A low-contrast spot that activates just one ganglion cell in the retina is detected in the spike train of the cell with about the same sensitivity as it is detected behaviorally. This is consistent with Barlow’s proposal that the ganglion cell and later stages of spiking neurons transfer information essentially without loss. Yet, when losses of sensitivity by all preneural factors are accounted for, predicted sensitivity near threshold is considerably greater than behavioral sensitivity, implying that somewhere in the brain information is lost. We hypothesized that the losses occur mainly in the retina, where graded signals are processed by analog circuits that transfer information at high rates and low metabolic cost. To test this, we constructed a model that included all preneural losses for an in vitro mammalian retina, and evaluated the model to predict sensitivity at the cone output. Recording graded responses postsynaptic to the cones (from the type A horizontal cell) and comparing to predicted preneural sensitivity, we found substantial loss of sensitivity (4.2-fold) across the first visual synapse. Recording spike responses from brisk-transient ganglion cells stimulated with the same spot, we found a similar loss (3.5-fold) across the second synapse. The total retinal loss approximated the known overall loss, supporting the hypothesis that from stimulus to perception, most loss near threshold is retinal.

The genetically encoded calcium indicator GCaMP2 shows promise for neural network activity imaging, but is currently limited by low signal-to-noise ratio. We describe x-ray crystal structures as well as solution biophysical and spectroscopic characterization of GCaMP2 in the calcium-free dark state, and in two calcium-bound bright states: a monomeric form that dominates at intracellular concentrations observed during imaging experiments and an unexpected domain-swapped dimer with decreased fluorescence. This series of structures provides insight into the mechanism of Ca2+-induced fluorescence change. Upon calcium binding, the calmodulin (CaM) domain wraps around the M13 peptide, creating a new domain interface between CaM and the circularly permuted enhanced green fluorescent protein domain. Residues from CaM alter the chemical environment of the circularly permuted enhanced green fluorescent protein chromophore and, together with flexible inter-domain linkers, block solvent access to the chromophore. Guided by the crystal structures, we engineered a series of GCaMP2 point mutants to probe the mechanism of GCaMP2 function and characterized one mutant with significantly improved signal-to-noise. The mutation is located at a domain interface and its effect on sensor function could not have been predicted in the absence of structural data.

Understanding molecular-scale architecture of cells requires determination of 3D locations of specific proteins with accuracy matching their nanometer-length scale. Existing electron and light microscopy techniques are limited either in molecular specificity or resolution. Here, we introduce interferometric photoactivated localization microscopy (iPALM), the combination of photoactivated localization microscopy with single-photon, simultaneous multiphase interferometry that provides sub-20-nm 3D protein localization with optimal molecular specificity. We demonstrate measurement of the 25-nm microtubule diameter, resolve the dorsal and ventral plasma membranes, and visualize the arrangement of integrin receptors within endoplasmic reticulum and adhesion complexes, 3D protein organization previously resolved only by electron microscopy. iPALM thus closes the gap between electron tomography and light microscopy, enabling both molecular specification and resolution of cellular nanoarchitecture.

In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is critical, however, for both basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brainwide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brainwide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open-access data repository; compatibility with existing resources; and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.

Volume-object annotation system (VANO) is a cross-platform image annotation system that enables one to conveniently visualize and annotate 3D volume objects including nuclei and cells. An application of VANO typically starts with an initial collection of objects produced by a segmentation computation. The objects can then be labeled, categorized, deleted, added, split, merged and redefined. VANO has been used to build high-resolution digital atlases of the nuclei of Caenorhabditis elegans at the L1 stage and the nuclei of Drosophila melanogaster’s ventral nerve cord at the late embryonic stage. AVAILABILITY: Platform independent executables of VANO, a sample dataset, and a detailed description of both its design and usage are available at research.janelia.org/peng/proj/vano. VANO is open-source for co-development.

Understanding cortical circuits will require mapping the connections between specific populations of neurons, as well as determining the dendritic locations where the synapses occur. The dendrites of individual cortical neurons overlap with numerous types of local and long-range excitatory axons, but axodendritic overlap is not always a good predictor of actual connection strength. Here we developed an efficient channelrhodopsin-2 (ChR2)-assisted method to map the spatial distribution of synaptic inputs, defined by presynaptic ChR2 expression, within the dendritic arborizations of recorded neurons. We expressed ChR2 in two thalamic nuclei, the whisker motor cortex and local excitatory neurons and mapped their synapses with pyramidal neurons in layers 3, 5A and 5B (L3, L5A and L5B) in the mouse barrel cortex. Within the dendritic arborizations of L3 cells, individual inputs impinged onto distinct single domains. These domains were arrayed in an orderly, monotonic pattern along the apical axis: axons from more central origins targeted progressively higher regions of the apical dendrites. In L5 arborizations, different inputs targeted separate basal and apical domains. Input to L3 and L5 dendrites in L1 was related to whisker movement and position, suggesting that these signals have a role in controlling the gain of their target neurons. Our experiments reveal high specificity in the subcellular organization of excitatory circuits.

The R‐specific alcohol dehydrogenase from Lactobacillus brevis (Lb‐ADH) catalyzes the enantioselective reduction of prochiral ketones to the corresponding secondary alcohols. It is stable and has broad substrate specificity. These features make this enzyme an attractive candidate for biotechnological applications. A drawback is its preference for NADP(H) as a cofactor, which is more expensive and labile than NAD(H). Structure‐based computational protein engineering was used to predict mutations to alter the cofactor specificity of Lb‐ADH. Mutations were introduced into Lb‐ADH and tested against the substrate acetophenone, with either NAD(H) or NADP(H) as cofactor. The mutant Arg38Pro showed fourfold increased activity with acetophenone and NAD(H) relative to the wild type. Both Arg38Pro and wild type exhibit a pH optimum of 5.5 with NAD(H) as cofactor, significantly more acidic than with NADP(H). These and related Lb‐ADH mutants may prove useful for the green synthesis of pharmaceutical precursors.

Photoconvertible fluorescent proteins are potential tools for investigating dynamic processes in living cells and for emerging super-resolution microscopy techniques. Unfortunately, most probes in this class are hampered by oligomerization, small photon budgets or poor photostability. Here we report an EosFP variant that functions well in a broad range of protein fusions for dynamic investigations, exhibits high photostability and preserves the approximately 10-nm localization precision of its parent.

In this paper, we present an automatic method for estimating the trajectories of Escherichia coli bacteria from in vivo phase-contrast microscopy. To address the low-contrast boundaries in cellular images, an adaptive kernel-based technique is applied to detect cells in each frame. In addition to intensity features, region homogeneity measure and class uncertainty are also applied in this detection technique. To track cells with complex motion, a novel matching gain measure is introduced to cope with the challenges, particularly the presence of low-contrast boundary, the variations of appearance, and the frequent overlapping and occlusion. For multicell tracking over time, an optimal matching strategy is introduced to improve the handling of cell collision and broken trajectories. The results of successful tracking of Escherichia coli from various phase-contrast sequences are reported and compared with manually determined trajectories, as well as those obtained from existing tracking schemes. The stability of the algorithm with different parameter values is also analyzed and discussed.

We describe an approach for automation of the process of reconstruction of neural tissue from serial section transmission electron micrographs. Such reconstructions require 3D segmentation of individual neuronal processes (axons and dendrites) performed in densely packed neuropil. We first detect neuronal cell profiles in each image in a stack of serial micrographs with multi-scale ridge detector. Short breaks in detected boundaries are interpolated using anisotropic contour completion formulated in fuzzy-logic framework. Detected profiles from adjacent sections are linked together based on cues such as shape similarity and image texture. Thus obtained 3D segmentation is validated by human operators in computer-guided proofreading process. Our approach makes possible reconstructions of neural tissue at final rate of about 5 microm3/manh, as determined primarily by the speed of proofreading. To date we have applied this approach to reconstruct few blocks of neural tissue from different regions of rat brain totaling over 1000microm3, and used these to evaluate reconstruction speed, quality, error rates, and presence of ambiguous locations in neuropil ssTEM imaging data.