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

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.

scholarly journals Label-free, normalized quantification of complex mass spectrometry data for proteomic analysis

2010 ◽  
Vol 28 (1) ◽  
pp. 83-89 ◽  
Author(s):  
Noelle M Griffin ◽  
Jingyi Yu ◽  
Fred Long ◽  
Phil Oh ◽  
Sabrina Shore ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Proteomic Analysis ◽  
Mass Spectrometry Data ◽  
Label Free ◽  
Complex Mass

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 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 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).

Sign in / Sign up

Export Citation Format

Share Document