MSIght: A Modular Platform for Improved Confidence in Global, Untargeted Mass Spectrometry Imaging Annotation

Area of Science:

• Biomedical imaging
• Proteomics
• Analytical chemistry

Background:

• Mass spectrometry imaging (MSI) offers high sensitivity and specificity for clinical analysis.
• Current MSI methods face limitations in throughput and spatial localization for peptide identification.
• Integrating histological stains and LC-MS/MS peptide confirmation presents data analysis bottlenecks.

Purpose of the Study:

• To present MSIght, a novel, automated platform for integrating MSI data with histological stains and LC-MS/MS peptide confirmation.
• To enhance spatial localization and confidence in peptide identification for untargeted proteomic profiling.
• To overcome data analysis bottlenecks and increase throughput for MSI experiments.

Main Methods:

• Developed MSIght, a modular platform automating multi-modal data integration.
• Coregistered histological stains with MSI datasets for improved spatial resolution.
• Employed untargeted LC-MS/MS for MS/MS peptide identification to confirm MSI findings.

Main Results:

• MSIght successfully integrates MSI, histological stains, and LC-MS/MS data.
• Achieved enhanced spatial localization and confidence in identified peptide mapping.
• Demonstrated high-throughput, global proteomic profiling capabilities.

Conclusions:

• MSIght automates and streamlines MSI data analysis, overcoming previous throughput limitations.
• The platform enables confident, spatially resolved proteomic profiling for clinical discovery.
• MSIght has the potential to facilitate large-scale clinical cohort studies utilizing MSI for biomarker identification.