Interdisciplinary challenges in non-equilibrium physics: from soft to active, biological and complex matter

Flocking, as paradigmatically exemplified by birds, is the coherent collective motion of active agents. As originally conceived, flocking emerges through alignment interactions between the agents. Here, I will show a mechanism of flocking based on interactions that turn agents away from each other. Combining simulations, kinetic theory, and experiments, we demonstrate this mechanism of flocking in self-propelled Janus colloids with stronger repulsion on the front than on the rear. The polar flocking state is stable because particles achieve a compromise between turning away from left and right neighbors. Unlike for alignment interactions, the emergence of polar order from turn-away interactions requires particle repulsion. At high concentration, repulsion produces flocking Wigner crystals. Whereas repulsion often leads to motility-induced phase separation of active particles, here it combines with turn-away torques to produce flocking. Therefore, our findings bridge the classes of aligning and non-aligning active matter. Our results could help to reconcile the observations that cells can flock despite turning away from each other via contact inhibition of locomotion. Overall, our work shows that flocking is a very robust phenomenon that arises even when the orientational interactions would seem to prevent it.

Biofilms are communities of microorganisms that embed themselves in a matrix of self-secreted extracellular polymeric substances. The matrix protects the microbial community from chemical and mechanical insults, thus favoring its survival and evolutionary success. Biofilms are the primary mode of growth of bacteria and have a crucial impact in environmental, industrial, and medical settings. However, there is a significant lack of understanding about how the physical structure and chemical composition of biofilms determine their resistance to harsh environments. Our work focuses on the bio-physical drivers of biofilm assembly and the emergence of distinctive morphological and mechanical properties. I will showcase examples of biofilms grown under different environmental conditions, ranging from moist surfaces to surfaces exposed to fluid flow and porous media and by different bacterial species. For each case, I will present the experimental platform we developed to investigate the specific system and the results we obtained. Through our research, we discovered that the interplay between biological functions and physics mechanisms controls biofilm assembly, morphology, and rheology, ultimately affecting their physiological protective function. Shedding light on this interplay can help us control biofilm development and shows the prominent role that material science can play in developing novel antimicrobial and antifouling strategies.

Active matter describes systems comprising elementary units able to exert non-conservative forces on their environment. Activity leads to a fascinating variety of collective behaviours unmatched in passive systems, such as the transition to collective motion. The latter is arguably the most studied phase transition in active matter and the ordered phases emerging from the interplay between self-propulsion and aligning interactions have naturally attracted a lot of attention. In this talk, I will instead focus on the role of aligning interactions in the disordered phase. In particular, I will show that nematic alignment plays an unexpected role in the ‘high-temperature’ phase: it can induce or suppress phase separation, increase particle accumulation at boundaries, and suppress demixing in systems comprising active and passive particles. I will then show how all these phenomena can be understood by introducing a field-theoretical framework to go beyond the mean-field description of the system. In the presence of nematic torques, fluctuations are then shown to enhance polar order, leading to an increase in the particle persistence length. In turn, the latter accounts quantitatively for all the phenomena reported above. To show this, I will briefly describe a new theory for motility-induced phase separation in the presence of aligning torques.

Active matter is a broad class of materials within which individual entities consume energy in order to perform movement. These are thus out of thermodynamic equilibrium and display a wealth of surprising phenomena which challenge our conception of equilibrium phases and dynamics. We pay specific attention to collective motion, which has been shown to emerge in systems as diverse as crowds, flocks, schools, or swarms, yet with common characteristics. One of the simplest class of active matter models, namely athermal particles with isotropic self-propulsions in 2D, are a good first approximation of dense tissues of cells which experience cell-substrate active forces. We find in size-polydisperse systems that an homogeneous active liquid exists at arbitrary large persistence times, and is characterized by remarkable velocity correlations and irregular turbulent-like flows. We show that different collective phenomena are ruled by the competition between three fundamental time scales: the intrinsic persistence and interaction time scales, and the emerging relaxation time scale. We then move on to more realistic models of cell tissues, namely vertex models, which are able to capture both non-isotropic cell-cell interactions, and also more general forms of active forces. We investigate if and how these new microscopic dynamical ingredients modify collective motion on larger scales. (1) doi.org/10.1103/PhysRevLett.129.048002 (2) doi.org/10.1039/D3SM00034F (3) doi.org/10.48550/arXiv.2306.07172

The study of active matter, which consists of self-propelled particles, has developed into one of the central areas of soft matter physics in the past decade. A major reason for this is is the remarkable collective dynamics of active particles, which differs considerably from that of their passive counterparts. In this talk, I will give a general introduction to active field theories, which are a very useful theoretical tool for modeling the collective dynamics of active matter. Moreover, I will discuss different methods for deriving active field theories.

Systems containing active components are intrinsically out of equilibrium, while binary mixtures reach their equilibrium configuration when complete phase separation is achieved. Active particles are found to stabilise non-equilibrium morphologies in phase separating binary mixtures by arresting coarsening, exerting active pressure that competes with surface tension driving forces. For moderate activities, an emulsion morphology is stabilised, where the droplet size is well-defined and controlled by activity. Conversely, the ability of active particles to drive phase-separated mixtures away from their equilibrium configuration is shown. A rich co-assembly behaviour is shown due to the competing energy scales involved in the system. In systems formed by droplets enclosing active particles, it is found that activity enhances shape fluctuations of the interface, matching recent experimental results using Quincke rollers.

Associative polymers are a class of functionalised polymeric objects in which a fraction of the monomers can bind to each other, forming either intra- or inter-polymer bonds. If the chain flexibility is large enough and the associative monomers can form only single bonds, then at low density bonding takes place essentially within the same polymer, forming soft nano-objects named single-chain nanoparticles (SCNP)[1]. At larger densities, these particles form an interconnected spanning network, and a continuous cross-over from isolated SCNPs to a network state has been observed in experiments[2,3] and simulations[4], with no hints of a first-order transition, consistent with predictions of mean-field theory[5]. In this contribution I will show by theory and simulation that a judicious design of the patterns of reactive monomers along the polymer chain can drive a fully-entropic gas-liquid phase separation in SCNP systems, achieving control over the discontinuous (first-order) change, from a phase of diluted (fully-bonded) polymers to a phase in which polymers entropically bind to each other to form a (fully-bonded) polymer network. Such a sensitivity arises from a delicate balance between the distinct entropic contributions controlling the binding, which can be exploited to design new self-assembling systems, as well as to better understand phase separation phenomena in associative (bio-)macromolecular systems[6]. [1] A. J. Pomposo, Single-Chain Polymer Nanoparticles: Synthesis, Characterization, Simulations, and Applications, John Wiley & Sons (2017) [2] E. D. Whitaker, C. S. Mahon and D. A. Fulton, Angew. Chem. 125, 990 (2013) [3] S. Tang, M. Wang, and B. D. Olsen, J. Am. Chem. Soc. 137, 3946 (2015) [4] M. Formanek et al, Macromol. 54, 6613 (2021) [5] A. N. Semenov and M. Rubinstein, Macromol. 31, 1373 (1998) [6] L. Rovigatti and F. Sciortino, Phys. Rev. Lett. 129, 047801 (2022)

In living cells, proteins self-assemble into large functional structures based on specific interactions between molecularly complex patches. Due to this complexity, protein self-assembly results from a competition between a large number of distinct interaction energies, of the order of one per pair of patches. Current self-assembly models however typically ignore this aspect, and the principles by which it determines the large-scale structure of protein assemblies are largely unknown. Here, we use Monte-Carlo simulations and machine learning to start to unravel these principles. We observe that despite widespread geometrical frustration, aggregates of particles with complex interactions fall within only a few categories that often display high degrees of spatial order, including crystals, fibers, and micelles. We then successfully identify the most relevant aspect of the interaction complexity in predicting these outcomes, namely the particles' ability to form periodic structures. We finally show that geometrical frustration can lead to the self-assembly of aggregates of bulk of finite radius, or fibers of finite width. The equilibrium size of such aggregates can be solely controlled by the strength of the directional interactions between the identical rigid particles, allowing for an experimental implementation with DNA-origami.

Despite its importance in any adhesion and wetting phenomena, there is a fundamental property that is not yet understood in soft solids: surface elasticity. Also called the Shuttleworth effect, surface elasticity is intimately linked to the solid physico-chemistry and can be boiled down to one question. Does stretching the surface of a soft solid change its surface tension? In 2021, we demonstrated that the mechanical response of a textured silicone gel could only be explained by an elastic surface (1). It is, however, still unclear whether the measured surface elasticity is a true material property or a mere consequence of the surface preparation. This presentation will focus on a novel experimental setup that exploits Marangoni stresses and TFM techniques to characterize the surface mechanics of pristine surfaces. (1) Nicolas Bain, Anand Jagota, Katrina Smith-Mannschott, Stefanie Heyden, Robert W. Style, and Eric R. Dufresne Phys. Rev. Lett. 127, 208001 – Published 8 November 2021.

Living organisms rely on flows to perform essential functions that range from swimming and feeding in unicellular organisms to mucus clearance in humans. These flows are generated by the inte­grated activity of thousands of micrometer scale cilia attached to cell surfaces. Collections of cilia exhibit highly complex temporal patterns known as metachronal waves. While patterns of cilia coordination have been observed for decades, the mechanisms underlying their formation and their contribution to flow generation remain unclear. In my talk I will discuss the advantages of ciliated swimmers as experimental model systems where measurements of the geometric and dynamic properties of cilia arrays and can be readily performed. Performing precise measurements and perturbations of temporal patterning in cilia arrays and flows will enable the identification of the mechanisms underlying pattern formation. This integrated view that seeks to link cilia dynamics with flow structure will significantly increase our understanding of the physiology of cilia arrays. Beyond their physiological significance, arrays of cilia provide an accessible experimental platform to explore the physics of multi scale pattern formation.

Whether one considers swarming insects, flocking birds, or bacterial colonies, collective motion arises from the coordination of individuals and entails the adjustment of their respective velocities. In particular, in close confinement, such as those encountered by dense cell populations during development or regeneration, collective migration can only arise coordinately. Yet, how individuals unify their velocities is often not understood. Focusing on a finite number of cells in circular confinements, we identify waves of polymerizing actin that function as a pacemaker governing the speed of individual cells. We show that the onset of collective motion coincides with the synchronization of the wave nucleation frequencies across the population. Employing a simpler and more readily accessible mechanical model system of active spheres, we identify the synchronization of the individuals' internal oscillators as one of the essential requirements to reach the corresponding collective state. The mechanical 'toy' experiment illustrates that the global synchronous state is achieved by nearest neighbore coupling. We suggest by analogy that local coupling and the synchronization of actin waves are essential for emergent, self-organized motion of cell collectives.

Scientific publishers play a major role in the communication and dissemination of research. Throughout the publication process, scientific editors assess manuscripts, manage the peer review, and eventually make a decision as to publication. Understanding how editors work and how to interact with them is useful to navigate the publication process. Through the lens of the Physical Review journals, we will delve into the peer-review process, the role of editors, the significant changes that the publication landscape has witnessed in recent years, and the current challenges that it faces.

Active fluids, like all other fluids, exert mechanical pressure on confining walls. Unlike equilibrium, this pressure is generally not a function of the fluid state in the bulk and displays some peculiar properties. For example, when activity is not uniform, fluid regions with different activity may exert different pressures on the container walls but they can coexist side by side in mechanical equilibrium. Here we show that by spatially modulating bacterial motility with light, we can generate active pressure gradients capable of transporting passive probe particles in controlled directions. Although bacteria swim faster in the brighter side, we find that bacteria in the dark side apply a stronger pressure resulting in a net drift motion that points away from the low activity region. Using a combination of experiments and numerical simulations, we show that this drift originates mainly from an interaction pressure term that builds up due to the compression exerted by a layer of polarized cells surrounding the slow region. In addition to providing new insights into the generalization of pressure for interacting systems with non-uniform activity, our results demonstrate the possibility of exploiting active pressure for the controlled transport of microscopic objects.

Most predictive models of ecosystem dynamics are based on interactions between organisms: their influence on each other’s growth and death. I will discuss here how theoretical approaches are used to extract interaction measurements from experimental data in microbiology, particularly focusing on the generalized Lotka–Volterra (gLV) framework. Though widely used, I argue that the gLV model should be avoided for estimating interactions in batch culture — the most common, simplest and cheapest in vitro approach to culturing microbes. Fortunately, alternative approaches offer a way out of this conundrum. Firstly, on the experimental side, alternatives such as the serial-transfer and chemostat systems more closely match the theoretical assumptions of the gLV model. Secondly, on the theoretical side, explicit organism-environment interaction models can be used to study the dynamics of batch-culture systems. I illustrate the use of such mechanistic models on a recent system in which interactions can depend on environmental conditions. Varying the concentration of a single compound, linoleic acid (LA), modifies the interaction between two bacterial species, \textit{Agrobacterium tumefaciens} and \textit{Comamonas testosteroni}, from competitive at a low concentration, to facilitative at higher concentrations where LA becomes toxic for one of the two species. We demonstrate that the mechanism behind facilitation is that one species is able to reduce reactive oxygen species (ROS) that are produced spontaneously at higher concentrations of LA, allowing for short-term rescue of the species that is sensitive to ROS and longer coexistence in serial transfers. The interplay of experiments and modelling allows to understand how competition and facilitation between species can occur simultaneously, and changing the concentration of a single compound can alter the balance between the two.

I will present two examples of collective phenomena that emerge due to fluctuations and local heterogeneities in the underlying interaction network. Firstly, moving animal groups exemplify collective behaviour in social species in which the tools of statistical physics can be fruitfully used. As the animals change their position within a group and interact with different neighbours, the interaction network fluctuates over time potentially giving rise to collective changes of state. An example of such emergent dynamics are spontaneous rapid collective turns in natural flocks of starlings. Starting from the ideas obtained from flocking, I will discuss an example of collective reorientation dynamics in aqueous systems that originate from the fluctuations in the network formed between the water molecules through hydrogen bonds that are continuously breaking and reforming. We show that large angular jumps in liquid water require a highly collective dynamic process involving correlated motion of many water molecules that form spatially connected clusters. The mechanism we propose involves a cascade of hydrogen-bond fluctuations underlying angular jumps and provides new insights into the current localized picture of angular jumps.

Noether’s calculus of invariant variations in statistical mechanics yields exact identities (“sum rules”) from functional symmetries. The invariance of spatial transformation of the underlying classical many-body Hamiltonian at first order in the transformation field Noether’s theorem yields the local force balance. At second order three distinct two-body correlation functions emerge, namely the standard two-body density, the localized force-force correlation function, and the localized force gradient. An exact Noether sum rule interrelates these correlators [1]. More generally exploiting invariance of a thermally averaged classical phase space functions results in hyperforce sum rules [2]. These relate the mean gradient of a phase-space function to its negative mean product with the total force. Both global and locally resolved identities hold and similar to Hirschfelder’s hypervirial theorem, the hyperforce sum rules apply to arbitrary observables in equilibrium. As applications we investigate via computer simulations (including Lennard-Jones, Yukawa, soft-sphere dipolar, Stockmayer, Gay-Berne and Weeks-Chandler-Andersen liquids, monatomic water and a colloidal gel former) the emerging one-body force fluctuation profiles in bulk and confined liquids [1,2]. These local correlators quantify spatially inhomogeneous self-organization, demonstrate their fundamental role in the characterization of spatial structure and their measurement allows for the development of stringent convergence tests and enhanced sampling schemes in complex systems. References [1] F. Sammüller, S. Hermann, D. de las Heras, and M. Schmidt, Noether-constrained correlations in equilibrium liquids, Phys. Rev. Lett. 130, 268203 (2023). [2] S. Robitschko, F. Sammüller, M. Schmidt, and S. Hermann, Hyperforce balance from thermal Noether invariance of any observable, Commun. Phys. 7, 103 (2024).

Linear response theory is a fundamental tool for understanding how a system responds to a weak external perturbation. Moreover, the seminal contributions of Onsager and Kubo regarding linear irreversible processes and fluctuation-dissipation relations highlight its relevance for investigating non-equilibrium dynamics. After outlining the fundamental concepts of irreversibility, I will show how linear response theory offers invaluable insights regarding the non-equilibrium character of a system. Special attention will be devoted to exploring linear Gaussian processes, illustrating the inherent challenge of determining the thermodynamic state of the system from partial information without conducting response experiments. In this context, I will also discuss the pivotal role of response functions in guiding theoretical model selection. In cases where it is not possible to carry out response experiments, I will explain a possible strategy for inferring the thermodynamic state of the system by combining the information of different data sets acquired in different experimental conditions. Finally, I will focus on a high-dimensional multiscale deterministic system by showing that the temporal behavior of the response functions provides useful information on statistical properties of the system including its thermodynamic state.

Many biological sensory systems are extremely sensitive to small input signals and need to integrate information from many noisy molecular receptors into a collective response. A tempting hypothesis is that these systems operate close to bifurcation or critical points; close to such points the system’s response exhibits a diverging susceptibility to the control parameter and small signals are amplified into a large collective response. However, a common concern is that being close to these points requires fine-tuning of parameters, which seems impossible for noisy biological systems. Based on several examples ranging from snake thermosensing to E. coli chemosensing, we have investigated a feedback motif inspired by work on self-organized criticality that robustly maintains these systems close to their respective critical point. In this talk, I will share our view on the role of criticality for biological function and argue that feedback from the collective response onto the control parameter might be a common design principle for sensory systems which need to detect tiny signals in a varying environment.

Symbiotic associations are essential for one or both partners, for example between a fungus and a root of living plant this is primarily responsible for nutrient transfer. In this study, we focus on arbuscular mycorrhizal fungi (AMF), they are obligate symbionts depending on the plant for their carbon nutrition, in return, they grow in large underground mycelia foraging for inorganic nutrients such as phosphorous and nitrogen. The translocation of nutrients, across the fungal network, is crucial for the AMF to evolve trading strategies. However, its mechanism is poorly understood. We mimicked the AMF-plant trade underground market using an in-vitro culture system. Our system consists in conventional split-petri plates where in one compartment the root is inoculated with AMF and only the fungi is able to cross over to the second compartment. In the second compartment the fungal growth its confined into a 2D geometry and is stimulated by high concentration of phosphorus. With staining intracellular lipids, we show that the translocation mechanism is triggered by instabilities in the emulsion-like cytoplasm. These instabilities lead into a multiphase system creating, among others, simultaneous bidirectional flows. Moreover, the lipids clusterize and form emulsion condensates. Those condensates deform during translocation. We use this deformation as a feature to measure, for the first time, rheological properties of the cytoplasmic flow in an in-vivo AMF-root system.

Understanding epitope immunodominance is of paramount importance for developing universal vaccines against highly mutable pathogens and for studying pathogen coevolution in immunized hosts or populations. We introduce here a novel, multi-scale population dynamics model for affinity maturation, which aims to capture the intra-clonal, inter-clonal and epitope-specific organization of the B cell population in a germinal center. We describe the evolution of the B cell population via a quasispecies dynamics, where the desired multi-scale structure is reflected on the mutational connectivity of the accessible B cell space, and on the statistical properties of its complex fitness landscape. The analysis of this coarse-grained mathematical model yields a simple framework to characterize how immunodominance hierarchies emerge from the statistical features of the epitope-specific fitness landscapes in which B cells evolve. As new high-throughput data would be available to statistically characterize these fitness landscapes, the proposed construction could help identify general principles for rational vaccine design and detect evolving immunodominance patterns in mutating pathogens.

DNA-coated colloids can self-assemble into a wide range of mechanically and optically interesting micro-structured materials, guided by the binding specificity encoded in their DNA. Typically, the design principle is for the target structure to occupy the global minimum in the free energy landscape. However, this approach lacks control over assembly kinetics, so neither can undesirable kinetic traps be avoided nor can desirable meta-stable structures be targeted. To address this limitation, we present a strategy for controlling the colloidal assembly kinetics using a DNA-encoded recipe. The recipe dictates how the binding strength and specificity of each colloid type change over time and the time-dependent binding properties in turn control the aggregation time scales. We demonstrate multi-stage assembly into core-shell clusters with this kinetic control and show that the same set of building blocks can form clusters with varying core-shell compositions by tuning only the DNA-encoded assembly kinetics. Our findings introduce control over assembly kinetics as a tool in the design of self-assembled colloidal materials and pave the way to target specific meta-stable structures.

Knowing the interaction potential between particles as a function of distance, $u(r)$, is beneficial for developing formulations. This work provides an efficient method to infer these interactions, as well as to better understand the liquid state. The interaction potential, $u(r)$, is found by an inverse method, which matches the radial distribution function, $g(r)$, found from two different methods. The inverse method is demonstrated using simulated equilibrium configurations of passive particles. Interestingly, although active particles are inherently not in equilibrium, we can obtain effective interaction potentials as if they were in equilibrium, $u(r)_{\rm eff}$. Both the passive interactions and active motion can be seen in the effective interaction potentials.

Diffusiophoresis in geological porous media: dominant or negligible effect? In near-surface geological environments, local concentration gradients of species originate from several physicochemical processes, e.g. mineral dissolution/precipitation, redox reaction, desiccation, and interphase mass transfer. These local chemical gradients could be used to control colloidal particle displacement in geological porous media using diffusiophoresis, i.e., the transport of charged particles driven by concentration gradients. The ability of diffusiophoresis to reroute colloid trajectories offers an appealing solution to deliver healing materials toward target regions of a porous formation for groundwater remediation or to seal damaged geological confinement barriers. However, colloid injection methods remain for now at the stage of prototypes as the delivery of the particles to the area of interest is not well controlled, indeed, pressure-driven flows are often predominant in geological environments leading to advection-dominated conditions. Thus, it is not clear whether local concentration gradients allow colloids to be driven by diffusiophoresis in subsurface environments. We use microfluidic experiments that enable direct visualization of flows, reactions, and transport to study the interaction between hydrodynamics, species concentration, and colloid transport. This work shows that diffusiophoretic effects can be used to drive specifically chosen colloids toward a source of concentration gradient in the presence of strong advective flux. Depending on the properties of the colloids, the source of concentration gradient is preserved or on the contrary, is inhibited. This work paves the way for diffusiophoresis-aided remediation for subsurface environments.

Active matter encompasses a wide range of systems that consist of individuals, which extract energy from their surroundings and convert it into mechanical work. Such individuals, including bacteria and eukaryotic cells, exist in extremely diverse environments, which, in turn, lead to a complex network of inter- and intra-population interactions. Mechanical forces, exerted and experienced by cells, can act as messengers, regulating individual behaviour, however, how they lead to emergent collective behaviours and the emergence of liquid crystalline features in such active systems have not been elucidated yet. Here, by utilising a suite of theoretical models at different scales, such as continuum liquid crystal theory and cell-based phase-field formulation, we investigate how mechanical interactions with surroundings and other cells can lead to collective cell migration.

Active nematics are a class of liquid crystals composed of rod-like constituents that transmute energy from their surroundings to exert mechanical forces that intrinsically drive the material out of equilibrium. These materials display spontaneous disorderly flows and a steady-state populations of topological defects through continuous pair creation and annihilation. Studies have found complex dynamical behaviours associated to defects —including self-propulsion in two dimensions, and defect loop growth, shrinking, merging, and splitting in three dimensions. Understanding how defect dynamics relate to the emergent flows is an ongoing topic of research. In this talk, we show that motile point defects are constrained to borders between rotationally dominated and strain-rate dominated flows. Our results establish the importance of these boundaries as paths for defect dynamics and demonstrate that the constraint extends to defect lines and loops three-dimensions, which suggests potential new avenues for exploring topological dynamics in active systems.

Active emulsions and liquid crystalline shells are intriguing and experimentally realizable types of topological matter. We numerically study the morphology and spatiotemporal dynamics emulsion, where one or two passive small droplets are embedded in a larger active droplet. We find that activity introduces a variety of rich and nontrivial nonequilibrium states in the system. First, a double emulsion with a single active droplet becomes self-motile, and there is a transition between translational and rotational motion: both of these regimes remain defect-free, hence topologically trivial. Second, a pair of particles nucleate one or more disclination loops, with conformational dynamics resembling a rotor or chaotic oscillator, accessed by tuning activity. In the first state, a single, topologically charged disclination loop powers the rotation. In the latter state, this disclination stretches and writhes in 3D, continuously undergoing recombination to yield an example of an active living polymer. These emulsions can be self-assembled in the lab and provide a pathway to form flow and topology patterns in active matter in a controllable way, as opposed to bulk systems that typically yield active turbulence.

The transport of charged species through a membrane is key to many processes in cellular biology, from sensory detection to osmoregulation and neurotransmission. Likewise, new types of artificial membranes have led to quantum technological leaps: water desalination, DNA sequencing, blue energy and bio-mimetic computing. In all these cases, non-linear and dynamical effects occur when ions cross a nanometric channel. There is therefore a need for a better understanding of the dynamics of ion transport at the molecular scale. In this talk, I will present how progess in nanofluidics has enabled to build new types of channels, with dynamical properties that resemble that of biological pores (voltage gating, memory effects, etc.). In particular, I will focus on types of atomically small channels where fluctuations of water and ions can be coupled to structural and dynamical properties of the walls. I will show how this coupling can be harnessed to develop ‘iontronic’ devices, where one can control flows of ions to carry out computations.

The nuclear pore complex (NPC) is a massive protein complex that constitutes a permeable barrier on the nuclear envelope. The NPC consists of a ring with octagonal symmetry composed of multiple copies of different proteins (called Nups), many of which are intrinsically disordered. This disordered mesh is crossed by hundreds nuclear transport receptors (NTRs) bound to cargos translocating between the nucleus and the cytoplasm in a milliseconds time scale. Due to the high number, intrinsic flexibility, and fast motions of the NPC components, it is challenging to thoroughly resolve the physical mechanism underlying the transport through the barrier. To overcome this issue, we use biomimetic bottom-up approaches to reconstitute the essential features for the NPC selectivity in a controlled manner. In a first approach, we prepare Nups-coated solid-state nanopore arrays containing gold-labeled NTRs, which can be frozen and imaged by cryo-electron microscopy (cryo-EM). By determining the NTRs’ location in the nanopores, it is possible to resolve their preferred positions and pathways in the Nups mesh. Moreover, by labeling the Nups with gold nanoparticles and adding different concentrations of unlabeled NTRs, potential conformational changes in the Nup mesh can be revealed. In a second approach, we reconstitute the NPC using DNA origami nanopores as a scaffold functionalized with Nups. This gives us control over the position, number, and types of Nups involved in the system. We then integrate these DNA origami pores into lipid bilayers to study NTR transport through biomimetic NPCs. These methods allow us to directly visualize and probe the interaction between the NTRs and the Nups to unravel how the transport through the NPC is regulated.

Cells constantly experience environmental changes requiring a fast adaptation of their structures in order to modify shape or type of movement for example. Understanding how cells adjust the size of their dynamic actin architectures in relation to overall cell size is a fundamental question. However, due to their complexity, the relationship between the self-assembling properties of actin architectures and their ability to scale with cell size remains poorly understood. As decoupling these parameters to assess their relative contributions in a cellular context is extremely challenging, we have developed a bottom-up approach in order to identify the key molecular mechanisms involved in the scaling of dynamic actin architectures. We have developed an experimental system in which polystyrene beads are propelled by an actin comet in a cell-sized microwell containing a limited amount of components. Then, we established the biochemical conditions to ensure bead movement over tens of hours. Subsequently, we studied how compartment size, biochemical conditions and number of actin structures in competition affect actin architecture size and dynamics at steady state. Thanks to this reductionist approach, we were able to establish some general principles controlling the scaling of actin architectures.