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Volume electron microscopy (vEM) datasets such as those generated for connectome studies allow nanoscale quantifications and comparisons of the cell biological features underpinning circuit architectures. Quantifications of cell biological relationships in the connectome result in rich multidimensional datasets that benefit from data science approaches, including dimensionality reduction and integrated graphical representations of neuronal relationships. We developed NeuroSCAN, an online open-source platform that bridges sophisticated graph analytics from data science approaches with the underlying cell biological features in the connectome. We analyze a series of published C. elegans brain neuropils and demonstrate how these integrated representations of neuronal relationships facilitate comparisons across connectomes, catalyzing new insights on the structure-function relationships of the circuits and their changes during development. NeuroSCAN is designed for intuitive examination and comparisons across connectomes, enabling synthesis of knowledge from high-level abstractions of neuronal relationships derived from data science techniques to the detailed identification of the cell biological features underpinning these abstractions., Competing Interests: Competing Interests Authors do not declare any competing interests. Declaration of generative AI and AI-assisted technologies in the writing process. During the preparation of this work the author(s) used ChatGPT in order to improve readability. After using this tool, the author(s) reviewed and edited the content as needed and take full responsibility for the content of the published article.

We present Richardson-Lucy network (RLN), a fast and lightweight deep learning method for three-dimensional fluorescence microscopy deconvolution. RLN combines the traditional Richardson-Lucy iteration with a fully convolutional network structure, establishing a connection to the image formation process and thereby improving network performance. Containing only roughly 16,000 parameters, RLN enables four- to 50-fold faster processing than purely data-driven networks with many more parameters. By visual and quantitative analysis, we show that RLN provides better deconvolution, better generalizability and fewer artifacts than other networks, especially along the axial dimension. RLN outperforms classic Richardson-Lucy deconvolution on volumes contaminated with severe out of focus fluorescence or noise and provides four- to sixfold faster reconstructions of large, cleared-tissue datasets than classic multi-view pipelines. We demonstrate RLN's performance on cells, tissues and embryos imaged with widefield-, light-sheet-, confocal- and super-resolution microscopy., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

During development, neurites and synapses segregate into specific neighborhoods or layers within nerve bundles. The developmental programs guiding placement of neurites in specific layers, and hence their incorporation into specific circuits, are not well understood. We implement novel imaging methods and quantitative models to document the embryonic development of the C. elegans brain neuropil , and discover that differential adhesion mechanisms control precise placement of single neurites onto specific layers. Differential adhesion is orchestrated via developmentally regulated expression of the IgCAM SYG-1, and its partner ligand SYG-2. Changes in SYG-1 expression across neuropil layers result in changes in adhesive forces, which sort SYG-2-expressing neurons. Sorting to layers occurs, not via outgrowth from the neurite tip, but via an alternate mechanism of retrograde zippering, involving interactions between neurite shafts. Our study indicates that biophysical principles from differential adhesion govern neurite placement and synaptic specificity in vivo in developing neuropil bundles., Competing Interests: TS, NK, NV, MM, LD, SE, XH, LS, YW, AS, LF, ZB, WM, HS, DC No competing interests declared

We demonstrate diffraction-limited and super-resolution imaging through thick layers (tens-hundreds of microns) of BIO-133, a biocompatible, UV-curable, commercially available polymer with a refractive index (RI) matched to water. We show that cells can be directly grown on BIO-133 substrates without the need for surface passivation and use this capability to perform extended time-lapse volumetric imaging of cellular dynamics 1) at isotropic resolution using dual-view light-sheet microscopy, and 2) at super-resolution using instant structured illumination microscopy. BIO-133 also enables immobilization of 1) Drosophila tissue, allowing us to track membrane puncta in pioneer neurons, and 2) Caenorhabditis elegans, which allows us to image and inspect fine neural structure and to track pan-neuronal calcium activity over hundreds of volumes. Finally, BIO-133 is compatible with other microfluidic materials, enabling optical and chemical perturbation of immobilized samples, as we demonstrate by performing drug and optogenetic stimulation on cells and C. elegans.

Neuropil is a fundamental form of tissue organization within the brain 1 , in which densely packed neurons synaptically interconnect into precise circuit architecture 2,3 . However, the structural and developmental principles that govern this nanoscale precision remain largely unknown 4,5 . Here we use an iterative data coarse-graining algorithm termed 'diffusion condensation' 6 to identify nested circuit structures within the Caenorhabditis elegans neuropil, which is known as the nerve ring. We show that the nerve ring neuropil is largely organized into four strata that are composed of related behavioural circuits. The stratified architecture of the neuropil is a geometrical representation of the functional segregation of sensory information and motor outputs, with specific sensory organs and muscle quadrants mapping onto particular neuropil strata. We identify groups of neurons with unique morphologies that integrate information across strata and that create neural structures that cage the strata within the nerve ring. We use high resolution light-sheet microscopy 7,8 coupled with lineage-tracing and cell-tracking algorithms 9,10 to resolve the developmental sequence and reveal principles of cell position, migration and outgrowth that guide stratified neuropil organization. Our results uncover conserved structural design principles that underlie the architecture and function of the nerve ring neuropil, and reveal a temporal progression of outgrowth-based on pioneer neurons-that guides the hierarchical development of the layered neuropil. Our findings provide a systematic blueprint for using structural and developmental approaches to understand neuropil organization within the brain.

The contrast and resolution of images obtained with optical microscopes can be improved by deconvolution and computational fusion of multiple views of the same sample, but these methods are computationally expensive for large datasets. Here we describe theoretical and practical advances in algorithm and software design that result in image processing times that are tenfold to several thousand fold faster than with previous methods. First, we show that an 'unmatched back projector' accelerates deconvolution relative to the classic Richardson-Lucy algorithm by at least tenfold. Second, three-dimensional image-based registration with a graphics processing unit enhances processing speed 10- to 100-fold over CPU processing. Third, deep learning can provide further acceleration, particularly for deconvolution with spatially varying point spread functions. We illustrate our methods from the subcellular to millimeter spatial scale on diverse samples, including single cells, embryos and cleared tissue. Finally, we show performance enhancement on recently developed microscopes that have improved spatial resolution, including dual-view cleared-tissue light-sheet microscopes and reflective lattice light-sheet microscopes.

The internalization of the central nervous system, termed neurulation in vertebrates, is a critical step in embryogenesis. Open questions remain regarding how force propels coordinated tissue movement during the process, and little is known as to how internalization happens in invertebrates. We show that in C. elegans morphogenesis, apical constriction in the retracting pharynx drives involution of the adjacent neuroectoderm. HMR-1/cadherin mediates this process via inter-tissue attachment, as well as cohesion within the neuroectoderm. Our results demonstrate that HMR-1 is capable of mediating embryo-wide reorganization driven by a centrally located force generator, and indicate a non-canonical use of cadherin on the basal side of an epithelium that may apply to vertebrate neurulation. Additionally, we highlight shared morphology and gene expression in tissues driving involution, which suggests that neuroectoderm involution in C. elegans is potentially homologous with vertebrate neurulation and thus may help elucidate the evolutionary origin of the brain., Competing Interests: KB, LF, MM, CB, YX, DC, AS, ZB No competing interests declared, (© 2020, Barnes et al.)

In the following pages, we share a collection of photos, drawings, and mixed-media creations, most of them especially made for this JoN issue, manifesting C. elegans researchers' affection for their model organism and the founders of the field. This is a celebration of our community's growth, flourish, spread, and bright future. Descriptions provided by the contributors, edited for space. 1 .

Big data often has emergent structure that exists at multiple levels of abstraction, which are useful for characterizing complex interactions and dynamics of the observations. Here, we consider multiple levels of abstraction via a multiresolution geometry of data points at different granularities. To construct this geometry we define a time-inhomogemeous diffusion process that effectively condenses data points together to uncover nested groupings at larger and larger granularities. This inhomogeneous process creates a deep cascade of intrinsic low pass filters on the data affinity graph that are applied in sequence to gradually eliminate local variability while adjusting the learned data geometry to increasingly coarser resolutions. We provide visualizations to exhibit our method as a "continuously-hierarchical" clustering with directions of eliminated variation highlighted at each step. The utility of our algorithm is demonstrated via neuronal data condensation, where the constructed multiresolution data geometry uncovers the organization, grouping, and connectivity between neurons.

In the eukaryotic cell cycle, a threshold level of cyclin B accumulation triggers the G2-to-M transition, and subsequent cyclin B destruction triggers mitotic exit. The anaphase-promoting complex/cyclosome (APC/C) is the E3 ubiquitin ligase that, together with its co-activator Cdc20, targets cyclin B for destruction during mitotic exit. Here, we show that two pathways act in concert to protect cyclin B from Cdc20-activated APC/C in G2, in order to enable cyclin B accumulation and the G2-to-M transition. The first pathway involves the Mad1-Mad2 spindle checkpoint complex, acting in a distinct manner from checkpoint signaling after mitotic entry but employing a common molecular mechanism-the promotion of Mad2-Cdc20 complex formation. The second pathway involves cyclin-dependent kinase phosphorylation of Cdc20, which is known to reduce Cdc20's affinity for the APC/C. Cooperation of these two mechanisms, which target distinct APC/C binding interfaces of Cdc20, enables cyclin B accumulation and the G2-to-M transition., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Caenorhabditis elegans (C. elegans) stands out as the only organism in which the challenge of understanding the cellular origins of an entire nervous system can be observed, with single cell resolution, in vivo. Here, we present an integrated protocol for the examination of neurodevelopment in C. elegans embryos. Our protocol combines imaging, lineaging and neuroanatomical tracing of single cells in developing embryos. We achieve long-term, four-dimensional (4D) imaging of living C. elegans embryos with nearly isotropic spatial resolution through the use of Dual-view Inverted Selective Plane Illumination Microscopy (diSPIM). Nuclei and neuronal structures in the nematode embryos are imaged and isotropically fused to yield images with resolution of ~330 nm in all three dimensions. These minute-by-minute high-resolution 4D data sets are then analyzed to correlate definitive cell-lineage identities with gene expression and morphological dynamics at single-cell and subcellular levels of detail. Our protocol is structured to enable modular implementation of each of the described steps and enhance studies on embryogenesis, gene expression, or neurodevelopment.

The conserved Bub1/Bub3 complex is recruited to the kinetochore region of mitotic chromosomes, where it initiates spindle checkpoint signaling and promotes chromosome alignment. Here we show that, in contrast to the expectation for a checkpoint pathway component, the BUB-1/BUB-3 complex promotes timely anaphase onset in Caenorhabditis elegans embryos. This activity of BUB-1/BUB-3 was independent of spindle checkpoint signaling but required kinetochore localization. BUB-1/BUB-3 inhibition equivalently delayed separase activation and other events occurring during mitotic exit. The anaphase promotion function required BUB-1's kinase domain, but not its kinase activity, and this function was independent of the role of BUB-1/BUB-3 in chromosome alignment. These results reveal an unexpected role for the BUB-1/BUB-3 complex in promoting anaphase onset that is distinct from its well-studied functions in checkpoint signaling and chromosome alignment, and suggest a new mechanism contributing to the coordination of the metaphase-to-anaphase transition., (© 2015 Kim et al.)

Recruitment of Mad1-Mad2 complexes to unattached kinetochores is a central event in spindle checkpoint signaling. Despite its importance, the mechanism that recruits Mad1-Mad2 to kinetochores is unclear. In this paper, we show that MAD-1 interacts with BUB-1 in Caenorhabditis elegans. Mutagenesis identified specific residues in a segment of the MAD-1 coiled coil that mediate the BUB-1 interaction. In addition to unattached kinetochores, MAD-1 localized between separating meiotic chromosomes and to the nuclear periphery. Mutations in the MAD-1 coiled coil that selectively disrupt interaction with BUB-1 eliminated MAD-1 localization to unattached kinetochores and between meiotic chromosomes, both of which require BUB-1, and abrogated checkpoint signaling. The identified MAD-1 coiled-coil segment interacted with a C-terminal region of BUB-1 that contains its kinase domain, and mutations in this region prevented MAD-1 kinetochore targeting independently of kinase activity. These results delineate an interaction between BUB-1 and MAD-1 that targets MAD-1-MAD-2 complexes to kinetochores and is essential for spindle checkpoint signaling.

Endosomes are emerging as specialized signaling compartments that endow receptors with distinct signaling properties. The diversity of endosomal signaling pathways and their contribution to various biological responses is still unclear. CD158d, which is also known as the killer cell immunoglobulin-like receptor (KIR) 2DL4 (KIR2DL4), is an endosome-resident receptor in natural killer (NK) cells that stimulates the release of a unique set of proinflammatory and proangiogenic mediators in response to soluble human leukocyte antigen G (HLA-G). Here, we identified the CD158d signaling cascade. In response to soluble agonist antibody or soluble HLA-G, signaling by CD158d was dependent on the activation of nuclear factor kappaB (NF-kappaB) and the serine-threonine kinase Akt. CD158d associated with the catalytic subunit of DNA-dependent protein kinase (DNA-PKcs), promoted the recruitment of Akt to endosomes, and stimulated the DNA-PKcs-dependent phosphorylation of Akt. The sequential requirement for DNA-PKcs, Akt, and NF-kappaB in signaling by CD158d delineates a previously uncharacterized endosomal signaling pathway for a proinflammatory response in NK cells.

Mutations in SEPN1 result in a spectrum of early-onset muscle disorders referred to as SEPN1-related myopathy. The SEPN1 gene encodes selenoprotein N (SelN), which contains the amino acid selenocysteine (Sec). Incorporation of Sec occurs due to redefinition of a UGA codon during translation. Efficient insertion requires a Sec insertion sequence (SECIS) in the 3'UTR and, for at least a subset of selenoprotein genes, a Sec redefinition element (SRE) located adjacent to the UGA codon. We report the effect of three novel and one previously reported point mutation in the SelN SRE element on Sec insertion efficiency. Notably, the previously reported mutation c.1397G>A (p.R466Q), which weakens the secondary structure of the SRE element, reduces Sec insertion efficiency and SelN RNA levels. Muscle from patients with this mutation have negligible levels of SelN protein. This data highlights the importance of the SRE element during SelN expression and illustrates a novel molecular mechanism by which point mutations may lead to SEPN1-related myopathy., (2008 Wiley-Liss, Inc.)

Selenocysteine insertion during decoding of eukaryotic selenoprotein mRNA requires several trans-acting factors and a cis-acting selenocysteine insertion sequence (SECIS) usually located in the 3' UTR. A second cis-acting selenocysteine codon redefinition element (SRE) has recently been described that resides near the UGA-Sec codon of selenoprotein N (SEPN1). Similar phylogenetically conserved elements can be predicted in a subset of eukaryotic selenoprotein mRNAs. Previous experimental analysis of the SEPN1 SRE revealed it to have a stimulatory effect on readthrough of the UGA-Sec codon, which was not dependent upon the presence of a SECIS element in the 3' UTR; although, as expected, readthrough efficiency was further elevated by inclusion of a SECIS. In order to examine the nature of the redefinition event stimulated by the SEPN1 SRE, we have modified an experimentally tractable in vitro translation system that recapitulates efficient selenocysteine insertion. The results presented here illustrate that the SRE element has a stimulatory effect on decoding of the UGA-Sec codon by both the methylated and unmethylated isoforms of Sec tRNA([Ser]Sec), and confirm that efficient selenocysteine insertion is dependent on the presence of a 3'-UTR SECIS. The variation in recoding elements predicted near UGA-Sec codons implies that these elements may play a differential role in determining the amount of selenoprotein produced by acting as controllers of UGA decoding efficiency.