IsoMatchMS: Open-Source Software for Automated Annotation and Visualization of High Resolution MALDI-MS Spectra

Area of Science:

• Biochemistry
• Analytical Chemistry
• Bioinformatics

Background:

• Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is widely used for identifying molecular isotope profiles in biological samples.
• Current MALDI-MS software often struggles with complex isotopic distributions in proteins, limiting their application in proteomics.
• Compound identification typically relies on external databases for accurate mass matching, especially when tandem MS fragmentation data is absent.

Purpose of the Study:

• To introduce IsoMatchMS, an R package designed for automated annotation of MALDI-MS data.
• To extend MALDI-MS data analysis capabilities to multiple datatypes, including intact proteins, peptides, and glycans.
• To provide a user-friendly tool for simplifying the annotation and visualization of complex MALDI-MS data.

Main Methods:

• Development of an R package, IsoMatchMS, for automated MALDI-MS data annotation.
• Implementation of functionality to accept pre-derived molecular formulas or derive them from peptide/protein lists, including post-translational modifications.
• Integration of a trelliscope display for interactive visualization and filtering of matched isotopic profiles.

Main Results:

• IsoMatchMS enables automated annotation of MALDI-MS data for intact proteins, peptides, and glycans.
• The package can derive molecular formulas for proteomics applications, accommodating post-translational modifications.
• Interactive visualization via trelliscope display allows for efficient filtering and sorting of results based on match scores and peak counts.

Conclusions:

• IsoMatchMS simplifies the annotation of MALDI-MS data, particularly for complex biological molecules like proteins.
• The tool enhances downstream analysis by providing accessible and filterable visualizations of isotopic profiles.
• IsoMatchMS broadens the utility of MALDI-MS in biological sample analysis, especially in proteomics and glycomics.