
Data Independent Acquisition ◽  
General Utility ◽  
Ultrahigh Sensitivity

Abstract Single cell proteomics provides the ultimate resolution to reveal cellular phenotypic heterogeneity and functional network underlying biological processes. Here, we present an ultra-streamlined workflow combining an integrated proteomic chip (iProChip) and data-independent-acquisition (DIA) mass spectrometry for sensitive microproteomics analysis down to single cell level. The iProChip offers multiplexed and automated all-in-one station from cell isolation/counting/imaging to complete proteomic processing within a single device. By mapping to project-specific spectra libraries, the iProChip-DIA enables profiling of 1160 protein groups from triplicate analysis of a single mammalian cell. Furthermore, the applicability of iProChip-DIA was demonstrated using both adherent and non-adherent malignant cells, which reveals 5 orders of proteome coverage, highly consistent ~100-fold protein quantification (1-100 cells) and high reproducibility with low missing values (<16%). With the demonstrated all-in-one cell characterization, ultrahigh sensitivity, robustness, and versatility to add other functionalities, the iProChip-DIA is anticipated to offer general utility to realize advanced proteomics applications at single cell level.

scholarly journals Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry

2016 ◽  
Author(s):  
Ben C. Collins ◽  
Christie L. Hunter ◽  
Yansheng Liu ◽  
Birgit Schilling ◽  
George Rosenberger ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Life Science ◽  
Science Research ◽  
Protein Quantification ◽  
Hek293 Cells ◽  
Selected Reaction Monitoring ◽  
Laboratory Evaluation ◽  
Targeted Proteomics ◽  
Life Science Research

AbstractQuantitative proteomics employing mass spectrometry has become an indispensable tool in basic and applied life science research. Methods based on data-dependent acquisition have proved extremely valuable for qualitative proteome analysis but historically have struggled to achieve reproducible quantitative data if large sample cohorts are comparatively analyzed. Targeted proteomics, most commonly implemented as selected reaction monitoring, has emerged as a powerful alternative and succeeded in providing a data independent approach for reproducible quantitative proteomics data but is limited in the number of proteins quantified. SWATH-MS is a recently introduced technique consisting of a data-independent acquisition and a targeted data analysis strategy that aims to maintain the favorable quantitative characteristics (accuracy, sensitivity, specificity) achieved in targeted proteomics but on the scale of thousands of proteins. While previous SWATH-MS studies have shown high intra-lab reproducibility, this has not been evaluated on an inter-lab basis. In this multi-laboratory evaluation study using data from 11 sites worldwide, we have demonstrated that using SWATH-MS we can consistently detect and quantify more than 4,000 proteins from HEK293 cells and that the quantitative protein data generated across laboratories is reproducible. Using synthetic peptide dilution series, we have shown that the sensitivity, dynamic range and reproducibility established with SWATH-MS methods are also uniformly achieved across labs. This study demonstrates that SWATH-MS is a reproducible and accurate technique that can be confidently deployed for large-scale protein quantification in life science research.

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