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Label-free protein quantification is a mass spectrometry-based method for identifying and quantifying relative changes in two or more biological samples instead of using a stable isotope-containing compound to label proteins.
2. Applicable to any kind
of samples
No limit on the number
of samples
No need to use chemical
or metabolic labeling
A mass spectrometry-
based method
1. Introduction
It is ideal for large-sample analyses in clinical screening or biomarker
discovery experiments.
3. 2. Strategy
Label-free approaches can be divided into two distinct groups according to the
method used for data extraction.
Counting the number of peptides or spectra assigned to a given protein
Spectral counting methods
1
Precursor signal intensity
The extraction of the area of the precursor ions’ chromatographic peaks - area
under the curve (AUC) or MS1 signal intensity methods
2
4. 2.1 Spectral counting methods
• Relative protein quantification is achieved by comparing the number of identified MS/MS spectra.
• An increase in protein abundance typically results in an increase in the number of its proteolytic
peptides. The increasing amounts of digests usually lead to an increase in protein sequence
coverage, the number of identified unique peptides, and the number of identified total MS/MS
spectra (spectral count) for each protein.
• Due to ease of implementation, no specific tools or algorithms have been developed specially for
spectral counting approaches. But normalization and statistical analysis of spectral counting
datasets are necessary for accurate and reliable detection of protein changes in complex
mixtures.
5. 2.2 Ion Intensity
• It has been observed that signal intensity from electrospray ionization (ESI) correlates with ion
concentration.
• The height or area of a peak at a particular mass-to-charge ratio (m/z) from a mass spectrum
reflects the number of ions for that m/z detected by the mass spectrometer at any given time.
• Although the ion abundance cannot be used to directly infer absolute protein or peptide
concentration (due to different ionization efficiency for each peptide), comparing the ratio of ion
abundances between identical peptides obtained in different experiment runs can be used to
estimate differential expression.
• Some software is available for protein quantification methods based on MS peak intensity of
identified peptides, such as Pavel, Drik, MassView, SIEVE, ProteinLynx, Nathan and so on.
6. 3. Workflow
LC-MS/MS
Peak intensity Spectral count
protein extraction, reduction,
alkylation, and digestion
Each sample is separately prepared and then subjected to individual LC-MS/MS or LC/LC-MS/MS runs.
Quantification is based on the comparison of peak intensity of the same peptide or the spectral count of
the same protein.
7. Advantages and Limitations
• The variability is eliminated
• Chaper than chemical and metabolic
tags
• The time for sample preparation is
significantly reduced
• Label-free quantitation must rely on
other parameters
• Sequence coverage and the degree of
complex sample fractionations prior to
analysis in a mass spectrometer
8. Applications
Monitoring changes in certain biological process proteomes
Diagnosing certain diseases and cancer biomarkers
Identifying expression profiles in different biological processes
Studying protein interaction networks
The label-free quantitative method has been widely used as one of the most commonly used
quantitative methods
9. • iTRAQ-based proteomics analysis service
• TMT-based proteomics analysis service
• SILAC-based proteomics analysis service
• Absolute quantification (AQUA) service
• Label-free quantification service
• Semi-quantitative proteomics analysis service
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Label-free methods have been widely used for quantitative analysis of proteins.
Hello, welcome to watch the creative proteomics videos about proteomics quantification. Today, we are going to learn some basic knowledge about Label-free Quantitation Methods.
Label-free protein quantification is a mass spectrometry-based method for identifying and quantifying relative changes in two or more biological samples instead of using a stable isotope-containing compound to label proteins. There is no limit on the number of samples in label-free protein quantification and it’s in principle applicable to any kind of sample, including materials that cannot be directly metabolically. It is ideal for large-sample analyses in clinical screening or biomarker discovery experiments.
In general, label-free approaches can be divided into two distinct groups according to the method used for data extraction. On one hand, the quantification can be inferred by counting the number of peptides or spectra assigned to a given protein, and therefore are generically called spectral counting methods. On the other hand, when liquid chromatography is coupled with mass spectrometry, quantitative values can be measured through the extraction of the area of the precursor ions’ chromatographic peaks— the area under the curve or signal intensity.
As for spectral counting methods, relative protein quantification is achieved by comparing the numbers of identified tandem mass spectrometry spectra from the same protein, which has been shown to directly correlate with protein abundance. Some researchers think it is possible because an increase in protein abundance typically results in an increase in the number of its proteolytic peptides. The increasing amounts of digests usually lead to an increase in protein sequence coverage, the number of identified unique peptides, and the number of identified total MS/MS spectra (spectral count) for each protein. Due to ease of implementation, no specific tools or algorithms have been developed specially for spectral counting approaches. But normalization and statistical analysis of spectral counting datasets are necessary for accurate and reliable detection of protein changes in complex mixtures.
As for ion intensity methods, it has been observed that signal intensity from electrospray ionization (ESI) correlates with ion concentration. The height or area of a peak at a particular mass-to-charge ratio (m/z) from a mass spectrum reflects the number of ions for that m/z detected by the mass spectrometer at any given time, which is typically known as the ion abundance. Although the ion abundance cannot be used to directly infer absolute protein or peptide concentration (due to different ionization efficiency for each peptide), comparing the ratio of ion abundances between identical peptides obtained in different experiment runs can be used to estimate differential expression. Some software are available for protein quantification methods based on MS peak intensity of identified peptides, such as Pavel, Drik, MassView, SIEVE, ProteinLynx, Nathan and so on.
There are several fundamental steps involved in the label-free quantitative proteomics, including sample preparation (protein extraction, reduction, alkylation, and digestion), sample separation by liquid chromatography and analysis by tandem mass spectrometry, and data analysis (peptide/protein identification, quantification, and statistical analysis). In label-free quantitative proteomics methods, each sample is separately prepared and then subjected to individual Liquid chromatography-tandem mass spectrometry runs. Quantification is based on the comparison of peak intensity of the same peptide or the spectral count of the same protein.
Label-free quantitation is an attractive approach for three major reasons. First, the variability that chemical labeling/tagging may introduce is eliminated. Second, chemical and metabolic tags are usually expensive. Third, the time for sample preparation is significantly reduced by elimination of numerous steps. While the relative abundance of chemical or metabolic tags can be easily measured, label-free quantitation must rely on other parameters such as peptide or spectral count, which also has inherent limitations. Other issues associated with label-free MS-based quantitation are sequence coverage and the degree of complex sample fractionations prior to analysis in a mass spectrometer. All of these issues and limitations need to be carefully considered before a decision of the optimal approach for a specific experiment.
Renal transplantation provides clear benefits for patients with end-stage kidney disease,and significant cost savings compared with dialysis. However, early complications can significantly impact clinical and economic outcomes, such as delayed graft function (DGF) . In this study , as shown at the figure, we have compared serum proteins pre- and postoperatively from patients undergoing renal transplantation, with and without DGF, using our previously optimized immunodepletion followed by label-free singledimensional liquid chromatography-tandem mass spectrometry analysis strategy.
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