A pathogenetic feature of Alzhemier disease is the aggregation of monomeric beta-amyloid proteins (Abeta) to form oligomers. Usually these oligomers of long peptides aggregate on time scales of microseconds or longer, making computational studies using atomistic molecular dynamics models prohibitively expensive and making it essential to develop computational models that are cheaper and at the same time faithful to physical features of the process. We benchmark the ability of our implicit solvent model to describe equilibrium and dynamic properties of monomeric Abeta(10-35) using all-atom Langevin dynamics (LD) simulations, since Alphabeta(10-35) is the only fragment whose monomeric properties have been measured. The accuracy of the implicit solvent model is tested by comparing its predictions with experiment and with those from a new explicit water MD simulation, (performed using CHARMM and the TIP3P water model) which is approximately 200 times slower than the implicit water simulations. The dependence on force field is investigated by running multiple trajectories for Alphabeta(10-35) using the CHARMM, OPLS-aal, and GS-AMBER94 force fields, whereas the convergence to equilibrium is tested for each force field by beginning separate trajectories from the native NMR structure, a completely stretched structure, and from unfolded initial structures. The NMR order parameter, S2, is computed for each trajectory and is compared with experimental data to assess the best choice for treating aggregates of Alphabeta. The computed order parameters vary significantly with force field. Explicit and implicit solvent simulations using the CHARMM force fields display excellent agreement with each other and once again support the accuracy of the implicit solvent model. Alphabeta(10-35) exhibits great flexibility, consistent with experiment data for the monomer in solution, while maintaining a general strand-loop-strand motif with a solvent-exposed hydrophobic patch that is believed to be important for aggregation. Finally, equilibration of the peptide structure requires an implicit solvent LD simulation as long as 30 ns.

Small-molecule fluorescent probes embody an essential facet of chemical biology. Although numerous compounds are known, the ensemble of fluorescent probes is based on a modest collection of modular "core" dyes. The elaboration of these dyes with diverse chemical moieties is enabling the precise interrogation of biochemical and biological systems. The importance of fluorescence-based technologies in chemical biology elicits a necessity to understand the major classes of small-molecule fluorophores. Here, we examine the chemical and photophysical properties of oft-used fluorophores and highlight classic and contemporary examples in which utility has been built upon these scaffolds.

Genetically-encoded calcium indicators (GECIs) hold the promise of monitoring [Ca(2+)] in selected populations of neurons and in specific cellular compartments. Relating GECI fluorescence to neuronal activity requires quantitative characterization. We have characterized a promising new genetically-encoded calcium indicator-GCaMP2-in mammalian pyramidal neurons. Fluorescence changes in response to single action potentials (17+/-10% DeltaF/F [mean+/-SD]) could be detected in some, but not all, neurons. Trains of high-frequency action potentials yielded robust responses (302+/-50% for trains of 40 action potentials at 83 Hz). Responses were similar in acute brain slices from in utero electroporated mice, indicating that long-term expression did not interfere with GCaMP2 function. Membrane-targeted versions of GCaMP2 did not yield larger signals than their non-targeted counterparts. We further targeted GCaMP2 to dendritic spines to monitor Ca(2+) accumulations evoked by activation of synaptic NMDA receptors. We observed robust DeltaF/F responses (range: 37%-264%) to single spine uncaging stimuli that were correlated with NMDA receptor currents measured through a somatic patch pipette. One major drawback of GCaMP2 was its low baseline fluorescence. Our results show that GCaMP2 is improved from the previous versions of GCaMP and may be suited to detect bursts of high-frequency action potentials and synaptic currents in vivo.

Phase-sensitive sum-frequency spectroscopy provides correct characterization of vibrational resonances of water-vapor interfaces and allows better identification of interfacial water species contributing to different parts of the spectra. Iodine ions emerging at an interface create a surface field that tends to reorient the more loosely bonded water molecules below the topmost layer.

BACKGROUND: Among the most prominent molecular constituents of a recycling synaptic vesicle is the clathrin triskelion, composed of clathrin light chain (Clc) and clathrin heavy chain (Chc). Remarkably, it remains unknown whether clathrin is strictly necessary for the stimulus-dependent re-formation of a synaptic vesicle and, conversely, whether clathrin-independent vesicle endocytosis exists at the neuronal synapse.

RESULTS: We employ FlAsH-FALI-mediated protein photoinactivation to rapidly (3 min) and specifically disrupt Clc function at the Drosophila neuromuscular junction. We first demonstrate that Clc photoinactivation does not impair synaptic-vesicle fusion. We then provide electrophysiological and ultrastructural evidence that synaptic vesicles, once fused with the plasma membrane, cannot be re-formed after Clc photoinactivation. Finally, we demonstrate that stimulus-dependent membrane internalization occurs after Clc photoinactivation. However, newly internalized membrane fails to resolve into synaptic vesicles. Rather, newly internalized membrane forms large and extensive internal-membrane compartments that are never observed at a wild-type synapse.

CONCLUSIONS: We make three major conclusions. (1) FlAsH-FALI-mediated protein photoinactivation rapidly and specifically disrupts Clc function with no effect on synaptic-vesicle fusion. (2) Synaptic-vesicle re-formation does not occur after Clc photoinactivation. By extension, clathrin-independent "kiss-and-run" endocytosis does not sustain synaptic transmission during a stimulus train at this synapse. (3) Stimulus-dependent, clathrin-independent membrane internalization exists at this synapse, but it is unable to generate fusion-competent, small-diameter synaptic vesicles.

Ethanol (EtOH), isopropyl alcohol (IPA), and propylene glycol (PG) increase topical drug delivery, but are sometimes associated with erythema. A potential genetic basis for alcohol-associated erythema was investigated as the function of polymorphisms in coding and non-coding regions of class IB alcohol dehydrogenase (ADHIB) and evaluated for altered gene expression in vitro and metabolic activity in vivo via altered skin blood flow (Doppler velocimeter) and erythema (reflectance colorimeter a*) following topical challenge to 5 M EtOH, IPA, PG, and butanol (ButOH). Promoter polymorphisms G-887A and C-739T and exon G143A form eight ADHIB haplotypes with different frequencies in Caucasians vs Asians and exhibit variable gene expression and metabolic activity. Polymorphisms C-739T and G-887A independently alter gene expression, which is further increased by IPA and PG, but not EtOH or ButOH. EtOH and ButOH increase erythema as a function of skin blood flow. IPA increases skin blood flow without erythema and PG increased erythema with decreased skin blood flow, all as a function of ADHIB haplotype. PG-induced erythema was uniquely associated with tumor necrosis factor-alpha expression. Thus, erythema following alcohol exposure is alcohol type specific, has a pharmacogenetic basis related to ADHIB haplotype and can be functionally evaluated via Doppler velocimetry and reflectance colorimetry in vivo.

Although information storage in the central nervous system is thought to be primarily mediated by various forms of synaptic plasticity, other mechanisms, such as modifications in membrane excitability, are available. Local dendritic spikes are nonlinear voltage events that are initiated within dendritic branches by spatially clustered and temporally synchronous synaptic input. That local spikes selectively respond only to appropriately correlated input allows them to function as input feature detectors and potentially as powerful information storage mechanisms. However, it is currently unknown whether any effective form of local dendritic spike plasticity exists. Here we show that the coupling between local dendritic spikes and the soma of rat hippocampal CA1 pyramidal neurons can be modified in a branch-specific manner through an N-methyl-d-aspartate receptor (NMDAR)-dependent regulation of dendritic Kv4.2 potassium channels. These data suggest that compartmentalized changes in branch excitability could store multiple complex features of synaptic input, such as their spatio-temporal correlation. We propose that this ’branch strength potentiation’ represents a previously unknown form of information storage that is distinct from that produced by changes in synaptic efficacy both at the mechanistic level and in the type of information stored.

Vertebrate somitogenesis is a rhythmically repeated morphogenetic process. The dependence of somitogenesis dynamics on axial position and temperature has not been investigated systematically in any species. Here we use multiple embryo time-lapse imaging to precisely estimate somitogenesis period and somite length under various conditions in the zebrafish embryo. Somites form at a constant period along the trunk, but the period gradually increases in the tail. Somite length varies along the axis in a stereotypical manner, with tail somites decreasing in size. Therefore, our measurements prompt important modifications to the steady-state Clock and Wavefront model: somitogenesis period, somite length, and wavefront velocity all change with axial position. Finally, we show that somitogenesis period changes more than threefold across the standard developmental temperature range, whereas the axial somite length distribution is temperature invariant. This finding indicates that the temperature-induced change in somitogenesis period exactly compensates for altered axial growth.

Understanding the principles of information processing in neural circuits requires systematic characterization of the participating cell types and their connections, and the ability to measure and perturb their activity. Genetic approaches promise to bring experimental access to complex neural systems, including genetic stalwarts such as the fly and mouse, but also to nongenetic systems such as primates. Together with anatomical and physiological methods, cell-type-specific expression of protein markers and sensors and transducers will be critical to construct circuit diagrams and to measure the activity of genetically defined neurons. Inactivation and activation of genetically defined cell types will establish causal relationships between activity in specific groups of neurons, circuit function, and animal behavior. Genetic analysis thus promises to reveal the logic of the neural circuits in complex brains that guide behaviors. Here we review progress in the genetic analysis of neural circuits and discuss directions for future research and development.

We present a method for automatic full-precision alignment of the images in a tomographic tilt series. Full-precision automatic alignment of cryo electron microscopy images has remained a difficult challenge to date, due to the limited electron dose and low image contrast. These facts lead to poor signal to noise ratio (SNR) in the images, which causes automatic feature trackers to generate errors, even with high contrast gold particles as fiducial features. To enable fully automatic alignment for full-precision reconstructions, we frame the problem probabilistically as finding the most likely particle tracks given a set of noisy images, using contextual information to make the solution more robust to the noise in each image. To solve this maximum likelihood problem, we use Markov Random Fields (MRF) to establish the correspondence of features in alignment and robust optimization for projection model estimation. The resulting algorithm, called Robust Alignment and Projection Estimation for Tomographic Reconstruction, or RAPTOR, has not needed any manual intervention for the difficult datasets we have tried, and has provided sub-pixel alignment that is as good as the manual approach by an expert user. We are able to automatically map complete and partial marker trajectories and thus obtain highly accurate image alignment. Our method has been applied to challenging cryo electron tomographic datasets with low SNR from intact bacterial cells, as well as several plastic section and X-ray datasets.