Extending three-dimensional (3D) single-molecule localization microscopy away from the coverslip and into thicker specimens will greatly broaden its biological utility. However, because of the limitations of both conventional imaging modalities and conventional labeling techniques, it is a challenge to localize molecules in three dimensions with high precision in such samples while simultaneously achieving the labeling densities required for high resolution of densely crowded structures. Here we combined lattice light-sheet microscopy with newly developed, freely diffusing, cell-permeable chemical probes with targeted affinity for DNA, intracellular membranes or the plasma membrane. We used this combination to perform high-localization precision, ultrahigh-labeling density, multicolor localization microscopy in samples up to 20 μm thick, including dividing cells and the neuromast organ of a zebrafish embryo. We also demonstrate super-resolution correlative imaging with protein-specific photoactivable fluorophores, providing a mutually compatible, single-platform alternative to correlative light-electron microscopy over large volumes.

Microelectron diffraction (MicroED) is a new cryo-electron microscopy (cryo-EM) method capable of determining macromolecular structures at atomic resolution from vanishingly small 3D crystals. MicroED promises to solve atomic resolution structures from even the tiniest of crystals, less than a few hundred nanometers thick. MicroED complements frontier advances in crystallography and represents part of the rebirth of cryo-EM that is making macromolecular structure determination more accessible for all. Here we review the concept and practice of MicroED, for both the electron microscopist and crystallographer. Where other reviews have addressed specific details of the technique (Hattne et al., 2015, Shi et al., 2016 and Shi et al., 2013), we aim to provide context and highlight important features that should be considered when performing a MicroED experiment.

Two long-standing problems for superresolution (SR) fluorescence microscopy are high illumination intensity and long acquisition time, which significantly hamper its application for live-cell imaging. Reversibly photoswitchable fluorescent proteins (RSFPs) have made it possible to dramatically lower the illumination intensities in saturated depletion-based SR techniques, such as saturated depletion nonlinear structured illumination microscopy (NL-SIM) and reversible saturable optical fluorescence transition microscopy. The characteristics of RSFPs most critical for SR live-cell imaging include, first, the integrated fluorescence signal across each switching cycle, which depends upon the absorption cross-section, effective quantum yield, and characteristic switching time from the fluorescent "on" to "off" state; second, the fluorescence contrast ratio of on/off states; and third, the photostability under excitation and depletion. Up to now, the RSFPs of the Dronpa and rsEGFP (reversibly switchable EGFP) families have been exploited for SR imaging. However, their limited number of switching cycles, relatively low fluorescence signal, and poor contrast ratio under physiological conditions ultimately restrict their utility in time-lapse live-cell imaging and their ability to reach the desired resolution at a reasonable signal-to-noise ratio. Here, we present a truly monomeric RSFP, Skylan-NS, whose properties are optimized for the recently developed patterned activation NL-SIM, which enables low-intensity (∼100 W/cm(2)) live-cell SR imaging at ∼60-nm resolution at subsecond acquisition times for tens of time points over broad field of view.

Hippocampal place cells encode the animal's spatial position. However, it is unknown how different long-range sensory systems affect spatial representations. Here we alternated usage of vision and echolocation in Egyptian fruit bats while recording from single neurons in hippocampal areas CA1 and subiculum. Bats flew back and forth along a linear flight track, employing echolocation in darkness or vision in light. Hippocampal representations remapped between vision and echolocation via two kinds of remapping: subiculum neurons turned on or off, while CA1 neurons shifted their place fields. Interneurons also exhibited strong remapping. Finally, hippocampal place fields were sharper under vision than echolocation, matching the superior sensory resolution of vision over echolocation. Simulating several theoretical models of place-cells suggested that combining sensory information and path integration best explains the experimental sharpening data. In summary, here we show sensory-based global remapping in a mammal, suggesting that the hippocampus does not contain an abstract spatial map but rather a 'cognitive atlas', with multiple maps for different sensory modalities.

Clarifying gene expression in narrowly defined neuronal populations can provide insight into cellular identity, computation, and functionality. Here, we used next-generation RNA sequencing (RNA-seq) to produce a quantitative, whole genome characterization of gene expression for the major excitatory neuronal classes of the hippocampus; namely, granule cells and mossy cells of the dentate gyrus, and pyramidal cells of areas CA3, CA2, and CA1. Moreover, for the canonical cell classes of the trisynaptic loop, we profiled transcriptomes at both dorsal and ventral poles, producing a cell-class- and region-specific transcriptional description for these populations. This dataset clarifies the transcriptional properties and identities of lesser-known cell classes, and moreover reveals unexpected variation in the trisynaptic loop across the dorsal-ventral axis. We have created a public resource, Hipposeq (http://hipposeq.janelia.org), which provides analysis and visualization of these data and will act as a roadmap relating molecules to cells, circuits, and computation in the hippocampus.

We use Drosophila larval locomotion as a model to elucidate the working principles of motor circuits. Larval locomotion is generated by rhythmic and sequential contractions of body-wall muscles from the posterior to anterior segments, which in turn are regulated by motor neurons present in the corresponding neuromeres. Motor neurons are known to receive both excitatory and inhibitory inputs, combined action of which likely regulates patterned motor activity during locomotion. Although recent studies identified candidate inhibitory premotor interneurons, the identity of premotor interneurons that provide excitatory drive to motor neurons during locomotion remains unknown. In this study, we searched for and identified two putative excitatory premotor interneurons in this system, termed CLI1 and CLI2 (cholinergic lateral interneuron 1 and 2). These neurons were segmentally arrayed and activated sequentially from the posterior to anterior segments during peristalsis. Consistent with their being excitatory premotor interneurons, the CLIs formed GRASP- and ChAT-positive putative synapses with motoneurons and were active just prior to motoneuronal firing in each segment. Moreover, local activation of CLI1s induced contraction of muscles in the corresponding body segments. Taken together, our results suggest that the CLIs directly activate motoneurons sequentially along the segments during larval locomotion.

Context plays a foundational role in determining how to interpret potentially fear-producing stimuli, yet the precise neurobiological substrates of context are poorly understood. In this issue of Cell, Xu et al. elegantly show that parallel neuronal circuits are necessary for two distinct roles of context in fear conditioning.

MOTIVATION: Serial section microscopy is an established method for detailed anatomy reconstruction of biological specimen. During the last decade, high resolution electron microscopy (EM) of serial sections has become the de-facto standard for reconstruction of neural connectivity at ever increasing scales (EM connectomics). In serial section microscopy, the axial dimension of the volume is sampled by physically removing thin sections from the embedded specimen and subsequently imaging either the block-face or the section series. This process has limited precision leading to inhomogeneous non-planar sampling of the axial dimension of the volume which, in turn, results in distorted image volumes. This includes that section series may be collected and imaged in unknown order.

RESULTS: We developed methods to identify and correct these distortions through image-based signal analysis without any additional physical apparatus or measurements. We demonstrate the efficacy of our methods in proof of principle experiments and application to real world problems.

AVAILABILITY AND IMPLEMENTATION: We made our work available as libraries for the ImageJ distribution Fiji and for deployment in a high performance parallel computing environment. Our sources are open and available at http://github.com/saalfeldlab/section-sort, http://github.com/saalfeldlab/z-spacing and http://github.com/saalfeldlab/z-spacing-spark CONTACT: : saalfelds@janelia.hhmi.orgSupplementary information: Supplementary data are available at Bioinformatics online.

A custom-built objective lens called the Mesolens allows relatively large biological specimens to be imaged with cellular resolution.

Transcription, the first step of gene expression, is exquisitely regulated in higher eukaryotes to ensure correct development and homeostasis. Traditional biochemical, genetic, and genomic approaches have proved successful at identifying factors, regulatory sequences, and potential pathways that modulate transcription. However, they typically only provide snapshots or population averages of the highly dynamic, stochastic biochemical processes involved in transcriptional regulation. Single-molecule live-cell imaging has, therefore, emerged as a complementary approach capable of circumventing these limitations. By observing sequences of molecular events in real time as they occur in their native context, imaging has the power to derive cause-and-effect relationships and quantitative kinetics to build predictive models of transcription. Ongoing progress in fluorescence imaging technology has brought new microscopes and labeling technologies that now make it possible to visualize and quantify the transcription process with single-molecule resolution in living cells and animals. Here we provide an overview of the evolution and current state of transcription imaging technologies. We discuss some of the important concepts they uncovered and present possible future developments that might solve long-standing questions in transcriptional regulation.