Computable early Caenorhabditis elegans embryo with a phase field model.

Morphogenesis is a precise and robust dynamic process during metazoan embryogenesis, consisting of both cell proliferation and cell migration. Despite the fact that much is known about specific regulations at molecular level, how cell proliferation and migration together drive the morphogenesis at cellular and organismic levels is not well understood. Using Caenorhabditis elegans as the model animal, we present a phase field model to compute early embryonic morphogenesis within a confined eggshell. With physical information about cell division obtained from three-dimensional time-lapse cellular imaging experiments, the model can precisely reproduce the early morphogenesis process as seen in vivo, including time evolution of location and morphology of each cell. Furthermore, the model can be used to reveal key cell-cell attractions critical to the development of C. elegans embryo. Our work demonstrates how genetic programming and physical forces collaborate to drive morphogenesis and provides a predictive model to decipher the underlying mechanism.

Multilevel regulation of muscle-specific transcription factor hlh-1 during Caenorhabditis elegans embryogenesis.

hlh-1 is a myogenic transcription factor required for body-wall muscle specification during embryogenesis in Caenorhabditis elegans. Despite its well-known role in muscle specification, comprehensive regulatory control upstream of hlh-1 remains poorly defined. Here, we first established a statistical reference for the spatiotemporal expression of hlh-1 at single-cell resolution up to the second last round of divisions for most of the cell lineages (from 4- to 350-cell stage) using 13 wild-type embryos. We next generated lineal expression of hlh-1 after RNA interference (RNAi) perturbation of 65 genes, which were selected based on their degree of conservation, mutant phenotypes, and known roles in development. We then compared the expression profiles between wild-type and RNAi embryos by clustering according to their lineal expression patterns using mean-shift and density-based clustering algorithms, which not only confirmed the roles of existing genes but also uncovered the potential functions of novel genes in muscle specification at multiple levels, including cellular, lineal, and embryonic levels. By combining the public data on protein-protein interactions, protein-DNA interactions, and genetic interactions with our RNAi data, we inferred regulatory pathways upstream of hlh-1 that function globally or locally. This work not only revealed diverse and multilevel regulatory mechanisms coordinating muscle differentiation during C. elegans embryogenesis but also laid a foundation for further characterizing the regulatory pathways controlling muscle specification at the cellular, lineal (local), or embryonic (global) level.

Why and how the nematode's early embryogenesis can be precise and robust: a mechanical perspective.

The early embryogenesis in the nematode Caenorhabditis elegans is well-known for its stereotypic precision of cell arrangements and their lineage relationship. Much research has been focused on how biochemical processes achieve the highly reproducible cell lineage tree. However, the origin of the robustness in the cell arrangements is poorly understood. Here, we set out to provide a mechanistic explanation of how combining mechanical forces with the order and orientation of cell division ensures a robust arrangement of cells. We used a simplified mechanical model to simulate the arrangement of cells in the face of different disturbances. As a result, we revealed three fail-safe principles for cell self-organization in early nematode embryogenesis: ordering, simultaneity, and the division orientation of cell division events. Our work provides insight into the developmental strategy and contributes to the understanding of how robust or variable the cell arrangement can be in developing embryos.

Characterization and complete genomic analysis of two Salmonella phages, SenALZ1 and SenASZ3, new members of the genus Cba120virus.

Salmonella phages SenALZ1 and SenASZ3, two novel phages infecting Salmonella enterica, were isolated and analyzed. The genomes of these two phages consist of 154,811 and 157,630 base pairs (bp), with G+C contents of 44.56% and 44.74%, respectively. Fifty-nine of 199 open reading frames (ORFs) in the SenALZ1 genome, and 60 of the 204 in the SenASZ3 genome show similarity to reference sequences in the NCBI nr database that encode putative phage proteins with predicted functions. Based on the results of transmission electron microscopy (TEM) examination, complete genome sequence alignment, phylogenetic analysis, and gene annotation, we propose that these two phages are representative isolates of two new species of the genus Cba120virus, subfamily Cvivirinae, family Ackermannviridae.

Modulating cell proliferation by asymmetric division: A conserved pattern in the early embryogenesis of nematode species.

In the early stage of the nematode Caenorhabditis elegans embryogenesis, the zygote divides asymmetrically into a symmetric fast lineage and an asymmetric slow lineage, producing 16 and 8 cells respectively almost at the same time, followed by the onset of gastrulation. It was recently reported that this cell division pattern is optimal for rapid cell proliferation. In this work, we compare the cell lineages of 9 nematode species, revealing that this pattern is conserved for >60 million years. It further suggests that such lineage design has an important functional role and it might speed up embryonic development in the nematode kingdom, not limited to C. elegans , and independent of the maternal-zygotic transition dynamics.

Characterizing Cellular Physiological States with Three-Dimensional Shape Descriptors for Cell Membranes.

The shape of a cell as defined by its membrane can be closely associated with its physiological state. For example, the irregular shapes of cancerous cells and elongated shapes of neuron cells often reflect specific functions, such as cell motility and cell communication. However, it remains unclear whether and which cell shape descriptors can characterize different cellular physiological states. In this study, 12 geometric shape descriptors for a three-dimensional (3D) object were collected from the previous literature and tested with a public dataset of ~400,000 independent 3D cell regions segmented based on fluorescent labeling of the cell membranes in Caenorhabditis elegans embryos. It is revealed that those shape descriptors can faithfully characterize cellular physiological states, including (1) cell division (cytokinesis), along with an abrupt increase in the elongation ratio; (2) a negative correlation of cell migration speed with cell sphericity; (3) cell lineage specification with symmetrically patterned cell shape changes; and (4) cell fate specification with differential gene expression and differential cell shapes. The descriptors established may be used to identify and predict the diverse physiological states in numerous cells, which could be used for not only studying developmental morphogenesis but also diagnosing human disease (e.g., the rapid detection of abnormal cells).

MorphoSim: an efficient and scalable phase-field framework for accurately simulating multicellular morphologies.

The phase field model can accurately simulate the evolution of microstructures with complex morphologies, and it has been widely used for cell modeling in the last two decades. However, compared to other cellular models such as the coarse-grained model and the vertex model, its high computational cost caused by three-dimensional spatial discretization hampered its application and scalability, especially for multicellular organisms. Recently, we built a phase field model coupled with in vivo imaging data to accurately reconstruct the embryonic morphogenesis of Caenorhabditis elegans from 1- to 8-cell stages. In this work, we propose an improved phase field model by using the stabilized numerical scheme and modified volume constriction. Then we present a scalable phase-field framework, MorphoSim, which is 100 times more efficient than the previous one and can simulate over 100 mechanically interacting cells. Finally, we demonstrate how MorphoSim can be successfully applied to reproduce the assembly, self-repairing, and dissociation of a synthetic artificial multicellular system - the synNotch system.

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.

Initial characterization of gap phase introduction in every cell cycle of C. elegans embryogenesis.

Early embryonic cell cycles usually alternate between S and M phases without any gap phase. When the gap phases are developmentally introduced in various cell types remains poorly defined especially during embryogenesis. To establish the cell-specific introduction of gap phases in embryo, we generate multiple fluorescence ubiquitin cell cycle indicators (FUCCI) in C. elegans. Time-lapse 3D imaging followed by lineal expression profiling reveals sharp and differential accumulation of the FUCCI reporters, allowing the systematic demarcation of cell cycle phases throughout embryogenesis. Accumulation of the reporters reliably identifies both G1 and G2 phases only in two embryonic cells with an extended cell cycle length, suggesting that the remaining cells divide either without a G1 phase, or with a brief G1 phase that is too short to be picked up by our reporters. In summary, we provide an initial picture of gap phase introduction in a metazoan embryo. The newly developed FUCCI reporters pave the way for further characterization of developmental control of cell cycle progression.

Volume segregation programming in a nematode's early embryogenesis.

Nematode species are well-known for their invariant cell lineage pattern during development. Combining knowledge about the fate specification induced by asymmetric division and the anti-correlation between cell cycle length and cell volume in Caenorhabditis elegans, we propose a minimal model to simulate lineage initiation by altering cell volume segregation ratio in each division, and quantify the derived pattern's performance in proliferation speed, fate diversity, and space robustness. The stereotypic pattern in C. elegans embryo is found to be one of the most optimal solutions taking minimum time to achieve the cell number before gastrulation, by programming asymmetric divisions as a strategy.

Establishment of a morphological atlas of the Caenorhabditis elegans embryo using deep-learning-based 4D segmentation.

The invariant development and transparent body of the nematode Caenorhabditis elegans enables complete delineation of cell lineages throughout development. Despite extensive studies of cell division, cell migration and cell fate differentiation, cell morphology during development has not yet been systematically characterized in any metazoan, including C. elegans. This knowledge gap substantially hampers many studies in both developmental and cell biology. Here we report an automatic pipeline, CShaper, which combines automated segmentation of fluorescently labeled membranes with automated cell lineage tracing. We apply this pipeline to quantify morphological parameters of densely packed cells in 17 developing C. elegans embryos. Consequently, we generate a time-lapse 3D atlas of cell morphology for the C. elegans embryo from the 4- to 350-cell stages, including cell shape, volume, surface area, migration, nucleus position and cell-cell contact with resolved cell identities. We anticipate that CShaper and the morphological atlas will stimulate and enhance further studies in the fields of developmental biology, cell biology and biomechanics.