DropMS: Petroleomics Data Treatment Based in Web Server for High-Resolution Mass Spectrometry

Area of Science:

• Petroleum Geochemistry
• Analytical Chemistry
• Computational Chemistry

Background:

• High-resolution mass spectrometry is crucial for detailed oil analysis.
• Processing complex oil mass spectrometry data requires specialized tools and expertise.
• Existing methods can be cumbersome, necessitating user-friendly alternatives.

Purpose of the Study:

• To introduce DropMS, a novel, browser-based online tool for processing oil mass spectrometry data.
• To validate the accuracy of DropMS algorithms against established methods and real-world samples.
• To demonstrate the utility of processed data for quantitative property prediction.

Main Methods:

• Development of a user-friendly, server-based online tool (DropMS) for mass spectrometry data processing.
• Implementation of algorithms including S/N ratio filters, recalibration, and chemical formula assimilation.
• Utilization of Van Krevelen and Kendrick diagrams, and DBE vs C# plots for data visualization.
• Validation using Electrospray Ionization Positive-Ion Fourier-Transform Ion Cyclotron Resonance Mass Spectrometry (ESI(+)-FT-ICR/MS) data from Brazilian oil.
• Application of Partial Least-Squares (PLS) multivariate regression for property quantification.

Main Results:

• DropMS provides accurate processing of high-resolution oil mass spectrometry data.
• Validation showed good agreement with established software (Sierra Analytics DropMS and Composer) for heteroatomic class identification.
• PLS regression accurately predicted API density (R² = 0.971, RMSEC = 0.997) using processed FT-ICR MS spectra.

Conclusions:

• DropMS is an effective, accessible tool for analyzing complex oil mass spectrometry data.
• The tool facilitates robust data processing and visualization, aiding in chemical characterization.
• Accurate prediction of oil properties like API density is achievable using PLS regression on processed MS data.