Recent advancements in MARS for computer driven-analysis in stable isotope labeling studies in untargeted metabolomics
73rd ASMS Conference on Mass Spectrometry. June 2025
Stefano Bonciarelli1; Paolo Tiberi2; Ismael Zamora1; Marta Piroddi3; Giovanna Ilaria Passeri2; Gabriele Cruciani4; Laura Goracci4
1Mass Spec Analytica, Sant Cugat del Vallés, Spain; 2Molecular Discovery Ltd, Borehamwood, United Kingdom; 3Molecular Horizon Srl, Bettona, Italy; 4University of Perugia, Perugia, Italy
Abstract
Introduction
High resolution mass spectrometry has become routinely used in untargeted metabolomics especially coupled with liquid chromatography. However, the huge amount of data generated by these approaches humpers an easy interpretation of the data. Complexity increases when stable isotope labelling (SIL) studies are performed. Indeed, unlabeled and labelled species coelute during the chromatography originating overlapping peaks to be distinguished during the analysis in order to annotate labelled and unlabelled species within the same dataset. In addition, the projection of the identified species in metabolic maps is crucial for the biological interpretation of results. Several software solutions have been to assist the data processing in untargeted metabolomic studies. However, only a few are equipped with tailored tools for SIL analysis.
Methods
Here, we describe the improvements of the computational workflow for SIL analysis already in place in the previous version of MARS (https://mass-analytica.com/products/mars/) a software solution for untargeted LC-MS untargeted metabolomics analysis.
Preliminary data
In particular, MARS allows the generation of database of partially and/or uniformly labelled species starting from a database of native metabolite. Native species can be easy edited and labelled with common isotopes (e.g. D, 13C, 15N, 34S, 37Cl). MS and MS/MS data of labelled species are automatically computed from those of native metabolites and stored in the database for identification purpose. In addition, 9 ready-to-use databases including native and labelled metabolites reported in SIL studies using a specific isotope tracers are available for download. The isotopic pattern clustering algorithm was also recently optimized to take into consideration instrument resolution and isotopes of any element. Native and labelled compounds identified as different ionization adducts and at different
level (MS or MS/MS) can be inspected together or separately for an easier investigation and for projection into the metabolic maps included in the package.
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