SMAnalyst: A Web Server for Spatial Metabolomic Data Analysis and Annotation

Area of Science:

• * Spatial metabolomics and its role in understanding tissue metabolic heterogeneity.

Background:

• * Current spatial metabolomics analysis is hampered by fragmented tools and a lack of integrated, open-source GUI software.
• * A comprehensive workflow covering quality control, preprocessing, identification, pattern, and differential analysis is missing.

Purpose of the Study:

• * To develop SMAnalyst, an integrated, open-source, web-based platform for spatial metabolomics data analysis.
• * To provide a user-friendly GUI that lowers the barrier to entry for complex spatial metabolomics workflows.

Main Methods:

• * Development of an integrated platform consolidating multi-dimensional data quality assessment.
• * Implementation of a metabolite annotation scoring system based on mass accuracy, isotopic similarity, and adduct evidence.
• * Inclusion of dual-dimension spatial pattern discovery (metabolite co-expression, pixel clustering) and flexible differential analysis.

Main Results:

• * SMAnalyst offers a unified solution, eliminating the need for tool switching and advanced computational skills.
• * The platform was successfully tested on a mouse brain dataset, efficiently handling large-scale data (>14,000 pixels, >3000 ion peaks).
• * Demonstrated capability in multi-dimensional data quality assessment, metabolite annotation, and spatial pattern discovery.

Conclusions:

• * SMAnalyst effectively addresses the critical gap in integrated analytical solutions for spatial metabolomics.
• * The platform significantly lowers the analysis barrier, promoting wider adoption of spatial metabolomics.
• * Provides a comprehensive, user-friendly tool for analyzing metabolic heterogeneity in biological tissues.