Unlabeled proteomics analysis is a crucial technology used to investigate the composition and expression of proteins. Compared to labeled technology, unlabeled proteomics analysis has advantages such as simplicity, high throughput, and high sensitivity. This article will provide a detailed introduction to the process of unlabeled proteomics analysis, from sample preparation to data interpretation, emphasizing the significance of each step and method selection, and its application value in biomedical research. Operational phase framing for the same unlabeled route is summarized in Overview of Label-Free Proteomics Experimental Workflow.
Figure 1. A typical label-free proteomics analysis workflow proceeds from sample preparation and separation to mass spectrometry and data interpretation.
Sample Preparation
Sample preparation is the first step of unlabeled proteomics analysis. This includes the collection of samples, cell lysis, and protein extraction. For complex samples, such as tissues or serum, layered centrifugation, ultrasonic crushing, or acidic precipitation methods can be used for sample pretreatment. The determination of protein content in the sample is also necessary for the control of sample normalization and loading amount.
Protein Separation
Protein separation is a key step in unlabeled proteomics analysis. Common protein separation methods include gel electrophoresis and liquid chromatography. Gel electrophoresis can be used to separate the molecular weight and charge characteristics of proteins, with common methods being SDS-PAGE and 2D electrophoresis. Liquid chromatography can separate the hydrophilicity, hydrophobicity, and affinity characteristics of proteins, with reverse phase chromatography and ion exchange chromatography being common methods.
Figure 2. Sample preparation and separation choices set protein input quality before mass spectrometry in unlabeled proteomics workflows.
Mass Spectrometry Analysis
Mass spectrometry analysis is the core step of unlabeled proteomics analysis. By ionizing and analyzing protein samples with a mass spectrometer, the mass and sequence information of proteins can be obtained. Common mass spectrometry analysis methods include Time-of-Flight mass spectrometry (TOF-MS), tandem mass spectrometry (MS/MS), and quantitative mass spectrometry. The choice of mass spectrometry analysis is based on factors such as the complexity of the sample, the required resolution, and sensitivity.
Mass spectrometry-centered step detail for unlabeled quantification is described further in How to Perform Label-Free Quantitative Proteomics Analysis Using Mass Spectrometry?.
Data Analysis
Data analysis is the final step in unlabeled proteomics analysis. It involves the preprocessing of mass spectrometry data, peak identification, quantification, and labeling. Preprocessing of mass spectrometry data includes denoising, mass correction, and feature extraction. Peak identification is the process of associating mass peaks with protein labels. Quantification and labeling are used to determine the relative abundance of proteins in different samples and their identification.
Figure 3. After acquisition, label-free proteomics data analysis covers preprocessing, peak identification, and relative quantification across samples.
Unlabeled proteomics analysis is an essential technical means for studying protein composition and expression. Through the steps of sample preparation, protein separation, mass spectrometry analysis, and data analysis, detailed information about the proteome can be obtained and biological processes and disease mechanisms revealed. Reasonable selection and optimization of each step in the analysis process can improve the reliability of the experiment and the accuracy of the data. Unlabeled proteomics analysis has significant application value in biomedical research and drug development. Researchers can also review the MtoZ Biolabs Label-Free Quantitative Proteomics Service for project-specific sample evaluation, workflow planning, and unlabeled quantitative analysis support.
