Cell shape characterization, alignment, and comparison using FlowShape.

MOTIVATION: The shape of a cell is tightly controlled, and reflects important processes including actomyosin activity, adhesion properties, cell differentiation, and polarization. Hence, it is informative to link cell shape to genetic and other perturbations. However, most currently used cell shape descriptors capture only simple geometric features such as volume and sphericity. We propose FlowShape, a new framework to study cell shapes in a complete and generic way. RESULTS: In our framework a cell shape is represented by measuring the curvature of the shape and mapping it onto a sphere in a conformal manner. This single function on the sphere is next approximated by a series expansion: the spherical harmonics decomposition. The decomposition facilitates many analyses, including shape alignment and statistical cell shape comparison. The new tool is applied to perform a complete, generic analysis of cell shapes, using the early Caenorhabditis elegans embryo as a model case. We distinguish and characterize the cells at the seven-cell stage. Next, a filter is designed to identify protrusions on the cell shape to highlight lamellipodia in cells. Further, the framework is used to identify any shape changes following a gene knockdown of the Wnt pathway. Cells are first optimally aligned using the fast Fourier transform, followed by calculating an average shape. Shape differences between conditions are next quantified and compared to an empirical distribution. Finally, we put forward a highly performant implementation of the core algorithm, as well as routines to characterize, align and compare cell shapes, through the open-source software package FlowShape. AVAILABILITY AND IMPLEMENTATION: The data and code needed to recreate the results are freely available at https://doi.org/10.5281/zenodo.7778752. The most recent version of the software is maintained at https://bitbucket.org/pgmsembryogenesis/flowshape/.

Yolk-deprived Caenorhabditis elegans secure brood size at the expense of competitive fitness.

Oviparous animals support reproduction via the incorporation of yolk as a nutrient source into the eggs. In Caenorhabditis elegans, however, yolk proteins seem dispensable for fecundity, despite constituting the vast majority of the embryonic protein pool and acting as carriers for nutrient-rich lipids. Here, we used yolk protein-deprived C. elegans mutants to gain insight into the traits that may yet be influenced by yolk rationing. We show that massive yolk provisioning confers a temporal advantage during embryogenesis, while also increasing early juvenile body size and promoting competitive fitness. Opposite to species that reduce egg production under yolk deprivation, our results indicate that C. elegans relies on yolk as a fail-safe to secure offspring survival, rather than to maintain offspring numbers.

Stability of asymmetric cell division: A deformable cell model of cytokinesis applied to C. elegans.

Cell division during early embryogenesis is linked to key morphogenic events such as embryo symmetry breaking and tissue patterning. It is thought that the physical surrounding of cells together with cell intrinsic cues act as a mechanical "mold," guiding cell division to ensure these events are robust. To quantify how cell division is affected by the mechanical and geometrical environment, we present a novel computational mechanical model of cytokinesis, the final phase of cell division. Simulations with the model reproduced experimentally observed furrow dynamics and describe the volume ratio of daughter cells in asymmetric cell divisions, based on the position and orientation of the mitotic spindle. For dividing cells in geometrically confined environments, we show how the orientation of confinement relative to the division axis modulates the volume ratio in asymmetric cell division. Further, we quantified how cortex viscosity and surface tension determine the shape of a dividing cell and govern bubble-instabilities in asymmetric cell division. Finally, we simulated the formation of the three body axes via sequential (a)symmetric divisions up until the six-cell stage of early C. elegans development, which proceeds within the confines of an eggshell. We demonstrate how model input parameters spindle position and orientation provide sufficient information to reliably predict the volume ratio of daughter cells during the cleavage phase of development. However, for egg geometries perturbed by compression, the model predicts that a change in confinement alone is insufficient to explain experimentally observed differences in cell volume. This points to an effect of the compression on the spindle positioning mechanism. Additionally, the model predicts that confinement stabilizes asymmetric cell divisions against bubble-instabilities.

Wnt Signaling Induces Asymmetric Dynamics in the Actomyosin Cortex of the C. elegans Endomesodermal Precursor Cell.

During asymmetrical division of the endomesodermal precursor cell EMS, a cortical flow arises, and the daughter cells, endodermal precursor E and mesodermal precursor MS, have an enduring difference in the levels of F-actin and non-muscular myosin. Ablation of the cell cortex suggests that these observed differences lead to differences in cortical tension. The higher F-actin and myosin levels in the MS daughter coincide with cell shape changes and relatively lower tension, indicating a soft, actively moving cell, whereas the lower signal in the E daughter cell is associated with higher tension and a more rigid, spherical shape. The cortical flow is under control of the Wnt signaling pathway. Perturbing the pathway removes the asymmetry arising during EMS division and induces subtle defects in the cellular movements at the eight-cell stage. The perturbed cellular movement appears to be associated with an asymmetric distribution of E-cadherin across the EMS cytokinesis groove. ABpl forms a lamellipodium which preferentially adheres to MS by the E-cadherin HMR-1. The HMR-1 asymmetry across the groove is complete just at the moment cytokinesis completes. Perturbing Wnt signaling equalizes the HMR-1 distribution across the lamellipodium. We conclude that Wnt signaling induces a cortical flow during EMS division, which results in a transition in the cortical contractile network for the daughter cells, as well as an asymmetric distribution of E-cadherin.

spheresDT/Mpacts-PiCS: cell tracking and shape retrieval in membrane-labeled embryos.

MOTIVATION: Uncovering the cellular and mechanical processes that drive embryo formation requires an accurate read out of cell geometries over time. However, automated extraction of 3D cell shapes from time-lapse microscopy remains challenging, especially when only membranes are labeled. RESULTS: We present an image analysis framework for automated tracking and three-dimensional cell segmentation in confocal time lapses. A sphere clustering approach allows for local thresholding and application of logical rules to facilitate tracking and unseeded segmentation of variable cell shapes. Next, the segmentation is refined by a discrete element method simulation where cell shapes are constrained by a biomechanical cell shape model. We apply the framework on Caenorhabditis elegans embryos in various stages of early development and analyze the geometry of the 7- and 8-cell stage embryo, looking at volume, contact area and shape over time. AVAILABILITY AND IMPLEMENTATION: The Python code for the algorithm and for measuring performance, along with all data needed to recreate the results is freely available at 10.5281/zenodo.5108416 and 10.5281/zenodo.4540092. The most recent version of the software is maintained at https://bitbucket.org/pgmsembryogenesis/sdt-pics. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Physically asymmetric division of the C. elegans zygote ensures invariably successful embryogenesis.

Asymmetric divisions that yield daughter cells of different sizes are frequent during early embryogenesis, but the importance of such a physical difference for successful development remains poorly understood. Here, we investigated this question using the first division of Caenorhabditis elegans embryos, which yields a large AB cell and a small P1 cell. We equalized AB and P1 sizes using acute genetic inactivation or optogenetic manipulation of the spindle positioning protein LIN-5. We uncovered that only some embryos tolerated equalization, and that there was a size asymmetry threshold for viability. Cell lineage analysis of equalized embryos revealed an array of defects, including faster cell cycle progression in P1 descendants, as well as defects in cell positioning, division orientation, and cell fate. Moreover, equalized embryos were more susceptible to external compression. Overall, we conclude that unequal first cleavage is essential for invariably successful embryonic development of C. elegans.

Gene Loss Predictably Drives Evolutionary Adaptation.

Loss of gene function is common throughout evolution, even though it often leads to reduced fitness. In this study, we systematically evaluated how an organism adapts after deleting genes that are important for growth under oxidative stress. By evolving, sequencing, and phenotyping over 200 yeast lineages, we found that gene loss can enhance an organism's capacity to evolve and adapt. Although gene loss often led to an immediate decrease in fitness, many mutants rapidly acquired suppressor mutations that restored fitness. Depending on the strain's genotype, some ultimately even attained higher fitness levels than similarly adapted wild-type cells. Further, cells with deletions in different modules of the genetic network followed distinct and predictable mutational trajectories. Finally, losing highly connected genes increased evolvability by facilitating the emergence of a more diverse array of phenotypes after adaptation. Together, our findings show that loss of specific parts of a genetic network can facilitate adaptation by opening alternative evolutionary paths.

Neuromedin U signaling regulates retrieval of learned salt avoidance in a C. elegans gustatory circuit.

Learning and memory are regulated by neuromodulatory pathways, but the contribution and temporal requirement of most neuromodulators in a learning circuit are unknown. Here we identify the evolutionarily conserved neuromedin U (NMU) neuropeptide family as a regulator of C. elegans gustatory aversive learning. The NMU homolog CAPA-1 and its receptor NMUR-1 are required for the retrieval of learned salt avoidance. Gustatory aversive learning requires the release of CAPA-1 neuropeptides from sensory ASG neurons that respond to salt stimuli in an experience-dependent manner. Optogenetic silencing of CAPA-1 neurons blocks the expression, but not the acquisition, of learned salt avoidance. CAPA-1 signals through NMUR-1 in AFD sensory neurons to modulate two navigational strategies for salt chemotaxis. Aversive conditioning thus recruits NMU signaling to modulate locomotor programs for expressing learned avoidance behavior. Because NMU signaling is conserved across bilaterian animals, our findings incite further research into its function in other learning circuits.

Network hubs affect evolvability.

The regulatory processes in cells are typically organized into complex genetic networks. However, it is still unclear how this network structure modulates the evolution of cellular regulation. One would expect that mutations in central and highly connected modules of a network (so-called hubs) would often result in a breakdown and therefore be an evolutionary dead end. However, a new study by Koubkova-Yu and colleagues finds that in some circumstances, altering a hub can offer a quick evolutionary advantage. Specifically, changes in a hub can induce significant phenotypic changes that allow organisms to move away from a local fitness peak, whereas the fitness defects caused by the perturbed hub can be mitigated by mutations in its interaction partners. Together, the results demonstrate how network architecture shapes and facilitates evolutionary adaptation.

Mitochondrial ubiquinone-mediated longevity is marked by reduced cytoplasmic mRNA translation.

Mutations in the clk-1 gene impair mitochondrial ubiquinone biosynthesis and extend lifespan in C. elegans. We demonstrate here that this life extension is linked to the repression of cytoplasmic mRNA translation, independent of the alleged nuclear form of CLK-1. Clk-1 mutations inhibit polyribosome formation similarly to daf-2 mutations that dampen insulin signaling. Comparisons of total versus polysomal RNAs in clk-1(qm30) mutants reveal a reduction in the translational efficiencies of mRNAs coding for elements of the translation machinery and an increase in those coding for the oxidative phosphorylation and autophagy pathways. Knocking down the transcription initiation factor TAF-4, a protein that becomes sequestered in the cytoplasm during early embryogenesis to induce transcriptional silencing, ameliorates the clk-1 inhibition of polyribosome formation. These results underscore a prominent role for the repression of cytoplasmic protein synthesis in eukaryotic lifespan extension and suggest that mutations impairing mitochondrial function are able to exploit this repression similarly to reductions of insulin signaling. Moreover, this report reveals an unexpected role for TAF-4 as a repressor of polyribosome formation when ubiquinone biosynthesis is compromised.

Compensatory Cell Movements Confer Robustness to Mechanical Deformation during Embryonic Development.

Embryonic development must proceed despite both internal molecular fluctuations and external perturbations. However, mechanisms that provide robustness to mechanical perturbation remain largely uncharacterized. Here, we use light-sheet microscopy, comprehensive single-cell tracking, and targeted cell ablation to study the response of Caenorhabditis elegans embryos to external compression. Compression changes the relative positions of many cells and causes severe distortions of the embryonic axes. A large-scale movement of cells then corrects this distortion. Only a few specific cells are required for these compensatory movements, and one cell, ABarppap, appears to generate force, dramatically changing as it moves to its correct local cellular environment. During these movements, we also observed "egressions", cells moving out onto the surface, and lineages that undergo both ingression and egression. In total, our work describes how the embryo responds to a major mechanical deformation that can occur during the early development in situ and puts forward a model to explain how the response is coordinated.

Adaptation to High Ethanol Reveals Complex Evolutionary Pathways.

Tolerance to high levels of ethanol is an ecologically and industrially relevant phenotype of microbes, but the molecular mechanisms underlying this complex trait remain largely unknown. Here, we use long-term experimental evolution of isogenic yeast populations of different initial ploidy to study adaptation to increasing levels of ethanol. Whole-genome sequencing of more than 30 evolved populations and over 100 adapted clones isolated throughout this two-year evolution experiment revealed how a complex interplay of de novo single nucleotide mutations, copy number variation, ploidy changes, mutator phenotypes, and clonal interference led to a significant increase in ethanol tolerance. Although the specific mutations differ between different evolved lineages, application of a novel computational pipeline, PheNetic, revealed that many mutations target functional modules involved in stress response, cell cycle regulation, DNA repair and respiration. Measuring the fitness effects of selected mutations introduced in non-evolved ethanol-sensitive cells revealed several adaptive mutations that had previously not been implicated in ethanol tolerance, including mutations in PRT1, VPS70 and MEX67. Interestingly, variation in VPS70 was recently identified as a QTL for ethanol tolerance in an industrial bio-ethanol strain. Taken together, our results show how, in contrast to adaptation to some other stresses, adaptation to a continuous complex and severe stress involves interplay of different evolutionary mechanisms. In addition, our study reveals functional modules involved in ethanol resistance and identifies several mutations that could help to improve the ethanol tolerance of industrial yeasts.

A Long Noncoding RNA on the Ribosome Is Required for Lifespan Extension.

The biogenesis of ribosomes and their coordination of protein translation consume an enormous amount of cellular energy. As such, it has been established that the inhibition of either process can extend eukaryotic lifespan. Here, we used next-generation sequencing to compare ribosome-associated RNAs from normal strains of Caenorhabditis elegans to those carrying the life-extending daf-2 mutation. We found a long noncoding RNA (lncRNA), transcribed telomeric sequence 1 (tts-1), on ribosomes of the daf-2 mutant. Depleting tts-1 in daf-2 mutants increases ribosome levels and significantly shortens their extended lifespan. We find tts-1 is also required for the longer lifespan of the mitochondrial clk-1 mutants but not the feeding-defective eat-2 mutants. In line with this, the clk-1 mutants express more tts-1 and fewer ribosomes than the eat-2 mutants. Our results suggest that the expression of tts-1 functions in different longevity pathways to reduce ribosome levels in a way that promotes life extension.

Comprehensive single cell-resolution analysis of the role of chromatin regulators in early C. elegans embryogenesis.

Chromatin regulators are widely expressed proteins with diverse roles in gene expression, nuclear organization, cell cycle regulation, pluripotency, physiology and development, and are frequently mutated in human diseases such as cancer. Their inhibition often results in pleiotropic effects that are difficult to study using conventional approaches. We have developed a semi-automated nuclear tracking algorithm to quantify the divisions, movements and positions of all nuclei during the early development of Caenorhabditis elegans and have used it to systematically study the effects of inhibiting chromatin regulators. The resulting high dimensional datasets revealed that inhibition of multiple regulators, including F55A3.3 (encoding FACT subunit SUPT16H), lin-53 (RBBP4/7), rba-1 (RBBP4/7), set-16 (MLL2/3), hda-1 (HDAC1/2), swsn-7 (ARID2), and let-526 (ARID1A/1B) affected cell cycle progression and caused chromosome segregation defects. In contrast, inhibition of cir-1 (CIR1) accelerated cell division timing in specific cells of the AB lineage. The inhibition of RNA polymerase II also accelerated these division timings, suggesting that normal gene expression is required to delay cell cycle progression in multiple lineages in the early embryo. Quantitative analyses of the dataset suggested the existence of at least two functionally distinct SWI/SNF chromatin remodeling complex activities in the early embryo, and identified a redundant requirement for the egl-27 and lin-40 MTA orthologs in the development of endoderm and mesoderm lineages. Moreover, our dataset also revealed a characteristic rearrangement of chromatin to the nuclear periphery upon the inhibition of multiple general regulators of gene expression. Our systematic, comprehensive and quantitative datasets illustrate the power of single cell-resolution quantitative tracking and high dimensional phenotyping to investigate gene function. Furthermore, the results provide an overview of the functions of essential chromatin regulators during the early development of an animal.

Predicting phenotypic variation in yeast from individual genome sequences.

A central challenge in genetics is to predict phenotypic variation from individual genome sequences. Here we construct and evaluate phenotypic predictions for 19 strains of Saccharomyces cerevisiae. We use conservation-based methods to predict the impact of protein-coding variation within genes on protein function. We then rank strains using a prediction score that measures the total sum of function-altering changes in different sets of genes reported to influence over 100 phenotypes in genome-wide loss-of-function screens. We evaluate our predictions by comparing them with the observed growth rate and efficiency of 15 strains tested across 20 conditions in quantitative experiments. The median predictive performance, as measured by ROC AUC, was 0.76, and predictions were more accurate when the genes reported to influence a trait were highly connected in a functional gene network.

Integrated genome-scale prediction of detrimental mutations in transcription networks.

A central challenge in genetics is to understand when and why mutations alter the phenotype of an organism. The consequences of gene inhibition have been systematically studied and can be predicted reasonably well across a genome. However, many sequence variants important for disease and evolution may alter gene regulation rather than gene function. The consequences of altering a regulatory interaction (or "edge") rather than a gene (or "node") in a network have not been as extensively studied. Here we use an integrative analysis and evolutionary conservation to identify features that predict when the loss of a regulatory interaction is detrimental in the extensively mapped transcription network of budding yeast. Properties such as the strength of an interaction, location and context in a promoter, regulator and target gene importance, and the potential for compensation (redundancy) associate to some extent with interaction importance. Combined, however, these features predict quite well whether the loss of a regulatory interaction is detrimental across many promoters and for many different transcription factors. Thus, despite the potential for regulatory diversity, common principles can be used to understand and predict when changes in regulation are most harmful to an organism.

Literature-aided interpretation of gene expression data with the weighted global test.

Most methods for the interpretation of gene expression profiling experiments rely on the categorization of genes, as provided by the Gene Ontology (GO) and pathway databases. Due to the manual curation process, such databases are never up-to-date and tend to be limited in focus and coverage. Automated literature mining tools provide an attractive, alternative approach. We review how they can be employed for the interpretation of gene expression profiling experiments. We illustrate that their comprehensive scope aids the interpretation of data from domains poorly covered by GO or alternative databases, and allows for the linking of gene expression with diseases, drugs, tissues and other types of concepts. A framework for proper statistical evaluation of the associations between gene expression values and literature concepts was lacking and is now implemented in a weighted extension of global test. The weights are the literature association scores and reflect the importance of a gene for the concept of interest. In a direct comparison with classical GO-based gene sets, we show that use of literature-based associations results in the identification of much more specific GO categories. We demonstrate the possibilities for linking of gene expression data to patient survival in breast cancer and the action and metabolism of drugs. Coupling with online literature mining tools ensures transparency and allows further study of the identified associations. Literature mining tools are therefore powerful additions to the toolbox for the interpretation of high-throughput genomics data.

Model-based approach for tracking embryogenesis in Caenorhabditis elegans fluorescence microscopy data.

The nematode Caenorhabditis elegans (C. elegans) is a widely used model organism in biological investigations. Due to its well-known and invariant cell lineage tree, it can be used to study the effects of mutations and various disease processes. Effective and efficient analysis of the wealth of time-lapse fluorescence microscopy image data acquired in such studies requires automation of the cell segmentation and tracking tasks involved. This is hampered by many factors, including autofluorescence effects, low and uneven contrast throughout the images, high noise levels, large numbers of possibly simultaneous cell divisions, and touching or clustering cells. In this paper, we present a new algorithm for segmentation and tracking of cells in C. elegans embryogenesis image data. It is based on the model evolution framework for image segmentation and uses a novel multi-object tracking scheme based on energy minimization via graph cuts. Preliminary experiments on publicly available test data demonstrate the potential of the algorithm compared to existing approaches.

Anni 2.0: a multipurpose text-mining tool for the life sciences.

Anni 2.0 is an online tool (http://biosemantics.org/anni/) to aid the biomedical researcher with a broad range of information needs. Anni provides an ontology-based interface to MEDLINE and retrieves documents and associations for several classes of biomedical concepts, including genes, drugs and diseases, with established text-mining technology. In this article we illustrate Anni's usability by applying the tool to two use cases: interpretation of a set of differentially expressed genes, and literature-based knowledge discovery.

Literature-aided meta-analysis of microarray data: a compendium study on muscle development and disease.

BACKGROUND: Comparative analysis of expression microarray studies is difficult due to the large influence of technical factors on experimental outcome. Still, the identified differentially expressed genes may hint at the same biological processes. However, manually curated assignment of genes to biological processes, such as pursued by the Gene Ontology (GO) consortium, is incomplete and limited. We hypothesised that automatic association of genes with biological processes through thesaurus-controlled mining of Medline abstracts would be more effective. Therefore, we developed a novel algorithm (LAMA: Literature-Aided Meta-Analysis) to quantify the similarity between transcriptomics studies. We evaluated our algorithm on a large compendium of 102 microarray studies published in the field of muscle development and disease, and compared it to similarity measures based on gene overlap and over-representation of biological processes assigned by GO. RESULTS: While the overlap in both genes and overrepresented GO-terms was poor, LAMA retrieved many more biologically meaningful links between studies, with substantially lower influence of technical factors. LAMA correctly grouped muscular dystrophy, regeneration and myositis studies, and linked patient and corresponding mouse model studies. LAMA also retrieves the connecting biological concepts. Among other new discoveries, we associated cullin proteins, a class of ubiquitinylation proteins, with genes down-regulated during muscle regeneration, whereas ubiquitinylation was previously reported to be activated during the inverse process: muscle atrophy. CONCLUSION: Our literature-based association analysis is capable of finding hidden common biological denominators in microarray studies, and circumvents the need for raw data analysis or curated gene annotation databases.