A biophysical characterization of the folded domains of KCTD12: insights into interaction with the GABAB2 receptor

Recent investigations have shown that members of the KCTD family play important roles in fundamental biological processes. Despite their roles, very limited information is available on their structures and molecular organization. By combining different experimental and theoretical techniques, we have here characterized the two folded domains of KCTD12, an integral component and modulator of the GABA_B2 receptor. Secondary prediction methods and CD spectroscopy have shown that the N‐terminal domain KCTD12_BTB assumes an α/β structure, whereas the C‐terminal domain KCTD12_H1 is predominantly characterized by a β‐structure. Binding assays indicate that the two domains independently expressed show a good affinity for each other. This suggests that the overall protein is likely endowed with a rather compact structure with two interacting structured domains joint by a long disordered region. Notably, both KCTD12_BTB and KCTD12_H1 are tetrameric when individually expressed. This finding could modify the traditional view that ascribes only to POZ/BTB domain a specific oligomerization role. The first quantification of the affinity of KCTD12_POZ/BTB for the C‐terminal region of GABA_B2 shows that it falls in the low micromolar range. Interestingly, we also demonstrate that a GABA_B2‐related peptide is able to bind KCTD12_BTB with a very high affinity. This peptide may represent a useful tool for modulating KCTD12/GABA_B2 interaction in vitro and may also constitute the starting point for the development of peptidomimetic compounds with a potential for therapeutic applications. Copyright © 2013 John Wiley & Sons, Ltd.     

A common landscape for membrane‐active peptides

Three families of membrane‐active peptides are commonly found in nature and are classified according to their initial apparent activity. Antimicrobial peptides are ancient components of the innate immune system and typically act by disruption of microbial membranes leading to cell death. Amyloid peptides contribute to the pathology of diverse diseases from Alzheimer's to type II diabetes. Preamyloid states of these peptides can act as toxins by binding to and permeabilizing cellular membranes. Cell‐penetrating peptides are natural or engineered short sequences that can spontaneously translocate across a membrane. Despite these differences in classification, many similarities in sequence, structure, and activity suggest that peptides from all three classes act through a small, common set of physical principles. Namely, these peptides alter the Brownian properties of phospholipid bilayers, enhancing the sampling of intrinsic fluctuations that include membrane defects. A complete energy landscape for such systems can be described by the innate membrane properties, differential partition, and the associated kinetics of peptides dividing between surface and defect regions of the bilayer. The goal of this review is to argue that the activities of these membrane‐active families of peptides simply represent different facets of what is a shared energy landscape.     

A new method for identifying rapid decline dynamics in wild vertebrate populations

Tracking trends in the abundance of wildlife populations is a sensitive method for assessing biodiversity change due to the short time‐lag between human pressures and corresponding shifts in population trends. This study tests for proposed associations between different types of human pressures and wildlife population abundance decline‐curves and introduces a method to distinguish decline trajectories from natural fluctuations in population time‐series. First, we simulated typical mammalian population time‐series under different human pressure types and intensities and identified significant distinctions in population dynamics. Based on the concavity of the smoothed population trend and the algebraic function which was the closest fit to the data, we determined those differences in decline dynamics that were consistently attributable to each pressure type. We examined the robustness of the attribution of pressure type to population decline dynamics under more realistic conditions by simulating populations under different levels of environmental stochasticity and time‐series data quality. Finally, we applied our newly developed method to 124 wildlife population time‐series and investigated how those threat types diagnosed by our method compare to the specific threatening processes reported for those populations. We show how wildlife population decline curves can be used to discern between broad categories of pressure or threat types, but do not work for detailed threat attributions. More usefully, we find that differences in population decline curves can reliably identify populations where pressure is increasing over time, even when data quality is poor, and propose this method as a cost‐effective technique for prioritizing conservation actions between populations.     

A Conserved Role for Atlastin GTPases in Regulating Lipid Droplet Size

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