IDSL.CSA: Composite Spectra Analysis for Chemical Annotation of Untargeted Metabolomics Datasets.

Area of Science:

• Metabolomics
• Mass Spectrometry
• Bioinformatics

Background:

• Untargeted metabolomics using high-resolution mass spectrometry (HRMS) is powerful but limited by poor chemical annotation.
• Lack of MS2 fragmentation spectra often hinders the identification of metabolites in complex biological samples.

Approach:

• Developed the Integrated Data Science Laboratory for Metabolomics and Exposomics - Composite Spectra Analysis (IDSL.CSA) R package.
• IDSL.CSA generates composite mass spectra libraries from MS1-only data.
• Enables chemical annotation of liquid chromatography/high-resolution mass spectrometry (LC/HRMS) peaks without requiring MS2 fragmentation data.

Key Points:

• Achieved comparable annotation rates for endogenous metabolites in human blood samples using IDSL.CSA libraries versus traditional MS/MS libraries.
• IDSL.CSA is applicable to any untargeted metabolomics dataset from LC/HRMS or GC/HRMS instruments.
• Composite spectra libraries can be applied across independent studies, potentially uncovering missed biological insights.

Conclusions:

• IDSL.CSA significantly improves chemical annotation in untargeted metabolomics, overcoming limitations of missing MS2 data.
• The R package offers a versatile tool for researchers utilizing HRMS in metabolomics and exposomics.
• Facilitates broader data interpretation and discovery in biological and environmental sciences.