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 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 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 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 IsoSearch: An Untargeted and Unbiased Metabolite and Lipid Isotopomer Tracing Strategy from HR-LC-MS/MS Datasets

2020 ◽  
Vol 3 (3) ◽  
pp. 54
Author(s):  
He Huang ◽  
Min Yuan ◽  
Phillip Seitzer ◽  
Susan Ludwigsen ◽  
John M. Asara
Keyword(s):  
Mass Spectrometry ◽  
High Resolution ◽  
Defense Mechanism ◽  
High Resolution Mass Spectrometry ◽  
Pentose Phosphate ◽  
Selected Reaction Monitoring ◽  
Reaction Monitoring ◽  
Triglyceride Accumulation ◽  
Pathway Inhibition ◽  
Mcf 7

Stable isotopic tracer analysis is a technique used to determine carbon or nitrogen atom incorporation into biological systems. A number of mass spectrometry based approaches have been developed for this purpose, including high-resolution tandem mass spectrometry (HR-LC-MS/MS), selected reaction monitoring (SRM) and parallel reaction monitoring (PRM). We have developed an approach for analyzing untargeted metabolomic and lipidomic datasets using high-resolution mass spectrometry with polarity switching and implemented our approach in the open-source R script IsoSearch and in Scaffold Elements software. Using our strategy, which requires an unlabeled reference dataset and isotope labeled datasets across various biological conditions, we traced metabolic isotopomer alterations in breast cancer cells (MCF-7) treated with the metabolic drugs 2-deoxy-glucose, 6-aminonicotinamide, compound 968, and rapamycin. Metabolites and lipids were first identified by the commercial software Scaffold Elements and LipidSearch, then IsoSearch successfully profiled the 13C-isotopomers extracted metabolites and lipids from 13C-glucose labeled MCF-7 cells. The results interpreted known models, such as glycolysis and pentose phosphate pathway inhibition, but also helped to discover new metabolic/lipid flux patterns, including a reactive oxygen species (ROS) defense mechanism induced by 6AN and triglyceride accumulation in rapamycin treated cells. The results suggest the IsoSearch/Scaffold Elements platform is effective for studying metabolic tracer analysis in diseases, drug metabolism, and metabolic engineering for both polar metabolites and non-polar lipids.

Label-Free Quantification by Data Independent Acquisition Mass Spectrometry to Map Cardiovascular Proteomes

2016 ◽  
pp. 227-245
Author(s):  
Sarah J. Parker ◽  
Ronald J. Holewinski ◽  
Irina Tchernyshyov ◽  
Vidya Venkatraman ◽  
Laurie Parker ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Label Free ◽  
Label Free Quantification ◽  
Data Independent Acquisition ◽  
Free Quantification

scholarly journals A general strategy for studying multisite protein phosphorylation using label-free selected reaction monitoring mass spectrometry

2011 ◽  
Vol 418 (2) ◽  
pp. 267-275 ◽  
Author(s):  
Christie L. Eissler ◽  
Steven C. Bremmer ◽  
Juan S. Martinez ◽  
Laurie L. Parker ◽  
Harry Charbonneau ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Phosphorylation ◽  
Selected Reaction Monitoring ◽  
General Strategy ◽  
Reaction Monitoring ◽  
Label Free

scholarly journals Assay Development and Screening of Human DGAT1 Inhibitors with an LC/MS-Based Assay

2010 ◽  
Vol 15 (6) ◽  
pp. 695-702 ◽  
Author(s):  
Ji-Hu Zhang ◽  
Thomas P. Roddy ◽  
Pei-I Ho ◽  
Christopher R. Horvath ◽  
Chad Vickers ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Throughput ◽  
High Throughput Screening ◽  
Screening Method ◽  
Biological Response ◽  
Fluorescent Labeling ◽  
Assay Development ◽  
Label Free ◽  
Chemical Library ◽  
Label Free Detection

Many attractive targets for therapeutic intervention are enzymes that catalyze biological reactions involving small molecules such as lipids, fatty acids, amino acid derivatives, nucleic acid derivatives, and cofactors. Some of the reactions are difficult to detect by methods commonly used in high-throughput screening (HTS) without specific radioactive or fluorescent labeling of substrates. In addition, there are instances when labeling has a detrimental effect on the biological response. Generally, applicable assay methodologies for detection of such reactions are thus required. Mass spectrometry (MS), being a label-free detection tool, has been actively pursued for assay detection in HTS in the past several years. The authors have explored the use of multiparallel liquid chromatography coupled with tandem mass spectrometry (LC/MS/MS) for high-throughput detection of biochemical reactions. In this report, we describe in detail the assay development and screening with a LC/MS-based system for inhibitors of human diacylglycerol acyltransferase (DGAT1) with a chemical library of approximately 800,000 compounds. Several strategies and process improvements have been investigated to overcome technical challenges such as data variation and throughput. Results indicated that, through these innovative approaches, the LC/MS-based screening method is both feasible and suitable for high-throughput primary screening.

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