Bulk-surface coupling identifies the mechanistic connection between Min-protein patterns in vivo and in vitro

Enhanced Stability and Chaotic Condensates in Multispecies Nonreciprocal Mixtures

Random nonreciprocal interactions between a large number of conserved densities are shown to enhance the stability of the system toward pattern formation. The enhanced stability is an exact result when the number of species approaches infinity and is confirmed numerically by simulations of the multispecies nonreciprocal Cahn-Hilliard model. Furthermore, the diversity in dynamical patterns increases with an increasing number of components, and novel steady states such as pulsating or spatiotemporally chaotic condensates are observed. Our results may help to unravel the mechanisms by which living systems self-organize via metabolism.

Binding affinities for 2D protein dimerization benefit from enthalpic stabilization

Dimerization underpins all macromolecular assembly processes both on and off the membrane. While the strength of dimerization,K D , is commonly quantified in solution (3D), many proteins like the soluble BAR domain-containing proteins also reversibly dimerize while bound to a membrane surface (2D). The ratio of dissociation constants, h = K D 2 D K D 3 D , defines a lengthscale that is essential for determining whether dimerization is more favorable in solution or on the membrane surface, particularly for these proteins that reversibly transition between 3D and 2D. While purely entropic rigid-body estimates of h apply well to transmembrane adhesion proteins, we show here using Molecular Dynamics simulations that even moderate flexibility in BAR domains dramatically alters the free energy landscape from 3D to 2D, driving enhanced selectivity and stability of the native dimer in 2D. By simulating BAR homodimerization in three distinct environments, 1) solution (3D), 2) bound to a lipid bilayer (2D), and 3) fully solvated but restrained to a pseudo membrane (2D), we show that both 2D environments induce backbone configurations that better match the crystal structure and produce more enthalpically favorable dimer states, violating the rigid-body estimates to drive h ≪ h R I G I D . Remarkably, contact with an explicit lipid bilayer is not necessary to drive these changes, as the solvated pseudo membrane induces this same result. We show this outcome depends on the stability of the protein interaction, as a parameterization that produces exceptionally stable binding in 3D does not induce systematic improvements on the membrane. With h lengthscales calculated here that are well below a physiological volume-to-surface-area lengthscale, assembly will be dramatically enhanced on the membrane, which aligns with BAR domain function as membrane remodelers. Our approach provides simple metrics to move beyond rigid-body estimates of 2D affinities and assess whether conformational flexibility selects for enhanced stability on membranes.

Dynamical phase transitions in the nonreciprocal Ising model

Nonreciprocal interactions in many-body systems lead to time-dependent states, commonly observed in biological, chemical, and ecological systems. The stability of these states in the thermodynamic limit and the critical behavior of the phase transition from static to time-dependent states are not yet fully understood. To address these questions, we study a minimalistic system endowed with nonreciprocal interactions: an Ising model with two spin species having opposing goals. The mean-field equation predicts three stable phases: disorder, static order, and a time-dependent swap phase. Large-scale numerical simulations support the following: (i) in two dimensions, the swap phase is destabilized by defects; (ii) in three dimensions, the swap phase is stable and has the properties of a time crystal; (iii) the transition from disorder to swap in three dimensions is characterized by the critical exponents of the 3D XY model and corresponds to the breaking of a continuous symmetry, time translation invariance; (iv) when the two species have fully antisymmetric couplings, the static-order phase is unstable in any finite dimension due to droplet growth; and (v) in the general case of asymmetric couplings, static order can be restored by a droplet-capture mechanism preventing the droplets from growing indefinitely. We provide details on the full phase diagram, which includes first- and second-order-like phase transitions, and study how the system coarsens into swap and static-order states.

Controlled Protein-Membrane Interactions Modulate Self-Organization of Min Protein Patterns

Self-organizing protein patterns are crucial for living systems, governing important cellular processes such as polarization and division. While the field of protein self-organization has reached a point where basic pattern-forming mechanisms can be reconstituted in vitro using purified proteins, understanding how cells can dynamically switch and modulate these patterns, especially when transiently needed, remains an interesting frontier. Here, we demonstrate the efficient regulation of self-organizing protein patterns through the modulation of simple biophysical membrane parameters. Our investigation focuses on the impact of membrane affinity changes on Min protein patterns at lipid membranes composed of Escherichia coli lipids or minimal lipid compositions, and we present three major results. First, we observed the emergence of a diverse array of pattern phenotypes, ranging from waves over flower-shaped patterns to snowflake-like structures. Second, we demonstrated the dependency of these patterns on the density of protein-membrane linkers. Finally, we demonstrate that the shape of snowflake-like patterns is fine-tuned by membrane charge. Our results demonstrate the significant influence of membrane linkage as a straightforward biophysical parameter governing protein pattern formation. Our research points towards a simple yet intriguing mechanism by which cells can adeptly tune and switch protein patterns on the mesoscale.

Artificial cell system as a tool for investigating pattern formation mechanisms of intracellular reaction-diffusion waves

Intracellular positional information is crucial for the precise control of biological phenomena, including cell division, polarity, and motility. Intracellular reaction-diffusion (iRD) waves are responsible for regulating positional information within cells as morphogens in multicellular tissues. However, iRD waves are explained by the coupling of biochemical reactions and molecular diffusion which indicates nonlinear systems under far from equilibrium conditions. Because of this complexity, experiments using defined elements rather than living cells containing endogenous factors are necessary to elucidate their pattern formation mechanisms. In this review, we summarize the effectiveness of artificial cell systems for investigating iRD waves derived from their high controllability and ability to emulate cell-size space effects. We describe how artificial cell systems reveal the characteristics of iRD waves, including the mechanisms of wave generation, mode selection, and period regulation. Furthermore, we introduce remaining open questions and discuss future challenges even in Min waves and in applying artificial cell systems to various iRD waves.

Dimensionality reduction in bulk-boundary reaction-diffusion systems

Intracellular protein patterns regulate many vital cellular functions, such as the processing of spatiotemporal information or the control of shape deformations. To do so, pattern-forming systems can be sensitive to the cell geometry by means of coupling the protein dynamics on the cell membrane to dynamics in the cytosol. Recent studies demonstrated that modeling the cytosolic dynamics in terms of an averaged protein pool disregards possibly crucial aspects of the pattern formation, most importantly concentration gradients normal to the membrane. At the same time, the coupling of two domains (surface and volume) with different dimensions renders many standard tools for the numerical analysis of self-organizing systems inefficient. Here, we present a generic framework for projecting the cytosolic dynamics onto the lower-dimensional surface that respects the influence of cytosolic concentration gradients in static and evolving geometries. This method uses a priori physical information about the system to approximate the cytosolic dynamics by a small number of dominant characteristic concentration profiles (basis), akin to basis transformations of finite element methods. As a proof of concept, we apply our framework to a toy model for volume-dependent interrupted coarsening, evaluate the accuracy of the results for various basis choices, and discuss the optimal basis choice for biologically relevant systems. Our analysis presents an efficient yet accurate method for analyzing pattern formation with surface-volume coupling in evolving geometries.

A dynamic duo: Understanding the roles of FtsZ and FtsA for Escherichia coli cell division through in vitro approaches

Bacteria divide by binary fission. The protein machine responsible for this process is the divisome, a transient assembly of more than 30 proteins in and on the surface of the cytoplasmic membrane. Together, they constrict the cell envelope and remodel the peptidoglycan layer to eventually split the cell into two. For Escherichia coli, most molecular players involved in this process have probably been identified, but obtaining the quantitative information needed for a mechanistic understanding can often not be achieved from experiments in vivo alone. Since the discovery of the Z-ring more than 30 years ago, in vitro reconstitution experiments have been crucial to shed light on molecular processes normally hidden in the complex environment of the living cell. In this review, we summarize how rebuilding the divisome from purified components - or at least parts of it - have been instrumental to obtain the detailed mechanistic understanding of the bacterial cell division machinery that we have today.

Forceful patterning: theoretical principles of mechanochemical pattern formation

Biological pattern formation is essential for generating and maintaining spatial structures from the scale of a single cell to tissues and even collections of organisms. Besides biochemical interactions, there is an important role for mechanical and geometrical features in the generation of patterns. We review the theoretical principles underlying different types of mechanochemical pattern formation across spatial scales and levels of biological organization.

Coarsening and wavelength selection far from equilibrium: A unifying framework based on singular perturbation theory

Intracellular protein patterns are described by (nearly) mass-conserving reaction-diffusion systems. While these patterns initially form out of a homogeneous steady state due to the well-understood Turing instability, no general theory exists for the dynamics of fully nonlinear patterns. We develop a unifying theory for nonlinear wavelength-selection dynamics in (nearly) mass-conserving two-component reaction-diffusion systems independent of the specific mathematical model chosen. Previous work has shown that these systems support an extremely broad band of stable wavelengths, but the mechanism by which a specific wavelength is selected has remained unclear. We show that an interrupted coarsening process selects the wavelength at the threshold to stability. Based on the physical intuition that coarsening is driven by competition for mass and interrupted by weak source terms that break strict mass conservation, we develop a singular perturbation theory for the stability of stationary patterns. The resulting closed-form analytical expressions enable us to quantitatively predict the coarsening dynamics and the final pattern wavelength. We find excellent agreement with numerical results throughout the diffusion- and reaction-limited regimes of the dynamics, including the crossover region. Further, we show how, in these limits, the two-component reaction-diffusion systems map to generalized Cahn-Hilliard and conserved Allen-Cahn dynamics, therefore providing a link to these two fundamental scalar field theories. The systematic understanding of the length-scale dynamics of fully nonlinear patterns in two-component systems provided here builds the basis to reveal the mechanisms underlying wavelength selection in multicomponent systems with potentially several conservation laws.

The mechanism of MinD stability modulation by MinE in Min protein dynamics

The patterns formed both in vivo and in vitro by the Min protein system have attracted much interest because of the complexity of their dynamic interactions given the apparent simplicity of the component parts. Despite both the experimental and theoretical attention paid to this system, the details of the biochemical interactions of MinD and MinE, the proteins responsible for the patterning, are still unclear. For example, no model consistent with the known biochemistry has yet accounted for the observed dual role of MinE in the membrane stability of MinD. Until now, a statistical comparison of models to the time course of Min protein concentrations on the membrane has not been carried out. Such an approach is a powerful way to test existing and novel models that are difficult to test using a purely experimental approach. Here, we extract time series from previously published fluorescence microscopy time lapse images of in vitro experiments and fit two previously described and one novel mathematical model to the data. We find that the novel model, which we call the Asymmetric Activation with Bridged Stability Model, fits the time-course data best. It is also consistent with known biochemistry and explains the dual MinE role via MinE-dependent membrane stability that transitions under the influence of rising MinE to membrane instability with positive feedback. Our results reveal a more complex network of interactions between MinD and MinE underlying Min-system dynamics than previously considered.

Geometry-induced patterns through mechanochemical coupling

Intracellular protein patterns regulate a variety of vital cellular processes such as cell division and motility, which often involve dynamic cell-shape changes. These changes in cell shape may in turn affect the dynamics of pattern-forming proteins, hence leading to an intricate feedback loop between cell shape and chemical dynamics. While several computational studies have examined the rich resulting dynamics, the underlying mechanisms are not yet fully understood. To elucidate some of these mechanisms, we explore a conceptual model for cell polarity on a dynamic one-dimensional manifold. Using concepts from differential geometry, we derive the equations governing mass-conserving reaction-diffusion systems on time-evolving manifolds. Analyzing these equations mathematically, we show that dynamic shape changes of the membrane can induce pattern-forming instabilities in parts of the membrane, which we refer to as regional instabilities. Deformations of the local membrane geometry can also (regionally) suppress pattern formation and spatially shift already existing patterns. We explain our findings by applying and generalizing the local equilibria theory of mass-conserving reaction-diffusion systems. This allows us to determine a simple onset criterion for geometry-induced pattern-forming instabilities, which is linked to the phase-space structure of the reaction-diffusion system. The feedback loop between membrane shape deformations and reaction-diffusion dynamics then leads to a surprisingly rich phenomenology of patterns, including oscillations, traveling waves, and standing waves, even if these patterns do not occur in systems with a fixed membrane shape. Our paper reveals that the local conformation of the membrane geometry acts as an important dynamical control parameter for pattern formation in mass-conserving reaction-diffusion systems.

Modeling membrane reshaping driven by dynamic protein assemblies

Remodeling of membranes in living systems is almost universally coupled to self-assembly of soluble proteins. Proteins assemble into semi-rigid shells that reshape attached membranes, and into filaments that protrude membranes. These assemblies are temporary, building from reversible protein and membrane interactions that must nucleate in the proper location. The interactions are strongly influenced by the nonequilibrium environment of the cell, such as gradients of components or active modifications by kinases. From a modeling perspective, understanding mechanisms and control thus requires 1. time-dependent approaches that ideally incorporate 2. macromolecular structure, 3. out-of-equilibrium processes, and 4. deformable membranes over microns and seconds. Realistically, tradeoffs must be made with these last three features. However, we see recent developments from the highly coarsened molecule-based scale, the continuum reaction-diffusion scale, and hybrid approaches as stimulating efforts in diverse applications. We discuss here methodological advances and progress towards simulating these processes as they occur physiologically.

Directing Min protein patterns with advective bulk flow

The Min proteins constitute the best-studied model system for pattern formation in cell biology. We theoretically predict and experimentally show that the propagation direction of in vitro Min protein patterns can be controlled by a hydrodynamic flow of the bulk solution. We find downstream propagation of Min wave patterns for low MinE:MinD concentration ratios, upstream propagation for large ratios, but multistability of both propagation directions in between. Whereas downstream propagation can be described by a minimal model that disregards MinE conformational switching, upstream propagation can be reproduced by a reduced switch model, where increased MinD bulk concentrations on the upstream side promote protein attachment. Our study demonstrates that a differential flow, where bulk flow advects protein concentrations in the bulk, but not on the surface, can control surface-pattern propagation. This suggests that flow can be used to probe molecular features and to constrain mathematical models for pattern-forming systems.

Spatial programming of self-organizing chemical systems using sustained physicochemical gradients from reaction, diffusion and hydrodynamics

Living organisms employ chemical self-organization to build structures, and inspire new strategies to design synthetic systems that spontaneously take a particular form, via a combination of integrated chemical reactions, assembly pathways and physicochemical processes. However, spatial programmability that is required to direct such self-organization is a challenge to control. Thermodynamic equilibrium typically brings about a homogeneous solution, or equilibrium structures such as supramolecular complexes and crystals. This perspective addresses out-of-equilibrium gradients that can be driven by coupling chemical reaction, diffusion and hydrodynamics, and provide spatial differentiation in the self-organization of molecular, ionic or colloidal building blocks in solution. These physicochemical gradients are required to (1) direct the organization from the starting conditions (e.g. a homogeneous solution), and (2) sustain the organization, to prevent it from decaying towards thermodynamic equilibrium. We highlight four different concepts that can be used as a design principle to establish such self-organization, using chemical reactions as a driving force to sustain the gradient and, ultimately, program the characteristics of the gradient: (1) reaction-diffusion coupling; (2) reaction-convection; (3) the Marangoni effect and (4) diffusiophoresis. Furthermore, we outline their potential as attractive pathways to translate chemical reactions and molecular/colloidal assembly into organization of patterns in solution, (dynamic) self-assembled architectures and collectively moving swarms at the micro-, meso- and macroscale, exemplified by recent demonstrations in the literature.

Bridging scales in a multiscale pattern-forming system

Self-organized pattern formation is vital for many biological processes. Reaction-diffusion models have advanced our understanding of how biological systems develop spatial structures, starting from homogeneity. However, biological processes inherently involve multiple spatial and temporal scales and transition from one pattern to another over time, rather than progressing from homogeneity to a pattern. To deal with such multiscale systems, coarse-graining methods are needed that allow the dynamics to be reduced to the relevant degrees of freedom at large scales, but without losing information about the patterns at small scales. Here, we present a semiphenomenological approach which exploits mass conservation in pattern formation, and enables reconstruction of information about patterns from the large-scale dynamics. The basic idea is to partition the domain into distinct regions (coarse grain) and determine instantaneous dispersion relations in each region, which ultimately inform about local pattern-forming instabilities. We illustrate our approach by studying the Min system, a paradigmatic model for protein pattern formation. By performing simulations, we first show that the Min system produces multiscale patterns in a spatially heterogeneous geometry. This prediction is confirmed experimentally by in vitro reconstitution of the Min system. Using a recently developed theoretical framework for mass-conserving reaction-diffusion systems, we show that the spatiotemporal evolution of the total protein densities on large scales reliably predicts the pattern-forming dynamics. Our approach provides an alternative and versatile theoretical framework for complex systems where analytical coarse-graining methods are not applicable, and can, in principle, be applied to a wide range of systems with an underlying conservation law.

A versatile cortical pattern-forming circuit based on Rho, F-actin, Ect2, and RGA-3/4

Many cells can generate complementary traveling waves of actin filaments (F-actin) and cytoskeletal regulators. This phenomenon, termed cortical excitability, results from coupled positive and negative feedback loops of cytoskeletal regulators. The nature of these feedback loops, however, remains poorly understood. We assessed the role of the Rho GAP RGA-3/4 in the cortical excitability that accompanies cytokinesis in both frog and starfish. RGA-3/4 localizes to the cytokinetic apparatus, "chases" Rho waves in an F-actin-dependent manner, and when coexpressed with the Rho GEF Ect2, is sufficient to convert the normally quiescent, immature Xenopus oocyte cortex into a dramatically excited state. Experiments and modeling show that changing the ratio of RGA-3/4 to Ect2 produces cortical behaviors ranging from pulses to complex waves of Rho activity. We conclude that RGA-3/4, Ect2, Rho, and F-actin form the core of a versatile circuit that drives a diverse range of cortical behaviors, and we demonstrate that the immature oocyte is a powerful model for characterizing these dynamics.

Forced and spontaneous symmetry breaking in cell polarization

How does breaking the symmetry of an equation alter the symmetry of its solutions? Here, we systematically examine how reducing underlying symmetries from spherical to axisymmetric influences the dynamics of an archetypal model of cell polarization, a key process of biological spatial self-organization. Cell polarization is characterized by nonlinear and non-local dynamics, but we overcome the theory challenges these traits pose by introducing a broadly applicable numerical scheme allowing us to efficiently study continuum models in a wide range of geometries. Guided by numerical results, we discover a dynamical hierarchy of timescales that allows us to reduce relaxation to a purely geometric problem of area-preserving geodesic curvature flow. Through application of variational results, we analytically construct steady states on a number of biologically relevant shapes. In doing so, we reveal non-trivial solutions for symmetry breaking.

Dendrimersome Synthetic Cells Harbor Cell Division Machinery of Bacteria

The integration of active cell machinery with synthetic building blocks is the bridge toward developing synthetic cells with biological functions and beyond. Self-replication is one of the most important tasks of living systems, and various complex machineries exist to execute it. In Escherichia coli, a contractile division ring is positioned to mid-cell by concentration oscillations of self-organizing proteins (MinCDE), where it severs membrane and cell wall. So far, the reconstitution of any cell division machinery has exclusively been tied to liposomes. Here, the reconstitution of a rudimentary bacterial divisome in fully synthetic bicomponent dendrimersomes is shown. By tuning the membrane composition, the interaction of biological machinery with synthetic membranes can be tailored to reproduce its dynamic behavior. This constitutes an important breakthrough in the assembly of synthetic cells with biological elements, as tuning of membrane-divisome interactions is the key to engineering emergent biological behavior from the bottom-up.

Mode selection mechanism in traveling and standing waves revealed by Min wave reconstituted in artificial cells

Reaction-diffusion coupling (RDc) generates spatiotemporal patterns, including two dynamic wave modes: traveling and standing waves. Although mode selection plays a substantial role in the spatiotemporal organization of living cell molecules, the mechanism for selecting each wave mode remains elusive. Here, we investigated a wave mode selection mechanism using Min waves reconstituted in artificial cells, emerged by the RDc of MinD and MinE. Our experiments and theoretical analysis revealed that the balance of membrane binding and dissociation from the membrane of MinD determines the mode selection of the Min wave. We successfully demonstrated that the transition of the wave modes can be regulated by controlling this balance and found hysteresis characteristics in the wave mode transition. These findings highlight a previously unidentified role of the balance between activators and inhibitors as a determinant of the mode selection of waves by RDc and depict an unexplored mechanism in intracellular spatiotemporal pattern formations.

Extrusion: A New Method for Rapid Formulation of High-Yield, Monodisperse Nanobubbles

Shell-stabilized gas microbubbles (MB) and nanobubbles (NB) are frequently used for biomedical ultrasound imaging and therapeutic applications. While it is widely recognized that monodisperse bubbles can be more effective in these applications, the efficient formulation of uniform bubbles at high concentrations is difficult to achieve. Here, it is demonstrated that a standard mini-extruder setup, commonly used to make vesicles or liposomes, can be used to quickly and efficiently generate monodisperse NBs with high yield. In this highly reproducible technique, the NBs obtained have an average diameter of 0.16 ± 0.05 µm and concentration of 6.2 ± 1.8 × 10¹⁰  NBs mL^-1 compared to 0.32 ± 0.1 µm and 3.2 ± 0.7 × 10¹¹  mL^-1 for NBs made using mechanical agitation. Parameters affecting the extrusion and NB generation process including the temperature, concentration of the lipid solution, and the number of passages through the extruder are also examined. Moreover, it is demonstrated that extruded NBs show a strong acoustic response in vitro and a strong and persistent US signal enhancement under nonlinear contrast enhanced ultrasound imaging in mice. The extrusion process is a new, efficient, and scalable technique that can be used to easily produce high yield smaller monodispersed nanobubbles.

Spatiotemporal development of coexisting wave domains of Rho activity in the cell cortex

The Rho family GTPases are molecular switches that regulate cytoskeletal dynamics and cell movement through a complex spatiotemporal organization of their activity. In Patiria miniata (starfish) oocytes under in vitro experimental conditions (with overexpressed Ect2, induced expression of Δ90 cyclin B, and roscovitine treatment), such activity generates multiple co-existing regions of coherent propagation of actin waves. Here we use computational modeling to investigate the development and properties of such wave domains. The model reveals that the formation of wave domains requires a balance between the activation and inhibition in the Rho signaling motif. Intriguingly, the development of the wave domains is preceded by a stage of low-activity quasi-static patterns, which may not be readily observed in experiments. Spatiotemporal patterns of this stage and the different paths of their destabilization define the behavior of the system in the later high-activity (observable) stage. Accounting for a strong intrinsic noise allowed us to achieve good quantitative agreement between simulated dynamics in different parameter regimes of the model and different wave dynamics in Patiria miniata and wild type Xenopus laevis (frog) data. For quantitative comparison of simulated and experimental results, we developed an automated method of wave domain detection, which revealed a sharp reversal in the process of pattern formation in starfish oocytes. Overall, our findings provide an insight into spatiotemporal regulation of complex and diverse but still computationally reproducible cell-level actin dynamics.