Comparison of Label Free and 18 O Labeling Mass Spectrometry in Relative Protein Quantification

2009 ◽  
Author(s):  
Chao Yuan ◽  
Gaurav S.J.B. Rana ◽  
Jinsook Chang ◽  
Rob M. Ewing ◽  
Mark R. Chance
Keyword(s):  
Mass Spectrometry ◽  
Protein Quantification ◽  
Label Free

Recent Technological Advances in the Mass Spectrometry-based Nanomedicine Studies: An Insight from Nanoproteomics

2019 ◽  
Vol 25 (13) ◽  
pp. 1536-1553 ◽  
Author(s):  
Jing Tang ◽  
Yunxia Wang ◽  
Yi Li ◽  
Yang Zhang ◽  
Runyuan Zhang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Information Sources ◽  
Protein Quantification ◽  
Protein Profiling ◽  
Label Free ◽  
Dynamic Information ◽  
Data Repositories ◽  
Research Directions ◽  
Technological Advances ◽  
Recent Trends

Nanoscience becomes one of the most cutting-edge research directions in recent years since it is gradually matured from basic to applied science. Nanoparticles (NPs) and nanomaterials (NMs) play important roles in various aspects of biomedicine science, and their influences on the environment have caused a whole range of uncertainties which require extensive attention. Due to the quantitative and dynamic information provided for human proteome, mass spectrometry (MS)-based quantitative proteomic technique has been a powerful tool for nanomedicine study. In this article, recent trends of progress and development in the nanomedicine of proteomics were discussed from quantification techniques and publicly available resources or tools. First, a variety of popular protein quantification techniques including labeling and label-free strategies applied to nanomedicine studies are overviewed and systematically discussed. Then, numerous protein profiling tools for data processing and postbiological statistical analysis and publicly available data repositories for providing enrichment MS raw data information sources are also discussed.

Comparative Study of Targeted and Label-free Mass Spectrometry Methods for Protein Quantification

2013 ◽  
Vol 12 (4) ◽  
pp. 2005-2011 ◽  
Author(s):  
Linda IJsselstijn ◽  
Marcel P. Stoop ◽  
Christoph Stingl ◽  
Peter A. E. Sillevis Smitt ◽  
Theo M. Luider ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Comparative Study ◽  
Protein Quantification ◽  
Label Free

scholarly journals Issues and Applications in Label-Free Quantitative Mass Spectrometry

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Xianyin Lai ◽  
Lianshui Wang ◽  
Frank A. Witzmann
Keyword(s):  
Mass Spectrometry ◽  
Protein Quantification ◽  
Area Measurement ◽  
Label Free ◽  
Quantitative Mass Spectrometry ◽  
Differential Protein Expression ◽  
Membrane Proteomics ◽  
Complex Protein ◽  
Tissue Proteomics

To address the challenges associated with differential expression proteomics, label-free mass spectrometric protein quantification methods have been developed as alternatives to array-based, gel-based, and stable isotope tag or label-based approaches. In this paper, we focus on the issues associated with label-free methods that rely on quantitation based on peptide ion peak area measurement. These issues include chromatographic alignment, peptide qualification for quantitation, and normalization. In addressing these issues, we present various approaches, assembled in a recently developed label-free quantitative mass spectrometry platform, that overcome these difficulties and enable comprehensive, accurate, and reproducible protein quantitation in highly complex protein mixtures from experiments with many sample groups. As examples of the utility of this approach, we present a variety of cases where the platform was applied successfully to assess differential protein expression or abundance in body fluids, in vitro nanotoxicology models, tissue proteomics in genetic knock-in mice, and cell membrane proteomics.

scholarly journals LFAQ: towards unbiased label-free absolute protein quantification by predicting peptide quantitative factors

2018 ◽  
Author(s):  
Cheng Chang ◽  
Zhiqiang Gao ◽  
Wantao Ying ◽  
Yan Zhao ◽  
Yan Fu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Physicochemical Properties ◽  
Data Acquisition ◽  
Large Scale ◽  
Protein Quantification ◽  
Label Free ◽  
Crucial Issue ◽  
Accuracy And Precision ◽  
Quantification Accuracy ◽  
Novel Algorithm

AbstractMass spectrometry (MS) has become a prominent choice for large-scale absolute protein quantification, but its quantification accuracy still has substantial room for improvement. A crucial issue is the bias between the peptide MS intensity and the actual peptide abundance, i.e., the fact that peptides with equal abundance may have different MS intensities. This bias is mainly caused by the diverse physicochemical properties of peptides. Here, we propose a novel algorithm for label-free absolute protein quantification, LFAQ, which can correct the biased MS intensities by using the predicted peptide quantitative factors for all identified peptides. When validated on datasets produced by different MS instruments and data acquisition modes, LFAQ presented accuracy and precision superior to those of existing methods. In particular, it reduced the quantification error by an average of 46% for low-abundance proteins.

Quantitative analysis of genetically modified soya using multiple reaction monitoring mass spectrometry with endogenous peptides as internal standards

2018 ◽  
Vol 25 (1) ◽  
pp. 50-57 ◽  
Author(s):  
Shobha Devi ◽  
Yi-Cheng Lin ◽  
Yen-Peng Ho
Keyword(s):  
Mass Spectrometry ◽  
Genetically Modified ◽  
Multiple Reaction Monitoring ◽  
Linear Regression Analysis ◽  
Exchange Chromatography ◽  
Protein Quantification ◽  
Reaction Monitoring ◽  
Label Free ◽  
Internal Standards ◽  
Phosphate Synthase

A simple label-free method was developed for the quantification of the herbicide-resistant gene-related protein 5-enolpyruvylshikimate-3-phosphate synthase using multiple reaction monitoring liquid chromatography–mass spectrometry. Sample pretreatment procedures including ion exchange chromatography and CaCl2 precipitation were used to purify the 5-enolpyruvylshikimate-3-phosphate synthase protein. Quantification of various percentages of genetically modified soya (0.5–100%) was performed by selecting suitable endogenous soybean peptides as internal standards. Results indicated that Gly P (QGDVFVVPR) and Lec P (LQLNK) are useful internal standards for the quantification of low and high percentages of genetically modified soya, respectively. Linear regression analysis of both calibration curves yielded good linearity with R2 of 0.99. This approach is a convenient and accurate quantification method for genetically modified soya at a level as low as 0.5% (less than the current EU threshold for labeling genetically modified soya).

Label-Free Protein Quantification Using LC-Coupled Ion Trap or FT Mass Spectrometry:  Reproducibility, Linearity, and Application with Complex Proteomes

2006 ◽  
Vol 5 (5) ◽  
pp. 1214-1223 ◽  
Author(s):  
Guanghui Wang ◽  
Wells W. Wu ◽  
Weihua Zeng ◽  
Chung-Lin Chou ◽  
Rong-Fong Shen
Keyword(s):  
Mass Spectrometry ◽  
Ion Trap ◽  
Protein Quantification ◽  
Label Free ◽  
Free Protein

scholarly journals Label-free mass spectrometry-based protein quantification technologies in proteomic analysis

2008 ◽  
Vol 7 (5) ◽  
pp. 329-339 ◽  
Author(s):  
M. Wang ◽  
J. You ◽  
K. G. Bemis ◽  
T. J. Tegeler ◽  
D. P. G. Brown
Keyword(s):  
Mass Spectrometry ◽  
Proteomic Analysis ◽  
Protein Quantification ◽  
Label Free

scholarly journals freeQuant: A Mass Spectrometry Label-Free Quantification Software Tool for Complex Proteome Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Ning Deng ◽  
Zhenye Li ◽  
Chao Pan ◽  
Huilong Duan
Keyword(s):  
Mass Spectrometry ◽  
Functional Analysis ◽  
Quantitative Analysis ◽  
Protein Quantification ◽  
Mouse Heart ◽  
Label Free ◽  
Spectral Count ◽  
Label Free Quantification ◽  
Mass Spectrometry Technology ◽  
Free Quantification

Study of complex proteome brings forward higher request for the quantification method using mass spectrometry technology. In this paper, we present a mass spectrometry label-free quantification tool for complex proteomes, called freeQuant, which integrated quantification with functional analysis effectively. freeQuant consists of two well-integrated modules: label-free quantification and functional analysis with biomedical knowledge. freeQuant supports label-free quantitative analysis which makes full use of tandem mass spectrometry (MS/MS) spectral count, protein sequence length, shared peptides, and ion intensity. It adopts spectral count for quantitative analysis and builds a new method for shared peptides to accurately evaluate abundance of isoforms. For proteins with low abundance, MS/MS total ion count coupled with spectral count is included to ensure accurate protein quantification. Furthermore, freeQuant supports the large-scale functional annotations for complex proteomes. Mitochondrial proteomes from the mouse heart, the mouse liver, and the human heart were used to evaluate the usability and performance of freeQuant. The evaluation showed that the quantitative algorithms implemented in freeQuant can improve accuracy of quantification with better dynamic range.

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