Single-cell dynamics of chromatin activity during cell lineage differentiation in Caenorhabditis elegans embryos

Single-cell level LasR-mediated quorum sensing response of Pseudomonas aeruginosa to pulses of signal molecules

Quorum sensing (QS) is a communication form between bacteria via small signal molecules that enables global gene regulation as a function of cell density. We applied a microfluidic mother machine to study the kinetics of the QS response of Pseudomonas aeruginosa bacteria to additions and withdrawals of signal molecules. We traced the fast buildup and the subsequent considerably slower decay of a population-level and single-cell-level QS response. We applied a mathematical model to explain the results quantitatively. We found significant heterogeneity in QS on the single-cell level, which may result from variations in quorum-controlled gene expression and protein degradation. Heterogeneity correlates with cell lineage history, too. We used single-cell data to define and quantitatively characterize the population-level quorum state. We found that the population-level QS response is well-defined. The buildup of the quorum is fast upon signal molecule addition. At the same time, its decay is much slower following signal withdrawal, and the quorum may be maintained for several hours in the absence of the signal. Furthermore, the quorum sensing response of the population was largely repeatable in subsequent pulses of signal molecules.

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).

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.

Novel metrics reveal new structure and unappreciated heterogeneity in Caenorhabditis elegans development

High throughput experimental approaches are increasingly allowing for the quantitative description of cellular and organismal phenotypes. Distilling these large volumes of complex data into meaningful measures that can drive biological insight remains a central challenge. In the quantitative study of development, for instance, one can resolve phenotypic measures for single cells onto their lineage history, enabling joint consideration of heritable signals and cell fate decisions. Most attempts to analyze this type of data, however, discard much of the information content contained within lineage trees. In this work we introduce a generalized metric, which we term the branch edit distance, that allows us to compare any two embryos based on phenotypic measurements in individual cells. This approach aligns those phenotypic measurements to the underlying lineage tree, providing a flexible and intuitive framework for quantitative comparisons between, for instance, Wild-Type (WT) and mutant developmental programs. We apply this novel metric to data on cell-cycle timing from over 1300 WT and RNAi-treated Caenorhabditis elegans embryos. Our new metric revealed surprising heterogeneity within this data set, including subtle batch effects in WT embryos and dramatic variability in RNAi-induced developmental phenotypes, all of which had been missed in previous analyses. Further investigation of these results suggests a novel, quantitative link between pathways that govern cell fate decisions and pathways that pattern cell cycle timing in the early embryo. Our work demonstrates that the branch edit distance we propose, and similar metrics like it, have the potential to revolutionize our quantitative understanding of organismal phenotype.

Novel metrics reveal new structure and unappreciated heterogeneity in C. elegans development

High throughput experimental approaches are increasingly allowing for the quantitative description of cellular and organismal phenotypes. Distilling these large volumes of complex data into meaningful measures that can drive biological insight remains a central challenge. In the quantitative study of development, for instance, one can resolve phenotypic measures for single cells onto their lineage history, enabling joint consideration of heritable signals and cell fate decisions. Most attempts to analyze this type of data, however, discard much of the information content contained within lineage trees. In this work we introduce a generalized metric, which we term the branch distance, that allows us to compare any two embryos based on phenotypic measurements in individual cells. This approach aligns those phenotypic measurements to the underlying lineage tree, providing a flexible and intuitive framework for quantitative comparisons between, for instance, Wild-Type (WT) and mutant developmental programs. We apply this novel metric to data on cell-cycle timing from over 1300 WT and RNAi-treated Caenorhabditis elegans embryos. Our new metric revealed surprising heterogeneity within this data set, including subtle batch effects in WT embryos and dramatic variability in RNAi-induced developmental phenotypes, all of which had been missed in previous analyses. Further investigation of these results suggests a novel, quantitative link between pathways that govern cell fate decisions and pathways that pattern cell cycle timing in the early embryo. Our work demonstrates that the branch distance we propose, and similar metrics like it, have the potential to revolutionize our quantitative understanding of organismal phenotype.

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.

Live imaging of postembryonic developmental processes in C. elegans

Live imaging is an important tool to track dynamic processes such as neuronal patterning events. Here, we describe a protocol for time-lapse microscopy analysis using neuronal migration and dendritic growth as examples. This protocol can provide detailed information for understanding cellular dynamics during postembryonic development in Caenorhabditis elegans (C. elegans). For complete details on the use and execution of this protocol, please refer to Feng et al. (2020), Li et al. (2021), and Wang et al. (2021).