13.1. 2020, Laboratory of Translational Metabolism

Laboratory of Translational Metabolism

PhD project: Novel analytical tools for the study of biological systems using mass spectrometry-based metabolomics

Over the last decade, mass spectrometry-based metabolomics and lipidomics have become established as the key platforms for comprehensive profiling of low-molecular-weight compounds in complex biological systems. Coupling liquid chromatography to mass spectrometry (LC-MS) is the preferred technique in metabolomics and lipidomics permitting effective compound separations and detection. However, there is still a lack of sufficient data on the metabolome characterizing biofluids (i.e., urine, plasma, serum) and tissues which can be easily accessible and reused at any time for future studies.

The aim of the PhD project is to focus on novel approaches in metabolomics workflow such as (i) merging targeted and untargeted methods, (ii) standardization and harmonization of the methods, and (iii) extending the breadth and scope of polar metabolites, complex lipids, and various exogenous compounds to ultimately deliver a comprehensive database of a wide range of metabolites in various biological matrices.

Candidate’s profile (requirements):

We are seeking outstanding self-motivated candidates with master's degree or equivalent in analytical chemistry, biochemistry, bioinformatics or related fields, or those expecting to obtain their degree this year. Candidates should be fluent in English. Experience with LC-MS analysis, data processing as well as statistical analysis is advantage.

Supervisor: Assoc. Prof. Tomas Cajka, Ph.D. (tomas.cajka@fgu.cas.cz)

Relevant publications:

T. Cajka, O. Fiehn: Toward merging untargeted and targeted methods in mass spectrometry-based metabolomics and lipidomics. Analytical Chemistry 88 (2016) 524–545. (doi: 10.1021/acs.analchem.5b04491)
T. Cajka, J.T. Smilowitz, O. Fiehn: Validating quantitative untargeted lipidomics across nine liquid chromatography–high-resolution mass spectrometry platforms. Analytical Chemistry 89 (2017) 12360–12368. (doi: 10.1021/acs.analchem.7b03404)
H. Tsugawa, T. Cajka, T. Kind, Y. Ma, B. Higgins, K. Ikeda, M. Kanazawa, J. VanderGheynst, O. Fiehn, M. Arita: MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis. Nature Methods 12 (2015) 523–526. (doi: 10.1038/nmeth.3393)
H. Tsugawa, T. Kind, R. Nakabayashi, D. Yukihira, W. Tanaka, T. Cajka, K. Saito, O. Fiehn, M. Arita: Hydrogen rearrangement rules: Computational MS/MS fragmentation and structure elucidation using MS-FINDER software. Analytical Chemistry 88 (2016) 7946–7958 (doi: 10.1021/acs.analchem.6b00770)