Untargeted metabolomics profiling in pediatric patients and adult populations indicates a connection between lipid imbalance and epilepsy.

Introduction: Epilepsy is a common central nervous system disorder characterized by abnormal brain electrical activity. We aimed to compare the metabolic profiles of plasma from patients with epilepsy across different etiologies, seizure frequency, seizure type, and patient age to try to identify common disrupted pathways. Material and methods: We used data from three separate cohorts. The first cohort (PED-C) consisted of 31 pediatric patients with suspicion of a genetic disorder with unclear etiology; the second cohort (AD-C) consisted of 250 adults from the Estonian Biobank (EstBB), and the third cohort consisted of 583 adults ≥ 69 years of age from the EstBB (ELD-C). We compared untargeted metabolomics and lipidomics data between individuals with and without epilepsy in each cohort. Results: In the PED-C, significant alterations (p-value <0.05) were detected in sixteen different glycerophosphatidylcholines (GPC), dimethylglycine and eicosanedioate (C20-DC). In the AD-C, nine significantly altered metabolites were found, mainly triacylglycerides (TAG), which are also precursors in the GPC synthesis pathway. In the ELD-C, significant changes in twenty metabolites including multiple TAGs were observed in the metabolic profile of participants with previously diagnosed epilepsy. Pathway analysis revealed that among the metabolites that differ significantly between epilepsy-positive and epilepsy-negative patients in the PED-C, the lipid superpathway (p = 3.2*10-4) and phosphatidylcholine (p = 9.3*10-8) and lysophospholipid (p = 5.9*10-3) subpathways are statistically overrepresented. Analogously, in the AD-C, the triacylglyceride subclass turned out to be statistically overrepresented (p = 8.5*10-5) with the lipid superpathway (p = 1.4*10-2). The presented p-values are FDR-corrected. Conclusion: Our results suggest that cell membrane fluidity may have a significant role in the mechanism of epilepsy, and changes in lipid balance may indicate epilepsy. However, further studies are needed to evaluate whether untargeted metabolomics analysis could prove helpful in diagnosing epilepsy earlier.

Experimental and Computational Study of Aminoacridines as MALDI(-)-MS Matrix Materials for the Analysis of Complex Samples.

Monoaminoacridines (1-, 2-, 3-, 4-, and 9-aminoacridine) were studied for suitability as matrices in the negative ion mode matrix-assisted laser desorption/ionization mass spectrometry (MALDI(-)-MS) analysis of various samples. This is the first study to examine 1-, 2-, and 4-aminoacridine as potential matrix material candidates for MALDI(-)-MS. In addition, spectral (UV-Vis absorption and fluorescence), proton transfer-related (basicity and autoprotolysis), and crystallization properties of these compounds were characterized experimentally and/or computationally. For testing the capabilities of these aminoacridines as matrix materials, four samples related to cultural heritage materials-stearic acid, colophony resin, dyer's madder dye, and a resinous case-study sample from a shipwreck-were analyzed with MALDI(-)-MS. A novel algorithm (implemented as an executable Python script) for MS data analysis was developed to compare the five matrix materials and to help mass spectrometrists rapidly identify peaks originating from the sample and matrix material. It was determined that all five of the studied aminoacridines can successfully be used as matrix materials in MALDI(-)-MS analysis. As an interesting finding, in several cases, the best mass spectra were obtained by using a relatively small amount of matrix material mixed with an excess amount of sample. 3- and 4-aminoacridine outperformed the other aminoacridines in the ease of obtaining acceptable spectra, average number of ions identified in the mass spectra, and low dependence of the sample-to-matrix mass ratio on experimental results.

Quantitative analysis of fluorescent ligand binding to dopamine D3 receptors using live-cell microscopy.

Dopamine receptors are G protein-coupled receptors that have several essential functions in the central nervous system. A better understanding of the regulatory mechanisms of ligand binding to the receptor may open new possibilities to affect the downstream signal transduction pathways. The majority of the available ligand binding assays use either membrane preparations, cell suspensions, or genetically modified receptors, which may give at least partially incorrect understanding of ligand binding. In this study, we implemented an assay combining fluorescence and bright-field microscopy to measure ligand binding to dopamine D3 receptors in live mammalian cells. For membrane fluorescence intensity quantification from microscopy images, we developed a machine learning-based user-friendly software membrane tools and incorporated it into a data management software aparecium that has been previously developed in our workgroup. For the experiments, a fluorescent ligand NAPS-Cy3B was synthesized by conjugating a dopaminergic antagonist N-(p-aminophenethyl)spiperone with a fluorophore Cy3B. The subnanomolar affinity of NAPS-Cy3B makes it a suitable ligand for the characterization of D3 receptors in live HEK293 cells. Using a microplate compatible automated widefield fluorescence microscope, together with the membrane tools software, enables the detection and quantification of ligand binding with a high-throughput. The live cell assay is suitable for the characterization of fluorescent ligand binding and also in the competition experiments for the screening of novel unlabeled dopaminergic ligands. We propose that this simple yet more native-like approach is feasible in GPCR research, as it enables the detection of ligand binding in an environment containing more components involved in the signal transduction cascade.

Design, synthesis and application of carbazole macrocycles in anion sensors.

Carboxylate sensing solid-contact ion-selective electrodes (ISEs) were created to provide a proof-of-concept ISE development process covering all aspects from in silico ionophore design to functional sensor characterization. The biscarbazolylurea moiety was used to synthesize methylene-bridged macrocycles of different ring size aiming to fine tune selectivity towards different carboxylates. Cyclization was achieved with two separate strategies, using either amide synthesis to access up to -[CH2]10- macrocycles or acyl halides to access up to -[CH2]14- macrocycles. Seventy-five receptor-anion complexes were modelled and studied with COSMO-RS, in addition to all free host molecules. In order to predict initial selectivity towards carboxylates, 1H NMR relative titrations were used to quantify binding in DMSO-d 6/H2O solvent systems of two proportions - 99.5%:0.5% m/m and 90.0%:10.0% m/m, suggesting initial selectivity towards acetate. Three ionophores were selected for successful sensor prototype development and characterization. The constructed ion-selective electrodes showed higher selectivity towards benzoate than acetate, i.e., the selectivity patterns of the final sensors deviated from that predicted by the classic titration experiments. While the binding constants obtained by NMR titration in DMSO-d 6/H2O solvent systems provided important guidance for sensor development, the results obtained in this work emphasize the importance of evaluating the binding behavior of receptors in real sensor membranes.