An In Toto Approach to Dissecting Cellular Interactions in Complex Tissues

Glia Development and Function in the Nematode Caenorhabditis elegans

The nematode Caenorhabditis elegans is a powerful experimental setting for uncovering fundamental tenets of nervous system organization and function. Its nearly invariant and simple anatomy, coupled with a plethora of methodologies for interrogating single-gene functions at single-cell resolution in vivo, have led to exciting discoveries in glial cell biology and mechanisms of glia-neuron interactions. Findings over the last two decades reinforce the idea that insights from C. elegans can inform our understanding of glial operating principles in other species. Here, we summarize the current state-of-the-art, and describe mechanistic insights that have emerged from a concerted effort to understand C. elegans glia. The remarkable acceleration in the pace of discovery in recent years paints a portrait of striking molecular complexity, exquisite specificity, and functional heterogeneity among glia. Glial cells affect nearly every aspect of nervous system development and function, from generating neurons, to promoting neurite formation, to animal behavior, and to whole-animal traits, including longevity. We discuss emerging questions where C. elegans is poised to fill critical knowledge gaps in our understanding of glia biology.

Ultrack: pushing the limits of cell tracking across biological scales

Tracking live cells across 2D, 3D, and multi-channel time-lapse recordings is crucial for understanding tissue-scale biological processes. Despite advancements in imaging technology, achieving accurate cell tracking remains challenging, particularly in complex and crowded tissues where cell segmentation is often ambiguous. We present Ultrack, a versatile and scalable cell-tracking method that tackles this challenge by considering candidate segmentations derived from multiple algorithms and parameter sets. Ultrack employs temporal consistency to select optimal segments, ensuring robust performance even under segmentation uncertainty. We validate our method on diverse datasets, including terabyte-scale developmental time-lapses of zebrafish, fruit fly, and nematode embryos, as well as multi-color and label-free cellular imaging. We show that Ultrack achieves state-of-the-art performance on the Cell Tracking Challenge and demonstrates superior accuracy in tracking densely packed embryonic cells over extended periods. Moreover, we propose an approach to tracking validation via dual-channel sparse labeling that enables high-fidelity ground truth generation, pushing the boundaries of long-term cell tracking assessment. Our method is freely available as a Python package with Fiji and napari plugins and can be deployed in a high-performance computing environment, facilitating widespread adoption by the research community.

LET-381/FoxF and its target UNC-30/Pitx2 specify and maintain the molecular identity of C. elegans mesodermal glia that regulate motor behavior

While most glial cell types in the central nervous system (CNS) arise from neuroectodermal progenitors, some, like microglia, are mesodermally derived. To understand mesodermal glia development and function, we investigated C. elegans GLR glia, which envelop the brain neuropil and separate it from the circulatory system cavity. Transcriptome analysis shows that GLR glia combine astrocytic and endothelial characteristics, which are relegated to separate cell types in vertebrates. Combined fate acquisition is orchestrated by LET-381/FoxF, a fate-specification/maintenance transcription factor also expressed in glia and endothelia of other animals. Among LET-381/FoxF targets, the UNC-30/Pitx2 transcription factor controls GLR glia morphology and represses alternative mesodermal fates. LET-381 and UNC-30 co-expression in naive cells is sufficient for GLR glia gene expression. GLR glia inactivation by ablation or let-381 mutation disrupts locomotory behavior and promotes salt-induced paralysis, suggesting brain-neuropil activity dysregulation. Our studies uncover mechanisms of mesodermal glia development and show that like neuronal differentiation, glia differentiation requires autoregulatory terminal selector genes that define and maintain the glial fate.

LET-381/FoxF and UNC-30/Pitx2 control the development of C. elegans mesodermal glia that regulate motor behavior

While most CNS glia arise from neuroectodermal progenitors, some, like microglia, are mesodermally derived. To understand mesodermal glia development and function, we investigated C. elegans GLR glia, which ensheath the brain neuropil and separate it from the circulatory-system cavity. Transcriptome analysis suggests GLR glia merge astrocytic and endothelial characteristics relegated to separate cell types in vertebrates. Combined fate acquisition is orchestrated by LET-381/FoxF, a fate-specification/maintenance transcription factor expressed in glia and endothelia of other animals. Among LET-381/FoxF targets, UNC-30/Pitx2 transcription factor controls GLR glia morphology and represses alternative mesodermal fates. LET-381 and UNC-30 co-expression in naïve cells is sufficient for GLR glia gene expression. GLR glia inactivation by ablation or let-381 mutation disrupts locomotory behavior and induces salt hypersensitivity, suggesting brain-neuropil activity dysregulation. Our studies uncover mechanisms of mesodermal glia development and show that like neurons, glia differentiation requires autoregulatory terminal selector genes that define and maintain the glial fate.

A compound PCP scheme underlies sequential rosettes-based cell intercalation

The formation of sequential rosettes is a type of collective cell behavior recently discovered in the Caenorhabditis elegans embryo that mediates directional cell migration through sequential formation and resolution of multicellular rosettes involving the migrating cell and its neighboring cells along the way. Here, we show that a planar cell polarity (PCP)-based polarity scheme regulates sequential rosettes, which is distinct from the known mode of PCP regulation in multicellular rosettes during the process of convergent extension. Specifically, non-muscle myosin (NMY) localization and edge contraction are perpendicular to that of Van Gogh as opposed to colocalizing with Van Gogh. Further analyses suggest a two-component polarity scheme: one being the canonical PCP pathway with MIG-1/Frizzled and VANG-1/Van Gogh localized to the vertical edges, the other being MIG-1/Frizzled and NMY-2 localized to the midline/contracting edges. The NMY-2 localization and contraction of the midline edges also required LAT-1/Latrophilin, an adhesion G protein-coupled receptor that has not been shown to regulate multicellular rosettes. Our results establish a distinct mode of PCP-mediated cell intercalation and shed light on the versatile nature of the PCP pathway.

Widespread employment of conserved C. elegans homeobox genes in neuronal identity specification

Homeobox genes are prominent regulators of neuronal identity, but the extent to which their function has been probed in animal nervous systems remains limited. In the nematode Caenorhabditis elegans, each individual neuron class is defined by the expression of unique combinations of homeobox genes, prompting the question of whether each neuron class indeed requires a homeobox gene for its proper identity specification. We present here progress in addressing this question by extending previous mutant analysis of homeobox gene family members and describing multiple examples of homeobox gene function in different parts of the C. elegans nervous system. To probe homeobox function, we make use of a number of reporter gene tools, including a novel multicolor reporter transgene, NeuroPAL, which permits simultaneous monitoring of the execution of multiple differentiation programs throughout the entire nervous system. Using these tools, we add to the previous characterization of homeobox gene function by identifying neuronal differentiation defects for 14 homeobox genes in 24 distinct neuron classes that are mostly unrelated by location, function and lineage history. 12 of these 24 neuron classes had no homeobox gene function ascribed to them before, while in the other 12 neuron classes, we extend the combinatorial code of transcription factors required for specifying terminal differentiation programs. Furthermore, we demonstrate that in a particular lineage, homeotic identity transformations occur upon loss of a homeobox gene and we show that these transformations are the result of changes in homeobox codes. Combining the present with past analyses, 113 of the 118 neuron classes of C. elegans are now known to require a homeobox gene for proper execution of terminal differentiation programs. Such broad deployment indicates that homeobox function in neuronal identity specification may be an ancestral feature of animal nervous systems.

Delineating the mechanisms and design principles of Caenorhabditis elegans embryogenesis using in toto high-resolution imaging data and computational modeling

The nematode (roundworm) Caenorhabditis elegans is one of the most popular animal models for the study of developmental biology, as its invariant development and transparent body enable in toto cellular-resolution fluorescence microscopy imaging of developmental processes at 1-min intervals. This has led to the development of various computational tools for the systematic and automated analysis of imaging data to delineate the molecular and cellular processes throughout the embryogenesis of C. elegans, such as those associated with cell lineage, cell migration, cell morphology, and gene activity. In this review, we first introduce C. elegans embryogenesis and the development of techniques for tracking cell lineage and reconstructing cell morphology during this process. We then contrast the developmental modes of C. elegans and the customized technologies used for studying them with the ones of other animal models, highlighting its advantage for studying embryogenesis with exceptional spatial and temporal resolution. This is followed by an examination of the physical models that have been devised-based on accurate determinations of developmental processes afforded by analyses of imaging data-to interpret the early embryonic development of C. elegans from subcellular to intercellular levels of multiple cells, which focus on two key processes: cell polarization and morphogenesis. We subsequently discuss how quantitative data-based theoretical modeling has improved our understanding of the mechanisms of C. elegans embryogenesis. We conclude by summarizing the challenges associated with the acquisition of C. elegans embryogenesis data, the construction of algorithms to analyze them, and the theoretical interpretation.

Visualizing and quantifying molecular and cellular processes in C. elegans using light microscopy

Light microscopes are the cell and developmental biologists' "best friend", providing a means to see structures and follow dynamics from the protein to the organism level. A huge advantage of C. elegans as a model organism is its transparency, which coupled with its small size means that nearly every biological process can be observed and measured with the appropriate probe and light microscope. Continuous improvement in microscope technologies along with novel genome editing techniques to create transgenic probes have facilitated the development and implementation of a dizzying array of methods for imaging worm embryos, larvae and adults. In this review we provide an overview of the molecular and cellular processes that can be visualized in living worms using light microscopy. A partial inventory of fluorescent probes and techniques successfully used in worms to image the dynamics of cells, organelles, DNA, and protein localization and activity is followed by a practical guide to choosing between various imaging modalities, including widefield, confocal, lightsheet, and structured illumination microscopy. Finally, we discuss the available tools and approaches, including machine learning, for quantitative image analysis tasks, such as colocalization, segmentation, object tracking, and lineage tracing. Hopefully, this review will inspire worm researchers who have not yet imaged their worms to begin, and push those who are imaging to go faster, finer, and longer.

Cross-modality synthesis of EM time series and live fluorescence imaging

Analyses across imaging modalities allow the integration of complementary spatiotemporal information about brain development, structure, and function. However, systematic atlasing across modalities is limited by challenges to effective image alignment. We combine highly spatially resolved electron microscopy (EM) and highly temporally resolved time-lapse fluorescence microscopy (FM) to examine the emergence of a complex nervous system in Caenorhabditis elegans embryogenesis. We generate an EM time series at four classic developmental stages and create a landmark-based co-optimization algorithm for cross-modality image alignment, which handles developmental heterochrony among datasets to achieve accurate single-cell level alignment. Synthesis based on the EM series and time-lapse FM series carrying different cell-specific markers reveals critical dynamic behaviors across scales of identifiable individual cells in the emergence of the primary neuropil, the nerve ring, as well as a major sensory organ, the amphid. Our study paves the way for systematic cross-modality data synthesis in C. elegans and demonstrates a powerful approach that may be applied broadly.

Structural and developmental principles of neuropil assembly in C. elegans

Neuropil is a fundamental form of tissue organization within the brain¹, 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.

Rapid image deconvolution and multiview fusion for optical microscopy

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.

Glia-Neuron Interactions in Caenorhabditis elegans

Glia are abundant components of animal nervous systems. Recognized 170 years ago, concerted attempts to understand these cells began only recently. From these investigations glia, once considered passive filler material in the brain, have emerged as active players in neuron development and activity. Glia are essential for nervous system function, and their disruption leads to disease. The nematode Caenorhabditis elegans possesses glial types similar to vertebrate glia, based on molecular, morphological, and functional criteria, and has become a powerful model in which to study glia and their neuronal interactions. Facile genetic and transgenic methods in this animal allow the discovery of genes required for glial functions, and effects of glia at single synapses can be monitored by tracking neuron shape, physiology, or animal behavior. Here, we review recent progress in understanding glia-neuron interactions in C. elegans. We highlight similarities with glia in other animals, and suggest conserved emerging principles of glial function.

Establishment of Signaling Interactions with Cellular Resolution for Every Cell Cycle of Embryogenesis

Intercellular signaling interactions play a key role in breaking fate symmetry during animal development. Identification of signaling interactions at cellular resolution is technically challenging, especially in a developing embryo. Here, we develop a platform that allows automated inference and validation of signaling interactions for every cell cycle of Caenorhabditis elegans embryogenesis. This is achieved by the generation of a systems-level cell contact map, which consists of 1114 highly confident intercellular contacts, by modeling analysis and is validated through cell membrane labeling coupled with cell lineage analysis. We apply the map to identify cell pairs between which a Notch signaling interaction takes place. By generating expression patterns for two ligands and two receptors of the Notch signaling pathway with cellular resolution using the automated expression profiling technique, we are able to refine existing and identify novel Notch interactions during C. elegans embryogenesis. Targeted cell ablation followed by cell lineage analysis demonstrates the roles of signaling interactions during cell division in breaking fate symmetry. Finally, we describe the development of a website that allows online access to the cell-cell contact map for mapping of other signaling interactions by the community. The platform can be adapted to establish cellular interactions from any other signaling pathway.