First developed in 2003, tandem mass tag (TMT) mass spectrometry is a potent quantitative proteomics tool for simultaneously analyzing multiple samples in a single experiment (1). In a TMT experiment, scientists digest proteins from different samples into peptides and label each peptide with a specific TMT tag. A TMT tag is a chemical label that consists of three key components: an isotope-containing reporter ion group, a mass normalization group that ensures each tag shares the same overall mass, and a reactive group that covalently binds to primary amines on peptides (2).

Scientists then mix the peptides from different samples into a single tube for tandem mass spectrometry (MS/MS) analysis. During MS/MS analysis, the labeled peptides undergo further fragmentation, generating characteristic ions including reporter ions. By comparing the relative intensities of reporter ions across samples, researchers can determine the relative abundance of corresponding peptides in each sample and infer differences in protein expression or modification levels between the samples.

TMT mass spectrometry informs various proteomic applications, including comparative analysis of protein expression levels, post-translational modifications, protein-protein interactions, and biomarker discovery. Moreover, TMT mass spectrometry enables quantitative profiling of complex biological samples, such as tissues, cells, and bodily fluids, offering a comprehensive view of the proteome in health and disease.

When planning a TMT mass spectrometry experiment, researchers should carefully consider the following aspects.

1. Sample preparation

The goal of sample preparation for TMT mass spectrometry experiments is to convert complex biological samples, such as cultured cells, tissues, or biofluids, into peptides suitable for TMT labeling. To extract proteins from cells, researchers may utilize physical methods like sonication or cell lysis reagents containing chaotropic agents such as urea or guanidinium hydrochloride or detergents like sodium dodecyl sulfate, depending on cell types and protein properties (3). To disrupt disulfide bridges and fully denature proteins, reducing agents like tris(2-carboxyethyl)phosphine or dithiothreitol and alkylation agents such as iodoacetamide are often added to the lysis buffer. Because these chemicals may react with TMT tags, researchers should remove these substances through protein precipitation with organic solvents or solid-phase extraction technology (4). Additionally, adding protease inhibitors to the sample minimizes protein degradation and maintains protein stability.

2. Labeling efficiency

During TMT labeling, factors such as pH, temperature, and buffer composition in the labeling reaction can significantly affect labeling efficiency (5). Researchers should determine the optimal conditions for each specific labeling reagent and sample type. Establishing the appropriate TMT-to-peptide ratio is also crucial. Insufficient sample labeling can lead to some peptides remaining unlabeled and undetected, whereas overusing TMT reagents wastes resources. TMT manufacturers typically recommend the ideal TMT-to-peptide ratio, but scientists may also refine labeling protocols to minimize TMT reagent consumption and achieve greater cost effectiveness (6). To determine the ideal TMT-to-peptide ratio, researchers conduct titration experiments, where varying amounts of a TMT reagent label a known quantity of peptides. They then compare the intensity of labeled and unlabeled peptides using mass spectrometry. Through iterative optimization, researchers can identify the TMT-to-peptide ratio that yields the highest labeling efficiency without excessive TMT reagent usage.

3. Reducing sample complexity

Simplifying the sample composition can improve the sensitivity and specificity of mass spectrometry analysis. One approach to reducing sample complexity is peptide prefractionation before mass spectrometry analysis. Researchers commonly employ high-performance liquid chromatography (HPLC) to separate peptides into smaller fractions based on their physicochemical properties such as hydrophobicity, charge, or size (7). This process reduces the number of peptides competing for ionization during mass spectrometry analysis, increasing the coverage of complex proteomes and improving the detection of low-abundance peptides.

4. Data acquisition

Tandem mass spectrometers are commonly chosen for TMT assays due to their capability to fragment peptides. To precisely differentiate between closely related ions and detect low-abundance TMT-labeled peptides, researchers should prioritize instruments with high resolution and sensitivity. Meanwhile, researchers need to carefully optimize various data acquisition parameters for each mass spectrometry system and experiment. For example, selecting appropriate fragmentation methods, such as collision-induced dissociation, high energy collision-induced dissociation, or electron-transfer dissociation, and fine-tuning collision energy help maximize fragment ion yield while reducing noise. Adjusting parameters such as isolation width, scan speed, and resolution is essential to balance data acquisition speed with spectral quality (3).

5. Quantification reliability

Sample handling, instrument calibration, and temperature changes can introduce variations in protein amount and composition between samples. To mitigate this, researchers can incorporate a standard peptide at a known concentration into each sample to normalize signal intensities across different TMT sets (3). In multibatch TMT mass spectrometry experiments, including a reference sample comprising a mixture of all samples facilitates comparisons across different batches and minimizes variations (8). Moreover, establishing replicate analyses enhances statistical confidence in quantification results. Utilizing advanced computational algorithms and statistical methods for data processing and normalization further enhances quantification accuracy and precision.

Multiplexing with precision

Today, commercial TMT tags allow for the analysis of up to 18 protein samples. With ongoing efforts to further increase this capacity, it is imperative to implement a controlled workflow encompassing refined sample preparation and labeling procedures, careful selection of data acquisition methods, and optimal data analysis strategies to ensure reliable and reproducible results. Additionally, researchers should validate their findings using complementary experimental techniques, such as Western blots or targeted proteomics, to confirm differential protein expression observed in TMT mass spectrometry experiments.

A multiplexed protein quantification workflow with TMT labeling

Essential materials for TMT mass spectrometry

References

1. Thompson, A. et al. Tandem Mass Tags: A Novel Quantification Strategy for Comparative Analysis of Complex Protein Mixtures by MS/MS. Anal. Chem. 75, 1895–1904 (2003).
2. Li, J. et al. TMTpro reagents: a set of isobaric labeling mass tags enables simultaneous proteome-wide measurements across 16 samples. Nat Methods 17, 399–404 (2020).
3. Chen, X. et al. Quantitative Proteomics Using Isobaric Labeling: A Practical Guide. Genomics, Proteomics & Bioinformatics 19, 689–706 (2021).
4. Hughes, C. S. et al. Single-pot, solid-phase-enhanced sample preparation for proteomics experiments. Nat Protoc 14, 68–85 (2019).
5. Hutchinson-Bunch, C. et al. Assessment of TMT Labeling Efficiency in Large-Scale Quantitative Proteomics: The Critical Effect of Sample pH. ACS Omega 6, 12660–12666 (2021).
6. Zecha, J. et al. TMT Labeling for the Masses: A Robust and Cost-efficient, In-solution Labeling Approach *[S]. Molecular & Cellular Proteomics 18, 1468–1478 (2019).
7. Manadas, B., Mendes, V. M., English, J. & Dunn, M. J. Peptide fractionation in proteomics approaches. Expert Review of Proteomics 7, 655–663 (2010).
8. Nakayasu, E. S. et al. Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation. Nat Protoc 16, 3737–3760 (2021).