Monitoring of signal molecules in brain


Neurotransmitters are endogenous signal molecules responsible for the transmission of information between neurons in neuronal tissues. The communication is enabled due to the release of a neurotransmitter from the presynaptic terminal into the synapse, where it bonds to specific receptors of the postsynaptic neuron. The most common neurotransmitters are e.g. acetylcholine, monoamines (dopamine, serotonin, adrenaline, noradrenaline, histamine), amino acids or their salts (GABA, glutamate, glycine), purines (adenosine, ATP), prostaglandins and peptides (e.g. substance P, opioids, liberines, statins).

Our group deals with quantification of neurotransmitters in brain tissue and microdialyzates using the techniques of mass spectrometry. Monitoring of the concentration levels these substances plays an important role in the preclinical research of brain since it helps us understand the molecular principle of physiological and pathophysiological expressions of brain and the mechanism of action of psychoactive substances. We developed selective detection methods consisting of high performance chromatographic separation connected with tandem mass spectrometry (HPLC-MS/MS) for the determination of dopamine, serotonin, their main metabolites (homovanillic acid, 3-methoxytyramine, 3,4-dihydroxyphenylacetic acid and 5-hydroxy-3-indolacetic acid), GABA and glutamate, both in brain tissue and in microdyalizates.


Study on dopamine signal pathway using the methods of mass spectrometry

Dopamine belongs to one of the most important monoaminoergic neurotrasmitters. It plays role in mood control, cognitive functions, motorics, motivation and reward system. Changes in metabolism of dopamine have been described in many neuropsychiatric diseases, e.g. Parkinson’s disease, drug addiction, schizophrenia and ADHD.

In our laboratory we are developing HPLC-MS/MS methods for the identification and quantification of metabolic pathway of dopamine (Schneme 1). We apply the developed methods in a preclinical model of drug addictions and schizophrenia.

Schéma 1