Division of Systems Biomedicine and Pharmacology
Biomedical Microscale Analytics
The Biomedical Microscale Analytics group is led by Dr. Rawi Ramautar. In present-day metabolomics, and bioanalysis in general, the analytical toolbox used encounters difficulties for the analysis of limited amounts of biological samples. As a result, a significant number of crucial biomedical/clinical questions cannot be addressed by the current metabolomics approach. The aim of the research in my group is to design microscale analytical separation techniques and workflows for highly sensitive metabolic profiling of size-limited biological samples. Moreover, attention will be paid to the development of microscale analytical tools for the enantioselective characterization of (endogenous) metabolites, thereby aiming to provide a unique and versatile tool in metabolomics.
On of the analytical technologies that will be considered for these purposes is capillary electrophoresis (CE)-mass spectrometry (MS). CE is a microscale technique providing highly efficient separations for (highly) polar and charged compounds, while requiring only minute amounts of sample. CE can be coupled to MS via various interfacing designs and the state-of-the-art in this area will be explored in order to allow hyphenation of CE and electrospray ionization (ESI)-MS under optimal conditions, i.e. where both the separation efficiency of CE and the ionization efficiency of ESI-MS are maximal. Tailor-made sample preparation strategies for limited amounts of biological samples will be developed. Another exciting field that is virtually unexplored in metabolomics is chirality. Therefore, a blend of chiral selectors will be evaluated to obtain a chiral perspective on the metabolic composition of volume-restricted samples by the CE-MS analytical technology.
The developed microscale analytical tools will be used to address relevant biomedical questions in the field of neuroscience, and other application areas intrinsically dealing with small sample amounts. The role of D-amino acids, a novel class of neuromodulators, and other chiral metabolites will be studied for various diseases. Overall, the analytical technologies and workflows developed in my group should enable especially those metabolomics studies that have so far been lacking. As such, research performed at Biomedical Microscale Analytics within the division of Systems Biomedicine and Pharmacology of the LACDR will provide novel analytical strategies for a deeper understanding of biological processes in sample-limited cases.
As outline above, CE-MS will be considered as a analytical main technology for volume-restricted metabolomics. For more information about the unique capabilities of this approach for metabolomics studies, please check the book "Capillary Electrophoresis - Mass Spectrometry for Metabolomics" edited by Dr. Rawi Ramautar, which will be published in May 2018 by the Royal Society of Chemistry.
In order to get an idea about the practical aspects of coupling CE to MS via a sheathless porous tip interface for metabolic profiling of cell culture samples, please consider the following video-protocol which is freely available at the Journal of Visualized Experiments.
- Ramautar R., Berger R., van der Greef J., Hankemeier T., Human metabolomics: Strategies to understand biology. Curr Opin Chem Biol 2013; 17:841-6.
- Ramautar R., Busnel J.M., Deelder A.M., Mayboroda O.A., Enhancing the coverage of the urinary metabolome by sheathless capillary electrophoresis-mass spectrometry. Anal Chem 2012; 84:885-92.
- Gulersonmez M.C., Lock S., Hankemeier T., Ramautar R., Sheathless capillary electrophoresis-mass spectrometry for anionic metabolic profiling. Electrophoresis 2016; 37:1007-14.
- Zhang W., Hankemeier T., Ramautar R., Next-generation capillary electrophoresis-mass spectrometry approaches in metabolomics. Curr Opin Biotechnol 2017; 43:1-7.
- Zhang W., Gulersonmez M.C., Hankemeier T., Ramautar R., Sheathless capillary electrophoresis-mass spectrometry for metabolic profiling of biological samples. Jove-J Vis Exp 2016; 116.