Modelling cell shape in 3D structured environments: A quantitative comparison with experiments.

Cell shape plays a fundamental role in many biological processes, including adhesion, migration, division and development, but it is not clear which shape model best predicts three-dimensional cell shape in structured environments. Here, we compare different modelling approaches with experimental data. The shapes of single mesenchymal cells cultured in custom-made 3D scaffolds were compared by a Fourier method with surfaces that minimize area under the given adhesion and volume constraints. For the minimized surface model, we found marked differences to the experimentally observed cell shapes, which necessitated the use of more advanced shape models. We used different variants of the cellular Potts model, which effectively includes both surface and bulk contributions. The simulations revealed that the Hamiltonian with linear area energy outperformed the elastic area constraint in accurately modelling the 3D shapes of cells in structured environments. Explicit modelling the nucleus did not improve the accuracy of the simulated cell shapes. Overall, our work identifies effective methods for accurately modelling cellular shapes in complex environments.

Lipoteichoic acids influence cell shape and bacterial division of Streptococcus suis serotype 2, but play a limited role in the pathogenesis of the infection.

Streptococcus suis serotype 2 is a major swine pathogen and a zoonotic agent, causing meningitis in both swine and humans, responsible for substantial economic losses to the swine industry worldwide. The pathogenesis of infection and the role of bacterial cell wall components in virulence have not been fully elucidated. Lipoproteins, peptidoglycan, as well as lipoteichoic acids (LTA) have all been proposed to contribute to virulence. In the present study, the role of the LTA in the pathogenesis of the infection was evaluated through the characterisation of a mutant of the S. suis serotype 2 strain P1/7 lacking the LtaS enzyme, which mediates the polymerization of the LTA poly-glycerolphosphate chain. The ltaS mutant was confirmed to completely lack LTA and displayed significant morphological defects. Although the bacterial growth of this mutant was not affected, further results showed that LTA is involved in maintaining S. suis bacterial fitness. However, its role in the pathogenesis of the infection appears limited. Indeed, LTA presence reduces self-agglutination, biofilm formation and even dendritic cell activation, which are important aspects of the pathogenesis of the infection caused by S. suis. In addition, it does not seem to play a critical role in virulence using a systemic mouse model of infection.

Discretised Flux Balance Analysis for Reaction-Diffusion Simulation of Single-Cell Metabolism.

Metabolites have to diffuse within the sub-cellular compartments they occupy to specific locations where enzymes are, so reactions could occur. Conventional flux balance analysis (FBA), a method based on linear programming that is commonly used to model metabolism, implicitly assumes that all enzymatic reactions are not diffusion-limited though that may not always be the case. In this work, we have developed a spatial method that implements FBA on a grid-based system, to enable the exploration of diffusion effects on metabolism. Specifically, the method discretises a living cell into a two-dimensional grid, represents the metabolic reactions in each grid element as well as the diffusion of metabolites to and from neighbouring elements, and simulates the system as a single linear programming problem. We varied the number of rows and columns in the grid to simulate different cell shapes, and the method was able to capture diffusion effects at different shapes. We then used the method to simulate heterogeneous enzyme distribution, which suggested a theoretical effect on variability at the population level. We propose the use of this method, and its future extensions, to explore how spatiotemporal organisation of sub-cellular compartments and the molecules within could affect cell behaviour.

Effect of cell shape on nonlinear electrophoresis migration.

This study contributes to the renewed interest in the study of nonlinear electrophoresis of colloidal particles. In this work the influence of cell shape on electrophoretic migration under the nonlinear regimes of moderate and strong field regimes was assessed. Four types of bacterial and yeast cells (one spherical, three non-spherical) were studied and their electrophoretic mobilities for the moderate and strong electric field magnitude regimes were estimated experimentally. The parameter of sphericity was employed to assess the effect cell shape on the nonlinear electrophoresis migration velocity and corresponding mobility under the two electric field magnitude regimes studied. As particle migration under nonlinear electrophoresis depends on particle size and shape, the results in terms of mobilities of nonlinear electrophoresis were presented as function of cell hydrodynamic diameter and sphericity. The results indicated that the magnitude of the mobilities of nonlinear electrophoresis for cells increase with increasing cell size and increase with increasing deviations from spherical shape, which is indicated by lower sphericity values. The results presented here are the very first assessment of the two types of mobilities of nonlinear electrophoresis of cells as a function of size and shape.

Calibration of agent based models for monophasic and biphasic tumour growth using approximate Bayesian computation.

Agent-based models (ABMs) are readily used to capture the stochasticity in tumour evolution; however, these models are often challenging to validate with experimental measurements due to model complexity. The Voronoi cell-based model (VCBM) is an off-lattice agent-based model that captures individual cell shapes using a Voronoi tessellation and mimics the evolution of cancer cell proliferation and movement. Evidence suggests tumours can exhibit biphasic growth in vivo. To account for this phenomena, we extend the VCBM to capture the existence of two distinct growth phases. Prior work primarily focused on point estimation for the parameters without consideration of estimating uncertainty. In this paper, approximate Bayesian computation is employed to calibrate the model to in vivo measurements of breast, ovarian and pancreatic cancer. Our approach involves estimating the distribution of parameters that govern cancer cell proliferation and recovering outputs that match the experimental data. Our results show that the VCBM, and its biphasic extension, provides insight into tumour growth and quantifies uncertainty in the switching time between the two phases of the biphasic growth model. We find this approach enables precise estimates for the time taken for a daughter cell to become a mature cell. This allows us to propose future refinements to the model to improve accuracy, whilst also making conclusions about the differences in cancer cell characteristics.

Identification of structural and regulatory cell-shape determinants in Haloferax volcanii.

Archaea play indispensable roles in global biogeochemical cycles, yet many crucial cellular processes, including cell-shape determination, are poorly understood. Haloferax volcanii, a model haloarchaeon, forms rods and disks, depending on growth conditions. Here, we used a combination of iterative proteomics, genetics, and live-cell imaging to identify mutants that only form rods or disks. We compared the proteomes of the mutants with wild-type cells across growth phases, thereby distinguishing between protein abundance changes specific to cell shape and those related to growth phases. The results identified a diverse set of proteins, including predicted transporters, transducers, signaling components, and transcriptional regulators, as important for cell-shape determination. Through phenotypic characterization of deletion strains, we established that rod-determining factor A (RdfA) and disk-determining factor A (DdfA) are required for the formation of rods and disks, respectively. We also identified structural proteins, including an actin homolog that plays a role in disk-shape morphogenesis, which we named volactin. Using live-cell imaging, we determined volactin's cellular localization and showed its dynamic polymerization and depolymerization. Our results provide insights into archaeal cell-shape determination, with possible implications for understanding the evolution of cell morphology regulation across domains.

Mechanical forces across compartments coordinate cell shape and fate transitions to generate tissue architecture.

Morphogenesis and cell state transitions must be coordinated in time and space to produce a functional tissue. An excellent paradigm to understand the coupling of these processes is mammalian hair follicle development, which is initiated by the formation of an epithelial invagination-termed placode-that coincides with the emergence of a designated hair follicle stem cell population. The mechanisms directing the deformation of the epithelium, cell state transitions and physical compartmentalization of the placode are unknown. Here we identify a key role for coordinated mechanical forces stemming from contractile, proliferative and proteolytic activities across the epithelial and mesenchymal compartments in generating the placode structure. A ring of fibroblast cells gradually wraps around the placode cells to generate centripetal contractile forces, which, in collaboration with polarized epithelial myosin activity, promote elongation and local tissue thickening. These mechanical stresses further enhance compartmentalization of Sox9 expression to promote stem cell positioning. Subsequently, proteolytic remodelling locally softens the basement membrane to facilitate a release of pressure on the placode, enabling localized cell divisions, tissue fluidification and epithelial invagination into the underlying mesenchyme. Together, our experiments and modelling identify dynamic cell shape transformations and tissue-scale mechanical cooperation as key factors for orchestrating organ formation.

Spherical harmonics analysis reveals cell shape-fate relationships in zebrafish lateral line neuromasts.

Cell shape is a powerful readout of cell state, fate and function. We describe a custom workflow to perform semi-automated, 3D cell and nucleus segmentation, and spherical harmonics and principal components analysis to distill cell and nuclear shape variation into discrete biologically meaningful parameters. We apply these methods to analyze shape in the neuromast cells of the zebrafish lateral line system, finding that shapes vary with cell location and identity. The distinction between hair cells and support cells accounted for much of the variation, which allowed us to train classifiers to predict cell identity from shape features. Using transgenic markers for support cell subpopulations, we found that subtypes had different shapes from each other. To investigate how loss of a neuromast cell type altered cell shape distributions, we examined atoh1a mutants that lack hair cells. We found that mutant neuromasts lacked the cell shape phenotype associated with hair cells, but did not exhibit a mutant-specific cell shape. Our results demonstrate the utility of using 3D cell shape features to characterize, compare and classify cells in a living developing organism.

High-dimensional phenotyping to define the genetic basis of cellular morphology.

The morphology of cells is dynamic and mediated by genetic and environmental factors. Characterizing how genetic variation impacts cell morphology can provide an important link between disease association and cellular function. Here, we combine genomic sequencing and high-content imaging approaches on iPSCs from 297 unique donors to investigate the relationship between genetic variants and cellular morphology to map what we term cell morphological quantitative trait loci (cmQTLs). We identify novel associations between rare protein altering variants in WASF2, TSPAN15, and PRLR with several morphological traits related to cell shape, nucleic granularity, and mitochondrial distribution. Knockdown of these genes by CRISPRi confirms their role in cell morphology. Analysis of common variants yields one significant association and nominate over 300 variants with suggestive evidence (P < 10-6) of association with one or more morphology traits. We then use these data to make predictions about sample size requirements for increasing discovery in cellular genetic studies. We conclude that, similar to molecular phenotypes, morphological profiling can yield insight about the function of genes and variants.

Differences in boundary behavior in the 3D vertex and Voronoi models.

An important open question in the modeling of biological tissues is how to identify the right scale for coarse-graining, or equivalently, the right number of degrees of freedom. For confluent biological tissues, both vertex and Voronoi models, which differ only in their representation of the degrees of freedom, have effectively been used to predict behavior, including fluid-solid transitions and cell tissue compartmentalization, which are important for biological function. However, recent work in 2D has hinted that there may be differences between the two models in systems with heterotypic interfaces between two tissue types, and there is a burgeoning interest in 3D tissue models. Therefore, we compare the geometric structure and dynamic sorting behavior in mixtures of two cell types in both 3D vertex and Voronoi models. We find that while the cell shape indices exhibit similar trends in both models, the registration between cell centers and cell orientation at the boundary are significantly different between the two models. We demonstrate that these macroscopic differences are caused by changes to the cusp-like restoring forces introduced by the different representations of the degrees of freedom at the boundary, and that the Voronoi model is more strongly constrained by forces that are an artifact of the way the degrees of freedom are represented. This suggests that vertex models may be more appropriate for 3D simulations of tissues with heterotypic contacts.

Numerical analysis of oxygen uptake processes by red blood cells in stopped-flow measurements: Effects of cell shape, membrane permeability and unstirred layer.

The transport process of oxygen and other gas species across red blood cell (RBC) membrane is of great importance for better understanding the critical biological functions of RBCs, and the stopped-flow experiments have often been employed for such investigations. In previous stopped-flow analyses, the RBC had usually been represented by a spherical capsule based on the RBC volume, and an assumed unstirred layer (USL) thickness had been used to determine the membrane permeability. In this research, unlike these previous studies, we simulate the oxygen uptake process with different RBC shapes (shperical, ellipsoidal and biconcave) and examine the effects of USL thickness and membrane permeability over broad ranges based on literature values. Our results show that the excess membrane area can greatly improve the oxygen transport efficiency, and a same uptake half-time can be obtained using different combinations of USL thickness and membrane permeability. These findings raise concerns on the reliability and uncertainty for the results and conclusions in previous studies, and also call for more complete numerical models, for example, with the fluid flow and cell deformation considered, and more in-depth investigations on the oxygen transport processes.

Constitutive model for the rheology of biological tissue.

The rheology of biological tissue is key to processes such as embryo development, wound healing, and cancer metastasis. Vertex models of confluent tissue monolayers have uncovered a spontaneous liquid-solid transition tuned by cell shape; and a shear-induced solidification transition of an initially liquidlike tissue. Alongside this jamming/unjamming behavior, biological tissue also displays an inherent viscoelasticity, with a slow time and rate-dependent mechanics. With this motivation, we combine simulations and continuum theory to examine the rheology of the vertex model in nonlinear shear across a full range of shear rates from quastistatic to fast, elucidating its nonlinear stress-strain curves after the inception of shear of finite rate, and its steady state flow curves of stress as a function of strain rate. We formulate a rheological constitutive model that couples cell shape to flow and captures both the tissue solid-liquid transition and its rich linear and nonlinear rheology.

SCRIB controls apical contractility during epithelial differentiation.

Although mutations in the SCRIB gene lead to multiple morphological organ defects in vertebrates, the molecular pathway linking SCRIB to organ shape anomalies remains elusive. Here, we study the impact of SCRIB-targeted gene mutations during the formation of the gut epithelium in an organ-on-chip model. We show that SCRIB KO gut-like epithelia are flatter with reduced exposed surface area. Cell differentiation on filters further shows that SCRIB plays a critical role in the control of apical cell shape, as well as in the basoapical polarization of myosin light chain localization and activity. Finally, we show that SCRIB serves as a molecular scaffold for SHROOM2/4 and ROCK1 and identify an evolutionary conserved SHROOM binding site in the SCRIB carboxy-terminal that is required for SCRIB function in the control of apical cell shape. Our results demonstrate that SCRIB plays a key role in epithelial morphogenesis by controlling the epithelial apical contractility during cell differentiation.

Archaeal Tubulin-like Proteins Modify Cell Shape in Haloferax volcanii during Early Biofilm Development.

Tubulin, an extensively studied self-assembling protein, forms filaments in eukaryotic cells that affect cell shape, among other functions. The model archaeon Haloferax volcanii uses two tubulin-like proteins (FtsZ1/FtsZ2) for cell division, similar to bacteria, but has an additional six related tubulins called CetZ. One of them, CetZ1, was shown to play a role in cell shape. Typically, discoid and rod shapes are observed in planktonic growth, but under biofilm formation conditions (i.e., attached to a substratum), H. volcanii can grow filamentously. Here, we show that the deletion mutants of all eight tubulin-like genes significantly impacted morphology when cells were allowed to form a biofilm. ΔftsZ1, ΔcetZ2, and ΔcetZ4-6 created longer, less round cells than the parental and a higher percentage of filaments. ΔcetZ1 and ΔcetZ3 were significantly rounder than the parental, and ΔftsZ2 generated larger, flat, amorphic cells. The results show all tubulin homologs affect morphology at most timepoints, which therefore suggests these genes indeed have a function.

Differences in cell shape, motility, and growth reflect chromosomal number variations that can be visualized with live-cell ChReporters.

Chromosome numbers often change dynamically in tumors and cultured cells, which complicates therapy as well as understanding genotype-mechanotype relationships. Here we use a live-cell "ChReporter" method to identify cells with a single chromosomal loss in efforts to better understand differences in cell shape, motility, and growth. We focus on a standard cancer line and first show clonal populations that retain the ChReporter exhibit large differences in cell and nuclear morphology as well as motility. Phenotype metrics follow simple rules, including migratory persistence scaling with speed, and cytoskeletal differences are evident from drug responses, imaging, and single-cell RNA sequencing. However, mechanotype-genotype relationships between fluorescent ChReporter-positive clones proved complex and motivated comparisons of clones that differ only in loss or retention of a Chromosome-5 ChReporter. When lost, fluorescence-null cells show low expression of Chromosome-5 genes, including a key tumor suppressor APC that regulates microtubules and proliferation. Colonies are compact, nuclei are rounded, and cells proliferate more, with drug results implicating APC, and patient survival data indicating an association in multiple tumor-types. Visual identification of genotype with ChReporters can thus help clarify mechanotype and mechano-evolution.

Shape-driven confluent rigidity transition in curved biological tissues.

Collective cell motions underlie structure formation during embryonic development. Tissues exhibit emergent multicellular characteristics such as jamming, rigidity transitions, and glassy dynamics, but there remain questions about how those tissue-scale dynamics derive from local cell-level properties. Specifically, there has been little consideration of the interplay between local tissue geometry and cellular properties influencing larger-scale tissue behaviors. Here, we consider a simple two-dimensional computational vertex model for confluent tissue monolayers, which exhibits a rigidity phase transition controlled by the shape index (ratio of perimeter to square root area) of cells, on surfaces of constant curvature. We show that the critical point for the rigidity transition is a function of curvature such that positively curved systems are likely to be in a less rigid, more fluid, phase. Likewise, negatively curved systems (saddles) are likely to be in a more rigid, less fluid, phase. A phase diagram we generate for the curvature and shape index constitutes a testable prediction from the model. The curvature dependence is interesting because it suggests a natural explanation for more dynamic tissue remodeling and facile growth in regions of higher surface curvature. Conversely, we would predict stability at the base of saddle-shaped budding structures without invoking the need for biochemical or other physical differences. This concept has potential ramifications for our understanding of morphogenesis of budding and branching structures.

To stay in shape and keep moving: MLL emerges as a new transcriptional regulator of Rho GTPases.

RhoA, Rac1 and CDC42 are small G proteins that play a crucial role in regulating various cellular processes, such as the formation of actin cytoskeleton, cell shape and cell migration. Our recent results suggest that MLL is responsible for maintaining the balance of these small Rho GTPases. MLL depletion affects the stability of Rho GTPases, leading to a decrease in their protein levels and loss of activity. These changes manifest in the form of abnormal cell shape and disrupted actin cytoskeleton, resulting in reduced cell spreading and migration. Interestingly, their chaperone protein RhoGDI1 but not the Rho GTPases, is under the direct transcriptional regulation of MLL. Here, we comment on the possible implications of these observations on the signalling by Rho GTPases protein network.

Spatial biology of Ising-like synthetic genetic networks.

BACKGROUND: Understanding how spatial patterns of gene expression emerge from the interaction of individual gene networks is a fundamental challenge in biology. Developing a synthetic experimental system with a common theoretical framework that captures the emergence of short- and long-range spatial correlations (and anti-correlations) from interacting gene networks could serve to uncover generic scaling properties of these ubiquitous phenomena. RESULTS: Here, we combine synthetic biology, statistical mechanics models, and computational simulations to study the spatial behavior of synthetic gene networks (SGNs) in Escherichia coli quasi-2D colonies growing on hard agar surfaces. Guided by the combined mechanisms of the contact process lattice simulation and two-dimensional Ising model (CPIM), we describe the spatial behavior of bi-stable and chemically coupled SGNs that self-organize into patterns of long-range correlations with power-law scaling or short-range anti-correlations. These patterns, resembling ferromagnetic and anti-ferromagnetic configurations of the Ising model near critical points, maintain their scaling properties upon changes in growth rate and cell shape. CONCLUSIONS: Our findings shed light on the spatial biology of coupled and bistable gene networks in growing cell populations. This emergent spatial behavior could provide insights into the study and engineering of self-organizing gene patterns in eukaryotic tissues and bacterial consortia.