IDSL.UFA Assigns High-Confidence Molecular Formula Annotations for Untargeted LC/HRMS Data Sets in Metabolomics and Exposomics
- 22 September 2022
- journal article
- research article
- Published by American Chemical Society (ACS) in Analytical Chemistry
- Vol. 94 (39) , 13315-13322
Abstract
Untargeted LC/HRMS assays in metabolomics and exposomics aim to characterize the small molecule chemical space in a biospecimen. To gain maximum biological insights from these datasets, LC/HRMS peaks should be annotated with chemical and functional information including molecular formula, structure, chemical class and metabolic pathways. Among these, molecular formulas may be assigned to LC/HRMS peaks through matching theoretical and observed isotopic profiles (MS1) of the underlying ionized compound. For this, we have developed the Integrated Data Science Laboratory for Metabolomics and Exposomics – United Formula Annotation (IDSL.UFA) R package. In the untargeted metabolomics validation tests, IDSL.UFA assigned 54.31%–85.51% molecular formula for true positive annotations as the top hit, and 90.58%–100% within the top five hits. Molecular formula annotations were also supported by MS/MS data. We have implemented new strategies to 1) generate formula sources and their theoretical isotopic profiles 2) optimize the formula hits ranking for the individual and the aligned peak lists and 3) scale IDSL.UFA-based workflows for studies with larger sample sizes. Annotating the raw data for a publicly available pregnancy metabolome study using IDSL.UFA highlighted hundreds of new pregnancy related compounds, and also suggested presence of chlorinated perfluorotriether alcohols (Cl-PFTrEAs) in human specimens. IDSL.UFA is useful for human metabolomics and exposomics studies where we need to minimize the loss of biological insights in untargeted LC/HRMS datasets. The IDSL.UFA package is available in the R CRAN repository https://cran.r-project.org/package=IDSL.UFA. Detailed documentation and tutorials are also provided at www.ufa.idsl.me.Keywords
Funding Information
- National Institute of Environmental Health Sciences (P30ES023515, R01ES032831, U2CES026555, U2CES026561, U2CES030859)
- National Center for Advancing Translational Sciences (UL1TR001433, UL1TR004419)
This publication has 41 references indexed in Scilit:
- Mass Spectral Feature List Optimizer (MS-FLO): A Tool To Minimize False Positive Peak Reports in Untargeted Liquid Chromatography–Mass Spectroscopy (LC-MS) Data ProcessingAnalytical Chemistry, 2017
- xMSannotator: An R Package for Network-Based Annotation of High-Resolution Metabolomics DataAnalytical Chemistry, 2016
- Comprehensive Emerging Chemical Discovery: Novel Polyfluorinated Compounds in Lake Michigan TroutEnvironmental Science & Technology, 2016
- Accelerated Isotope Fine Structure Calculation Using Pruned Transition TreesAnalytical Chemistry, 2015
- A cross-platform toolkit for mass spectrometry and proteomicsNature Biotechnology, 2012
- Highly sensitive feature detection for high resolution LC/MSBMC Bioinformatics, 2008
- LIPID MAPS online tools for lipid researchNucleic Acids Research, 2007
- Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometryBMC Bioinformatics, 2007
- Kendrick Mass Defect Spectrum: A Compact Visual Analysis for Ultrahigh-Resolution Broadband Mass SpectraAnalytical Chemistry, 2001
- Nomenclature in evaluation of analytical methods including detection and quantification capabilities (IUPAC Recommendations 1995)Pure and Applied Chemistry, 1995