Systems Properties and Spatiotemporal Regulation of Cell Position Variability during Embryogenesis

Automated cell lineage reconstruction using label-free 4D microscopy

Patterns of lineal descent play a critical role in the development of metazoan embryos. In eutelic organisms that generate a fixed number of somatic cells, invariance in the topology of their cell lineage provides a powerful opportunity to interrogate developmental events with empirical repeatability across individuals. Studies of embryonic development using the nematode Caenorhabditis elegans have been drivers of discovery. These studies have depended heavily on high-throughput lineage tracing enabled by 4D fluorescence microscopy and robust computer vision pipelines. For a range of applications, computer-aided yet manual lineage tracing using 4D label-free microscopy remains an essential tool. Deep learning approaches to cell detection and tracking in fluorescence microscopy have advanced significantly in recent years, yet solutions for automating cell detection and tracking in 3D label-free imaging of dense tissues and embryos remain inaccessible. Here, we describe embGAN, a deep learning pipeline that addresses the challenge of automated cell detection and tracking in label-free 3D time-lapse imaging. embGAN requires no manual data annotation for training, learns robust detections that exhibits a high degree of scale invariance, and generalizes well to images acquired in multiple labs on multiple instruments. We characterize embGAN's performance using lineage tracing in the C. elegans embryo as a benchmark. embGAN achieves near-state-of-the-art performance in cell detection and tracking, enabling high-throughput studies of cell lineage without the need for fluorescent reporters or transgenics.

A lineage-resolved cartography of microRNA promoter activity in C. elegans empowers multidimensional developmental analysis

Elucidating the expression of microRNAs in developing single cells is critical for functional discovery. Here, we construct scCAMERA (single-cell cartography of microRNA expression based on reporter assay), utilizing promoter-driven fluorescent reporters in conjunction with imaging and lineage tracing. The cartography delineates the transcriptional activity of 54 conserved microRNAs in lineage-resolved single cells throughout C. elegans embryogenesis. The combinatorial expression of microRNAs partitions cells into fine clusters reflecting their function and anatomy. Notably, the expression of individual microRNAs exhibits high cell specificity and divergence among family members. Guided by cellular expression patterns, we identify developmental functions of specific microRNAs, including miR-1 in pharynx development and physiology, miR-232 in excretory canal morphogenesis by repressing NHR-25/NR5A, and a functional synergy between miR-232 and miR-234 in canal development, demonstrating the broad utility of scCAMERA. Furthermore, integrative analysis reveals that tissue-specific fate determinants activate microRNAs to repress protein production from leaky transcripts associated with alternative, especially neuronal, fates, thereby enhancing the fidelity of developmental fate differentiation. Collectively, our study offers rich opportunities for multidimensional expression-informed analysis of microRNA biology in metazoans.

Spatiotemporal analysis of mRNA-protein relationships enhances transcriptome-based developmental inference

Elucidating the complex relationships between mRNA and protein expression at high spatiotemporal resolution is critical for unraveling multilevel gene regulation and enhancing mRNA-based developmental analyses. In this study, we conduct a single-cell analysis of mRNA and protein expression of transcription factors throughout C. elegans embryogenesis. Initially, cellular co-presence of mRNA and protein is low, increasing to a medium-high level (73%) upon factoring in delayed protein synthesis and long-term protein persistence. These factors substantially affect mRNA-protein concordance, leading to potential inaccuracies in mRNA-reliant gene detection and specificity characterization. Building on the learned relationship, we infer protein presence from mRNA expression and demonstrate its utility in identifying tissue-specific genes and elucidating relationships between genes and cells. This approach facilitates identifying the role of sptf-1/SP7 in neuronal lineage development. Collectively, this study provides insights into gene expression dynamics during rapid embryogenesis and approaches for improving the efficacy of transcriptome-based developmental analyses.

Automated Cell Lineage Reconstruction using Label-Free 4D Microscopy

Here we describe embGAN, a deep learning pipeline that addresses the challenge of automated cell detection and tracking in label-free 3D time lapse imaging. embGAN requires no manual data annotation for training, learns robust detections that exhibits a high degree of scale invariance and generalizes well to images acquired in multiple labs on multiple instruments.

Systematic analysis of cell morphodynamics in C. elegans early embryogenesis

The invariant cell lineage of Caenorhabditis elegans allows unambiguous assignment of the identity for each cell, which offers a unique opportunity to study developmental dynamics such as the timing of cell division, dynamics of gene expression, and cell fate decisions at single-cell resolution. However, little is known about cell morphodynamics, including the extent to which they are variable between individuals, mainly due to the lack of sufficient amount and quality of quantified data. In this study, we systematically quantified the cell morphodynamics in 52 C. elegans embryos from the two-cell stage to mid-gastrulation at the high spatiotemporal resolution, 0.5 μm thickness of optical sections, and 30-second intervals of recordings. Our data allowed systematic analyses of the morphological features. We analyzed sphericity dynamics and found a significant increase at the end of metaphase in every cell, indicating the universality of the mitotic cell rounding. Concomitant with the rounding, the volume also increased in most but not all cells, suggesting less universality of the mitotic swelling. Combining all features showed that cell morphodynamics was unique for each cell type. The cells before the onset of gastrulation could be distinguished from all the other cell types. Quantification of reproducibility in cell-cell contact revealed that variability in division timings and cell arrangements produced variability in contacts between the embryos. However, the area of such contacts occupied less than 5% of the total area, suggesting the high reproducibility of spatial occupancies and adjacency relationships of the cells. By comparing the morphodynamics of identical cells between the embryos, we observed diversity in the variability between cells and found it was determined by multiple factors, including cell lineage, cell generation, and cell-cell contact. We compared the variabilities of cell morphodynamics and cell-cell contacts with those in ascidian Phallusia mammillata embryos. The variabilities were larger in C. elegans, despite smaller differences in embryo size and number of cells at each developmental stage.

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.

Defect-buffering cellular plasticity increases robustness of metazoan embryogenesis

Developmental processes are intrinsically robust so as to preserve a normal-like state in response to genetic and environmental fluctuations. However, the robustness and potential phenotypic plasticity of individual developing cells under genetic perturbations remain to be systematically evaluated. Using large-scale gene perturbation, live imaging, lineage tracing, and single-cell phenomics, we quantified the phenotypic landscape of C. elegans embryogenesis in >2,000 embryos following individual knockdown of over 750 conserved genes. We observed that cellular genetic systems are not sufficiently robust to single-gene perturbations across all cells; rather, gene knockdowns frequently induced cellular defects. Dynamic phenotypic analyses revealed many cellular defects to be transient, with cells exhibiting phenotypic plasticity that serves to alleviate, correct, and accommodate the defects. Moreover, potential developmentally related cell modules may buffer the phenotypic effects of individual cell position changes. Our findings reveal non-negligible contributions of cellular plasticity and multicellularity as compensatory strategies to increase developmental robustness.

Feedforward regulatory logic controls the specification-to-differentiation transition and terminal cell fate during Caenorhabditis elegans endoderm development

The architecture of gene regulatory networks determines the specificity and fidelity of developmental outcomes. We report that the core regulatory circuitry for endoderm development in Caenorhabditis elegans operates through a transcriptional cascade consisting of six sequentially expressed GATA-type factors that act in a recursive series of interlocked feedforward modules. This structure results in sequential redundancy, in which removal of a single factor or multiple alternate factors in the cascade leads to a mild or no effect on gut development, whereas elimination of any two sequential factors invariably causes a strong phenotype. The phenotypic strength is successfully predicted with a computational model based on the timing and levels of transcriptional states. We found that one factor in the middle of the cascade, END-1, which straddles the distinct events of specification and differentiation, functions in both processes. Finally, we reveal roles for key GATA factors in establishing spatial regulatory state domains by repressing other fates, thereby defining boundaries in the digestive tract. Our findings provide a paradigm that could account for the genetic redundancy observed in many developmental regulatory systems.

Computational modeling and analysis of the morphogenetic domain signaling networks regulating C. elegans embryogenesis

Caenorhabditis elegans, often referred to as the ‘roundworm’, provides a powerful model for studying cell autonomous and cell–cell interactions through the direct observation of embryonic development in vivo. By leveraging the precisely mapped cell lineage at single cell resolution, we are able to study at a systems level how early embryonic cells communicate across morphogenetic domains for the coordinated processes of gene expressions and collective cellular behaviors that regulate tissue morphogenesis. In this study, we developed a computational framework for the exploration of the morphogenetic domain cell signaling networks that may regulate C. elegans gastrulation and embryonic organogenesis. We demonstrated its utility by producing the following results, i) established a virtual reference model of developing C. elegans embryos through the spatiotemporal alignment of individual embryo cell nuclear imaging samples; ii) integrated the single cell spatiotemporal gene expression profile with the established virtual embryo model by data pooling; iii) trained a Machine Learning model (Random Forest Regression), which predicts accurately the spatial positions of the cells given their gene expression profiles for a given developmental time (e.g. total cell number of the embryo); iv) enabled virtual 4-dimensional tomographic graphical modeling of single cell data; v) inferred the biology signaling pathways that act in each of morphogenetic domains by meta-data analysis. It is intriguing that the morphogenetic domain cell signaling network seems to involve some crosstalk of multiple biology signaling pathways during the formation of tissue boundary pattern. Lastly, we developed the Software tool ‘Embryo aligner version 1.0’ and provided it as an Open Source program to the research community for virtual embryo modeling, and phenotype perturbation analyses (https://github.com/csniuben/embryo_aligner/wiki and https://bioinfo89.github.io/C.elegansEmbryonicOrganogenesisweb/).

C. elegans: A biosensor for host-microbe interactions

Microbes are an integral part of life on this planet. Microbes and their hosts influence each other in an endless dance that shapes how the meta-organism interacts with its environment. Although great advances have been made in microbiome research over the past 20 years, the mechanisms by which both hosts and their microbes interact with each other and the environment are still not well understood. The nematode Caenorhabditis elegans has been widely used as a model organism to study a remarkable number of human-like processes. Recent evidence shows that the worm is a powerful tool to investigate in fine detail the complexity that exists in microbe-host interactions. By combining the large array of genetic tools available for both organisms together with deep phenotyping approaches, it has been possible to uncover key effectors in the complex relationship between microbes and their hosts. In this perspective, we survey the literature for insightful discoveries in the microbiome field using the worm as a model. We discuss the latest conceptual and technological advances in the field and highlight the strengths that make C. elegans a valuable biosensor tool for the study of microbe-host interactions.

Contact area-dependent cell communication and the morphological invariance of ascidian embryogenesis

Marine invertebrate ascidians display embryonic reproducibility: Their early embryonic cell lineages are considered invariant and are conserved between distantly related species, despite rapid genomic divergence. Here, we address the drivers of this reproducibility. We used light-sheet imaging and automated cell segmentation and tracking procedures to systematically quantify the behavior of individual cells every 2 minutes during Phallusia mammillata embryogenesis. Interindividual reproducibility was observed down to the area of individual cell contacts. We found tight links between the reproducibility of embryonic geometries and asymmetric cell divisions, controlled by differential sister cell inductions. We combined modeling and experimental manipulations to show that the area of contact between signaling and responding cells is a key determinant of cell communication. Our work establishes the geometric control of embryonic inductions as an alternative to classical morphogen gradients and suggests that the range of cell signaling sets the scale at which embryonic reproducibility is observed.

Cell lineage-dependent chiral actomyosin flows drive cellular rearrangements in early Caenorhabditis elegans development

Proper positioning of cells is essential for many aspects of development. Daughter cell positions can be specified via orienting the cell division axis during cytokinesis. Rotatory actomyosin flows during division have been implied in specifying and reorienting the cell division axis, but how general such reorientation events are, and how they are controlled, remains unclear. We followed the first nine divisions of Caenorhabditis elegans embryo development and demonstrate that chiral counter-rotating flows arise systematically in early AB lineage, but not in early P/EMS lineage cell divisions. Combining our experiments with thin film active chiral fluid theory we identify a mechanism by which chiral counter-rotating actomyosin flows arise in the AB lineage only, and show that they drive lineage-specific spindle skew and cell reorientation events. In conclusion, our work sheds light on the physical processes that underlie chiral morphogenesis in early development.

Systematic genetics and single-cell imaging reveal widespread morphological pleiotropy and cell-to-cell variability

Our ability to understand the genotype-to-phenotype relationship is hindered by the lack of detailed understanding of phenotypes at a single-cell level. To systematically assess cell-to-cell phenotypic variability, we combined automated yeast genetics, high-content screening and neural network-based image analysis of single cells, focussing on genes that influence the architecture of four subcellular compartments of the endocytic pathway as a model system. Our unbiased assessment of the morphology of these compartments-endocytic patch, actin patch, late endosome and vacuole-identified 17 distinct mutant phenotypes associated with ~1,600 genes (~30% of all yeast genes). Approximately half of these mutants exhibited multiple phenotypes, highlighting the extent of morphological pleiotropy. Quantitative analysis also revealed that incomplete penetrance was prevalent, with the majority of mutants exhibiting substantial variability in phenotype at the single-cell level. Our single-cell analysis enabled exploration of factors that contribute to incomplete penetrance and cellular heterogeneity, including replicative age, organelle inheritance and response to stress.