New Insights in CE-MS-based Metabolomics Nicolas Drouin (Presenter) University of Geneva Presenter Bio: I recently defenced my PhD. During my thesis work I focused on sample preparation and separation of highly polar compounds using electroassisted method such as electromembrane extraction and capillary electrophoresis respectively. In this context, I developped a new approach for features identification in untargeted metabolomic with CE-MS. This innovative approach is based on the conversion of migration time scale into an effective mobility (µeff) scale of the data and an experimental µeff based library of more than 400 endogenous compounds.

Authors: Nicolas Drouin, Julian Pezzati, Yoric Gagnebin, Victor Gonzalez-Ruiz, Julie Schappler, Serge Rudaz
School of Pharmaceutical Sciences, Unviersity of Geneva, Geneva, Switzerland

During this study, we developed an original workflow for features identification in CE-MS. This innovative approach is based on the conversion of migration time scale into an effective mobility (µeff) scale of data acquired in standardized conditions and an experimental µeff based library of more than 400 endogenous compounds.
This method allowed lab-to-lab identification of features from cell cultures.

Introduction

For years now, MS-based approaches are the gold standards in metabolomics , although the separation of charged and very polar molecules commonly found in biological samples remains challenging. In this context, CE-MS appears an attractive tool, as CE yields extremely high separation resolution and peak capacities when dealing with charged compounds. In addition, CE consumes very little volumes of samples so it is perfectly adapted to scarce biofluids. Despites their obvious advantages, CE-MS is still a marginal method for metabolomics, mainly because of (i) the lower sensitivity compared to LC, (ii) the numerous experimental conditions needed for a best coverage of metabolites and (iii) the lack of robustness due to the poor repeatability of the migration times.

Methods

To enable maximum metabolites coverage with a minimum of experimental conditions, a new method for the analysis of basic, neutral and acidic metabolites was developed using a single condition of capillary type, buffer composition, ESI mode, and sheath liquid composition. Normal and reverse CE polarity modes were used for basic/neutral and acidic compounds, respectively. Using a sheath liquid composed of ammonium acetate in iPrOH:H2O, only ESI in the positive mode was required, as acidic compounds were detected as [M+H]+ or as [M+NH4]+ammonium adducts.

Results

The new CE-ESI-Q-TOF/MS method was applied to the investigation of a recently proposed commercial Mass Spectrometry Metabolite Library. More than 450 compounds over 596 were detected, with the possibility to monitor negatively-charged compounds through their ammonium adducts. The effective mobility (µeff) of each compound was obtained for peak alignment prior to data pre-processing as well as a robust retention index for peak annotation and identification criterion. Metabolites’ coverage was compared to that obtained with conventional RPLC and HILIC conditions. CE-MS appeared more efficient for the analysis of very polar charged compounds such as amino acids, organic acids, and phosphorylated compounds. The method was eventually applied to the analysis of precipitated extracts of cellular cultures, and 77 features were identified. Unique annotation was not currently possible for 3 features corresponding to enantiomeric compounds, 2 features corresponding to 4 isotopomeric compounds, and 10 features corresponding to 25 possible isomeric compounds, mainly sugars, mono-phosphorylated sugars, and nucleotides-related compounds.

Conclusions & Discussion

An original CE-MS method was developed for the analysis of acidic and cationic compounds in acidic conditions by only switching the CE polarity. For the first time, a large database based on µeff was constituted, allowing the straightforward annotation of detected features in real biological samples, demonstrating the high level of complementarity proposed by this original approach for metabolomics. This work demonstrates the good complementarity of CE-MS and µeff based identification for polar ionized metabolites and the possibility to create a common database based on standardized CE-MS conditions.

Authors would like to acknowledge Dr Martin Greiner and Dr Christian Wenz from Agilent Technologies for the granting access to the CE-QTOF platform. Prof. Didier Picard and Mr Abhinav Joshi from the Department of Cell Biology, University of Geneva, are also acknowledged for kindly providing the cell culture extracts.