Carrillo, E. | Search bioRxiv

bioRxiv2021

TRICLOSAN IS A KCNQ3 POTASSIUM CHANNEL ACTIVATOR

KCNQ channels participate in the physiology of several cell types. In neurons of the central nervous system, the primary subunits are KCNQ2, 3 and 5. Activation of these channels silence the neurons, limiting action potential duration and preventing high-frequency action potential burst. Mutation of the KCNQ genes are associated with a wide spectrum of phenotypes characterized by hyperexcitability. Activation of KCNQ channels is an attractive strategy to treat epilepsy and other hyperexcitability conditions as are the evolution of stroke and traumatic brain injury. In this work we show that triclosan, a bactericide widely used in personal care products, activates the KCNQ3 channels but not the KCNQ2. Triclosan induces a voltage shift in the activation, increases the conductance and slows the closing of the channel. The effect is independent of PIP2. The putative binding site is located in the pore region but is distinct from the binding site for retigabine. Our results indicate that triclosan is a new activator for KCNQ channels.

biophysics↗

bioRxiv2021

Alignment of multiple metabolomics LC-MS datasets from disparate diseases to reveal fever-associated metabolites

Acute febrile illnesses are still a major cause of mortality and morbidity globally, particularly in low to middle income countries. The aim of this study was to determine any possible metabolic commonalities of patients infected with disparate pathogens that cause fever. Three liquid chromatography-mass spectrometry (LC-MS) datasets investigating the metabolic effects of malaria, leishmaniasis and Zika virus infection were used. The retention time (RT) drift between the datasets was determined using landmarks obtained from the standard reference mixtures generally used in the quality control of the LC-MS experiments. We used fitted Gaussian Process models (GPs) to perform a high level correction of the RT drift between the experiments, followed by standard peakset alignment between the samples with corrected RTs of the three LC-MS datasets. Statistical analysis, annotation and pathway analysis of the integrated peaksets were subsequently performed. Metabolic dysregulation patterns common across the datasets were identified, with kynurenine pathway being the most affected pathway between all three fever-associated datasets.

bioinformatics↗