MSI Analyte Browser: A web-based MicroApp for visualization and annotation of MS imaging data

Significance of the topic

Mass spectrometry imaging (MSI) enables spatial mapping of hundreds to thousands of molecular species directly from biological or material samples. This modality supports exploratory research in fields such as neuroscience, pathology and materials science by revealing the distribution of lipids, metabolites and other analytes without labeling or staining.

Objectives and Study Overview

This whitepaper introduces the MSI Analyte Browser, a web-based MicroApp designed to streamline MSI data interpretation. The key aims are:

• To provide automated annotation of ion images via accurate mass matching against metabolome databases.
• To offer interactive visualization of spatial and spectral MSI data.
• To facilitate discovery of biologically or chemically relevant analytes through ranking and overlay tools.

Methodology and Instrumentation

Mouse brain sections (18 µm) were prepared by cryosectioning at –20 °C and stored at –80 °C. Imaging was performed using DESI XS on a SELECT SERIES™ MRT Q-ToF mass spectrometer with >200 000 FWHM resolution and sub-ppm mass accuracy.

• Source: DESI, negative ion mode
• Cone voltage: 40 V; capillary voltage: 0.8 kV
• Nitrogen nebulizing gas at 0.8 bar
• Solvent: 95 % methanol with 200 pg/µL leucine-enkephalin (lock mass: m/z 554.2620)
• Acquisition: 5 pixels/s, 50 µm pixel size

The acquired data were processed with HDI™ software to generate peak-picked analyte lists, which were imported into the MSI Analyte Browser.

Main Results and Discussion

Using a 1 ppm search tolerance, the browser matched pixel-specific m/z values to HMDB entries. For example, m/z 885.5497 was annotated as the [M-H]⁻ ion of PI(38:4) (C₄₇H₈₃O₁₃P) with 0.178 ppm error, returning all structural isomers within tolerance.

• The annotation module computes neutral masses for common adducts, filters by user-defined ppm tolerance and ion mode, and retrieves candidate IDs.
• Isotope patterns are detected via mass difference and image correlation metrics.

Visualization features include:

• Interactive 2D ion image display with customizable colormap, scaling, pan and zoom.
• Pixel-resolved spectra: clicking on an image pixel reveals its spectrum with hover-over peak annotations.
• Average spectrum generation for the entire dataset, highlighting peaks by annotation confidence.

Top analyte selection ranks m/z values by signal intensity ratio inside versus outside a detected tissue mask, enabling grid plots of the top 50 features. RGB overlays combine three selected ions to visualize co-localization patterns.

Benefits and Practical Applications

• Accelerates MSI data exploration by integrating annotation and visualization in a lightweight web interface.
• Improves confidence in compound identification through high-resolution mass accuracy and isotopic analysis.
• Guides targeted follow-up studies on consecutive or adjacent tissue sections using complementary ionization methods (e.g., MALDI, DESI).

Future Trends and Opportunities

Advances in mass analyzer resolution and sensitivity will further reduce annotation ambiguity. Integrating machine learning for pattern recognition and embedding multi-omics databases could enhance the accuracy of putative identifications. Cloud-based collaboration and batch processing will expand accessibility for large-scale MSI studies.

Conclusion

The MSI Analyte Browser offers a comprehensive platform for rapid annotation and visualization of MS imaging data. By combining accurate mass matching, isotope detection and interactive display tools, it streamlines the discovery of molecular distributions and supports informed decision-making in research and quality control.

Reference

No formal references were provided in the original document.