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Neurons collect their inputs from other neurons by sending out arborized dendritic structures. However, the relationship between the shape of dendrites and the precise organization of synaptic inputs in the neural tissue remains unclear. Inputs could be distributed in tight clusters, entirely randomly or else in a regular grid-like manner. Here, we analyze dendritic branching structures using a regularity index R, based on average nearest neighbor distances between branch and termination points, characterizing their spatial distribution. We find that the distributions of these points depend strongly on cell types, indicating possible fundamental differences in synaptic input organization. Moreover, R is independent of cell size and we find that it is only weakly correlated with other branching statistics, suggesting that it might reflect features of dendritic morphology that are not captured by commonly studied branching statistics. We then use morphological models based on optimal wiring principles to study the relation between input distributions and dendritic branching structures. Using our models, we find that branch point distributions correlate more closely with the input distributions while termination points in dendrites are generally spread out more randomly with a close to uniform distribution. We validate these model predictions with connectome data. Finally, we find that in spatial input distributions with increasing regularity, characteristic scaling relationships between branching features are altered significantly. In summary, we conclude that local statistics of input distributions and dendrite morphology depend on each other leading to potentially cell type specific branching features.
Glucokinase (GK) is a key enzyme of glucose metabolism in liver and pancreatic beta-cells, and small molecule activators of GK (GKAs) are under evaluation for the treatment of type 2 diabetes. In liver, GK activity is controlled by the GK regulatory protein (GKRP), which forms an inhibitory complex with the enzyme. Here, we performed isothermal titration calorimetry and surface plasmon resonance experiments to characterize GK-GKRP binding and to study the influence that physiological and pharmacological effectors of GK have on the protein-protein interaction. In the presence of fructose-6-phosphate, GK-GKRP complex formation displayed a strong entropic driving force opposed by a large positive enthalpy; a negative change in heat capacity was observed (Kd = 45 nm, DeltaH = 15.6 kcal/mol, TDeltaS = 25.7 kcal/mol, DeltaCp = -354 cal mol(-1) K(-1)). With k(off) = 1.3 x 10(-2) s(-1), the complex dissociated quickly. The thermodynamic profile suggested a largely hydrophobic interaction. In addition, effects of pH and buffer demonstrated the coupled uptake of one proton and indicated an ionic contribution to binding. Glucose decreased the binding affinity between GK and GKRP. This decrease was potentiated by an ATP analogue. Prototypical GKAs of the amino-heteroaryl-amide type bound to GK in a glucose-dependent manner and impaired the association of GK with GKRP. This mechanism might contribute to the antidiabetic effects of GKAs.
Capoeta damascina was earlier considered by many authors as one of the most common freshwater fish species found throughout the Levant, Mesopotamia, Turkey, and Iran. However, owing to a high variation in morphological characters among and within its various populations, 17 nominal species were described, several of which were regarded as valid by subsequent revising authors. Capoeta damascina proved to be a complex of closely related species, which had been poorly studied. The current study aims at defining C. damascina and the C. damascina species complex. It investigates phylogenetic relationships among the various members of the C. damascina complex, based on mitochondrial and nuclear DNA sequences. Phylogenetic relationships were projected against paleogeographical events to interpret the geographic distribution of the taxa under consideration in relation to the area’s geological history. Samples were obtained from throughout the geographic range and were subjected to genetic analyses, using two molecular markers targeting the mitochondrial cytochrome oxidase I (n = 103) and the two adjacent divergence regions (D1-D2) of the nuclear 28S rRNA genes (n = 65). Six closely related species were recognized within the C. damascina complex, constituting two main lineages: A western lineage represented by C. caelestis, C. damascina, and C. umbla and an eastern lineage represented by C. buhsei, C. coadi, and C. saadii. The results indicate that speciation of these taxa is rather a recent event. Dispersal occurred during the Pleistocene, resulting in present-day distribution patterns. A coherent picture of the phylogenetic relationships and evolutionary history of the C. damascina species complex is drawn, explaining the current patterns of distribution as a result of paleogeographic events and ecological adaptations.
We examined the feedback between the major protein degradation pathway, the ubiquitin-proteasome system (UPS), and protein synthesis in rat and mouse neurons. When protein degradation was inhibited, we observed a coordinate dramatic reduction in nascent protein synthesis in neuronal cell bodies and dendrites. The mechanism for translation inhibition involved the phosphorylation of eIF2α, surprisingly mediated by eIF2α kinase 1, or heme-regulated kinase inhibitor (HRI). Under basal conditions, neuronal expression of HRI is barely detectable. Following proteasome inhibition, HRI protein levels increase owing to stabilization of HRI and enhanced translation, likely via the increased availability of tRNAs for its rare codons. Once expressed, HRI is constitutively active in neurons because endogenous heme levels are so low; HRI activity results in eIF2α phosphorylation and the resulting inhibition of translation. These data demonstrate a novel role for neuronal HRI that senses and responds to compromised function of the proteasome to restore proteostasis.
Binding free energy calculations that make use of alchemical pathways are becoming increasingly feasible thanks to advances in hardware and algorithms. Although relative binding free energy (RBFE) calculations are starting to find widespread use, absolute binding free energy (ABFE) calculations are still being explored mainly in academic settings due to the high computational requirements and still uncertain predictive value. However, in some drug design scenarios, RBFE calculations are not applicable and ABFE calculations could provide an alternative. Computationally cheaper end-point calculations in implicit solvent, such as molecular mechanics Poisson–Boltzmann surface area (MMPBSA) calculations, could too be used if one is primarily interested in a relative ranking of affinities. Here, we compare MMPBSA calculations to previously performed absolute alchemical free energy calculations in their ability to correlate with experimental binding free energies for three sets of bromodomain–inhibitor pairs. Different MMPBSA approaches have been considered, including a standard single-trajectory protocol, a protocol that includes a binding entropy estimate, and protocols that take into account the ligand hydration shell. Despite the improvements observed with the latter two MMPBSA approaches, ABFE calculations were found to be overall superior in obtaining correlation with experimental affinities for the test cases considered. A difference in weighted average Pearson () and Spearman () correlations of 0.25 and 0.31 was observed when using a standard single-trajectory MMPBSA setup ( = 0.64 and = 0.66 for ABFE; = 0.39 and = 0.35 for MMPBSA). The best performing MMPBSA protocols returned weighted average Pearson and Spearman correlations that were about 0.1 inferior to ABFE calculations: = 0.55 and = 0.56 when including an entropy estimate, and = 0.53 and = 0.55 when including explicit water molecules. Overall, the study suggests that ABFE calculations are indeed the more accurate approach, yet there is also value in MMPBSA calculations considering the lower compute requirements, and if agreement to experimental affinities in absolute terms is not of interest. Moreover, for the specific protein–ligand systems considered in this study, we find that including an explicit ligand hydration shell or a binding entropy estimate in the MMPBSA calculations resulted in significant performance improvements at a negligible computational cost.
The sequenced genome of the poly-extremophile Exiguobacterium sp. S17, isolated from modern stromatolites at Laguna Socompa (3,570 m), a High-Altitude Andean Lake (HAAL) in Argentinean Puna revealed a putative proteorhodopsin-encoding gene. The HAAL area is exposed to the highest UV irradiation on Earth, making the microbial community living in the stromatolites test cases for survival strategies under extreme conditions. The heterologous expressed protein E17R from Exiguobacterium (248 amino acids, 85% sequence identity to its ortholog ESR from E. sibiricum) was assembled with retinal displaying an absorbance maximum at 524 nm, which makes it a member of the green-absorbing PR-subfamily. Titration down to low pH values (eventually causing partial protein denaturation) indicated a pK value between two and three. Global fitting of data from laser flash-induced absorption changes gave evidence for an early red-shifted intermediate (its formation being below the experimental resolution) that decayed (τ1 = 3.5 μs) into another red-shifted intermediate. This species decayed in a two-step process (τ2 = 84 μs, τ3 = 11 ms), to which the initial state of E17-PR was reformed with a kinetics of 2 ms. Proton transport capability of the HAAL protein was determined by BLM measurements. Additional blue light irradiation reduced the proton current, clearly identifying a blue light absorbing, M-like intermediate. The apparent absence of this intermediate is explained by closely matching formation and decay kinetics.
Microplastics (MPs) are ubiquitous and persistent pollutants, and have been detected in a wide variety of media, from soils to aquatic systems. MPs, consisting primarily of polyethylene, polypropylene, and polyacrylamide polymers, have recently been found in 12% of samples of honey collected in Ecuador. Recently, MPs have also been identified in honey bees collected from apiaries in Copenhagen, Denmark, as well as nearby semiurban and rural areas. Given these documented exposures, assessment of their effects is critical for understanding the risks of MP exposure to honey bees. Exposure to polystyrene (PS)-MPs decreased diversity of the honey bee gut microbiota, followed by changes in gene expression related to oxidative damage, detoxification, and immunity. As a result, the aim of this perspective was to investigate whether wide-spread prevalence of MPs might have unintended negative effects on health and fitness of honey bees, as well as to draw the scientific community’s attention to the possible risks of MPs to the fitness of honey bees. Several research questions must be answered before MPs can be considered a potential threat to bees.
Anaerobic ammonium oxidation (anammox) is a major process in the biogeochemical nitrogen cycle in which nitrite and ammonium are converted to dinitrogen gas and water through the highly reactive intermediate hydrazine. So far, it is unknown how anammox organisms convert the toxic hydrazine into nitrogen and harvest the extremely low potential electrons (−750 mV) released in this process. We report the crystal structure and cryo electron microscopy structures of the responsible enzyme, hydrazine dehydrogenase, which is a 1.7 MDa multiprotein complex containing an extended electron transfer network of 192 heme groups spanning the entire complex. This unique molecular arrangement suggests a way in which the protein stores and releases the electrons obtained from hydrazine conversion, the final step in the globally important anammox process.
Symbiotic nitrogen fixation (SNF) in root nodules of grain legumes such as chickpea is a highly complex process that drastically affects the gene expression patterns of both the prokaryotic as well as eukaryotic interacting cells. A successfully established symbiotic relationship requires mutual signaling mechanisms and a continuous adaptation of the metabolism of the involved cells to varying environmental conditions. Although some of these processes are well understood today many of the molecular mechanisms underlying SNF, especially in chickpea, remain unclear. Here, we reannotated our previously published transcriptome data generated by deepSuperSAGE (Serial Analysis of Gene Expression) to the recently published draft genome of chickpea to assess the root- and nodule-specific transcriptomes of the eukaryotic host cells. The identified gene expression patterns comprise up to 71 significantly differentially expressed genes and the expression of twenty of these was validated by quantitative real-time PCR with the tissues from five independent biological replicates. Many of the differentially expressed transcripts were found to encode proteins implicated in sugar metabolism, antioxidant defense as well as biotic and abiotic stress responses of the host cells, and some of them were already known to contribute to SNF in other legumes. The differentially expressed genes identified in this study represent candidates that can be used for further characterization of the complex molecular mechanisms underlying SNF in chickpea.