Abstract

Novel LC-HRMS/MS and Stable Isotope Labelling Assisted Metabolomics Workflows and Data Processing Tools

Christoph Bueschl, PhD Student, University of Natural Resources and Life Sciences (BOKU), Vienna

Stable isotope labelling (SIL) assisted experiments are being used more frequently in untargeted metabolomics studies. Many advantages include improved annotation of metabolites [1], easy discrimination between truly biological information from noise or background signals and improved relative quantification across different samples. In this respect we recently developed three analytical workflows and software tools for a) the global extraction of metabolic features accessible via LC-HRMS [2], b) the study of certain tracers in living organisms with the aim to find their metabolisation products and c) improved LC-MS/MS fragment annotation. All three workflows mix natural and fully 13C labelled sample material prior to LC-HRMS/MS analysis. The software tools then recognise true biological information with the unique mirror symmetric isotopologue distributions originating from both the natural and uniformly 13C labelled isotopologues of the same metabolites for highly efficient two-dimensional data filtering and improved annotation of the respective metabolic features or fragments. In this respect the workflows are also excellently suited for evaluating the performance of the used analytical methods. The implemented workflows are exemplified with data from metabolomics studies of wheat and the pathogen Fusarium graminearum as well as the untargeted profiling of plant-derived mycotoxin-detoxification products in wheat [3].