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Strain-Promoted Cycloadditions in Lipid Bilayers Triggered by Liposome Fusion.
Due to the variety of roles served by the cell membrane, its composition and structure are complex, making it difficult to study. Bioorthogonal reactions, such as the strain promoted azide-alkyne cycloaddition (SPAAC), are powerful tools for exploring the function of biomolecules in their native environment but have been largely unexplored within the context of lipid bilayers. Here, we developed a new approach to study the SPAAC reaction in liposomal membranes using azide- and strained alkyne-functionalized Förster resonance energy transfer (FRET) dye pairs. This study represents the first characterization of the SPAAC reaction between diffusing molecules inside liposomal membranes. Potential applications of this work include in situ bioorthogonal labeling of membrane proteins, improved understanding of membrane dynamics and fluidity, and the generation of new probes for biosensing assays.
Perilipin membrane integration determines lipid droplet heterogeneity in differentiating adipocytes.
The storage of fat within lipid droplets (LDs) of adipocytes is critical for whole-body health. Acute fatty acid (FA) uptake by differentiating adipocytes leads to the formation of at least two LD classes marked by distinct perilipins (PLINs). How this LD heterogeneity arises is an important yet unresolved cell biological problem. Here, we show that an unconventional integral membrane segment (iMS) targets the adipocyte specific LD surface factor PLIN1 to the endoplasmic reticulum (ER) and facilitates high-affinity binding to the first LD class. The other PLINs remain largely excluded from these LDs until FA influx recruits them to a second LD population. Preventing ER targeting turns PLIN1 into a soluble, cytoplasmic LD protein, reduces its LD affinity, and switches its LD class specificity. Conversely, moving the iMS to PLIN2 leads to ER insertion and formation of a separate LD class. Our results shed light on how differences in organelle targeting and disparities in lipid affinity of LD surface factors contribute to formation of LD heterogeneity.
Motor Complications in Parkinson's Disease: Results from 3343 Patients Followed for up to 12 Years.
BACKGROUND: Motor complications are well recognized in Parkinson's disease (PD), but their reported prevalence varies and functional impact has not been well studied. OBJECTIVES: To quantify the presence, severity, impact and associated factors for motor complications in PD. METHODS: Analysis of three large prospective cohort studies of recent-onset PD patients followed for up to 12 years. The MDS-UPDRS part 4 assessed motor complications and multivariable logistic regression tested for associations. Genetic risk score (GRS) for Parkinson's was calculated from 79 single nucleotide polymorphisms. RESULTS: 3343 cases were included (64.7% male). Off periods affected 35.0% (95% CI 33.0, 37.0) at 4-6 years and 59.0% (55.6, 62.3) at 8-10 years. Dyskinesia affected 18.5% (95% CI 16.9, 20.2) at 4-6 years and 42.1% (38.7, 45.5) at 8-10 years. Dystonia affected 13.4% (12.1, 14.9) at 4-6 years and 22.8% (20.1, 25.9) at 8-10 years. Off periods consistently caused greater functional impact than dyskinesia. Motor complications were more common among those with higher drug doses, younger age at diagnosis, female gender, and greater dopaminergic responsiveness (in challenge tests), with associations emerging 2-4 years post-diagnosis. Higher Parkinson's GRS was associated with early dyskinesia (0.026 ≤ P ≤ 0.050 from 2 to 6 years). CONCLUSIONS: Off periods are more common and cause greater functional impairment than dyskinesia. We confirm previously reported associations between motor complications with several demographic and medication factors. Greater dopaminergic responsiveness and a higher genetic risk score are two novel and significant independent risk factors for the development of motor complications.
ASPP2 maintains the integrity of mechanically stressed pseudostratified epithelia during morphogenesis.
During development, pseudostratified epithelia undergo large scale morphogenetic events associated with increased mechanical stress. Using a variety of genetic and imaging approaches, we uncover that in the mouse E6.5 epiblast, where apical tension is highest, ASPP2 safeguards tissue integrity. It achieves this by preventing the most apical daughter cells from delaminating apically following division events. In this context, ASPP2 maintains the integrity and organisation of the filamentous actin cytoskeleton at apical junctions. ASPP2 is also essential during gastrulation in the primitive streak, in somites and in the head fold region, suggesting that it is required across a wide range of pseudostratified epithelia during morphogenetic events that are accompanied by intense tissue remodelling. Finally, our study also suggests that the interaction between ASPP2 and PP1 is essential to the tumour suppressor function of ASPP2, which may be particularly relevant in the context of tissues that are subject to increased mechanical stress.
3,4-Ethylenedioxythiophene Hydrogels: Relating Structure and Charge Transport in Supramolecular Gels
Ionic charge transport is a ubiquitous language of communication in biological systems. As such, bioengineering is in constant need of innovative, soft, and biocompatible materials that facilitate ionic conduction. Low molecular weight gelators (LMWGs) are complex self-assembled materials that have received increasing attention in recent years. Beyond their biocompatible, self-healing, and stimuli responsive facets, LMWGs can be viewed as a “solid” electrolyte solution. In this work, we investigate 3,4-ethylenedioxythiophene (EDOT) as a capping group for a small peptide library, which we use as a system to understand the relationship between modes of assembly and charge transport in supramolecular gels. Through a combination of techniques including small-angle neutron scattering (SANS), NMR-based Van’t Hoff analysis, atomic force microscopy (AFM), rheology, four-point probe, and electrochemical impedance spectroscopy (EIS), we found that modifications to the peptide sequence result in distinct assembly pathways, thermodynamic parameters, mechanical properties, and ionic conductivities. Four-point probe conductivity measurements and electrochemical impedance spectroscopy suggest that ionic conductivity is approximately doubled by programmable gel assemblies with hollow cylinder morphologies relative to gels containing solid fibers or a control electrolyte. More broadly, it is hoped this work will serve as a platform for those working on charge transport of aqueous soft materials in general.
Current Research in Neurobiology, an experimental platform for innovation.
Welcome to Current Research in Neurobiology (CRNEUR), the gold open access, sibling journal to Current Opinion in Neurobiology, a journal for timely original research in neuroscience. At its very core, CRNEUR is a journal for creativity and innovation in science and publishing. As a journal, we ambitiously aim for CRNEUR to be a vehicle for what many of us envisioned an academic journal could be. Empowered by our commitment to fairness and transparency-to hold ourselves and others to a higher standard-here we describe our ambitions for innovation going forward. We need your help in this process and welcome your views via this survey (https://www.surveymonkey.co.uk/r/5LHWTML) and on social media (to start or join a discussion please use the hashtag #CRNEUR).
Hierarchical temporal prediction captures motion processing from retina to higher visual cortex
Visual neurons respond selectively to specific features that become increasingly complex in their form and dynamics from the eyes to the cortex. Retinal neurons prefer localized flashing spots of light, primary visual cortical (V1) neurons moving bars, and those in higher cortical areas, such as middle temporal (MT) cortex, favor complex features like moving textures. Whether there are general computational principles behind this diversity of response properties remains unclear. To date, no single normative model has been able to account for the hierarchy of tuning to dynamic inputs along the visual pathway. Here we show that hierarchical application of temporal prediction - representing features that efficiently predict future sensory input from past sensory input - can explain how neuronal tuning properties, particularly those relating to motion, change from retina to higher visual cortex. This suggests that the brain may not have evolved to efficiently represent all incoming information, as implied by some leading theories. Instead, the selective representation of sensory inputs that help in predicting the future may be a general neural coding principle, which when applied hierarchically extracts temporally-structured features that depend on increasingly high-level statistics of the sensory input.
Simple spectral transformations capture the contribution of peripheral processing to cortical responses to natural sounds
Processing in the sensory periphery involves various mechanisms that enable the detection and discrimination of sensory information. Despite their biological complexity, could these processing steps sub-serve a relatively simple transformation of sensory inputs, which are then transmitted to the CNS? Here we explored both biologically-detailed and very simple models of the auditory periphery to find the appropriate input to a phenomenological model of auditory cortical responses to natural sounds. We examined a range of cochlear models, from those involving detailed biophysical characteristics of the cochlea and auditory nerve to very pared-down spectrogram-like approximations of the information processing in these structures. We tested the capacity of these models to predict the time-course of single-unit neural responses recorded in the ferret primary auditory cortex, when combined with a linear non-linear encoding model. We show that a simple model based on a log-spaced, log-scaled power spectrogram with Hill-function compression performs as well as biophysically-detailed models of the cochlea and the auditory nerve. These findings emphasize the value of using appropriate simple models of the periphery when building encoding models of sensory processing in the brain, and imply that the complex properties of the auditory periphery may together result in a simpler than expected functional transformation of the inputs.
Simple spectral transformations capture the contribution of peripheral processing to cortical responses to natural sounds
Processing in the sensory periphery involves various mechanisms that enable the detection and discrimination of sensory information. Despite their biological complexity, could these processing steps sub-serve a relatively simple transformation of sensory inputs, which are then transmitted to the CNS? Here we explored both biologically-detailed and very simple models of the auditory periphery to find the appropriate input to a phenomenological model of auditory cortical responses to natural sounds. We examined a range of cochlear models, from those involving detailed biophysical characteristics of the cochlea and auditory nerve to very pared-down spectrogram-like approximations of the information processing in these structures. We tested the capacity of these models to predict the time-course of single-unit neural responses recorded in the ferret primary auditory cortex, when combined with a linear non-linear encoding model. We show that a simple model based on a log-spaced, log-scaled power spectrogram with Hill-function compression performs as well as biophysically-detailed models of the cochlea and the auditory nerve. These findings emphasize the value of using appropriate simple models of the periphery when building encoding models of sensory processing in the brain, and imply that the complex properties of the auditory periphery may together result in a simpler than expected functional transformation of the inputs.