Cellular Flows Research Articles

A multimodal zebrafish developmental atlas reveals the state-transition dynamics of late-vertebrate pluripotent axial progenitors

Elucidating organismal developmental processes requires a comprehensive understanding of cellular lineages in the spatial, temporal, and molecular domains. In this study, we introduce Zebrahub, a dynamic atlas of zebrafish embryonic development that integrates single-cell sequencing time course data with lineage reconstructions facilitated by light-sheet microscopy. This atlas offers high-resolution and in-depth molecular insights into zebrafish development, achieved through the sequencing of individual embryos across ten developmental stages, complemented by reconstructions of cellular trajectories. Zebrahub also incorporates an interactive tool to navigate the complex cellular flows and lineages derived from light-sheet microscopy data, enabling in silico fate-mapping experiments. To demonstrate the versatility of our multimodal resource, we utilize Zebrahub to provide fresh insights into the pluripotency of neuro-mesodermal progenitors (NMPs) and the origins of a joint kidney-hemangioblast progenitor population.

Bilateral cellular flows display asymmetry prior to left-right organizer formation in amniote gastrulation.

Bilaterians are defined by a bilaterally symmetrical body plan. Vertebrates exhibit external bilateral symmetry but display left-right (LR) asymmetry in their internal organs. Amniote embryos switch patterning of internal organs from bilateral symmetry to LR-asymmetry, but the initiation of LR symmetry breaking is not well understood. Using chick embryo as a model system due to its easy accessibility and similarity to human development, our biophysical approaches to quantify cellular flows inferred that LR symmetry breaking occurs prior to the formation of Hensen's node, a LR organizer, which serves as a signaling center for LR patterning-gene programs. Our work demonstrates that quantitative biophysical parameters can help unravel the initiation of LR symmetry breaking, suggesting involvement of physical mechanisms in this critical biological patterning process.

Effect of micro-vessel stenosis severity and hematocrit level on red blood cell dynamics and platelet margination: A numerical study

Understanding many micro-vascular diseases is aided by examining the dynamical behavior of blood cells. For instance, micro-vascular stenosis significantly influences the dynamics of red blood cells and hence causes several micro-vascular disorders. Thus, the objective of the current study is to numerically simulate cellular blood flow in stenosed micro-vessels with different stenosis severities and hematocrits to examine hemodynamic features which have important clinical implications. Red blood cells’ migration, velocity, and deformation are predicted. Furthermore, platelets’ margination and cell-free layer formation are examined. Accordingly, a three-dimensional numerical simulation of blood cells and their interaction with the surrounding plasma is considered. The simulation is performed using a validated code developed for cellular blood flows. Red blood cells’ migration and platelets’ margination are confirmed, which enhances the validity of the code. The obtained results report a high dependence of red blood cells’ migration and platelets’ margination on the hematocrit level, which agrees with other published studies. An asymmetrical cell-free layer thickness is exhibited along the stenosed vessel, with a maximum value at the throat of the stenosis, which greatly affects blood apparent viscosity and induces plasma skimming in this region. In addition, it is found that the cell-free layer thickness is strongly linked to stenosis severity and the hematocrit level. Due to its role in the endothelial cells’ function and structure, the wall shear stress is estimated. A reduction more than 75 % in the wall shear stress is obtained due to stenosis, with maximum values at the throat compared with the healthy case. The Fahraeus effect is examined, and the obtained results are compared with published experimental and computational works with an acceptable degree of agreement.

Intercellular friction and motility drive orientational order in cell monolayers

Spatiotemporal patterns in multicellular systems are important to understanding tissue dynamics, for instance, during embryonic development and disease. Here, we use a multiphase field model to study numerically the behavior of a near-confluent monolayer of deformable cells with intercellular friction. Varying friction and cell motility drives a solid-liquid transition, and near the transition boundary, we find the emergence of local nematic order of cell deformation driven by shear-aligning cellular flows. Intercellular friction contributes to the monolayer's viscosity, which significantly increases the spatial correlation in the flow and, concomitantly, the extent of nematic order. We also show that local hexatic and nematic order are tightly coupled and propose a mechanical-geometric model for the colocalization of [Formula: see text] nematic defects and 5-7 disclination pairs, which are the structural defects in the hexatic phase. Such topological defects coincide with regions of high cell-cell overlap, suggesting that they may mediate cellular extrusion from the monolayer, as found experimentally. Our results delineate a mechanical basis for the recent observation of nematic and hexatic order in multicellular collectives in experiments and simulations and pinpoint a generic pathway to couple topological and physical effects in these systems.

Analyzing two-dimensional cellular detonation flows from numerical simulations with proper orthogonal decomposition and Lagrangian descriptors

Analyzing two-dimensional cellular detonation flows from numerical simulations with proper orthogonal decomposition and Lagrangian descriptors

Service-aware real-time slicing for virtualized beyond 5G networks

Edge Intelligence is expected to play a vital role in the evolution of 5G networks, empowering them with the capability to make real-time decisions regarding various allocations related to their management and service provisioning to end-users. This shift facilitates the transition from a network-aware approach, where applications are developed to manage network quality fluctuations, to a service-aware network that self-adjusts based on the hosted applications. In this paper, we design and implement a service-aware network managed from the network edge. We utilize and assess various Machine Learning models to classify cellular network traffic flows in the backhaul, aiming to predict their future impact on network load. Leveraging these predictions, the network can proactively and autonomously reallocate slices in the Radio Access Network via programmable APIs, ensuring the demands of the traffic-generating applications are met. The approach integrates innovative MLOps methodologies for distributed and online training, enabling continuous model refinement and adaptation to evolving network dynamics. Our framework was tested in a real-world environment with realistic traffic scenarios, and the results were evaluated in real-time, down to a granularity of 10ms. Our findings indicate that the network can swiftly adjust to traffic, providing users with slices tailored to their application needs. Notably, our experiments show that under the studied settings, the users experienced up to 4 times lower latency (jitter) and nearly 4 times higher throughput when interacting with various applications, compared to the standard non-AI/ML unit. Furthermore, our dynamic scheme significantly optimizes resource allocation, ensuring energy efficiency by avoiding over- and under-provisioning of resources.

Influence of gravitational tilt on the thermocapillary convection in a non-axisymmetric liquid bridge

Fluid slosh caused by residual acceleration in microgravity is a common problem encountered in space engineering. To solve this problem, the ground-based experiment research on the influence of gravity jitter and gravitational tilt on the thermocapillary convection (TCC) transition behaviour of non-axisymmetric liquid bridge has become an important issue in microgravity fluid management. Based on a mesoscale liquid bridge experimental platform which can realize gravitational tilt, the effect of gravitational tilt on TCC by using a high-speed camera equipped with a near-focus lens and a self-developed interface image recognition package. The results show that the spatio-temporal evolution of TCC by the influence of gravitational tilt is still divided into steady and oscillatory flow. In the stable TCC, the vortex core distortion of cellular flow caused by the imbalance left and right interface curvature invites cellular flow close to the free surface, and it shrinks to the intermediate height. As gravitational tilt increases, the transverse/longitudinal velocity peaks are significantly reduced, peak velocity has been reduced by 26%–27%. Meanwhile, the longitudinal velocity gradient at the free interface increases significantly. Therefore, gravitational tilt plays an important role in improving the surface flow velocity. In the oscillatory TCC, the position of vortex core is closer to the free interface at the hot/cold corner as the periodic mutual occupation of the left and right cellular flows. The TCC is obviously inhibited due to the gravitational tilt. The critical temperature difference is increased by 25% and the onset of temperature oscillation at the hot corner is delayed by 20% compared with conventional gravity condition.

Adherens junctions as molecular regulators of emergent tissue mechanics.

Tissue and organ development during embryogenesis relies on the collective and coordinated action of many cells. Recent studies have revealed that tissue material properties, including transitions between fluid and solid tissue states, are controlled in space and time to shape embryonic structures and regulate cell behaviours. Although the collective cellular flows that sculpt tissues are guided by tissue-level physical changes, these ultimately emerge from cellular-level and subcellular-level molecular mechanisms. Adherens junctions are key subcellular structures, built from clusters of classical cadherin receptors. They mediate physical interactions between cells and connect biochemical signalling to the physical characteristics of cell contacts, hence playing a fundamental role in tissue morphogenesis. In this Review, we take advantage of the results of recent, quantitative measurements of tissue mechanics to relate the molecular and cellular characteristics of adherens junctions, including adhesion strength, tension and dynamics, to the emergent physical state of embryonic tissues. We focus on systems in which cell-cell interactions are the primary contributor to morphogenesis, without significant contribution from cell-matrix interactions. We suggest that emergent tissue mechanics is an important direction for future research, bridging cell biology, developmental biology and mechanobiology to provide a holistic understanding of morphogenesis in health and disease.

Quantifying the Dissipation Enhancement of Cellular Flows

Quantifying the Dissipation Enhancement of Cellular Flows

Serotonin signaling regulates actomyosin contractility during morphogenesis in evolutionarily divergent lineages

Serotonin is a neurotransmitter that signals through 5-HT receptors to control key functions in the nervous system. Serotonin receptors are also ubiquitously expressed in various organs and have been detected in embryos of different organisms. Potential morphogenetic functions of serotonin signaling have been proposed based on pharmacological studies but a mechanistic understanding is still lacking. Here, we uncover a role of serotonin signaling in axis extension of Drosophila embryos by regulating Myosin II (MyoII) activation, cell contractility and cell intercalation. We find that serotonin and serotonin receptors 5HT2A and 5HT2B form a signaling module that quantitatively regulates the amplitude of planar polarized MyoII contractility specified by Toll receptors and the GPCR Cirl. Remarkably, serotonin signaling also regulates actomyosin contractility at cell junctions, cellular flows and epiblast morphogenesis during chicken gastrulation. This phylogenetically conserved mechanical function of serotonin signaling in regulating actomyosin contractility and tissue flow reveals an ancestral role in morphogenesis of multicellular organisms.

The mechano-chemical circuit drives skin organoid self-organization

Stem cells in organoids self-organize into tissue patterns with unknown mechanisms. Here, we use skin organoids to analyze this process. Cell behavior videos show that the morphological transformation from multiple spheroidal units with morphogenesis competence (CMU) to planar skin is characterized by two abrupt cell motility-increasing events before calming down. The self-organizing processes are controlled by a morphogenetic module composed of molecular sensors, modulators, and executers. Increasing dermal stiffness provides the initial driving force (driver) which activates Yap1 (sensor) in epidermal cysts. Notch signaling (modulator 1) in epidermal cyst tunes the threshold of Yap1 activation. Activated Yap1 induces Wnts and MMPs (epidermal executers) in basal cells to facilitate cellular flows, allowing epidermal cells to protrude out from the CMU. Dermal cell-expressed Rock (dermal executer) generates a stiff force bridge between two CMU and accelerates tissue mixing via activating Laminin and β1-integrin. Thus, this self-organizing coalescence process is controlled by a mechano-chemical circuit. Beyond skin, self-organization in organoids may use similar mechano-chemical circuit structures.

Front propagation in cellular flows: scale dependence versus scale invariance

We experimentally study front propagation in a vortex lattice providing closed steady cellular flows and no mean flow. To this end, we trigger an autocatalytic reaction in a solution stirred by magnetohydrodynamic flows in a Hele-Shaw cell. We evidence a scale-invariant regime below some flow magnitude and a scale-dependent regime above, the scales referring here to the vortex scale and the front thickness. The transition between these regimes corresponds to a unitary Damköhler number $Da$ : $Da=1$ . The enhancement of the mean front velocity with the flow magnitude nicely agrees with the literature on numerical simulations and theoretical analyses in the scale-invariant regime $Da>1$ , but displays noticeable discrepancies in the scale-dependent one $Da<1$ . This shows that the transition between regimes is qualitatively sharp but quantitatively smooth.

Global regularity and stability analysis of the Patlak–Keller–Segel system with flow advection in a bounded domain: A semigroup approach

We discuss the problem of suppression of singularity via flow advection in chemotaxis modeled by the Patlak–Keller–Segel (PKS) equations. It is well-known that for the system without advection, singularity of the solution may develop at finite time. Specifically, if the initial condition is above certain critical threshold, the solution may blow up in finite time by concentrating positive mass at a single point. In this work, we mainly focus on the global regularity and stability analysis of the PKS system in the presence of flow advection in a bounded domain Ω⊂Rd,d=2,3, by using a semigroup approach. We will show that the global well-posedness can be obtained as long as the semigroup generated by the associated advection–diffusion operator has a rapid decay property. We will also show that for cellular flows in rectangle-like domains, such property can be achieved by rescaling both the cell size and the flow amplitude. This is analogous to the result established by Iyer, Xu and Zlatoš (2021) on the torus Td,d=2,3.

Blebs promote cell survival by assembling oncogenic signalling hubs.

Most human cells require anchorage for survival. Cell-substrate adhesion activates diverse signalling pathways, without which cells undergo anoikis-a form of programmed cell death1. Acquisition of anoikis resistance is a pivotal step in cancer disease progression, as metastasizing cells often lose firm attachment to surrounding tissue2,3. In these poorly attached states, cells adopt rounded morphologies and form small hemispherical plasma membrane protrusions called blebs4-11. Bleb function has been thoroughly investigated in the context of amoeboid migration, but it has been examined far less in other scenarios12. Here we show by three-dimensional imaging and manipulation of cell morphological states that blebbing triggers the formation of plasma membrane-proximal signalling hubs that confer anoikis resistance. Specifically, in melanoma cells, blebbing generates plasma membrane contours that recruit curvature-sensing septin proteins as scaffolds for constitutively active mutant NRAS and effectors. These signalling hubs activate ERK and PI3K-well-established promoters of pro-survival pathways. Inhibition of blebs or septins has little effect on the survival of well-adhered cells, but in detached cells it causes NRAS mislocalization, reduced MAPK and PI3K activity, and ultimately, death. This unveils a morphological requirement for mutant NRAS to operate as an effective oncoprotein. Furthermore, whereas some BRAF-mutated melanoma cells do not rely on this survival pathway in a basal state, inhibition of BRAF and MEK strongly sensitizes them to both bleb and septin inhibition. Moreover, fibroblasts engineered to sustain blebbing acquire the same anoikis resistance as cancer cells even without harbouring oncogenic mutations. Thus, blebs are potent signalling organelles capable of integrating myriad cellular information flows into concerted cellular responses, in this case granting robust anoikis resistance.

The dynamics of biofouled particles in vortical flows

When using mathematical models to predict the pathways of biofouled microplastic in the ocean, it is necessary to parametrise the impact of turbulence on their motions. In this paper, statistics on particle motion have been computed from simulations of small, spherical particles with time-dependent mass in cellular flow fields. The cellular flows are a prototype for Langmuir circulation and flows dominated by vortical motion. Upwelling regions lead to particle suspension and particles fall out at different times. The uncertainty of fallout time and a particle's vertical position is quantified across a range of parameters. A slight increase in settling velocities, for short times, is observed for particles with inertia due to clustering in fast downwelling regions for steady, background flow. For particles in time-dependent, chaotic flows, uncertainty is significantly reduced and we observe no significant increase in the average settling rates due to inertial effects.

Morphogen gradient orchestrates pattern-preserving tissue morphogenesis via motility-driven unjamming

Embryo development requires biochemical signalling to generate patterns of cell fates and active mechanical forces to drive tissue shape changes. However, how these processes are coordinated, and how tissue patterning is preserved despite the cellular flows occurring during morphogenesis, remains poorly understood. Gastrulation is a crucial embryonic stage that involves both patterning and internalization of the mesendoderm germ layer tissue. Here we show that, in zebrafish embryos, a gradient in Nodal signalling orchestrates pattern-preserving internalization movements by triggering a motility-driven unjamming transition. In addition to its role as a morphogen determining embryo patterning, graded Nodal signalling mechanically subdivides the mesendoderm into a small fraction of highly protrusive leader cells, able to autonomously internalize via local unjamming, and less protrusive followers, which need to be pulled inwards by the leaders. The Nodal gradient further enforces a code of preferential adhesion coupling leaders to their immediate followers, resulting in a collective and ordered mode of internalization that preserves mesendoderm patterning. Integrating this dual mechanical role of Nodal signalling into minimal active particle simulations quantitatively predicts both physiological and experimentally perturbed internalization movements. This provides a quantitative framework for how a morphogen-encoded unjamming transition can bidirectionally couple tissue mechanics with patterning during complex three-dimensional morphogenesis.

Phoresis in cellular flows: from enhanced dispersion to blockage

In this article, we study numerically the dispersion of colloids in a two-dimensional cellular flow in the presence of an imposed mean salt gradient. Owing to the additional scalar, the colloids do not follow exactly the Eulerian flow field, but have a (small) extra-velocity proportional to the salt gradient, $\boldsymbol {v}_{dp}=\alpha \boldsymbol {\nabla } S$ , where $\alpha$ is the phoretic constant and $S$ the salt concentration. We study the demixing of an homogenous distribution of colloids and how their long-term mean velocity $\boldsymbol {V_m}$ and effective diffusivity $D_{eff}$ are influenced by the phoretic drift. We observe two regimes of colloids dynamics depending on a blockage criterion $R=\alpha G L/\sqrt {4 D_cD_s}$ , where $G$ is the mean salt gradient amplitude, $L$ the length scale of the flow and $D_c$ and $D_s$ the molecular diffusivities of colloids and salt. When $R<1$ , the mean velocity is strongly enhanced with $V_m \propto \alpha G \sqrt {Pe_s}$ , ${Pe}_s$ being the salt Péclet number. When $R > 1$ , the compressibility effect due to the phoretic drift is so strong that a depletion of colloids occurs along the separatrices inhibiting cell-to-cell transport.

A Review of Mathematical and Computational Methods in Cancer Dynamics.

Cancers are complex adaptive diseases regulated by the nonlinear feedback systems between genetic instabilities, environmental signals, cellular protein flows, and gene regulatory networks. Understanding the cybernetics of cancer requires the integration of information dynamics across multidimensional spatiotemporal scales, including genetic, transcriptional, metabolic, proteomic, epigenetic, and multi-cellular networks. However, the time-series analysis of these complex networks remains vastly absent in cancer research. With longitudinal screening and time-series analysis of cellular dynamics, universally observed causal patterns pertaining to dynamical systems, may self-organize in the signaling or gene expression state-space of cancer triggering processes. A class of these patterns, strange attractors, may be mathematical biomarkers of cancer progression. The emergence of intracellular chaos and chaotic cell population dynamics remains a new paradigm in systems medicine. As such, chaotic and complex dynamics are discussed as mathematical hallmarks of cancer cell fate dynamics herein. Given the assumption that time-resolved single-cell datasets are made available, a survey of interdisciplinary tools and algorithms from complexity theory, are hereby reviewed to investigate critical phenomena and chaotic dynamics in cancer ecosystems. To conclude, the perspective cultivates an intuition for computational systems oncology in terms of nonlinear dynamics, information theory, inverse problems, and complexity. We highlight the limitations we see in the area of statistical machine learning but the opportunity at combining it with the symbolic computational power offered by the mathematical tools explored.

A Convergent Interacting Particle Method and Computation of KPP Front Speeds in Chaotic Flows

In this paper, we study the propagation speeds of reaction-diffusion-advection (RDA) fronts in time-periodic cellular and chaotic flows with Kolmogorov-Petrovsky-Piskunov (KPP) nonlinearity. We first apply the variational principle to reduce the computation of KPP front speeds to a principal eigenvalue problem of a linear advection-diffusion operator with space-time periodic coefficients on a periodic domain. To this end, we develop efficient Lagrangian particle methods to compute the principal eigenvalue through the Feynman-Kac formula. By estimating the convergence rate of Feynman-Kac semigroups and the operator splitting methods for approximating the linear advection-diffusion solution operators, we obtain convergence analysis for the proposed numerical methods. Finally, we present numerical results to demonstrate the accuracy and efficiency of the proposed method in computing KPP front speeds in time-periodic cellular and chaotic flows, especially the time-dependent Arnold-Beltrami-Childress (ABC) flow and time-dependent Kolmogorov flow in three-dimensional space.

Transport of condensing droplets in Taylor-Green vortex flow in the presence of thermal noise.

We study the role of phase change and thermal noise in particle transport in turbulent flows. We employ a toy model to extract the main physics: Condensing droplets are modelled as heavy particles which grow in size, the ambient flow is modelled as a two-dimensional Taylor-Green flow consisting of an array of vortices delineated by separatrices, and thermal noise are modelled as uncorrelated Gaussian white noise. In general, heavy inertial particles are centrifuged out of regions of high vorticity and into regions of high strain. In cellular flows, we find, in agreement with earlier results, that droplets with Stokes numbers smaller than a critical value, St<St_{cr}, remain trapped in the vortices in which they are initialized, while larger droplets move ballistically away from their initial positions by crossing separatrices. We independently vary the Péclet number Pe characterizing the amplitude of thermal noise and the condensation rate Π to study their effects on the critical Stokes number for droplet trapping, as well as on the final states of motion of the droplets. We find that the imposition of thermal noise, or of a finite condensation rate, allows droplets of St<St_{cr} to leave their initial vortices. We find that the effects of thermal noise become negligible for growing droplets and that growing droplets achieve ballistic motion when their Stokes numbers become O(1). We also find an intermediate regime prior to attaining the ballistic state, in which droplets move diffusively away from their initial vortices in the presence of thermal noise.