Retention Time Prediction for TMT-Labeled Peptides in Proteomic LC-MS Experiments

Area of Science:

• Proteomics
• Analytical Chemistry
• Chromatography

Background:

• Tandem mass tags (TMT and TMTpro) are widely used for quantitative proteomics.
• Understanding their impact on chromatographic behavior is essential for data interpretation.

Purpose of the Study:

• To comprehensively investigate the chromatographic behavior of TMT- and TMTpro-labeled peptides in 2D LC.
• To develop predictive models for retention times of labeled peptides.

Main Methods:

• Large-scale 2D LC experiments were performed using various separation modes (low pH RP, high-pH RP, HILIC, SCX).
• Over 100,000 peptide pairs (labeled vs. unlabeled) were analyzed.
• Sequence-specific retention calculator (SSRCalc) models were adapted and validated.

Main Results:

• TMT labeling increased peptide retention in RPLC by an average of 3.3% acetonitrile.
• TMTpro labeling showed similar behavior with a 3.7% acetonitrile shift.
• Sequence-dependent features, particularly N-terminal chemistry, influenced retention shifts.
• SSRCalc models achieved high prediction accuracy (R² ~ 0.98) for both labeled and unlabeled peptides.
• Higher retention was observed in high-pH RP and HILIC; SCX selectivity was unaffected.

Conclusions:

• TMT and TMTpro labeling significantly alter peptide retention in LC, with predictable patterns.
• Developed SSRCalc models accurately predict retention times, aiding proteomic data analysis.
• These findings are critical for optimizing 2D LC methods in quantitative proteomics.