Application of iTRAQ/TMT in Quantitative Proteomics

With the rapid development of proteomics technologies, quantitative proteomics has become an essential tool for revealing dynamic changes in proteins within organisms. iTRAQ (Isobaric Tags for Relative and Absolute Quantitation) and TMT (Tandem Mass Tag) are two widely used labeling techniques that enable high-throughput and accurate protein quantification.

 

Biomarker Discovery

One of the primary applications of quantitative proteomics is biomarker discovery. iTRAQ/TMT technologies allow relative and absolute quantification of proteins across multiple samples, helping researchers identify differentially expressed proteins associated with diseases. This capability is crucial for early diagnosis, prognosis, and monitoring of therapeutic responses. For example, in cancer research, iTRAQ/TMT technologies have been employed to discover protein biomarkers linked to tumor development, thereby advancing personalized medicine.

 

Disease Mechanism Studies

By comparing protein expression profiles between healthy and diseased tissues, iTRAQ/TMT technologies can unravel the molecular mechanisms underlying diseases. Researchers can identify disease-related signaling pathways and functional modules, leading to a deeper understanding of disease onset, progression, and metastasis. For instance, in Alzheimer's disease research, iTRAQ/TMT technologies have been extensively applied to analyze brain tissue samples, identifying proteins and regulatory networks linked to neurodegeneration.

 

Drug Target Identification

Identifying drug targets is a crucial step in drug development. iTRAQ/TMT technologies can pinpoint potential drug targets and mechanisms of action through high-throughput screening and quantitative analysis. Researchers can detect changes in protein expression before and after drug treatment, revealing interactions between drugs and specific proteins. This approach provides a theoretical basis for new drug development. For example, certain cancer drug targets have been identified using iTRAQ/TMT technologies.

 

Epigenetic Research

In epigenetic research, post-translational modifications of proteins (e.g., phosphorylation, acetylation) play a vital role in gene expression regulation. iTRAQ/TMT technologies can simultaneously quantify proteins and their modified forms, enabling researchers to elucidate the molecular mechanisms of epigenetic regulation. For instance, in studies on cancer-related DNA methylation, iTRAQ/TMT technologies have been employed to identify many disease-associated post-translationally modified proteins.

 

Analysis of Cell Signaling

Cell signaling is essential for understanding how cells respond to external environmental changes. iTRAQ/TMT technologies can help researchers quantitatively analyze key proteins and their interactions in signaling pathways, revealing dynamic changes in these pathways. For example, in immunology research, iTRAQ/TMT technologies have been used to analyze immune cell signaling mechanisms under different stimulation conditions, providing new insights into the development of immunotherapies.

 

Construction of Protein Interaction Networks

Protein interaction networks are fundamental to studying protein functions and cellular biological processes. iTRAQ/TMT technologies, through multiplex labeling and high-throughput analysis, can construct complex protein interaction networks, thereby elucidating functional relationships within biological systems. For example, in cancer research, iTRAQ/TMT technologies have been used to construct tumor-associated protein interaction networks, identifying key regulatory nodes and offering a theoretical basis for targeted therapy.

 

iTRAQ/TMT technologies are extensively applied in quantitative proteomics research. Their ability to perform high-throughput and precise protein quantification makes them powerful tools for biomarker discovery, disease mechanism studies, drug target identification, epigenetic research, analysis of cell signaling, and construction of protein interaction networks.