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TMT(Tandem Mass Tags) Quantitative Proteomics Analysis

TMT(Tandem Mass Tags) Quantitative Proteomics Analysis

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Introduction

The detection techniques used in biosensors can be broadly classified into label-based and label-free. TMT is a widely used protein marker quantification technique in the field of biological proteomics research[1] . This technique enables the labeling of peptides by binding to their amino terminal or lysine side chain amino groups. In mass spectrometry analysis, the same peptide from different samples, after labeling, has the same mass-to-charge ratio, and is selected for secondary fragmentation at the same time to produce reporter ions with different masses. The quantification of proteins between different samples is achieved by the abundance of reporter ions. This technique is suitable for the quantitative study of differential proteome in different samples.

TMT (Tandem Mass Tags) quantitative proteomics workflow employed for the identification and quantification of proteinsFigure 1 TMT (Tandem Mass Tags) quantitative proteomics workflow employed for the identification and quantification of proteins[2].

Table1 Comparison of isotope-labeled and unlabeled quantification

Category Label-free Labelled (iTRAQ/TMT)
Machine time more less
project cost low high
Repeatability of samples poor better
Data analysis complex complex
Study design flexible fixed
Demand for samples little more

Advantages of service

  • It is suitable for the analysis of various animal and plant tissues, cells, microorganisms and body fluid samples
  • Simultaneous quantitative analysis of up to 2-10 samples in one experiment (maximum 8 samples in one experiment with iTRAQ technology)
  • High-throughput quantitative data can be obtained in one experiment

Application Field

  • Medicine: disease mechanism research, disease marker discovery, drug target screening
  • Plants: stress resistance mechanism, growth and development mechanism, breeding protection research, etc.
  • Animal husbandry: quality research, animal nutrition, breed breeding, etc.
  • Food environment: storage and processing conditions optimization, quality identification, food nutrition

CD Genomics Data Analysis Pipeline

CD Genomics Data Analysis Pipeline

Bioinformatics Analysis Content

  • Quality assessment of mass spectrometry data
  • Database identification data statistics
  • Results of bioinformatics analysis
    PCA analysis
    Heat map analysis of all samples
    Differential protein screening and analysis
    Functional annotation of differential proteins
    PPI, Protein-Protein Interaction networks analysis

Sample requirements

  • Protein extract ≥ 100 μg
  • Cells ≥ 107
  • Organization
    ≥ 100 mg (animal tissue)
    ≥ 10 mg (plant tissue)
  • Body fluids
    ≥ 500 μl (serum, plasma)
    ≥ 25 mL (urine)
    ≥ 5 mL (saliva, cerebrospinal fluid, etc.)

How It Works

Even if you don't have data yet, we can help you plan your research, provide expert experimental advice, and can schedule your data generation. If you are interested in our services, please contact us or online inquiry for more detailed information.

How It Works

References

  1. Moulder, R., et al., Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling. Mass Spectrom Rev, 2018. 37(5): p. 583-606.
  2. Marx, H., et al., A proteomic atlas of the legume Medicago truncatula and its nitrogen-fixing endosymbiont Sinorhizobium meliloti. Nature Biotechnology, 2016. 34(11): p. 1198-1205.
* For Research Use Only. Not for use in diagnostic procedures.
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