Gating of a pH-Sensitive K2P Potassium Channel by an Electrostatic Effect of Basic Sensor Residues on the Selectivity Filter

K+ channels share common selectivity characteristics but exhibit a wide diversity in how they are gated open. Leak K2P K+ channels TASK-2, TALK-1 and TALK-2 are gated open by extracellular alkalinization. The mechanism for this alkalinization-dependent gating has been proposed to be the neutralization of the side chain of a single arginine (lysine in TALK-2) residue near the pore of TASK-2, which occurs with the unusual pKa of 8.0. We now corroborate this hypothesis by transplanting the TASK-2 extracellular pH (pHo) sensor in the background of a pHo-insensitive TASK-3 channel, which leads to the restitution of pHo-gating. Using a concatenated channel approach, we also demonstrate that for TASK-2 to open, pHo sensors must be neutralized in each of the two subunits forming these dimeric channels with no apparent cross-talk between the sensors. These results are consistent with adaptive biasing force analysis of K+ permeation using a model selectivity filter in wild-type and mutated channels. The underlying free-energy profiles confirm that either a doubly or a singly charged pHo sensor is sufficient to abolish ion flow. Atomic detail of the associated mechanism reveals that, rather than a collapse of the pore, as proposed for other K2P channels gated at the selectivity filter, an increased height of the energetic barriers for ion translocation accounts for channel blockade at acid pHo. Our data, therefore, strongly suggest that a cycle of protonation/deprotonation of pHo-sensing arginine 224 side chain gates the TASK-2 channel by electrostatically tuning the conformational stability of its selectivity filter

APBSmem: A Graphical Interface for Electrostatic Calculations at the Membrane

Electrostatic forces are one of the primary determinants of molecular interactions. They help guide the folding of proteins, increase the binding of one protein to another and facilitate protein-DNA and protein-ligand binding. A popular method for computing the electrostatic properties of biological systems is to numerically solve the Poisson-Boltzmann (PB) equation, and there are several easy-to-use software packages available that solve the PB equation for soluble proteins. Here we present a freely available program, called APBSmem, for carrying out these calculations in the presence of a membrane. The Adaptive Poisson-Boltzmann Solver (APBS) is used as a back-end for solving the PB equation, and a Java-based graphical user interface (GUI) coordinates a set of routines that introduce the influence of the membrane, determine its placement relative to the protein, and set the membrane potential. The software Jmol is embedded in the GUI to visualize the protein inserted in the membrane before the calculation and the electrostatic potential after completing the computation. We expect that the ease with which the GUI allows one to carry out these calculations will make this software a useful resource for experimenters and computational researchers alike. Three examples of membrane protein electrostatic calculations are carried out to illustrate how to use APBSmem and to highlight the different quantities of interest that can be calculated

Phylogenetic, structural, and functional characterization of AMT3;1, an ammonium transporter induced by mycorrhization among model grasses

In the arbuscular mycorrhizal (AM) symbiosis, plants satisfy part of their nitrogen (N) requirement through the AM pathway. In sorghum, the ammonium transporters (AMT) AMT3;1, and to a lesser extent AMT4, are induced in cells containing developing arbuscules. Here, we have characterized orthologs of AMT3;1 and AMT4 in four other grasses in addition to sorghum. AMT3;1 and AMT4 orthologous genes are induced in AM roots, suggesting that in the common ancestor of these five plant species, both AMT3;1 and AMT4 were already present and upregulated upon AM colonization. An artificial microRNA approach was successfully used to downregulate either AMT3;1 or AMT4 in rice. Mycorrhizal root colonization and hyphal length density of knockdown plants were not affected at that time, indicating that the manipulation did not modify the establishment of the AM symbiosis and the interaction between both partners. However, expression of the fungal phosphate transporter FmPT was significantly reduced in knockdown plants, indicating a reduction of the nutrient fluxes from the AM fungus to the plant. The AMT3;1 knockdown plants (but not the AMT4 knockdown plants) were significantly less stimulated in growth by AM fungal colonization, and uptake of both (15)N and (33)P from the AM fungal network was reduced. This confirms that N and phosphorus nutrition through the mycorrhizal pathway are closely linked. But most importantly, it indicates that AMT3;1 is the prime plant transporter involved in the mycorrhizal ammonium transfer and that its function during uptake of N cannot be performed by AMT4

Self-Learning Adaptive Umbrella Sampling Method for the Determination of Free Energy Landscapes in Multiple Dimensions

The potential of mean force describing conformational changes of biomolecules is a central quantity for understanding the function of biomolecular systems. Calculating an energy landscape of a process that depends on three or more reaction coordinates requires extensive computational power, making some multidimensional calculations practically impossible. Here, we present an efficient automatized umbrella sampling strategy for calculating a multidimensional potential of mean force. The method progressively learns by itself, through a feedback mechanism, which regions of a multidimensional space are worth exploring and automatically generates a set of umbrella sampling windows that is adapted to the system. The selflearning adaptive umbrella sampling method is first explained with illustrative examples based on simplified reduced model systems and then applied to two nontrivial situations: the conformational equilibrium of the pentapeptide Met-enkephalin in solution and ion permeation in the KcsA potassium channel. With this method, it is demonstrated that a significant smaller number of umbrella windows needs to be employed to characterize the free energy landscape over the most relevant regions without any loss in accuracy

A Multipoint Hydrogen-Bond Network Underlying KcsA C-Type Inactivation

In the prokaryotic potassium channel KcsA activation gating at the inner bundle gate is followed by C-type inactivation at the selectivity filter. Entry into the C-type inactivated state has been directly linked to the strength of the H-bond interaction between residues Glu-71 and Asp-80 behind the filter, and is allosterically triggered by the rearrangement of the inner bundle gate. Here, we show that H-bond pairing between residues Trp-67 and Asp-80, conserved in most K+ channels, constitutes another critical interaction that determines the rate and extent of KcsA C-type inactivation. Disruption of the equivalent interaction in Shaker (Trp-434-Asp-447) and Kv1.2 (Trp-366-Asp-379) leads also to modulation of the inactivation process, suggesting that these residues also play an analogous role in the inactivation gating of Kv channels. The present results show that in KcsA C-type inactivation gating is governed by a multipoint hydrogen-bond network formed by the triad Trp-67-Glu71-Asp-80. This triad exerts a critical role in the dynamics and conformational stability of the selectivity filter and might serve as a general modulator of selectivity filter gating in other members of the K+ channel family