We describe an implementation of maximum likelihood classification for single particle electron cryo-microscopy that is based on the FREALIGN software. Particle alignment parameters are determined by maximizing a joint likelihood that can include hierarchical priors, while classification is performed by expectation maximization of a marginal likelihood. We test the FREALIGN implementation using a simulated dataset containing computer-generated projection images of three different 70S ribosome structures, as well as a publicly available dataset of 70S ribosomes. The results show that the mixed strategy of the new FREALIGN algorithm yields performance on par with other maximum likelihood implementations, while remaining computationally efficient.

In fluorescence microscopy it has become possible to fundamentally overcome the diffraction limited resolution in all three spatial dimensions. However, to have the most impact in biological sciences, new optical microscopy techniques need to be compatible with live cell imaging: image acquisition has to be fast enough to capture cellular dynamics at the new resolution limit while light exposure needs to be minimized to prevent photo-toxic effects. With increasing spatial resolution, these requirements become more difficult to meet, even more so when volumetric imaging is performed. In this review, techniques that have been successfully applied to three-dimensional, super-resolution live microscopy are presented and their relative strengths and weaknesses are discussed.

All organisms react to noxious and mechanical stimuli but we still lack a complete understanding of cellular and molecular mechanisms by which somatosensory information is transformed into appropriate motor outputs. The small number of neurons and excellent genetic tools make Drosophila larva an especially tractable model system in which to address this problem. We developed high throughput assays with which we can simultaneously expose more than 1,000 larvae per man-hour to precisely timed noxious heat, vibration, air current, or optogenetic stimuli. Using this hardware in combination with custom software we characterized larval reactions to somatosensory stimuli in far greater detail than possible previously. Each stimulus evoked a distinctive escape strategy that consisted of multiple actions. The escape strategy was context-dependent. Using our system we confirmed that the nociceptive class IV multidendritic neurons were involved in the reactions to noxious heat. Chordotonal (ch) neurons were necessary for normal modulation of head casting, crawling and hunching, in response to mechanical stimuli. Consistent with this we observed increases in calcium transients in response to vibration in ch neurons. Optogenetic activation of ch neurons was sufficient to evoke head casting and crawling. These studies significantly increase our understanding of the functional roles of larval ch neurons. More generally, our system and the detailed description of wild type reactions to somatosensory stimuli provide a basis for systematic identification of neurons and genes underlying these behaviors.

We aim to improve segmentation through the use of machine learning tools during region agglomeration. We propose an active learning approach for performing hierarchical agglomerative segmentation from superpixels. Our method combines multiple features at all scales of the agglomerative process, works for data with an arbitrary number of dimensions, and scales to very large datasets. We advocate the use of variation of information to measure segmentation accuracy, particularly in 3D electron microscopy (EM) images of neural tissue, and using this metric demonstrate an improvement over competing algorithms in EM and natural images.

Discrete populations of brainstem spinal projection neurons (SPNs) have been shown to exhibit behavior-specific responses during locomotion [1-9], suggesting that separate descending pathways, each dedicated to a specific behavior, control locomotion. In an alternative model, a large variety of motor outputs could be generated from different combinations of a small number of basic motor pathways. We examined this possibility by studying the precise role of ventromedially located hindbrain SPNs (vSPNs) in generating turning behaviors. We found that unilateral laser ablation of vSPNs reduces the tail deflection and cycle period specifically during the first undulation cycle of a swim bout, whereas later tail movements are unaffected. This holds true during phototaxic [10], optomotor [11], dark-flash-induced [12], and spontaneous turns [13], suggesting a universal role of these neurons in controlling turning behaviors. Importantly, we found that the ablation not only abolishes turns but also results in a dramatic increase in the number of forward swims, suggesting that these neurons transform forward swims into turns by introducing turning kinematics into a basic motor pattern of symmetric tail undulations. Finally, we show that vSPN activity is direction specific and graded by turning angle. Together, these results provide a clear example of how a specific motor pattern can be transformed into different behavioral events by the graded activation of a small set of SPNs.

The Drosophila central brain develops from a fixed number of neuroblasts. Each neuroblast makes a clone of neurons that exhibit common trajectories. Here we identified 15 distinct clones that carry larval-born neurons innervating the Drosophila central complex (CX), which consists of four midline structures including the protocerebral bridge (PB), fan-shaped body (FB), ellipsoid body (EB), and noduli (NO). Clonal analysis revealed that the small-field CX neurons, which establish intricate projections across different CX substructures, exist in four isomorphic groups that respectively derive from four complex posterior asense-negative lineages. In terms of the region-characteristic large-field CX neurons, we found that two lineages make PB neurons, 10 lineages produce FB neurons, three lineages generate EB neurons, and two lineages yield NO neurons. The diverse FB developmental origins reflect the discrete input pathways for different FB subcompartments. Clonal analysis enlightens both development and anatomy of the insect locomotor control center.

The zebrafish Danio rerio has emerged as a powerful vertebrate model system that lends itself particularly well to quantitative investigations with live imaging approaches, owing to its exceptionally high optical clarity in embryonic and larval stages. Recent advances in light microscopy technology enable comprehensive analyses of cellular dynamics during zebrafish embryonic development, systematic mapping of gene expression dynamics, quantitative reconstruction of mutant phenotypes and the system-level biophysical study of morphogenesis. Despite these technical breakthroughs, it remains challenging to design and implement experiments for in vivo long-term imaging at high spatio-temporal resolution. This article discusses the fundamental challenges in zebrafish long-term live imaging, provides experimental protocols and highlights key properties and capabilities of advanced fluorescence microscopes. The article focuses in particular on experimental assays based on light sheet-based fluorescence microscopy, an emerging imaging technology that achieves exceptionally high imaging speeds and excellent signal-to-noise ratios, while minimizing light-induced damage to the specimen. This unique combination of capabilities makes light sheet microscopy an indispensable tool for the in vivo long-term imaging of large developing organisms.

Transcription is reported to be spatially compartmentalized in nuclear transcription factories with clusters of RNA polymerase II (Pol II). However, little is known about when these foci assemble or their relative stability. We developed a quantitative single-cell approach to characterize protein spatiotemporal organization, with single-molecule sensitivity in live eukaryotic cells. We observed that Pol II clusters form transiently, with an average lifetime of 5.1 (± 0.4) seconds, which refutes the notion that they are statically assembled substructures. Stimuli affecting transcription yielded orders-of-magnitude changes in the dynamics of Pol II clusters, which implies that clustering is regulated and plays a role in the cell’s ability to effect rapid response to external signals. Our results suggest that transient crowding of enzymes may aid in rate-limiting steps of gene regulation.

The extraction of directional motion information from changing retinal images is one of the earliest and most important processing steps in any visual system. In the fly optic lobe, two parallel processing streams have been anatomically described, leading from two first-order interneurons, L1 and L2, via T4 and T5 cells onto large, wide-field motion-sensitive interneurons of the lobula plate. Therefore, T4 and T5 cells are thought to have a pivotal role in motion processing; however, owing to their small size, it is difficult to obtain electrical recordings of T4 and T5 cells, leaving their visual response properties largely unknown. We circumvent this problem by means of optical recording from these cells in Drosophila, using the genetically encoded calcium indicator GCaMP5 (ref. 2). Here we find that specific subpopulations of T4 and T5 cells are directionally tuned to one of the four cardinal directions; that is, front-to-back, back-to-front, upwards and downwards. Depending on their preferred direction, T4 and T5 cells terminate in specific sublayers of the lobula plate. T4 and T5 functionally segregate with respect to contrast polarity: whereas T4 cells selectively respond to moving brightness increments (ON edges), T5 cells only respond to moving brightness decrements (OFF edges). When the output from T4 or T5 cells is blocked, the responses of postsynaptic lobula plate neurons to moving ON (T4 block) or OFF edges (T5 block) are selectively compromised. The same effects are seen in turning responses of tethered walking flies. Thus, starting with L1 and L2, the visual input is split into separate ON and OFF pathways, and motion along all four cardinal directions is computed separately within each pathway. The output of these eight different motion detectors is then sorted such that ON (T4) and OFF (T5) motion detectors with the same directional tuning converge in the same layer of the lobula plate, jointly providing the input to downstream circuits and motion-driven behaviours.

Comprehensive high-resolution structural maps are central to functional exploration and understanding in biology. For the nervous system, in which high resolution and large spatial extent are both needed, such maps are scarce as they challenge data acquisition and analysis capabilities. Here we present for the mouse inner plexiform layer–the main computational neuropil region in the mammalian retina–the dense reconstruction of 950 neurons and their mutual contacts. This was achieved by applying a combination of crowd-sourced manual annotation and machine-learning-based volume segmentation to serial block-face electron microscopy data. We characterize a new type of retinal bipolar interneuron and show that we can subdivide a known type based on connectivity. Circuit motifs that emerge from our data indicate a functional mechanism for a known cellular response in a ganglion cell that detects localized motion, and predict that another ganglion cell is motion sensitive.