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.

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 In vivo measurement of synthesis rate of multiple plasma proteins in humans

2006 ◽  
Vol 291 (1) ◽  
pp. E190-E197 ◽  
Author(s):  
Abdul Jaleel ◽  
Vandana Nehra ◽  
Xuan-Mai T. Persson ◽  
Yves Boirie ◽  
Maureen Bigelow ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Synthesis ◽  
Stable Isotope ◽  
Plasma Proteins ◽  
Large Scale ◽  
Protein Quantification ◽  
Gas Chromatography Mass Spectrometry ◽  
Synthesis Rate ◽  
Wide Range

Advances in quantitative proteomics have facilitated the measurement of large-scale protein quantification, which represents net changes in protein synthesis and breakdown. However, measuring the rate of protein synthesis is the only way to determine the translational rate of gene transcripts. Here, we report a technique to measure the rate of incorporation of amino acids from ingested protein labeled with stable isotope into individual plasma proteins. This approach involves three steps: 1) production of stable isotope-labeled milk whey protein, oral administration of this intrinsically labeled protein, and subsequent collection of blood samples; 2) fractionation of the plasma and separation of the individual plasma proteins by a combination of anion exchange high-pressure liquid chromatography and gel electrophoresis; and 3) identification of individual plasma proteins by tandem mass spectrometry and measurement of stable isotopic enrichment of these proteins by gas chromatography-mass spectrometry. This method allowed the measurement of the fractional synthesis rate (FSR) of 29 different plasma proteins by using the same precursor pool. We noted a 30-fold difference in FSR of different plasma proteins with a wide range of physiological functions. This approach offers a tremendous opportunity to study the regulation of plasma proteins in humans in many physiological and pathological states.

scholarly journals A high-throughput mass spectrometry-based assay for large-scale profiling of circulating human apolipoproteins

2020 ◽  
Vol 61 (7) ◽  
pp. 1128-1139 ◽  
Author(s):  
Valentin Blanchard ◽  
Damien Garçon ◽  
Catherine Jaunet ◽  
Kevin Chemello ◽  
Stéphanie Billon-Crossouard ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Cardiovascular Diseases ◽  
Large Scale ◽  
Lipoprotein Metabolism ◽  
Serum Samples ◽  
Coefficients Of Variation ◽  
Wide Range ◽  
Quantification Accuracy ◽  
Dilution Effects ◽  
Lower Limits

Apolipoproteins govern lipoprotein metabolism and are promising biomarkers of metabolic and cardiovascular diseases. Unlike immunoassays, MS enables the quantification and phenotyping of multiple apolipoproteins. Hence, here, we aimed to develop a LC-MS/MS assay that can simultaneously quantitate 18 human apolipoproteins [A-I, A-II, A-IV, A-V, B48, B100, C-I, C-II, C-III, C-IV, D, E, F, H, J, L1, M, and (a)] and determined apoE, apoL1, and apo(a) phenotypes in human plasma and serum samples. The plasma and serum apolipoproteins were trypsin digested through an optimized procedure and peptides were extracted and analyzed by LC-MS/MS. The method was validated according to standard guidelines in samples spiked with known peptide amounts. The LC-MS/MS results were compared with those obtained with other techniques, and reproducibility, dilution effects, and stabilities were also assessed. Peptide markers were successfully selected for targeted apolipoprotein quantification and phenotyping. After optimization, the assay was validated for linearity, lower limits of quantification, accuracy (biases: –14.8% to 12.1%), intra-assay variability [coefficients of variation (CVs): 1.5–14.2%], and inter-assay repeatability (CVs: 4.1–14.3%). Bland-Altman plots indicated no major statistically significant differences between LC-MS/MS and other techniques. The LC-MS/MS results were reproducible over five repeated experiments (CVs: 1.8–13.7%), and we identified marked differences among the plasma and serum samples. The LC-MS/MS assay developed here is rapid, requires only small sampling volumes, and incurs reasonable costs, thus making it amenable for a wide range of studies of apolipoprotein metabolism. We also highlight how this assay can be implemented in laboratories.

Multiresidue Analysis of Pesticides in Moringa Pods by GC-MS/MS and LC-MS/MS

2020 ◽  
Vol 103 (6) ◽  
pp. 1486-1497
Author(s):  
Anirban Dutta ◽  
Sandip Hingmire ◽  
Kaushik Banerjee
Keyword(s):  
Mass Spectrometry ◽  
Tandem Mass Spectrometry ◽  
Ethyl Acetate ◽  
Large Scale ◽  
Tandem Mass ◽  
Multiresidue Analysis ◽  
Method Performance ◽  
Chromatography Tandem Mass Spectrometry ◽  
Ms Analysis ◽  
Accuracy And Precision

Abstract Background Moringa pods are known for their nutritional and health benefits. The cultivation of this crop receives frequent pesticide applications. In the absence of risk assessment data, maximum residue limits of pesticides in this crop are considered at the default level (0.01 mg/kg). However, there exists scarcely any validated method for pesticide residue analysis in this matrix. Objective This study was undertaken to develop and validate a multiresidue method for the simultaneous analysis of multi-class pesticides in moringa pods by gas chromatography-tandem mass spectrometry (GC-MS/MS), and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Method The homogenized sample (10 g) was extracted with acetonitrile (10 mL). The extract was cleaned by dispersive solid-phase extraction using a combination of 50 mg primary secondary amine, 5 mg graphitized carbon black, and 25 mg C18 sorbents, and was directly analyzed by LC-MS/MS. Another portion of the extract was reconstituted in ethyl acetate before GC-MS/MS analysis. The method was validated as per the SANTE/12682/2019 guidelines using GC-MS/MS (180 pesticides) and LC-MS/MS instruments (203 pesticides). Results The method provided a satisfactory analysis of the targeted pesticides with good calibration linearity (r2>0.99), high precision (RSD < 20%), and accuracy (recoveries, 70 to 120%). The reconstitution of the acetonitrile extract in ethyl acetate significantly reduced the matrix effects on GC-MS/MS analysis. The use of matrix-matched standards could correct all recoveries. Conclusions The method offered a large-scale analysis of multi-class pesticides with high accuracy, and precision at 10 ng/g, and higher levels. The method performance complied with the regulatory requirements, and thus, can be implemented in routine testing purposes. Highlights The study reports a validated method for large-scale multiresidue analysis of pesticides in moringa matrix for the first time. The method provided a high throughput analysis of multi-class pesticides with satisfactory selectivity, sensitivity, accuracy, and precision.

scholarly journals Identification of an Arginase II Inhibitor via RapidFire Mass Spectrometry Combined with Hydrophilic Interaction Chromatography

2018 ◽  
Vol 24 (4) ◽  
pp. 457-465 ◽  
Author(s):  
Wataru Asano ◽  
Yu Takahashi ◽  
Motoaki Kawano ◽  
Yoshiji Hantani
Keyword(s):  
Mass Spectrometry ◽  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Hydrophilic Interaction Chromatography ◽  
Label Free ◽  
Hydrophilic Interaction ◽  
High Concentration ◽  
Allosteric Site ◽  
Arginase Ii

Peripheral arterial disease (PAD) is an occlusive disease that can lead to atherosclerosis. The involvement of arginase II (Arg II) in PAD progression has been proposed. However, no promising drugs targeting Arg II have been developed to date for the treatment of PAD. In this study, we established a method for detecting the activity of Arg II via high-throughput label-free RapidFire mass spectrometry using hydrophilic interaction chromatography, which enables the direct measurement of l-ornithine produced by Arg II. This approach facilitated a robust high-concentration screening of fragment compounds and the identification of a fragment that inhibits the activity of Arg II. We further confirmed binding of the fragment to the potential allosteric site of Arg II using a surface plasmon resonance assay. We concluded that the identified fragment is a promising compound that may lead to novel drugs to treat PAD, and our method for detecting the activity of Arg II can be applied to large-scale high-throughput screening to identify other structural types of Arg II inhibitors.

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 IceR improves proteome coverage and data completeness in global and single-cell proteomics

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Mathias Kalxdorf ◽  
Torsten Müller ◽  
Oliver Stegle ◽  
Jeroen Krijgsveld
Keyword(s):  
Single Cell ◽  
Large Scale ◽  
Missing Values ◽  
Peptide Identification ◽  
Protein Quantification ◽  
Developmental Trajectory ◽  
Ion Current ◽  
Label Free ◽  
Proteomics Data ◽  
Data Completeness

AbstractLabel-free proteomics by data-dependent acquisition enables the unbiased quantification of thousands of proteins, however it notoriously suffers from high rates of missing values, thus prohibiting consistent protein quantification across large sample cohorts. To solve this, we here present IceR (Ion current extraction Re-quantification), an efficient and user-friendly quantification workflow that combines high identification rates of data-dependent acquisition with low missing value rates similar to data-independent acquisition. Specifically, IceR uses ion current information for a hybrid peptide identification propagation approach with superior quantification precision, accuracy, reliability and data completeness compared to other quantitative workflows. Applied to plasma and single-cell proteomics data, IceR enhanced the number of reliably quantified proteins, improved discriminability between single-cell populations, and allowed reconstruction of a developmental trajectory. IceR will be useful to improve performance of large scale global as well as low-input proteomics applications, facilitated by its availability as an easy-to-use R-package.

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).

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