Isotope Labeling-Based Quantitative Service

MtoZ Biolabs provides isotope labeling-based quantitative service based on SILAC, TMT, iTRAQ, and Dimethyl Labeling. According to sample type, sample number, biological replicates, quantitative requirements, and research objectives, our team can design an appropriate labeling and mass spectrometry workflow. This service is well suited for treatment-versus-control studies, multi-condition comparisons, time-course experiments, disease research, drug mechanism studies, and post-translational modification analysis.

 

Technical Principles

The principle of isotope labeling-based quantitative analysis is to introduce distinguishable mass labels into proteins or peptides from different experimental groups so that multiple samples can be analyzed within the same mass spectrometry workflow.

 

Different technologies introduce labels at different stages. SILAC incorporates stable isotope-labeled amino acids during cell culture, whereas TMT, iTRAQ, and Dimethyl Labeling are generally performed after protein digestion.

 

After labeling, samples are combined and analyzed by LC-MS/MS. MS1 detects precursor ions and quantitative signals, while MS2 provides peptide sequence information and, for TMT/iTRAQ, reporter ion intensities for relative quantification. The data are then processed for protein identification, normalization, statistical analysis, and biological interpretation.

Kang C. et al. World Journal of Gastroenterology. 2016.

Figure 1. The Principle of Isotope Labeling-based Quantitative Proteomics

Choose the Right Isotope Labeling Workflow

Different isotope labeling strategies vary in sample compatibility, project scale, quantitative performance, and cost. Method selection should therefore be based on sample type, sample number, experimental design, and research objectives.

Method	Best-Suited Samples	Project Characteristics	Advantages
SILAC	Stable cultured cell lines and cell models	Suitable for treatment/control comparisons, drug stimulation, genetic perturbation, and cell-state studies	Labeling is completed during cell culture, reducing technical variation introduced during downstream sample handling and providing good quantitative reproducibility
TMT	Animal and plant tissues, cells, microorganisms, body fluids, and other routine biological samples	Best suited for projects with up to 10 samples requiring high quantitative precision and reproducibility; appropriate for tightly controlled multi-group studies. For cohorts larger than 10 samples, DIA may be more suitable	Multiple labeled samples can be pooled and analyzed in the same LC-MS/MS workflow, helping reduce batch effects and improve within-batch relative quantification
iTRAQ	Tissues, cells, and other complex proteome samples	Suitable for medium-scale multi-group relative quantification, including treatment-versus-control and disease-versus-normal comparisons	Enables simultaneous relative quantification of multiple samples and reduces variation caused by separate MS runs
Dimethyl Labeling	Cells, tissues, protein extracts, and routine proteomics samples	Suitable for smaller projects with relatively simple experimental designs and greater cost sensitivity	Flexible workflow and relatively low reagent cost, making it suitable for small-scale quantitative proteomics studies

Service Advantages

1. Efficient Project Turnaround

The typical turnaround time for quantitative proteomics projects is approximately 3–4 weeks. Expedited projects may be completed in about 3 weeks, depending on instrument scheduling. Actual timelines may be affected by sample QC failure, sample re-extraction, fractionation of large cohorts, or customized data analysis requirements.

 

2. Advanced Mass Spectrometry Platforms

MtoZ Biolabs is equipped with Thermo Fisher Orbitrap Exploris 480, Q Exactive, Orbitrap Astral, Fusion Lumos, and Bruker timsTOF Pro 2 mass spectrometers, supported by Thermo EASY-nLC 1200 and Vanquish Neo LC systems. Instrument platforms can be selected according to project requirements for depth, throughput, and resolution.

 

3. Multiple Isotope Labeling Strategies

SILAC, TMT, iTRAQ, and Dimethyl Labeling are available for different quantitative proteomics applications. The appropriate strategy can be selected according to sample type, sample number, experimental design, quantitative precision, and project budget.

 

4. Rigorous Quality Control

Quality control covers sample preparation, mass spectrometry analysis, and data processing. BCA protein quantification and SDS-PAGE are used to evaluate sample quality during preparation, while peptide length distribution, identification scores, and quantitative data quality are assessed during data analysis.

 

5. Complex Sample Preparation Expertise

Extensive experience with complex animal and plant tissues enables optimized preparation of high-lipid, high-polysaccharide, and high-polyphenol samples, helping reduce matrix interference and improve the reliability of downstream protein identification and quantification.

 

Analysis Workflow

1. Project Design

The isotope labeling strategy and LC-MS/MS workflow are determined according to sample type, experimental groups, biological replicates, key comparisons, and research objectives.

 

2. Protein Extraction and Quality Assessment

Proteins are extracted and evaluated for concentration, integrity, and overall sample quality to ensure comparability among experimental groups.

 

3. Protein Digestion and Labeling

Proteins are reduced, alkylated, and digested into peptides, followed by TMT, iTRAQ, or Dimethyl labeling. SILAC labeling is completed during cell culture.

 

4. Sample Mixing and Peptide Fractionation

Labeled samples are mixed according to the experimental design. High-pH reversed-phase fractionation can be applied to complex proteomes to improve protein identification depth.

 

5. LC-MS/MS Analysis

Peptides are separated and analyzed using high-resolution liquid chromatography-tandem mass spectrometry for peptide identification and quantitative signal acquisition.

 

6. Protein Identification and Relative Quantification

Database searching, peptide identification, protein inference, quantitative calculation, normalization, and quality control are performed to generate relative protein abundance data.

 

7. Bioinformatics Analysis

Differential protein screening, clustering, functional annotation, pathway enrichment, and protein-protein interaction analysis are performed according to project requirements.

Sample Submission Requirements

Item	Requirements
Sample Types	Cells, animal or plant tissues, microorganisms, body fluids, protein extracts, and other routine proteomics samples
Sample Quality	Samples should maintain good integrity, show no obvious degradation, and undergo minimal freeze-thaw cycles
Sample Amount and Concentration	Requirements vary depending on the selected labeling strategy and sample type and will be evaluated before project initiation
Buffer System	High concentrations of salts, detergents, and other components that may interfere with digestion, labeling, or LC-MS/MS analysis should be avoided
Storage and Shipping	Cells, tissues, and other degradable samples should be stored at low temperature and shipped under appropriate conditions such as dry ice when required
Project Information	Species, sample type, sample number, experimental groups, biological replicates, key comparisons, and research objectives should be provided

For limited, low-abundance, high-lipid, high-polysaccharide, high-polyphenol, or other complex samples, feasibility assessment can be performed before project initiation to determine an appropriate pretreatment and quantitative strategy.

Applications

1. Differential Protein Expression

Compare protein abundance between treatment and control groups, disease and normal samples, or different physiological and pathological conditions to identify significantly altered proteins.

 

2. Drug Mechanism Studies

Characterize proteome changes before and after drug treatment to investigate drug-responsive proteins, potential targets, signaling pathways, and resistance mechanisms.

 

3. Disease Mechanism Research

Identify proteins and pathways associated with disease development, progression, and phenotype changes through comparative quantitative proteomics.

 

4. Biomarker Discovery

Screen differentially expressed proteins for candidate biomarkers that may support downstream studies of diagnosis, classification, prognosis, or therapeutic response.

 

5. Post-Translational Modification Studies

Combine isotope labeling with enrichment strategies for phosphorylation, acetylation, ubiquitination, and other PTMs to investigate dynamic changes in modified proteins and modification sites.

 

Deliverables

1. Protein Identification and Relative Quantification Results

2. Differential Protein and Quality Control Results

3. PCA, Clustering, and Volcano Plots

4. GO, KEGG, and PPI Analyses

5. Raw MS Data, Excel Data Files, and Project Report

Customized bioinformatics analysis and multi-omics integration analysis are also available according to project requirements.

 

Start Your Project with MtoZ Biolabs

Selecting an appropriate isotope labeling strategy requires comprehensive consideration of sample type, sample number, experimental groups, biological replicates, quantitative precision, and research objectives.

 

Provide your sample information, experimental design, and research objectives, and the MtoZ Biolabs proteomics team will evaluate the suitability of SILAC, TMT, iTRAQ, or Dimethyl Labeling and develop a corresponding LC-MS/MS quantitative proteomics workflow.