Mnova Gears – MS Scan (Starting Guide)

Automated LC-MS Metabolomics Analysis with MS Scan 1.0

Significance of the Topic
The reliable and rapid quantification of targeted masses within specific retention time windows is essential in metabolomics research. Conventional vendor software can struggle when handling large batches or extensive lists of masses. MS Scan 1.0 for Mnova Gears addresses these challenges by automating spectrum extraction, chromatogram generation, and peak quantification, thereby streamlining high-throughput LC-MS data analysis.

Study Objectives and Overview
This application note introduces the workflow and configuration steps required to perform an MS Scan analysis using Mnova Gears. Key goals include:

• Extraction of mass spectra from user-defined retention time intervals.
• Automated peak picking and chromatogram generation for multiple masses.
• Generation of editable reports in CSV, HTML, Mnova, and PDF formats.

Methodology and Used Instrumentation
Input Configuration:

• Data sources supported: local disk directories, database retrieval, or real-time acquisition.
• Automatic detection of experiment files via user-defined file masks.

Processing and Plugins:

• Optional custom processing scripts can be applied prior to MS Scan.
• MS Scan plugin settings allow selection of up to three retention time ranges and specification of mass tolerance, minimum relative abundance, and peak area thresholds.

Output Design:

• Templates or custom scripts can format Mnova layout and final reports.
• Results saved in a structured output folder with time-stamp naming.

Used Instrumentation

• Liquid Chromatography–Mass Spectrometry (LC-MS) data acquired as Total Ion Current (TIC) files.
• Mnova Gears software suite with MS Scan 1.0 plugin and Mgears Viewer.

Main Results and Discussion
The automated workflow yielded:

• CSV reports listing m/z, retention time, total relative area, relative area, absolute area, and relative height for each detected peak.
• HTML reports with interactive tables and links to raw Mnova documents.
• Batch processing capability that validated mask-based file detection and optional filtering.

Benefits and Practical Applications

• Significant time savings when processing large sample sets.
• Standardized, reproducible quantification of targeted metabolites across experiments.
• Flexible report customization and compatibility with laboratory information management systems.

Future Trends and Opportunities
Advancements may include:

• Integration of machine-learning-driven peak detection to further reduce manual review.
• Real-time monitoring and adaptive thresholding during data acquisition.
• Expanded compatibility with emerging high-resolution MS techniques and vendor formats.

Conclusion
MS Scan 1.0 in Mnova Gears offers a robust, user-friendly platform for high-throughput metabolomics data analysis. By automating spectrum extraction and chromatogram quantification, it enhances reproducibility, reduces processing time, and delivers customizable reports suitable for diverse research and QA/QC environments.

Reference
No external literature references provided in the source document.