Modeling interactions between voltage-gated Ca2+ channels and KCa1.1 channels

High voltage-activated (HVA) Cav channels form complexes with KCa1.1 channels, allowing reliable activation of KCa1.1 current through a nanodomain interaction. We recently found that low voltage-activated Cav3 calcium channels also create KCa1.1-Cav3 complexes. While coimmunoprecipitation studies again supported a nanodomain interaction, the sensitivity to calcium chelating agents was instead consistent with a microdomain interaction. A computational model of the KCa1.1-Cav3 complex suggested that multiple Cav3 channels were necessary to activate KCa1.1 channels, potentially causing the KCa1.1-Cav3 complex to be more susceptible to calcium chelators. Here, we expanded the model and compared it to a KCa1.1-Cav2.2 model to examine the role of Cav channel conductance and kinetics on KCa1.1 activation. As found for direct recordings, the voltage-dependent and kinetic properties of Cav3 channels were reflected in the activation of KCa1.1 current, including transient activation from lower voltages than other KCa1.1-Cav complexes. Substantial activation of KCa1.1 channels required the concerted activity of several Cav3.2 channels. Combined with the effect of EGTA, these results suggest that the Ca²⁺ domains of several KCa1.1-Cav3 complexes need to cooperate to generate sufficient [Ca²⁺]_i, despite the physical association between KCa1.1 and Cav3 channels. By comparison, Cav2.2 channels were twice as effective at activating KCa1.1 channels and a single KCa1.1-Cav2.2 complex would be self-sufficient. However, even though Cav3 channels generate small, transient currents, the regulation of KCa1.1 activity by Cav3 channels is possible if multiple complexes cooperate through microdomain interactions.     

Machine learning techniques for protein function prediction

Proteins play important roles in living organisms, and their function is directly linked with their structure. Due to the growing gap between the number of proteins being discovered and their functional characterization (in particular as a result of experimental limitations), reliable prediction of protein function through computational means has become crucial. This paper reviews the machine learning techniques used in the literature, following their evolution from simple algorithms such as logistic regression to more advanced methods like support vector machines and modern deep neural networks. Hyperparameter optimization methods adopted to boost prediction performance are presented. In parallel, the metamorphosis in the features used by these algorithms from classical physicochemical properties and amino acid composition, up to text-derived features from biomedical literature and learned feature representations using autoencoders, together with feature selection and dimensionality reduction techniques, are also reviewed. The success stories in the application of these techniques to both general and specific protein function prediction are discussed.     

The structure of the Caenorhabditis elegans manganese superoxide dismutase MnSOD‐3‐azide complex

C. elegans MnSOD‐3 has been implicated in the longevity pathway and its mechanism of catalysis is relevant to the aging process and carcinogenesis. The structures of MnSOD‐3 provide unique crystallographic evidence of a dynamic region of the tetrameric interface (residues 41–54). We have determined the structure of the MnSOD‐3‐azide complex to 1.77‐Å resolution. Analysis of this complex shows that the substrate analog, azide, binds end‐on to the manganese center as a sixth ligand and that it ligates directly to a third and new solvent molecule also positioned within interacting distance to the His30 and Tyr34 residues of the substrate access funnel. This is the first structure of a eukaryotic MnSOD‐azide complex that demonstrates the extended, uninterrupted hydrogen‐bonded network that forms a proton relay incorporating three outer sphere solvent molecules, the substrate analog, the gateway residues, Gln142, and the solvent ligand. This configuration supports the formation and release of the hydrogen peroxide product in agreement with the 5‐6‐5 catalytic mechanism for MnSOD. The high product dissociation constant k₄ of MnSOD‐3 reflects low product inhibition making this enzyme efficient even at high levels of superoxide.     

Patterns of sequence variation in the mitochondrial D-loop region of shrews

Direct sequencing of the mitochondrial displacement loop (D-loop) of shrews (genus Sorex) for the region between the tRNA(Pro) and the conserved sequence block-F revealed variable numbers of 79-bp tandem repeats. These repeats were found in all 19 individuals sequenced, representing three subspecies and one closely related species of the masked shrew group (Sorex cinereus cinereus, S. c. miscix, S. c. acadicus, and S. haydeni) and an outgroup, the pygmy shrew (S. hoyi). Each specimen also possessed an adjacent 76-bp imperfect copy of the tandem repeats. One individual was heteroplasmic for length variants consisting of five and seven copies of the 79-bp tandem repeat. The sequence of the repeats is conducive to the formation of secondary structure. A termination-associated sequence is present in each of the repeats and in a unique sequence region 5' to the tandem array as well. Mean genetic distance between the masked shrew taxa and the pygmy shrew was calculated separately for the unique sequence region, one of the tandem repeats, the imperfect repeat, and these three regions combined. The unique sequence region evolved more rapidly than the tandem repeats or the imperfect repeat. The small genetic distance between pairs of tandem repeats within an individual is consistent with a model of concerted evolution. Repeats are apparently duplicated and lost at a high rate, which tends to homogenize the tandem array. The rate of D- loop sequence divergence between the masked and pygmy shrews is estimated to be 15%-20%/Myr, the highest rate observed in D-loops of mammals. Rapid sequence evolution in shrews may be due either to their high metabolic rate and short generation time or to the presence of variable numbers of tandem repeats.      

Calcium dynamics during fertilization in C. elegans

Background

Of the animals typically used to study fertilization-induced calcium dynamics, none is as accessible to genetics and molecular biology as the model organism Caenorhabditis elegans. Motivated by the experimental possibilities inherent in using such a well-established model organism, we have characterized fertilization-induced calcium dynamics in C. elegans.

Results

Owing to the transparency of the nematode, we have been able to study the calcium signal in C. elegans fertilization in vivo by monitoring the fluorescence of calcium indicator dyes that we introduce into the cytosol of oocytes. In C. elegans, fertilization induces a single calcium transient that is initiated soon after oocyte entry into the spermatheca, the compartment that contains sperm. Therefore, it is likely that the calcium transient is initiated by contact with sperm. This calcium elevation spreads throughout the oocyte, and decays monotonically after which the cytosolic calcium concentration returns to that preceding fertilization. Only this single calcium transient is observed.

Conclusion

Development of a technique to study fertilization induced calcium transients opens several experimental possibilities, e.g., identification of the signaling events intervening sperm binding and calcium elevation, identifying the possible roles of the calcium elevation such as the completion of meiosis, the formation of the eggshell, and the establishing of the embryo's axis of symmetry.     

Distribution of amiloride-sensitive sodium channels in the oral cavity of the hamster

The distribution of amiloride-sensitive sodium channels (ASSCs) in taste buds isolated from the oral cavity of hamsters was assessed by patch clamp recording. In contrast to the case for rats, taste cells from the fungiform, foliate and vallate papillae and from the soft palate all contain functional ASSCs. The differential distribution of ASSCs between the hamster and the rat may be important for understanding the physiology underlying the differing behavioral responses of these species to sodium salts.