Prof. Christoph Thiele, Rheinische Friedrich-Wilhelms University Bonn
Aberrations in fatty acid metabolism are associated with pathological states and have become a focus of current research, particularly due to the interest in metabolic overload diseases. Special Mass spectrometry may help to understand and detect diseases such as metabolic syndrome or type 2 diabetes. For studying the lipid metabolism, it is common that labeled precursor substances are administered to a test system, in which they can be introduced into newly synthetized lipids. Well-known analysis methods introduce labeling with radioisotopes (such as 3H or 14C), stable isotopes (2H, 13C) or fluorescence labels (e.g. fluorescent lipids). Up to now, the lipid metabolism is mostly monitored by methods using radioactive tracer. All these known methods have one or more disadvantages, such as long analysis times in the range of several days, only low to moderate sensitivity or resolution, complex analysis methods or complex sample preparation before analysis.
The present innovative click-chemistry-based method allows tracing of fatty acid metabolism in virtually any biological system. It combines high sensitivity with excellent linearity and fast sample turnover. Since it is free of radioactivity, it can be combined with any other modern analysis technology and can be used in high-throughput applications.
PROvendis is offering licenses for the invention to interested companies on behalf of the University of Bonn. There is also the possibility of collaboration with the inventor.
In an improved and preferred method, multiplexing of samples can be carried out. After the labeling reaction, samples are combined for MS analysis. This increases the sample turnover and improves comparison by reducing stochastic experimental variations. Absolute quantification along with correction for labeling efficiency is achieved by internal standardization, using a set of alkyne-labeled synthetic standard lipids.
A European Patent Application has been filed so far.
Thiele, C. et al. (2012) Tracing fatty acid metabolism by click chemistry. ACS Chem. Biol. 7, 2004-11