Relative Protein Quantitative Service, MS Based

What Is Relative Protein Quantification?

Relative protein quantification compares protein abundance between samples or experimental groups and reports relative abundance or fold changes rather than absolute protein concentration. It is widely used to identify differential proteins, characterize treatment responses, and compare biological states.

In MS-based proteomics, quantification strategy and data acquisition strategy are two separate considerations. Relative quantification can be performed using label-based or label-free approaches. TMT is a widely used label-based method for multiplexed sample comparison, while iTRAQ and SILAC can also be used for suitable study designs. Label-free quantification analyzes samples without isotope or isobaric labeling. DDA and DIA describe how mass spectrometry data are acquired. 

MtoZ Biolabs provides Relative Protein Quantification Service with the quantification and acquisition strategy selected according to sample number, study design, available material, and required quantitative performance.

Figure 1. Relative Protein Quantification Strategies

When This Service Is a Good Fit

Relative protein quantification is appropriate when the research question focuses on how protein abundance changes between samples, groups, or biological conditions rather than the exact concentration of individual proteins.

• Fixed Multi-Group Comparisons. TMT can be used when a defined set of samples needs to be analyzed together for precise relative comparison.
• Large-Cohort Comparisons. Label-free workflows are suitable when sample numbers exceed the practical capacity of multiplex labeling. DIA is especially useful when reproducibility and low missing values are priorities.
• Longitudinal or Expanding Studies. Label-free workflows allow samples to be analyzed independently, making it easier to add additional samples or time points.
• Treatment and Perturbation Studies. Relative quantification can measure proteome-wide abundance changes associated with drugs, gene perturbations, environmental conditions, or other experimental interventions.
• Discovery-Oriented Proteomics. Relative quantification supports broad differential protein screening before selected candidates are taken forward for targeted validation.

Relative Protein Quantification Service at MtoZ Biolabs

MtoZ Biolabs provides Relative Protein Quantification Service using both label-based and label-free proteomics workflows. The service supports tissues, cells, microorganisms, biofluids, and other biological samples with an available reference database.

1. Label-Based Quantification

TMT is commonly used for multiplexed relative protein comparison when a fixed set of samples requires high within-batch precision. TMT data are acquired on high-resolution Orbitrap platforms and processed using Proteome Discoverer. iTRAQ and SILAC can also be considered for suitable study designs.

2. Label-Free Quantification

For studies requiring greater sample-number flexibility, MtoZ Biolabs supports both Label-Free DDA and Label-Free DIA workflows.

• Label-Free DDA: Orbitrap-based acquisition with MaxQuant processing for relative protein quantification.
• Label-Free DIA: High-resolution acquisition on Orbitrap Exploris 480 or Astral platforms with DIA-NN processing. DIA workflows can achieve quantitative CVs below 10% and missing values below 5% in suitable projects.

3. Integrated Data Analysis

The Relative Protein Quantification Service can include protein and peptide identification, quantitative quality control, differential protein analysis, GO and KEGG enrichment, and PPI analysis when supported by the species database.

Typical project turnaround is 3-4 weeks, depending on sample preparation complexity, sample number, analytical strategy, and instrument scheduling.

Workflow of Relative Protein Quantification Service

1. Sample Evaluation and Protein Preparation

Samples are evaluated for type, quantity, concentration, and buffer compatibility before protein extraction. Proteins are then quality checked, reduced, alkylated, and enzymatically digested into peptides for LC-MS/MS analysis.

2. Quantification Strategy Setup

The workflow is selected according to the study design and sample number. TMT samples are labeled and pooled for multiplexed comparison, while label-free samples are processed individually without isotope or isobaric labeling.

3. LC-MS/MS Acquisition

Peptides are separated by liquid chromatography and analyzed by high-resolution mass spectrometry. DDA or DIA acquisition is selected according to the quantification workflow and the required balance between flexibility, reproducibility, and data completeness.

4. Relative Protein Quantification

Protein abundance is calculated from reporter-ion signals in TMT workflows or peptide signal intensities in label-free workflows. Quantitative quality control is performed to evaluate consistency across samples and experimental groups.

5. Differential Analysis and Bioinformatics

Protein abundance is compared across predefined groups to identify differential proteins. Results can be further analyzed using PCA, clustering, functional annotation, pathway enrichment, and other applicable bioinformatics analyses to support biological interpretation.

Figure 2. Workflow of Relative Protein Quantification Service

Why Choose MtoZ Biolabs?

MtoZ Biolabs combines flexible method selection, quantitative performance, and integrated project support to help researchers choose an appropriate relative protein quantification strategy rather than applying a fixed workflow to every study.

1. Study-Specific Strategy Selection

TMT, Label-Free DDA, and Label-Free DIA workflows are selected according to sample number, study design, and quantitative requirements.

2. Reliable Quantitative Performance

For suitable projects, TMT and DIA workflows can achieve quantitative CVs below 10%, while DIA workflows can maintain missing values below 5%.

3. High-Resolution MS and Dedicated Data Processing

High-resolution Orbitrap platforms are combined with workflow-specific software, including Proteome Discoverer, MaxQuant, and DIA-NN, for quantitative proteomics analysis.

4. End-to-End Project Support

MtoZ Biolabs supports projects from sample evaluation and method selection through LC-MS/MS analysis, bioinformatics, and final reporting.

Applications

The Relative Protein Quantification Service supports comparative proteomics studies across a wide range of biological and translational research areas.

1. Disease Mechanism Research

Identify proteins and pathways associated with disease-related changes in biological systems.

2. Drug and Treatment Response

Compare protein abundance changes across treatment groups, doses, or time points.

3. Biomarker Candidate Discovery

Screen differential proteins and prioritize candidates for subsequent validation.

4. Cell Signaling and Systems Biology

Analyze coordinated protein changes across signaling pathways and interaction networks.

5. Plant and Microbial Research

Compare proteomic responses across environmental conditions, developmental stages, or experimental treatments.

Sample Submission Suggestions

Sample requirements vary with sample type and the selected quantification workflow. The following amounts are general recommendations for relative quantitative proteomics and can be adjusted after sample evaluation. Please contact MtoZ Biolabs before submission to confirm the recommended sample amount for your specific study.

1. Recommended Amounts for Common Sample Types

Sample Type	Recommended Quantity	Minimum Quantity
Animal Tissue	20-100 mg	10-50 mg
Plant Tissue	0.1-5 g	0.05-2 g
Cell Pellet	1 × 10⁷ cells	2 × 10⁶ cells
Microbial Samples	50 mg or 50 μL	20 mg or 20 μL
Serum/Plasma	10-50 μL	5-25 μL
Urine	1 mL	0.5 mL
Cerebrospinal Fluid	0.1 mL	0.05 mL

2. Extracted Protein Requirements

If extracted protein is submitted directly, the required protein amount depends on the selected workflow.

Workflow	Recommended Protein Input	Minimum Input	Additional Requirement
TMT	100 μg per channel	>50 μg per channel	Protein concentration >1 μg/μL; detergent <0.1%
Label-Free DDA	≥50 μg	>20 μg	Protein concentration >0.5 μg/μL
Label-Free DIA	≥50 μg	>20 μg	Protein concentration >0.5 μg/μL

3. Storage and Shipping

• Store samples at -80°C when applicable and ship on dry ice. 
• Avoid repeated freeze-thaw cycles and keep collection and processing conditions consistent across comparison groups. 
• For extracted protein solutions, provide the buffer composition before submission.

Deliverables

1. Protein Identification Results

Protein and peptide identification tables with supporting quality information.

2. Relative Quantification Results

Protein abundance matrices and fold-change results across samples or predefined experimental groups.

3. Differential Protein Results

Statistical comparison of protein abundance changes, including differential protein lists and relevant quantitative parameters.

4. Data Visualization

Project-specific figures such as PCA plots, clustering heatmaps, volcano plots, and other quantitative visualizations.

5. Functional Interpretation

GO annotation, KEGG pathway enrichment, PPI analysis, and other database-supported analyses when applicable.

6. Data Files and Final Report

Processed result tables, project figures, a structured analysis report, and raw mass spectrometry data when included in the project scope.

Start Your Project with MtoZ Biolabs

Planning a comparative proteomics study? Share your species, sample type, sample number, group design, available sample amount, and research objective with MtoZ Biolabs.

MtoZ Biolabs provides a free project consultation for the Relative Protein Quantification Service. Our team can help determine whether a label-based or label-free strategy is more suitable, recommend an appropriate DDA or DIA acquisition approach, confirm sample requirements, and provide a project quote based on your study design.