Biology subjects

Klimentova, E.

Publications and source records attributed to Klimentova, E..

2 recordsLinked to original sources

bioRxiv2021

Endothelial Pannexin 1-TRPV4 channel signaling lowers pulmonary arterial pressure

Pannexin 1 (Panx1) is an ATP-efflux channel that controls endothelial function in the systemic circulation. However, the roles of endothelial Panx1 in resistance-sized pulmonary arteries (PAs) are unknown. Extracellular ATP dilates PAs through activation of endothelial TRPV4 (transient receptor potential vanilloid 4) ion channels. We hypothesized that endothelial Panx1-ATP- TRPV4 channel signaling promotes vasodilation and lowers pulmonary arterial pressure (PAP). Endothelial, but not smooth muscle, knockout of Panx1 or TRPV4 increased PA contractility and raised PAP. Panx1-effluxed extracellular ATP signaled through purinergic P2Y2 receptor (P2Y2R) to activate protein kinase C (PKC), which in turn activated endothelial TRPV4 channels. Finally, caveolin-1 provided a signaling scaffold for endothelial Panx1, P2Y2R, PKC, and TRPV4 channels in PAs, promoting their spatial proximity and enabling signaling interactions. These results indicate that endothelial Panx1-P2Y2R-TRPV4 channel signaling, facilitated by caveolin-1, reduces PA contractility and lowers PAP.

biochemistry↗

bioRxiv2020

PENGUINN: Precise Exploration of Nuclear G-quadruplexes Using Interpretable Neural Networks

G-quadruplexes (G4s) are a class of stable structural nucleic acid motifs that are known to play a role in a wide spectrum of genomic functions, such as DNA replication and transcription. The classical understanding of G4 structure points to four variable length guanine strands joined by variable length stretches of other nucleotides. Experiments using G4 immunoprecipitation and sequencing experiments have produced a high number of highly probable G4 forming genomic sequences. The expense and technical difficulty of experimental techniques highlights the need for computational approaches of G4 identification. Here, we present PENGUINN, a machine learning method based on Convolutional Neural Networks, that learns the characteristics of G4 sequences and accurately predicts G4s outperforming the state-of-the-art. We provide both a standalone implementation of the trained model, and a web application that can be used to evaluate sequences for their G4 potential.

bioinformatics↗