ABSTRACT
Gain-of-function (GOF) variants in K+ channels cause severe childhood epilepsies, but there are no mechanisms to explain how increased K+ currents lead to network hyperexcitability. Here, we introduce a human Na+-activated K+ (KNa) channel variant (KCNT1-Y796H) into mice and, using a multiplatform approach, find motor cortex hyperexcitability and early-onset seizures, phenotypes strikingly similar to those of human patients. Although the variant increases KNa currents in cortical excitatory and inhibitory neurons, there is an increase in the KNa current across subthreshold voltages only in inhibitory neurons, particularly in those with non-fast-spiking properties, resulting in inhibitory-neuron-specific impairments in excitability and action potential (AP) generation. We further observe evidence of synaptic rewiring, including increases in homotypic synaptic connectivity, accompanied by network hyperexcitability and hypersynchronicity. These findings support inhibitory-neuron-specific mechanisms in mediating the epileptogenic effects of KCNT1 channel GOF, offering cell-type-specific currents and effects as promising targets for therapeutic intervention.
Subject(s)
Action Potentials/genetics , Epilepsy/genetics , GABAergic Neurons/metabolism , Nerve Tissue Proteins/metabolism , Potassium Channels, Sodium-Activated/metabolism , Seizures/genetics , Animals , Disease Models, Animal , Humans , MiceABSTRACT
Cancer is a highly complex and heterogeneous disease and immunotherapy has shown promise as a therapeutic approach. The increased resolution afforded by single-cell analysis offers the hope of finding and characterizing previously underappreciated populations of cells that could prove useful in understanding cancer progression and treatment. Urologic and prostate cancers are inherently heterogeneous diseases, and the potential for single-cell analysis to help understand and develop immunotherapeutic approaches to treat these diseases is very exciting. In this review, we view cancer immunotherapy through a single-cell lens and discuss the state-of-the-art technologies that enable advances in this field.
Subject(s)
Immunotherapy/methods , Molecular Targeted Therapy/methods , Prostatic Neoplasms/genetics , Prostatic Neoplasms/therapy , Tumor Microenvironment/drug effects , Female , Forecasting , Humans , Male , Molecular Targeted Therapy/trends , Prognosis , Prostatic Neoplasms/pathology , Risk Assessment , Sequence Analysis, DNA , Sequence Analysis, RNA , Single-Cell Analysis , Treatment Outcome , Tumor Microenvironment/genetics , Urologic Neoplasms/genetics , Urologic Neoplasms/pathology , Urologic Neoplasms/therapyABSTRACT
Here we present an open-source R package 'meaRtools' that provides a platform for analyzing neuronal networks recorded on Microelectrode Arrays (MEAs). Cultured neuronal networks monitored with MEAs are now being widely used to characterize in vitro models of neurological disorders and to evaluate pharmaceutical compounds. meaRtools provides core algorithms for MEA spike train analysis, feature extraction, statistical analysis and plotting of multiple MEA recordings with multiple genotypes and treatments. meaRtools functionality covers novel solutions for spike train analysis, including algorithms to assess electrode cross-correlation using the spike train tiling coefficient (STTC), mutual information, synchronized bursts and entropy within cultured wells. Also integrated is a solution to account for bursts variability originating from mixed-cell neuronal cultures. The package provides a statistical platform built specifically for MEA data that can combine multiple MEA recordings and compare extracted features between different genetic models or treatments. We demonstrate the utilization of meaRtools to successfully identify epilepsy-like phenotypes in neuronal networks from Celf4 knockout mice. The package is freely available under the GPL license (GPL> = 3) and is updated frequently on the CRAN web-server repository. The package, along with full documentation can be downloaded from: https://cran.r-project.org/web/packages/meaRtools/.