SYNTHESIS AND CHARACTERIZATION OF A NOVEL MALDI MATRIX, DTB CHCA, AND AN AUTOMATED QUANTITATIVE DATA COLLECTION PROCESS FOR MALDI-MS

Author

Jared Michael Harzan, Southern Illinois University CarbondaleFollow

Date of Award

12-1-2025

Degree Name

Doctor of Philosophy

Department

Chemistry

First Advisor

Kinsel, Gary

Abstract

The initial development of matrix assisted laser desorption/ionization mass spectrometry (MALDI-MS) was empirical in nature, resulting in a constant search for new and improved matrices. Cinnamic acid derivatives, which are also well known for their use as natural antioxidants, have been commonly utilized as MALDI matrices since its inception, but the inclusion of tert-butyl groups on the phenolic ring, known to improve antioxidant performance of phenols, has not been tested for a MALDI matrix. In this work, the novel MALDI-MS matrix alpha-cyano-3,5-di-tert-butyl-4-hydroxycinnamic acid (DTB-CHCA) was synthesized and its performance with peptides, polymers, and proteins was compared with commercially available alpha-cyano-4-hydroxycinnamic acid (CHCA) and sinapinic acid (SA). The inclusion of di-tert-butyl groups onto the CHCA base structure improves the performance of the compound as a MALDI-MS matrix, particularly with large proteins and hydrophobic and acidic analytes.Additionally, quantitation via MALDI-MS is complicated due to the inhomogeneous nature of sample crystals resulting in inconsistent desorption. Previous work from our lab has demonstrated the ability to generate quantitative data by manually collecting mass spectra based on a fixed analyte peak width. In this work, a novel automated quantitative data collection method was developed which speeds up the time of analysis and removes the potential for user bias. This method utilizes the AutoXecute software bundled with the Bruker FlexControl software and functions by accepting spectra based on the matrix ion signal full width at half maximum and a minimum ion signal intensity. The software is demonstrated to be able to collect quantitative spectra (R2 > 0.99) over 1 to 2 orders of magnitude for a range of analytes from small organic molecules to peptides and proteins, and peptide mixtures. Improvements in sample reproducibility are demonstrated by coupling the automated data collection process with an airbrush sample preparation technique to produce more homogenous samples.