Objective:

To present advancements in mass spectrometry techniques for analyzing metabolites and proteins.

Approach:

• New Ionization Route for Amino Metabolites: Introduced TAC/OS, a tocopherol-based reagent for detecting amino-containing metabolites using laser post-ionization.
• HDX-MS at Residue Resolution: Developed a site-specific hydrogen–deuterium exchange workflow to analyze ligand binding on WDR5 at the residue level.
• Faster Motif Mining for MS/MS: Launched MS2LDA 2.0 for faster motif mining and introduced MAG for automated motif annotation guidance.
• Reconstructing Missing Proteomics Data: Implemented msBayesImpute, a Bayesian framework for improving recovery of missing values in proteomics datasets.

Key Findings:

• TAC/OS improved detection of amino metabolites in murine brain tissue, localizing over 30 metabolites.
• Site-specific HDX-MS revealed hidden residue-level changes in ligand binding that conventional methods missed.
• MS2LDA 2.0 increased analysis speed by up to 14 times, enhancing motif mining capabilities.
• msBayesImpute outperformed ten existing methods in reconstructing missing values in proteomics datasets.

Interpretation:

Limitations:

• The study on TAC/OS remains a proof of concept.
• Site-specific HDX-MS acquisition and analysis are still largely manual.
• MAG's effectiveness varies with the quality of the spectral data.

Conclusion:

The reported advancements in mass spectrometry techniques hold promise for improved metabolite and protein analysis.