Workflow of Quantitative Proteomics

Quantitative proteomics is a crucial tool for studying the variations in protein abundance and function within biological samples, widely applied in disease research, drug development, and biomarker discovery.

 

Sample Preparation

Sample preparation is a critical step in quantitative proteomics. First, appropriate biological samples, such as cells, tissues, or blood, are selected based on the research objective. Samples should undergo proper processing to remove interfering substances. Common processing methods include:

 

1. Cell Lysis

Using lysis buffer to rupture cell membranes and release proteins.

 

2. Precipitation Removal

Removing cell debris and other macromolecules via ultracentrifugation or filtration.

 

After sample processing, the protein concentration should be determined to ensure the accuracy of subsequent analyses.

 

Protein Separation

Protein separation is an important part of the quantitative proteomics workflow. Common methods include:

 

1. Two-Dimensional Gel Electrophoresis (2-DE)

Utilizing isoelectric focusing and SDS-PAGE for separation, suitable for comprehensive analysis of complex samples.

 

2. Liquid Chromatography (LC)

Separating samples into different fractions, ideal for high-throughput analyses.

 

The purpose of this step is to provide high-quality protein samples for subsequent mass spectrometry analysis.

 

Protein Digestion

After separation, proteins typically undergo enzymatic digestion to generate small peptide fragments suitable for mass spectrometry analysis. Commonly used enzymes include trypsin, which specifically cleaves proteins to produce peptides effectively detected by mass spectrometry.

 

Mass Spectrometry Analysis

Mass spectrometry (MS) is the core technology in quantitative proteomics, with main steps including:

 

1. Electrospray Ionization (ESI) or Matrix-Assisted Laser Desorption/Ionization (MALDI)

Ionizing peptide fragments for mass spectrometry analysis.

 

2. Mass Spectrometry Analysis

Measuring the mass-to-charge ratio (m/z) of peptide fragments to obtain mass spectra.

 

3. Data Acquisition

Recording mass spectrometry data as a foundation for further analysis.

 

Data Analysis

Data analysis is an important aspect of quantitative proteomics, primarily involving:

 

1. Peptide Identification

Determining the origin of peptides by comparing them with protein databases.

 

2. Relative Quantification

Comparing protein quantities across different samples using labels (e.g., TMT or iTRAQ).

 

3. Bioinformatics Analysis

Utilizing statistical and bioinformatics tools to analyze the biological significance of protein abundance variations.

 

Results Validation

To ensure the reliability of the results, experimental validation is typically required. Common methods include:

 

1. Western Blot

Validating the expression levels of specific proteins.

 

2. ELISA

Quantifying the concentration of specific proteins.

 

Quantitative proteomics is a complex yet invaluable technique that provides important insights into protein changes within biological systems. A systematic workflow ensures the accuracy and reliability of the data, thus providing a solid foundation for scientific research.