The transporter associated with antigen processing (TAP) is an ATP-binding cassette (ABC) transporter essential to cellular immunity against viral infection. Some persistent viruses have evolved strategies to inhibit TAP so that they may go undetected by the immune system. The herpes simplex virus for example evades immune surveillance by blocking peptide transport with a small viral protein ICP47. In this study, we determined the structure of human TAP bound to ICP47 by electron cryo-microscopy (cryo-EM) to 4.0 Å. The structure shows that ICP47 traps TAP in an inactive conformation distinct from the normal transport cycle. The specificity and potency of ICP47 inhibition result from contacts between the tip of the helical hairpin and the apex of the transmembrane cavity. This work provides a clear molecular description of immune evasion by a persistent virus. It also establishes the molecular structure of TAP to facilitate mechanistic studies of the antigen presentation process.

PURPOSE: To improve the imaging quality of vessel walls with an endoesophageal Wireless Amplified NMR Detector (WAND).

METHODS: A cylindrically shaped double-frequency resonator has been constructed with a single metal wire that is self-connected by a pair of nonlinear capacitors. The double-frequency resonator can convert wirelessly provided pumping power into amplified MR signals. This compact design makes the detector easily insertable into a rodent esophagus.

RESULTS: The detector has good longitudinal and axial symmetry. Compared to an external surface coil, the WAND can enhance detection sensitivity by at least 5 times, even when the distance separation between the region of interest and the detector's cylindrical surface is twice the detector's own radius. Such detection capability enables us to observe vessel walls near the aortic arch and carotid bifurcation with elevated sensitivity.

CONCLUSION: A cylindrical MRI detector integrated with a wireless-powered amplifier has been developed as an endoesophageal detector to enhance detection sensitivity of vessel walls. This detector can greatly improve the imaging quality for vessel regions that are susceptible to atherosclerotic lesions. Magn Reson Med, 2016. © 2016 International Society for Magnetic Resonance in Medicine.

Mitochondria are essential organelles whose biogenesis, structure, and function are regulated by many signaling pathways. In this study we present evidence that, in hippocampal neurons, activation of the Sonic hedgehog (Shh) signaling pathway impacts multiple aspects of mitochondria. Mitochondrial mass was increased significantly in neurons treated with Shh. Using biochemical and fluorescence imaging analyses, we show that Shh signaling activity reduces mitochondrial fission and promotes mitochondrial elongation, at least in part, via suppression of the mitochondrial fission protein dynamin-like GTPase Drp1. Mitochondria from Shh-treated neurons were more electron-dense as revealed by electron microscopy, and had higher membrane potential and respiratory activity. We further show that Shh protects neurons against a variety of stresses, including the mitochondrial poison rotenone, amyloid β-peptide, hydrogen peroxide, and high levels of glutamate. Collectively, our data suggest a link between Shh pathway activity and the physiological properties of mitochondria in hippocampal neurons.

Cortical networks exhibit intrinsic dynamics that drive coordinated, large-scale fluctuations across neuronal populations and create noise correlations that impact sensory coding. To investigate the network-level mechanisms that underlie these dynamics, we developed novel computational techniques to fit a deterministic spiking network model directly to multi-neuron recordings from different rodent species, sensory modalities, and behavioral states. The model generated correlated variability without external noise and accurately reproduced the diverse activity patterns in our recordings. Analysis of the model parameters suggested that differences in noise correlations across recordings were due primarily to differences in the strength of feedback inhibition. Further analysis of our recordings confirmed that putative inhibitory neurons were indeed more active during desynchronized cortical states with weak noise correlations. Our results demonstrate that network models with intrinsically-generated variability can accurately reproduce the activity patterns observed in multi-neuron recordings and suggest that inhibition modulates the interactions between intrinsic dynamics and sensory inputs to control the strength of noise correlations.

New silicon technology is enabling large-scale electrophysiological recordings in vivo from hundreds to thousands of channels. Interpreting these recordings requires scalable and accurate automated methods for spike sorting, which should minimize the time required for manual curation of the results. Here we introduce KiloSort, a new integrated spike sorting framework that uses template matching both during spike detection and during spike clustering. KiloSort models the electrical voltage as a sum of template waveforms triggered on the spike times, which allows overlapping spikes to be identified and resolved. Unlike previous algorithms that compress the data with PCA, KiloSort operates on the raw data which allows it to construct a more accurate model of the waveforms. Processing times are faster than in previous algorithms thanks to batch-based optimization on GPUs. We compare KiloSort to an established algorithm and show favorable performance, at much reduced processing times. A novel post-clustering merging step based on the continuity of the templates further reduced substantially the number of manual operations required on this data, for the neurons with near-zero error rates, paving the way for fully automated spike sorting of multichannel electrode recordings.

Cortical networks exhibit intrinsic dynamics that drive coordinated, large-scale fluctuations across neuronal populations and create noise correlations that impact sensory coding. To investigate the network-level mechanisms that underlie these dynamics, we developed novel computational techniques to fit a deterministic spiking network model directly to multi-neuron recordings from different rodent species, sensory modalities, and behavioral states. The model generated correlated variability without external noise and accurately reproduced the diverse activity patterns in our recordings. Analysis of the model parameters suggested that differences in noise correlations across recordings were due primarily to differences in the strength of feedback inhibition. Further analysis of our recordings confirmed that putative inhibitory neurons were indeed more active during desynchronized cortical states with weak noise correlations. Our results demonstrate that network models with intrinsically-generated variability can accurately reproduce the activity patterns observed in multi-neuron recordings and suggest that inhibition modulates the interactions between intrinsic dynamics and sensory inputs to control the strength of noise correlations.

Temperature dependent sex determination (TSD) is the process by which the environmental temperature experienced during embryogenesis influences the sex of an organism, as in the red-eared slider turtle Trachemys scripta elegans. In accord with current paradigms of vertebrate sex determination, temperature is believed to exert its effects on sexual development in T. scripta entirely within the middle third of development, when the gonad is forming. However, whether temperature regulates the transcriptome in T. scripta early embryos in a manner that could influence secondary sex characteristics or establish a pro-male or pro-female environment has not been investigated. In addition, apart from a handful of candidate genes, very little is known about potential similarities between the expression cascade during TSD and the genetic cascade that drives mammalian sex determination. Here, we conducted an unbiased transcriptome-wide analysis of the effects of male- and female-promoting temperatures on the turtle embryo prior to gonad formation, and on the gonad during the temperature sensitive period. We found sexually dimorphic expression reflecting differences in steroidogenic enzymes and brain development prior to gonad formation. Within the gonad, we mapped a cascade of differential expression similar to the genetic cascade established in mammals. Using a Hidden Markov Model based clustering approach, we identified groups of genes that show heterochronic shifts between M. musculus and T. scripta. We propose a model in which multiple factors influenced by temperature accumulate during early gonadogenesis, and converge on the antagonistic regulation of aromatase to canalize sex determination near the end of the temperature sensitive window of development.

Major resources are now available to develop tools and technologies aimed at dissecting the circuitry and computations underlying behavior, unraveling the underpinnings of brain disorders, and understanding the neural substrates of cognition. Scientists from around the world shared their views around new tools and technologies to drive advances in neuroscience.

The neural control of appetite is important for understanding motivated behavior along with the present rising prevalence of obesity. Over the past several years, new tools for cell type-specific neuron activity monitoring and perturbation have enabled increasingly detailed analyses of the mechanisms underlying appetite-control systems. Three major neural circuits strongly and acutely influence appetite but with notably different characteristics. Although these circuits interact, they have distinct properties and thus appear to contribute to separate but interlinked processes influencing appetite, thereby forming three pillars of appetite control. Here, we summarize some of the key characteristics of appetite circuits that are emerging from recent work and synthesize the findings into a provisional framework that can guide future studies. Expected final online publication date for the Annual Review of Physiology Volume 79 is February 10, 2017. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

In Drosophila, the Apaf-1-related killer (Dark) forms an apoptosome that activates procaspases. To investigate function, we have determined a near-atomic structure of Dark double rings using cryo-electron microscopy. We then built a nearly complete model of the apoptosome that includes 7- and 8-blade β-propellers. We find that the preference for dATP during Dark assembly may be governed by Ser325, which is in close proximity to the 2' carbon of the deoxyribose ring. Interestingly, β-propellers in V-shaped domains of the Dark apoptosome are more widely separated, relative to these features in the Apaf-1 apoptosome. This wider spacing may be responsible for the lack of cytochrome c binding to β-propellers in the Dark apoptosome. Our structure also highlights the roles of two loss-of-function mutations that may block Dark assembly. Finally, the improved model provides a framework to understand apical procaspase activation in the intrinsic cell death pathway.