Dynamic Additive Scanning for Precise Control in Electrospray Ionization Mass Spectrometry

Area of Science:

• Analytical Chemistry
• Mass Spectrometry
• Biochemistry

Background:

• Electrospray ionization mass spectrometry (ESI-MS) methods require optimization of additives like acids, bases, and solvents.
• Current optimization relies on iterative methods or literature, often using a single condition.
• Varying additive concentrations can yield different analytical insights for diverse analytes.

Purpose of the Study:

• To develop a precise MS optimization system for dynamic scanning of acid-base and additive concentrations in ESI-MS.
• To demonstrate enhanced signal intensity for low-molecular-weight analytes.
• To show manipulation of protein charge state distributions (CSDs) for structural insights.

Main Methods:

• A novel MS optimization system was developed using off-the-shelf components and Python code.
• The system enables dynamic scanning of acid-base and additive concentrations during ESI-MS.
• Online additive scans were coupled with ESI-MS to streamline optimization.

Main Results:

• Significant signal enhancement was observed for amino acids, glutathione, and phospholipids.
• Enhancement factors reached up to ~44.7 for glutathione.
• Protein CSDs were manipulated, with increased organic solvent concentrations shifting CSDs to lower charge states.

Conclusions:

• The developed system precisely optimizes ESI-MS conditions, enhancing signal intensity for various analytes.
• Dynamic scanning of additives provides valuable information on protein structure vulnerability.
• This approach streamlines ESI-MS method development, reducing the need for sequential analyses.