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Wu, Yicong, Shroff, Hari, Catena, Raul, Kovacevic, Ismar, Christensen, Ryan, Marquina-Solis, Javier, Santella, Anthony, Mohler, William A., Kumar, Abhishek, Bao, Zhirong, Moyle, Mark, Colon-Ramos, Daniel
[
International Worm Meeting,
2015]
WormGUIDES is a 4D interactive atlas of C. elegans embryogenesis. Its purpose is to support the exploration and analysis of embryogenesis at the molecular, cellular, tissue and organism levels. The current WormGUIDES release contains a minute-by-minute record of nuclear positions for all cells until twitching. Current efforts focus on adding records of 3D cell morphology to reconstruct neural morphogenesis and the dynamics of neurite outgrowth. Our strategy consists of acquiring 3D time-lapse images of embryogenesis using promoter-driven fluorescent markers to sparsely label subsets of neurons. Ubiquitous histone markers enable automated lineaging to identify cells and align datasets acquired from different embryos into a digital composite record.Data from our initial set of markers reveals dynamic processes that contribute to the architecture of the major neural organs such as the nerve ring, ventral nerve cord and the head nerve bundles. Much of this morphogenesis occurs before twitching. Surprisingly, some morphogenetic modules are formed in neural progenitors and maintained through two cell cycles. Perturbations suggest novel collective cell behaviors and unexpected roles for surrounding tissue in shaping the nervous system.Lineage-based cell identification has yielded a list of approximately 50 neurons that are currently being tracked and segmented. These cells account for about a quarter of embryonic neurons and include critical components of the major neural structures. To support the throughput needed for systematic reconstruction, we have developed computational pipelines for semi-automated segmentation and alignment of cell shapes from multiple embryos and markers. In addition, we have developed computational tools to untwist the elongating embryo and trace post-twitching events. We are making additional markers, and developing a desktop application extending the current mobile app. Ultimately, the goal is to produce a complete, dynamic record of the assembly of the C. elegans connectome.
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Bao, Zhirong, Santella, Anthony, Yu, Zidong, Shroff, Hari, Wu, Yicong, Du, Zhuo
[
International Worm Meeting,
2013]
The invariant lineage has been a cornerstone of C. elegans biology. John Sulston's initial lineage 30 years ago used multiple embryos to assemble the invariant pattern. Complete continuous lineaging has never been performed for a single animal. While image analysis software has facilitated lineage creation during early embryogenesis, embryo movement at later stages has hampered the analysis of later development. We have made progress towards lineage tracing during this developmental period through a combination of innovative computational and imaging methods. Our efforts on image analysis are focused on the challenge of reliably following small and crowded nuclei over long periods of time in under sampled images. Our nuclear detection method uses per slice segmentation and a learned shape model to robustly detect and segment nuclei in crowded configurations. The detection results are merged into a cell lineage using multiple linking steps, which select from a set of possible causes and actions, including cell movements, divisions, or detection errors. This is based on probabilistic models of nuclear appearance and local spatial configuration. These computational improvements are bolstered by a qualitative improvement in image quality through the dual-view inverted Selective Plane Illumination Microscope (diSPIM), which captures isotropically sampled volumes at speeds that largely eliminate motion artifacts even through the final stage of embryogenesis. We anticipate that our combined effort will allow not just lineage tracing, but that the detailed dynamics of development (including cell positions and expression patterns) can be followed at high spatiotemporal resolution to build a quantitative model of development. A long term application is the production of WormGUIDES, a 4D atlas tracking both cell positions and neuronal outgrowth.
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[
International Worm Meeting,
2011]
The study of embryonic phenotypes at high detail and large scale requires accurate and fast assembly of detected nuclei into a cell lineage. Accuracy is essential. Every error limits analysis, requiring either manual correction or a retreat from the goal of single cell tracking. In addition, high throughput work limits the effort that can be spent on correction and quality control of results. The time it would take to confirm, unguided, the correctness of even a perfectly accurate cell lineage may be unsupportable. As such, a measure of the local reliability of results is just as important as low error. Existing methods do not to provide this combination of features. Common, simple methods such as nearest neighbor association across time are error prone and lack a model that can provide confidence in results. More sophisticated general tracking methods such as particle filters lack an explicit model of cell division, a key source of ambiguity and error. These requirements lead to an approach that scores lineage configurations against a learned model. The key design decision is what aspects of the lineage, as revealed via imaging and cell detection, to include in the model used to judge alternative tree configurations. Our desire is for a general method applicable to any embryo capable of normal cell division. As such, we model key local behaviors of nuclei, firstly their individual change over time (in appearance and position), and secondly the correlation in these measures expected between daughter cells at division. We also model two key aspects of the detection method that provides the raw nuclear positions for lineage assembly, firstly the relationship between nuclear appearance and the probability of a detection being a false positive and secondly the probability of a hypothesized series of detection failures. This model, which can be learned from a set of corrected lineages, is relatively simple but sufficient to produce accurate results and to highlight ambiguous areas for human inspection.
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[
International Worm Meeting,
2021]
Advances in Electron Microscopy (EM) bring about the possibility of temporal analysis using staged samples over time as well as offering opportunities to gain insights by synthesizing EM with other imaging modalities. We present a pseudo time series of C. elegans embryonic development, four volumes covering around 2 hours particularly rich in development between 320 and 475 minutes post first cleavage. This period encompasses neurulation, neural organogenesis and neuropil formation key events that build most of the major structures of the nervous system as well as critical events for many other organ systems. We correlate this EM data with florescence data spanning the first eight hours of embryogenesis. Every cell in the florescence data is identifiable via lineaging. To correlate these data sets we develop a novel computational method for alignment of identities between data sets in the challenging presence of spatial and temporal variation. This approach involves co-optimization of spatial alignment and the structure of labeled data based on a model of dynamic anatomy in the form of an adjacency graph with expected variation. This model captures both variable elements and consistent spatial proximity relationships. We identify every cell in three of the four time points. Identity results are accurate, ranging from 72 to 78 percent correct when assessed against a large set of manual annotations based on position and morphology. This is better than any previously reported results for identifying all cells in an organism based on position alone. The resulting single cell level annotation allows efficient navigation of this large EM data set. We use the sequence to probe the interactions over time between different components within the nerve ring elucidating the relationship between the temporal and spatial location of initial outgrowths into the ring and ultimate structure. We also examine the interaction between cells during the formation of the amphid dendrite structure providing insight into the timing and succession of events at the inter and intra cellular level. Our observations only scratch the surface of the details available in the data set. We will provide the EM data with single-cell level annotation as a resource for the community.
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[
International Worm Meeting,
2009]
Reliable, automated cell detection is a critical component of automated biological image analysis. Accuracy is particularly important for efficient, high-throughput cell lineaging. When tracing a C. elegans lineage overall detection error rates as low as one or two percent result in lineages that can require hours of hand editing to correct. To achieve more reliable automation we are investigating image processing approaches tailored to the appearance of nuclei in confocal fluorescence images. Our approach uses a Difference of Gaussians blob detector to guide an efficient extraction of the nuclear boundary as a set of disks. Preliminary results show a significant improvement in detection rates over Starrynite, our existing detection and lineaging system. Total detection error during the 9th stage of cell division drops from 4.5 to 1.1 %, overall error through the 9th round is reduced from 1.5 to .78%. The method is both accurate and fast enough to be used in real time imaging applications. Results suggest that with further development on extraction and tracking, editing will cease to be a bottleneck. This will enable automated lineaging through the previously daunting 10th and final round of cell divisions and make possible uniquely detailed, large-scale studies of embryonic development.
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Mohler, William, Shroff, Hari, Kumar, Abhishek, Katzman, Braden, Nguyen, Nhan, Barnes, Kris, Sengupta, Titas, Bao, Zhirong, Christensen, Ryan, Duncan, Leighton, Santella, Anthony, Duncan, William, Bosque, Gabriela, Moyle, Mark, Fan, Li, Shah, Pavak, Harvey, Brandon, Ikegami, Richard, Colon-Ramos, Daniel, Tang, Doris
[
International Worm Meeting,
2017]
WormGUIDES is an interactive 4D atlas of C. elegans embryogenesis. Its goals are to (1) provide a model of neural development based on detailed time lapse measurements of nuclear positions and neurite outgrowth; (2) cross reference worm community data with the 4D model and (3) provide an easy to use visualization platform for exploring, understanding and annotating the model and sharing insights. The major tracts of the adult nervous system are laid out early and added to over time. By the 1.5 fold stage many major structures are established. The nerve ring (NR) forms a complete loop that includes dorsal and ventral cells. Sensory nerves have extended to the dent, and the amphid commissure is established. Motor neurons in the VNC have intercalated and others have extended into the VNC and toward the NR. The early emergence of tracts motivates a hierarchal approach to modeling and measuring neural development. Our model contains three levels of structure: (1) Tracts, major nerve tracts; (2) Multi-cellular structures, small groups of co-labeled neurons; and (3) Individual cells. The latter two include cell bodies as well as fascicules or individual neurites. Neurites are threaded through the tracts based on measured lengths and tip positions to minimize noise in alignment and maximize legibility. The current model contains 9 tracts representing the amphid sensory nerves, amphid commissures, NR, VNC and connections, 21 neurons (5 single cell) and nuclear positions up to twitching. We have mapped 6 groups of neurites in the NR with stereotypical positions involving 30 neurons, and sorted the 38 ventral-going amphid commissure axons into 4 temporal groups. 182 markers slated for analysis cover almost all neurons. Stochastic labeling by heat shock, mosaicism of reporter arrays and single cell photo conversion are being pursued to distinguish intertwined neurons. Additional imaging and analysis tools are being developed to push our model to hatching. The wormguides.org website provides comprehensive information on the project, access to our reagents and image data, and a download of the latest atlas. We accept nomination of markers and cells as priorities, and promote sharing of user-driven annotations of developmental processes.
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[
International Worm Meeting,
2015]
While in toto imaging and image analysis methods have advanced the study of multicellular phenomena in development at single-cell resolutions, not much progress has been made in the design of tools to perturb embryos with comparable spatial and temporal resolution. Both classical techniques such as laser ablation and new technologies built around light-activated proteins offer significant promise in filling this need. Their use to-date, however, remains limited by a need for cell-specific promoters or completely manual operation. We have developed a platform for the real-time segmentation and tracking of cells in the C. elegans embryo to enable more reproducible perturbations at higher throughput and without a need for cell-specific markers. The platform consists of three components: 1) Automated cell detection and tracking. 2) An interface for curating detection and tracking results. 3) Laser control for carrying out a pre-defined perturbation protocol when a target cell identity is detected (ie. cell killing by ablation with a pulse laser).The performance of the cell detection pipeline exhibits little dependence on the number of cells present in the embryo; segmentation requires only 3 s per volume on a high-performance workstation. The time required to track detected cells at each time-point, however, is strongly dependent on the number of cells present; currently matching an average of 7.6 cells / s. For an imaging period of 75 s, the on-line segmentation pipeline executes faster than the imaging rate through the 500-cell stage and thus potentially up until twitching begins. More heavily parallelizable strategies for cell tracking are also being pursued to enable perturbations later and in larger model systems. This platform should prove valuable for performing single-cell ablations in the late embryo (ie. for the ablation of individual neurons following their terminal division) and could be easily adapted for other perturbations such as the induction of photoactivatable signaling proteins or even to use in other model systems.
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[
International Worm Meeting,
2011]
An intrinsic property of many master transcription factors is their transient activity during development. While how to activate master regulators with temporal and spatial specificity is subject to intensive studies, the developmental significance of the turnover process is largely unexplored. Using the endomesoderm (EMS) lineage as a model we examined the developmental role of the turnover of SKN-1, a transiently activated master transcription factor crucial for EMS lineage specification and differentiation. Through systematic analysis of cell lineage, fate patterning, single-cell behavior and morphogenesis, we found, interestingly, that turnover of SKN-1 is required for EMS differentiation. When the activity of SKN-1 is maintained, the EMS blastomere, progenitor of endomesoderm, undergoes multiple rounds of asymmetric self-renewal in which the anterior daughter (MS) or anterior granddaughter (MSa) of EMS blastomere maintains EMS fate and differentiates into both mesoderm and endoderm. Mechanistically, the self-renewal is achieved by inducing a poised state of differentiation: when SKN-1 is sustained, transcription of its target genes, which are normally activated by SKN-1 and are required for differentiation, is delayed. During normal development, however, this self-renewal program is kept dormant by tightly regulated protein turnover cascades. Specifically, the activity of SCFLIN-23 and CUL-2ZYG-11, two conserved E3 ubiquitin ligase complexes, is required to suppress self-renewal and initiate differentiation by promoting SKN-1turnover. Furthermore, depletion of SCFLIN-23 also induces self-renewal in the germline progenitor cells, though the underlying mechanisms are different from that of EMS renewal. Our findings reveal a dormant self-renewal capacity of transient progenitor cells. We propose that turnover of master transcription factor can function to balance the choice between self-renewal and differentiation, and more generally, protein turnover is required for developmental state transition.
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[
International Worm Meeting,
2011]
Gastrulation is a key transition in embryogenesis and a complex morphogenetic process that requires self-organized cellular coordination, which has to be both robust - to ensure proper development - and plastic - to allow adaptation to environmental or evolutionary change. We report that cellular rearrangements during Caenorhabditis elegans gastrulation depend on the cooperative action of two cellular processes, contractile flow-dependent protrusion formation and oriented cell divisions. Contractile cortical flows in gastrulating cells organize the extension of polarized lateral protrusions in adjacent cells, which close over the gastrulating cells with radial symmetry thereby creating multicellular rosettes. Radial covering re-establishes a continuous epithelial-like monolayer on the embryo's surface after each cell internalization event and resembles embryonic wound closure. Moreover, we find that the formation of multicellular rosettes represents the major mechanism for scalable local and global tissue patterning. Furthermore, rosette formation can adapt to severe topological alterations, providing a mechanistic explanation for morphogenetic plasticity. We also find that cell divisions polarized during rosette formation release tissue strain generated due to volume constraints during cell internalization. Our findings extend the spectrum of metazoan gastrulation mechanisms and provide insight into self-organization of embryonic morphogenesis.
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[
International Worm Meeting,
2013]
Fluorescence microscopy at single-cell resolution offers exciting opportunities for investigating complex in vivo processes. In C. elegans, this allows systematic tracking of every cell at every minute through embryogenesis and the gathering of thousands of quantitative measurements of individual cell behavior per embryo. A major challenge lies in translating the information into a mechanistic understanding of development. We report an automated pipeline to infer the developmental landscape based on live imaging and single-cell phenotype analysis. The resulting depiction of the landscape includes: differentiated states, paths traversing the states and genetic pathways and cell-to-cell signaling events that regulate path choices. Our pipeline includes a series of algorithms to (1) digitize embryogenesis by constructing a cell lineage and determining the single-cell expression patterns of cell fate markers; (2) define differentiated states based on combinatorial gene expression patterns and detect state changes in mutants through pattern matching; (3) infer the decision points regulating binary state choices in development using detected homeotic transformations; and (4) predict genetic modules and cell-to-cell signaling events based on systems-level analysis of mutual information between genes and cells across multiple perturbations. These algorithms are general rules for automated reasoning not relying on prior knowledge of gene function or mechanisms. We have validated our approach by dissecting the developmental landscape underlying the specification of early progenitor cells. The resulting systems-wide mechanistic model recapitulates current knowledge of regulation and provides new insights into gene functions, hidden developmental paths and the decision points regulating state transitions.