The activity of the ERK has complex spatial and temporal dynamics that are important for the specificity of downstream effects. However, current biochemical techniques do not allow for the measurement of ERK signaling with fine spatiotemporal resolution. We developed a genetically encoded, FRET-based sensor of ERK activity (the extracellular signal-regulated kinase activity reporter, EKAR), optimized for signal-to-noise ratio and fluorescence lifetime imaging. EKAR selectively and reversibly reported ERK activation in HEK293 cells after epidermal growth factor stimulation. EKAR signals were correlated with ERK phosphorylation, required ERK activity, and did not report the activities of JNK or p38. EKAR reported ERK activation in the dendrites and nucleus of hippocampal pyramidal neurons in brain slices after theta-burst stimuli or trains of back-propagating action potentials. EKAR therefore permits the measurement of spatiotemporal ERK signaling dynamics in living cells, including in neuronal compartments in intact tissues.

Neurobiological processes occur on spatiotemporal scales spanning many orders of magnitude. Greater understanding of these processes therefore demands improvements in the tools used in their study. Here we review recent efforts to enhance the speed and resolution of one such tool, fluorescence microscopy, with an eye toward its application to neurobiological problems. On the speed front, improvements in beam scanning technology, signal generation rates, and photodamage mediation are bringing us closer to the goal of real-time functional imaging of extended neural networks. With regard to resolution, emerging methods of adaptive optics may lead to diffraction-limited imaging or much deeper imaging in optically inhomogeneous tissues, and super-resolution techniques may prove a powerful adjunct to electron microscopic methods for nanometric neural circuit reconstruction.

Neurobiological processes occur on spatiotemporal scales spanning many orders of magnitude. Greater understanding of these processes therefore demands improvements in the tools used in their study. Here we review recent efforts to enhance the speed and resolution of one such tool, fluorescence microscopy, with an eye toward its application to neurobiological problems. On the speed front, improvements in beam scanning technology, signal generation rates, and photodamage mediation are bringing us closer to the goal of real-time functional imaging of extended neural networks. With regard to resolution, emerging methods of adaptive optics may lead to diffraction-limited imaging or much deeper imaging in optically inhomogeneous tissues, and super-resolution techniques may prove a powerful adjunct to electron microscopic methods for nanometric neural circuit reconstruction.

Commentary: A brief review of recent trends in microscopy. The section “Caveats regarding the application of superresolution microscopy” was written in an effort to inject a dose of reality and caution into the unquestioning enthusiasm in the academic community for all things superresolution, covering the topics of labeling density and specificity, sample preparation artifacts, speed vs. resolution vs. photodamage, and the implications of signal-to-background for Nyquist vs. Rayleigh definitions of resolution.

Key to understanding a protein’s biological function is the accurate determination of its spatial distribution inside a cell. Although fluorescent protein markers allow the targeting of specific proteins with molecular precision, much of this information is lost when the resultant fusion proteins are imaged with conventional, diffraction-limited optics. In response, several imaging modalities that are capable of resolution below the diffraction limit (approximately 200 nm) have emerged. Here, both single- and dual-color superresolution imaging of biological structures using photoactivated localization microscopy (PALM) are described. The examples discussed focus on adhesion complexes: dense, protein-filled assemblies that form at the interface between cells and their substrata. A particular emphasis is placed on the instrumentation and photoactivatable fluorescent protein (PA-FP) tags necessary to achieve PALM images at approximately 20 nm resolution in 5 to 30 min in fixed cells.

Commentary: A paper spearheaded by Hari which gives a thorough description of the methods and hardware needed to successfully practice PALM, including cover slip preparation, cell transfection and fixation, drift correction with fiducials, characterization of on/off contrast ratios for different photoactivted fluorescent proteins, identifying PALM-suitable cells, and mechanical and optical components of a PALM system.

The chemical senses, smell and taste, are the most poorly understood sensory modalities. In recent years, however, the field of chemosensation has benefited from new methods and technical innovations that have accelerated the rate of scientific progress. For example, enormous advances have been made in identifying olfactory and gustatory receptor genes and mapping their expression patterns. Genetic tools now permit us to monitor and control neural activity in vivo with unprecedented precision. New imaging techniques allow us to watch neural activity patterns unfold in real time. Finally, improved hardware and software enable multineuron electrophysiological recordings on an expanded scale. These innovations have enabled some fresh approaches to classic problems in chemosensation.

Many important physiological processes operate at time and space scales far beyond those accessible to atom-realistic simulations, and yet discrete stochastic rather than continuum methods may best represent finite numbers of molecules interacting in complex cellular spaces. We describe and validate new tools and algorithms developed for a new version of the MCell simulation program (MCell3), which supports generalized Monte Carlo modeling of diffusion and chemical reaction in solution, on surfaces representing membranes, and combinations thereof. A new syntax for describing the spatial directionality of surface reactions is introduced, along with optimizations and algorithms that can substantially reduce computational costs (e.g., event scheduling, variable time and space steps). Examples for simple reactions in simple spaces are validated by comparison to analytic solutions. Thus we show how spatially realistic Monte Carlo simulations of biological systems can be far more cost-effective than often is assumed, and provide a level of accuracy and insight beyond that of continuum methods.

A fundamental task in sequence analysis is to calculate the probability of a multiple alignment given a phylogenetic tree relating the sequences and an evolutionary model describing how sequences change over time. However, the most widely used phylogenetic models only account for residue substitution events. We describe a probabilistic model of a multiple sequence alignment that accounts for insertion and deletion events in addition to substitutions, given a phylogenetic tree, using a rate matrix augmented by the gap character. Starting from a continuous Markov process, we construct a non-reversible generative (birth-death) evolutionary model for insertions and deletions. The model assumes that insertion and deletion events occur one residue at a time. We apply this model to phylogenetic tree inference by extending the program dnaml in phylip. Using standard benchmarking methods on simulated data and a new "concordance test" benchmark on real ribosomal RNA alignments, we show that the extended program dnamlepsilon improves accuracy relative to the usual approach of ignoring gaps, while retaining the computational efficiency of the Felsenstein peeling algorithm.

In recent years, the deluge of complicated molecular and cellular microscopic images creates compelling challenges for the image computing community. There has been an increasing focus on developing novel image processing, data mining, database and visualization techniques to extract, compare, search and manage the biological knowledge in these data-intensive problems. This emerging new area of bioinformatics can be called ’bioimage informatics’. This article reviews the advances of this field from several aspects, including applications, key techniques, available tools and resources. Application examples such as high-throughput/high-content phenotyping and atlas building for model organisms demonstrate the importance of bioimage informatics. The essential techniques to the success of these applications, such as bioimage feature identification, segmentation and tracking, registration, annotation, mining, image data management and visualization, are further summarized, along with a brief overview of the available bioimage databases, analysis tools and other resources.

The regulation of static allometry is a fundamental developmental process, yet little is understood of the mechanisms that ensure organs scale correctly across a range of body sizes. Recent studies have revealed the physiological and genetic mechanisms that control nutritional variation in the final body and organ size in holometabolous insects. The implications these mechanisms have for the regulation of static allometry is, however, unknown. Here, we formulate a mathematical description of the nutritional control of body and organ size in Drosophila melanogaster and use it to explore how the developmental regulators of size influence static allometry. The model suggests that the slope of nutritional static allometries, the ’allometric coefficient’, is controlled by the relative sensitivity of an organ’s growth rate to changes in nutrition, and the relative duration of development when nutrition affects an organ’s final size. The model also predicts that, in order to maintain correct scaling, sensitivity to changes in nutrition varies among organs, and within organs through time. We present experimental data that support these predictions. By revealing how specific physiological and genetic regulators of size influence allometry, the model serves to identify developmental processes upon which evolution may act to alter scaling relationships.

Back-propagating action potentials (bAPs) travelling from the soma to the dendrites of neurons are involved in various aspects of synaptic plasticity. The distance-dependent increase in Kv4.2-mediated A-type K(+) current along the apical dendrites of CA1 pyramidal cells (CA1 PCs) is responsible for the attenuation of bAP amplitude with distance from the soma. Genetic deletion of Kv4.2 reduced dendritic A-type K(+) current and increased the bAP amplitude in distal dendrites. Our previous studies revealed that the amplitude of unitary Schaffer collateral inputs increases with distance from the soma along the apical dendrites of CA1 PCs. We tested the hypothesis that the weight of distal synapses is dependent on dendritic Kv4.2 channels. We compared the amplitude and kinetics of mEPSCs at different locations on the main apical trunk of CA1 PCs from wild-type (WT) and Kv4.2 knockout (KO) mice. While wild-type mice showed normal distance-dependent scaling, it was missing in the Kv4.2 KO mice. We also tested whether there was an increase in inhibition in the Kv4.2 knockout, induced in an attempt to compensate for a non-specific increase in neuronal excitability (after-polarization duration and burst firing probability were increased in KO). Indeed, we found that the magnitude of the tonic GABA current increased in Kv4.2 KO mice by 53% and the amplitude of mIPSCs increased by 25%, as recorded at the soma. Our results suggest important roles for the dendritic K(+) channels in distance-dependent adjustment of synaptic strength as well as a primary role for tonic inhibition in the regulation of global synaptic strength and membrane excitability.