Automatic recalibration and processing of tandem mass spectra using formula annotation

Area of Science:

• Analytical Chemistry
• Computational Chemistry

Background:

• High accuracy, high resolution tandem mass spectrometry (MS/MS) is increasingly used, but limited spectral databases hinder its application.
• Manual processing of MS/MS data for database submission is time-consuming and complex.

Purpose of the Study:

• To develop an automated workflow for processing MS/MS data to generate high-quality spectra for public databases.
• To improve the accuracy and utility of MS/MS spectral data for compound identification.

Main Methods:

• An automated workflow using formula annotation for recalibration and noise reduction was developed.
• Seventy pesticide reference standards were analyzed using LTQ-Orbitrap XL MS/MS.
• The workflow was implemented as an R package (RMassBank) for generating MassBank records.

Main Results:

• A total of 944 high-quality MS/MS spectra were generated and uploaded to MassBank.
• The automated workflow significantly improved the ranking of correct molecular formulas in spectral database searches.
• Nitrogen adduct formation was observed, demonstrating the value of high accuracy MS/MS for interpretation.

Conclusions:

• The developed automated workflow effectively generates high-quality, recalibrated MS/MS spectra suitable for public databases.
• This approach addresses the need for more comprehensive MS/MS spectral data, aiding compound identification and spectral interpretation.
• The RMassBank R package offers a flexible solution for processing diverse MS/MS datasets.