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.

Label-free LC-MS/MS quantitative proteomics for large-scale biomarker discovery in complex samples

2007 ◽  
Vol 30 (14) ◽  
pp. 2198-2203 ◽  
Author(s):  
Yishai Levin ◽  
Emanuel Schwarz ◽  
Lan Wang ◽  
F. Markus Leweke ◽  
Sabine Bahn
Keyword(s):  
Quantitative Proteomics ◽  
Large Scale ◽  
Biomarker Discovery ◽  
Label Free ◽  
Complex Samples

Development of Algorithms for Mass Spectrometry-based Label-free Quantitative Proteomics*

2011 ◽  
Vol 38 (6) ◽  
pp. 506-518 ◽  
Author(s):  
Wei ZHANG ◽  
Ji-Yang ZHANG ◽  
Hui LIU ◽  
Han-Chang SUN ◽  
Chang-Ming XU ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Label Free

scholarly journals Label-Free Mass Spectrometry-Based Quantification of Linker Histone H1 Variants in Clinical Samples

2020 ◽  
Vol 21 (19) ◽  
pp. 7330
Author(s):  
Roberta Noberini ◽  
Cristina Morales Torres ◽  
Evelyn Oliva Savoia ◽  
Stefania Brandini ◽  
Maria Giovanna Jodice ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Histone H1 ◽  
Histone Variants ◽  
Linker Histone ◽  
Clinical Samples ◽  
Label Free ◽  
Complex Samples ◽  
Linker Histone H1 ◽  
Ideal Tool ◽  
Free Quantification

Epigenetic aberrations have been recognized as important contributors to cancer onset and development, and increasing evidence suggests that linker histone H1 variants may serve as biomarkers useful for patient stratification, as well as play an important role as drivers in cancer. Although traditionally histone H1 levels have been studied using antibody-based methods and RNA expression, these approaches suffer from limitations. Mass spectrometry (MS)-based proteomics represents the ideal tool to accurately quantify relative changes in protein abundance within complex samples. In this study, we used a label-free quantification approach to simultaneously analyze all somatic histone H1 variants in clinical samples and verified its applicability to laser micro-dissected tissue areas containing as low as 1000 cells. We then applied it to breast cancer patient samples, identifying differences in linker histone variants patters in primary triple-negative breast tumors with and without relapse after chemotherapy. This study highlights how label-free quantitation by MS is a valuable option to accurately quantitate histone H1 levels in different types of clinical samples, including very low-abundance patient tissues.

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 Affinity Capture Enrichment versus Affinity Depletion: A Comparison of Strategies for Increasing Coverage of Low-Abundant Human Plasma Proteins

2020 ◽  
Vol 21 (16) ◽  
pp. 5903
Author(s):  
Nicolai Bjødstrup Palstrøm ◽  
Lars Melholt Rasmussen ◽  
Hans Christian Beck
Keyword(s):  
Mass Spectrometry ◽  
Small Molecule ◽  
Plasma Proteins ◽  
Biomarker Discovery ◽  
Plasma Samples ◽  
Label Free ◽  
Affinity Capture ◽  
Liquid Chromatography Tandem Mass ◽  
Removal System ◽  
Equalization Method

In the present study, we evaluated four small molecule affinity-based probes based on agarose-immobilized benzamidine (ABA), O-Phospho-L-Tyrosine (pTYR), 8-Amino-hexyl-cAMP (cAMP), or 8-Amino-hexyl-ATP (ATP) for their ability to remove high-abundant proteins such as serum albumin from plasma samples thereby enabling the detection of medium-to-low abundant proteins in plasma samples by mass spectrometry-based proteomics. We compared their performance with the most commonly used immunodepletion method, the Multi Affinity Removal System Human 14 (MARS14) targeting the top 14 most abundant plasma proteins and also the ProteoMiner protein equalization method by label-free quantitative liquid chromatography tandem mass spectrometry (LC-MSMS) analysis. The affinity-based probes demonstrated a high reproducibility for low-abundant plasma proteins, down to picomol per mL levels, compared to the Multi Affinity Removal System (MARS) 14 and the Proteominer methods, and also demonstrated superior removal of the majority of the high-abundant plasma proteins. The ABA-based affinity probe and the Proteominer protein equalization method performed better compared to all other methods in terms of the number of analyzed proteins. All the tested methods were highly reproducible for both high-abundant plasma proteins and low-abundant proteins as measured by correlation analyses of six replicate experiments. In conclusion, our results demonstrated that small-molecule based affinity-based probes are excellent alternatives to the commonly used immune-depletion methods for proteomic biomarker discovery studies in plasma. Data are available via ProteomeXchange with identifier PXD020727.

scholarly journals Proteomics and Mass Spectrometry for Cancer Biomarker Discovery

2007 ◽  
Vol 2 ◽  
pp. 117727190700200 ◽  
Author(s):  
Ming Lu ◽  
Kym F. Faull ◽  
Julian P. Whitelegge ◽  
Jianbo He ◽  
Dejun Shen ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Cancer Research ◽  
Disease Management ◽  
Early Detection Of Cancer ◽  
Biomarker Discovery ◽  
Protein Biomarkers ◽  
Bioinformatic Tools ◽  
Translational Cancer Research ◽  
Basic Concepts ◽  
Detection And Diagnosis

Proteomics is a rapidly advancing field not only in the field of biology but also in translational cancer research. In recent years, mass spectrometry and associated technologies have been explored to identify proteins or a set of proteins specific to a given disease, for the purpose of disease detection and diagnosis. Such biomarkers are being investigated in samples including cells, tissues, serum/plasma, and other types of body fluids. When sufficiently refined, proteomic technologies may pave the way for early detection of cancer or individualized therapy for cancer. Mass spectrometry approaches coupled with bioinformatic tools are being developed for biomarker discovery and validation. Understanding basic concepts and application of such technology by investigators in the field may accelerate the clinical application of protein biomarkers in disease management.

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