This weekly seminar aims at gathering researcher form different thematics (physicists, biologists and chemists) and from different institutes in the center of Paris. The objective is to cover an interface between physics, chemistry and biology as broad as possible, with experimental, numerical and/or theoretical approaches. To describe life sciences all scales are needed, from single molecules, cell biology, organisms, population dynamics. That's why the range of our seminar is quite broad form embryonic development, genetic regulation, evolution, mechanics and cell migration, immunology, microbiology, synthetic biology, etc.
5 November 2020, 4pm - Paul François (McGill University)
Persistent neural activities are ubiquitous in neural systems. This capacity of networks to continuously discharge in the absence of on-going stimuli is believed to subserve short-term memorisation and temporal integration of sensory signals. Although persistence may reflect cellular mechanisms, it can also be a network emergent property. Here we investigate this latter mechanism on larval zebrafish, a model vertebrate that is accessible to brain-scale neuronal recording and high-throughput behavioral studies.
We thus combine behavioral assays, functional imaging and network modeling to understand the dynamics and function of a small bilaterally distributed neural circuit (ARTR). ARTR exhibits slow antiphasic alternations between its left and right subpopulation. This oscillation drives the coordinated orientation of the eyes and swim bouts, thus organizing the fish spatial exploration. The left/right transition can be induced through transient illumination of one eye such as to orient the fish towards towards light sources (phototaxis). We also show that the self-oscillatory frequency can be modulated by the water temperature. To elucidate the mechanism leading to the slow self-oscillation, we train a network (Ising) model on the neural recordings. The model allows us to generate synthetic oscillatory activity, whose features correctly captures the observed dynamics. It provides a simple physical interpretation of the persistent process.
We exploit a theoretical relation between two statistics on lineages trees, based either on forward lineages or on backward histories [1,2]. A fitness landscape is introduced, which quantifies the correlations between a trait of interest and the number of divisions. We derive various inequalities constraining the fluctuations of a trait of interest or its fitness on lineage trees. We apply this formalism to single-cell experiments with bacteria populations, carried out either in the mother machine configuration or in free conditions using time-lapse video-microscopy. We also investigate how the various sources of stochasticity at the single cell level can affect the population growth rate.
 Linking lineage and population observables in biological branching processes, R. Garcia-Garcia, A. Genthon and D. Lacoste, Phys. Rev. E, 042413 (2019).  Fluctuation relations and fitness landscapes of growing cell populations, Scientific Reports, 10, 11889 (2020).
Ants exhibit some of the most diverse and complex patterns of collective behavior in nature. However, the systematic study of these patterns and their computational significance has long been hindered by the lack of a lab model system, which would allow precise manipulations of the determinants of these emergent patterns. In this talk, I will present the potential of a specific ant species, the clonal raider ant Ooceraea biroi, to become such a model system. I will briefly describe the unique properties of the species and the opportunities they open for the understanding of collective behavior. I will then present results from two separate projects, studying different aspects of collective behavior. In the first, we study how ant colonies respond collectively to sensory input. We show that their response is characterized by an emergent threshold, which is sensitive to manipulations of colony properties. I will discuss the implications of this emergence for the understanding of how ants use interactions to reach collective decisions. In the second study, we analyze a more ecologically relevant behavior, the group raid, which is a swift offensive response of a colony to the detection of a potential prey by a scout. I will highlight the differences between this behavior and a behavior exhibited by related ant species, the army ants. Based on these analyses, we suggest that the emergent differences between the two behaviors can be explained by evolutionary changes in colony size alone.
The concept of the hematopoietic stem cell developed from the observation, reported in the 1950s, that the transplantation of bone marrow from adult mice rescues irradiated mice by regenerating their blood. Transplantation experiments have been the mainstay of hematopoiesis research until recently, when non-invasive genetic tools for tracing the progeny of hematopoietic stem cells were developed. Based on these tools, we and others found that post-transplantation recovery differs fundamentally from physiological hematopoiesis. Mathematical models of cell population dynamics, coupled with statistical inference, have been playing a key role in deriving quantitative insights on stem cell behavior from experimental data and in designing new experiments. I will discuss recent work on how the murine hematopoietic system develops in the fetus and functions in the adult. We find that the stem cells, while being highly productive during development, are remarkably unproductive in the adult, even during times of high demand for blood and immune cells. Cell population genetics suggest a function for idle hematopoietic stem cells.
The extensive heterogeneity of biological data poses challenges to analysis and interpretation. Construction of a large-scale mechanistic model of Escherichia coli enabled us to integrate and cross-evaluate a massive, heterogeneous dataset based on measurements reported by various labs over decades. We identified inconsistencies with functional consequences across the data, including: that the data describing total output of the ribosomes and RNA polymerases is not sufficient for a cell to reproduce measured doubling times; that measured metabolic parameters are neither fully compatible with each other nor with overall growth; that essential proteins are absent during the cell cycle - and the cell is robust to this absence. Finally, considering these data as a whole leads to successful predictions of new experimental outcomes, in this case protein half-lives.
Equilibrium statistical mechanics tells us how to control the self-assembly of passive materials by tuning the competition between energy and entropy to achieve desired states of organization. Out of equilibrium, no such principles apply and self-organization principles are scarce. In this talk I will review the progress which has been made over the past ten years to control the organization of self-propelled agents using motility control, either externally or through interactions. I will show that generic principles apply and illustrate the theoretical developments presented in the talk using recent experiments on run-and-tumble bacteria.
We study the origin and function of signaling oscillations in embryonic development. Oscillatory activities (period ~2 hours) of the Notch, Wnt and Fgf signaling pathway have been identified in mouse embryos and are linked to periodic mesoderm segmentation and the formation of pre-vertebrae, somites. Most strikingly, Notch signaling oscillations occur highly synchronized, yet phase-shifted, in cell ensembles, leading to spatio-temporal wave patterns sweeping through the embryo. I will discuss how we use general synchronisation principles based on entrainment/Arnold tongues to reveal general properties and function of collective oscillations during the mesoderm patterning process.
Active fluids consist of self-propelled particles (as bacteria or artificial microswimmers) and display properties that differ strongly from their passive counterparts. Unique physical phenomena, as enhanced Brownian diffusivity, viscosity reduction, active transport and mixing or the extraction of work from chaotic motion, result from the activity of the particles, locally injecting energy into the system. The presence of living and cooperative species may also induce collective motion and organization at the mesoscopic or macroscopic level impacting the constitutive relationships in the semi-dilute or dense regimes. Individual bacteria transported in viscous flows, show complex interactions with flows and bounding surfaces resulting from their complex shape as well as their activity. Understanding these transport dynamics is crucial, as they impact soil contamination, transport in biological conducts or catheters, and constitute thus a serious health thread. Here we investigate the trajectories of individual E-coli bacteria in confined geometries under flow, using microfluidic model systems in bulk flows as well as close to surfaces using a novel Langrangian 3D tracking method. Combining experimental observations and modelling we elucidate the origin of upstream swimming, lateral drift or persistent transport along corners. The understanding gained can be used to design channel geometries to guide bacteria towards specific locations or to prevent upstream contamination.
Spatial navigation constitutes an essential behavior that requires internal representations of environments and online memory processing to guide decisions. The precise integration of orientation and directions along trajectories critically determines the ability of animals to explore their surroundings efficiently. First, I will present recent results obtained in the fruit fly, Drosophila melanogaster. These results show how insects use an internal neural compass to store and compute the direction of cues present in their environments. Then, I will present the structure of the involved neural networks and the mechanisms at play during the processing of the information of direction. The results obtained in the fly mainly involve navigation in 2 dimensions, and thus the processing of a unique angular variable. However, a recent study in bats uncovered the existence of cells representing the orientation of bats in 3D. I will show possible mechanisms to extend the neural computation of directions to 3D rotations, a problem that presents much stronger theoretical challenges. I will propose a neural network model that displays activity patterns that continuously maps to the set of all the 3D rotations. Moreover, the general theory can account for psychophysics observations of "mental rotations.”
Coordinating collective behaviors across groups of cells is critical for a wide range of biological processes ranging from development to wound healing. How these basic group phenomena are regulated at the level of single cells, potentially by modulating factors like the frequency of synchronized signaling or the speed of group migration, is still an open question. Identifying what single cells tune in their own signaling programs to produce these phenotypic changes in multicellular population behaviors would yield parameters we can control when reprogramming these systems for our benefit. To address this challenge, we are pursuing complimentary efforts in multiple model systems where single-cell level and collective signaling can be simultaneously visualized with group behaviors. This talk will focus on these efforts in two systems: the social amoeba, Dictyostelium discoideum, and synthetic stromal tissues. We are interrogating signaling behaviors in these systems using a combination of techniques to visualize and control cellular signaling, and developing quantitative models to understand how the signaling behaviors we observe drive multicellular behaviors. Through directly controlling signaling, we can causally link our observations of single-cell signaling dynamics to the population-wide behaviors they control. Together, these efforts will allow us to identify how population-wide multicellular behaviors are regulated by single cells.
One of the most striking features of embryonic development is that differentiation is happening in a spatially ordered fashion: tissues self-organize to form well-defined patterns that pre-figure the body plan. During gastrulation, the cells of the embryo are allocated into three germ layers: ectoderm, mesoderm and endoderm. During the last decades, signaling pathways responsible for the initiation of gastrulation in mammalian embryos have been identified. However, the physical rules governing the tissue spatial patterning and the extensive morphogenetic movements occurring during that process are still elusive. Studying the spatio-temporal dynamics of pattern formation is difficult in live embryos, because of their inherent lack of observability but also because it is not possible in an embryo to control in a quantitative manner what is relevant for the establishment of the multi-cellular pattern, i.e. the cells' physical and chemical environment. I will discuss how culture and differentiation of mouse ESC on micro-patterned substrates allowed us to recapitulate some aspects of Antero/Posterior axis formation occurring at gastrulation and how microfluidic devices can help us dissect the emergence of A/P polarity.
The actin cytoskeleton assembles into very dynamic structures that generate various forces. In this active process, filament disassembly must be tightly regulated, either to maintain active units, or to discard excess filaments and replenish the pool of monomeric (G) actin. At the centre of all actin filaments disassembly machineries is the family of proteins ADF/cofilin. ADF/cofilin binds along filaments into domains, induces severing and regulates depolymerisation from filament ends. We performed in vitro experiments, in microfluidic chambers, with purified proteins, to directly observe and quantify interactions between single actin filaments and ADF/cofilin. We recently developed new methods to apply tension, curvature and torsion to filaments, and thus understand how mechanical constraints regulate ADF/cofilin activity. First, we discovered that filament curvature and torsion boost ADF/cofilin-mediated severing. Moreover, ADF/cofilin, by increasing the helicity of actin filaments, generates a torque on twist-constrained filaments that accelerates severing up to 100-fold. These findings highlight the deep connections between mechanical forces and biochemical reactions, and their importance for cell behaviour regulation.
Single-molecule techniques continue to transform imaging, biophysics and, more recently, optical sensing. I will introduce a new class of label-free micro and nanosensors that are starting to emerge and that allow us to observe dynamic processes at the single molecule level directly with light, with unprecedented spatial- and temporal resolution, and without significantly affecting the natural and functional movements of the molecules. Initial demonstration include single ion sensing, and visualisation of functional movements of enzymes directly with light.
Multi-drug resistant bacterial pathogens constitute a critical public health threat. This threat has spurred a multidisciplinary response to develop antibiotic alternatives, including the use of bacteriophage (phage), i.e., viruses that exclusively infect and lyse bacteria. Phage-induced lysis eliminates bacterial cells. However, the death of individuals cells need not translate into the elimination of a target population. Instead, lysis can lead to the depletion of bacterial hosts which, in turn, leads to decreased effectiveness of phage therapy and the evolution of phage-resistant hosts. As a consequence, phage are unlikely to eliminate a target population on their own and may even be eliminated altogether. However, a central difference between in vitro dynamics and in vivo therapy is the influence of the mammalian immune system. In this talk, I present collaborative efforts to address this gap via a dynamical systems approach to phage therapy in an immune system context. In doing so, I highlight how the combined use of mathematical models, in vitro manipulation, and in vivo experiments may shed light on principles underlying curative treatment of acute infections.
Mechanics are ubiquitous in the environments of bacteria, but we are only starting to appreciate how they may affect their physiology. Here, I will discuss how the human pathogen Pseudomonas aeruginosa uses a mechano-chemical sensory system to induce virulence upon mechanical stimulation during surface contact. I will show that successive type IV pili extension, attachment and retraction represents a mechanical input readout by a chemotaxis-like system (Chp). Using iSCAT, a microscopy method based on interference and scattering enabling label-free visualization of small extracellular structures in live cells, we were able to measure type IV pili dynamics during surface exploration, thereby providing a direct measurement of mechanical input. I will discuss how we are using these measurements to understand how type IV pili interacts with the Chp system to activate cellular response. This expands the range of known inputs that bacteria sense, providing a new class of signals that can be processed by two component systems. It furthermore argues that mechanics may play a role in the physiology of many other species.
One of the most critical aspects of cell functioning is the ability of protein molecules to quickly find and recognize specific target sequences on DNA. Kinetic measurements indicate that in many cases the corresponding association rates are surprisingly large. For some proteins they might be even larger than maximal allowed 3D diffusion rates, and these observations stimulated strong debates about possible mechanisms. Current experimental and theoretical studies suggest that the search process is a complex combination of 3D and 1D motions. Although significant progress in understanding protein search and recognition of targets on DNA has been achieved, detailed mechanisms of these processes are still not well understood. The most surprising observation is that proteins spend most of the search time being non-specifically bound on DNA where they supposedly move very slowly, but still the overall search is very fast. Another intriguing result is known as a speed-selectivity paradox. It suggests that experimentally observed fast findings of targets require smooth protein-DNA binding potentials, while the stability of the specific protein-DNA complex imposes a large energy gap which should significantly slow down the protein molecule. Here we discuss a theoretical picture that might explain fast protein search for targets on DNA. We developed a discrete-state stochastic framework that allowed us to investigate explicitly target search phenomena. Using exact calculations by analyzing first passage distributions, it is shown that strong coupling between 3D and 1D motion might accelerate the search. It is argued that the speed-selectivity paradox does not exist since it is an artifact of the continuum approximation. We also show how our method can be utilized for taking into account the inter-segment processes. This is important to explain large deviations from the diffusion limit. Our theoretical analysis is supported by Monte Carlo computer simulations, and it agrees with all available experimental observations. Physical-chemical aspects of the mechanism are also discussed.
The two hands of most humans almost superimpose. Similarly, flowers of an individual plant have almost identical shapes and sizes. This robustness is in striking contrast with growth and deformation of cells during organ morphogenesis, which feature considerable variations in space and in time, raising the question of how organs and organisms reach well-defined size and shape. Because heterogeneous growth induces mechanical stress in tissues, we are exploring the biophysical basis of morphogenesis. By combining approaches from developmental biology (molecular genetics, live imaging), and mechanics/physics (mechanical measurements, models), we are unravelling unexpected cellular patterns and behaviours. During this talk, I will discuss some of our recent results and the resulting perspectives, aiming at a general audience.
Range expansions coupled with fluid flows are of great importance in understanding the organization and competition of microorganism populations in liquid environments. However, combining growth dynamics of an expanding assembly of cells with hydrodynamics leads to challenging problems, involving the coupling of nonlinear dynamics, stochasticity and transport. We have created an extremely viscous medium that allows us to grow cells on a controlled liquid interface over macroscopic scales. In this talk, I will present laboratory experiments, combined with numerical modelling, focused on the collective dynamics of genetically labelled microorganisms undergoing division and competition in the presence of a flow. I will show that an expanding population of microbes can itself generate a flow, leading to an accelerated propagation and fragmentation of the initial colony. Finally, I will show the mechanism at the origin of this metabolically generated flow and how it affects the growth and morphology of these microbial populations.
Proteins are very heterogeneous objects: they are sensitive to perturbations at some sites distant from their active site while being insensitive to perturbations at closer sites. I’ll review the evidence for the ubiquity of these long range effects and discuss our current understanding of their physical nature and evolutionary origin. This will motivate the introduction of a new theoretical model where long-range effects emerge spontaneously. I’ll explain how this model accounts for the evolution of long-range regulation (allostery) and for the different patterns of coevolution that may be inferred from protein sequences.
The emergent active behaviors of systems comprising large numbers of molecular motors and cytoskeletal filaments remain poorly understood, even though individual molecules have been extensively characterized. Here, we show in vitro with a minimal acto-myosin system that flagellar-like beating emerges naturally and robustly in polar bundles of filaments. Using surface micro-patterns of a nucleation-promoting factor, we controlled the geometry of actin polymerization to produce thin networks of parallel actin filaments. With either myosin Va or heavy-mero myosin II motors added in bulk, growing actin filaments self-organized into bundles that displayed periodic wave-like beating resembling those observed in eukaryotic cilia and flagella. We studied how varying the motor type or changing the size of the actin bundles influenced the properties of the actin-bending waves. In addition, using myosin-Va-GFP to visualize the motors within the actin bundle, we identified a novel feedback mechanism between motor activity and filament bending. Overall, structural control over the self-assembly process provides key information to clarify the physical principles underlying flagellar-like beating.
Nuclear Pore Complex (NPC) is a biomolecular “nanomachine” that controls nucleocytoplasmic transport in eukaryotic cells, and is operation is central for a multitude of health and disease processes in the cell. The key component of the functional architecture of the NPC is the assembly of the polymer-like intrinsically disordered proteins that line its passageway and play a central role in the NPC transport mechanism. Due to the unstructured nature of the proteins in the NPC passageway, it does not possess a molecular “gate” that transitions from an open to a closed state during translocation of individual cargoes. Rather, its passageway is crowded with multiple transport proteins carrying different cargoes in both directions. It remains unclear how the NPC maintains selective and efficient bi-directional transport under such crowded conditions. Remarkably, although the molecular conservation of the NPC components is low, its physical transport mechanism appears to be universal across eukaryotes – from yeast to humans. Due to the paucity of experimental methods capable to directly probe the internal morphology and the dynamics of NPCs, much of our knowledge about its properties derives from in vitro experiments interpreted through theoretical and computational modeling. I will present the current understanding of the Nuclear Pore Complex structure and function arising from the analysis of in vitro and in vivo experimental data in light of minimal complexity models relying on the statistical physics of molecular assemblies on the nanoscale.
The actin cytoskeleton is able to exert both pushing and pulling forces on the cell membrane, mediating processes such as cellular motility, endocytosis and cytokinesis. In order to investigate the exclusive role of actin dynamics on membrane deformations, the actin dynamics is reconstituted on the outer surface of a deformable liposome. Depending on the elasticity of the membrane and the forces generated by the actin polymerization, both tubular extrusions (i.e. towards the actin cortex) and localized spike-like protrusions occur along the surface of the liposome. In this talk I present a theoretical model where uniform actin polymerization can drive localized membrane deformations and show how polymerization kinetics and membrane/cortex mechanics impact their size and stability.
The coordinated flight of bird flocks is a striking example of collective behavior in biology. Using 3D positions and velocities of large natural flocks of starlings, I will show how to build an explicit mapping of flock behaviour onto statistical physics models of magnetism. Learning the parameters of these models allows us to infer the local rules of alignment, and to reveal that flocks are poised close to a critical point, where susceptibility to external perturbations is maximal. Extending the approach to alignment dynamics shows that flocks are in a state of local quasi-equilibrium.
Developing tissues have the capacity to cope with perturbations, including the modification of cell growth rate and the elimination of a large number of cells through wounding. This plasticity is well illustrated by cell competition, a process that drives the elimination of suboptimal cells (so called “losers”) by fitter cells (so called “winners”) through apoptosis without morphological defects. In the past years, the number of genetic and tissular contexts leading to cell competition has been constantly increasing. Yet, the mechanisms allowing recognition and elimination of suboptimal cells is still actively debated. I will present here our attempt to characterize quantitatively the process of cell competition which led to the characterization of two independent modes of elimination: first a contact dependent elimination which can be modulated by the shape of the interfaces between the two populations, secondly a compaction-driven competition where cell elimination is triggered by mechanical stress and differential sensitivity to compaction. I will then present recent results regarding the characterization of the pathway sensing cell compaction and triggering cell elimination in the Drosophila pupal notum (a single layer epithelium). Eventually I will present our ongoing characterization of the process of cell extrusion (the concerted removal of one cell from the epithelial layer) and its regulation by caspases.
In a similar way to bacteria that have to navigate in their environment, soaring birds try to minimize their effort by finding and exploiting ascending currents. However the environment is highly turbulent and unpredictable with thermals constantly forming, disintegrating and being transported within minutes timescales. How the birds navigate these environments remains unknown. It is a notoriously difficult/impossible task to assess what cues are used by the soaring birds and what strategies they developed to explore and exploit such turbulent environments. For this investigation, we chose to emulate how an agent could learn to see what strategies would emerge. I then set up an experimental reinforcement learning framework that I implemented in a two-meter wingspan glider. Here, the soaring agent measured its state (height and a set of cues), took actions (change the left/right direction it is heading to) and recorded what resulted from these actions given the previous state. After an initial learning period, the glider chose the actions according to their state that would maximize the gain in altitude. In short, the glider learned to soar through its past experience. The learned strategy was based on accurate estimates of local wind accelerations and roll-wise torque. In the field, the glider could typically gain hundreds of meters in height in a few minutes when facing environments with thermals. Our results not only highlight the vertical wind accelerations and roll-wise torques as effective mechanosensory cues for soaring birds but also provide navigational strategy that is directly applicable to the development of autonomous soaring vehicles to increase their time aloft with minimal energy cost.
Fertilization is one of the fundamental processes of living systems. Here I will address marine external fertilization and comment on recent work on mammals. I will show experiments that substantiate that sea urchin sperms exhibit chemotaxis as they swim towards the ovum. They are guided by flagellum internal [Ca2+] concentration fluctuations triggered by the binding of chemicals from the oocyte surroundings. Based on experiment, I present a family of logical regulatory networks for the [Ca2+] fluctuation signaling-pathway that reproduce previously observed electrophysiological behaviors and provide predictions, which have been confirmed with new experiments. These studies give insight on the operation of drugs that control sperm navigation. In this systems biology approach, global properties of the [Ca2+] discrete regulatory network dynamics such as: stability, redundancy, degeneracy, chaoticity and criticality can be determined. Our models operate near a critical dynamical regime, where robustness and evolvablity coexist. This regime is preserved under a class of strong perturbations. Based on global dynamics considerations, we have implemented a network node-reduction method. The coincidence of this reduced network with our bottom-up step-by-step, continuous differential equation modeling is reassuring. For the case of mammals our research has centered on the understanding of capacitation and acrosomal reaction. The first is a process by means of which roughly one third of the spermatozoa acquire the “capacity” to fertilize; the second enables the spermatozoa to penetrate the egg´s surrounding zona pellucida. Overall, our studies might contribute to fertility issues such as the development of male contraception treatments, which is an area of intense research.
The development of most metazoans can be divided in an early phase of embryogenesis and a subsequent phase of post-embryonic development. Developmental dynamics during the post-embryonic phase are generally much slower and often controlled by very different molecular mechanisms that, e.g., ensure tissue synchrony and integrate metabolic queues. However, obtaining long-term in-vivo quantitative imaging data post-embryonically with good statistical and cellular resolution has been highly challenging because animals must be allowed to grow, feed, and move in order to properly develop after embryogenesis. In this talk, I will discuss our recent progress in overcoming these challenges in the model organism C. elegans, using microfluidics technology. I will then outline two of our studies, in which quantitative in-vivo imaging data of post-embryonic development allows novel insights into mechanisms of cell-fate acquisition and the regulation of oscillatory gene expression in C. elegans.
Early embryogenesis of most metazoans is characterized by rapid and synchronous cleavage divisions. After fertilization, Drosophila embryos undergo 13 swift rounds of DNA replication and mitosis without cytokinesis, resulting in a multinucleated syncytium containing about 6,000 nuclei. The very first cycles involve substantial flows, both in the bulk and at the cortex of the syncytial embryo. Waves of activity of Cdk1, the main regulator of the cell cycle, are observed in late cycles. I shall discuss the corresponding experimental data and models that capture those dynamics.
Microtubules are dynamic polymers that are used for intracellular transport and chromosome segregation during cell division. Their unique property to grow and shrink at steady state conditions stems from the low energy of dimer interactions, which sets the growing polymer close to its disassembly conditions. Microtubules function in coordination with molecular motors, such as kinesins and dyneins, which use ATP hydrolysis to produce mechanical work and move on microtubules. This raises the possibility that the forces produced by walking motors can break dimer interactions and trigger microtubule disassembly. We tested this hypothesis by studying the interplay between non-stabilized microtubules and moving molecular motors in vitro. Our results show that the mechanical work of molecular motors is able to remove tubulin dimers from the lattice and rapidly destroys microtubules. This effect was not observed when free tubulin dimers were present in the assay. Using fluorescently labelled tubulin dimers we found that motor motion fosters the insertion of free tubulin dimers into the microtubule lattice. This self-repair mechanism allows microtubules to survive the damages induced by molecular motors as they move along their tracks. Thus, our study reveals the existence of a coupling between the motion of molecular motors and the renewal of microtubules lattice.
In order to guide spatial behaviour the brain has the complex task of keeping track of movement through space, which it accomplishes by integrating information about learned environmental features together with information about movements, both linear and angular. The system that performs this integration contains several canonical cell types including place cells, head direction cells and grid cells. How these neurons achieve this environment/movement integration in two-dimensional space is relatively well understood, but movement in more than two dimensions introduces additional problems such as non-commutativity and anholonomy. This talk will review these problems, and discuss emerging evidence that the brain deals with the resulting complexity by a process of dimension reduction - that is, by reducing the problem to the lowest number of dimensions that will suffice to solve a given task. Not only does this allow for efficient processing of three-dimensional space, it might even be possible, at least in humans, that the brain could learn to apprehend four-dimensional space in this way.
The nuclear pore complex is the unique gateway between the nucleus and the cytoplasm of the cells. It ensures both directional and selective transport of nucleic acids and proteins. Its detailed mechanism is still highly debated. We study its dynamic through two complementary approaches. In a bottom-up approach we use hydrophobic polymer grafted nanopores that mimic the crowding of the native pore. We show using a near field optics (ZMW, ) that we can measure the free energy of translocation and reproduce some of the selectivity and directionality features of the nuclear pore. In a top-down approach we extract nuclear membranes from Xenopus Laevis. Our results obtained using ZMW and optical super-resolution (dSTORM) indicates that the nuclear pore has a plastic architecture. Its large scale organization and its internal structure are strongly influenced by transporters molecular crowding, developmental stage and transcriptional activity .  Zero-mode waveguide detection of flow-driven DNA translocation through nanopores. Auger T, Mathé J, Viasnoff V, Charron G, Di Meglio JM, Auvray L, Montel F. Phys Rev Lett. 2014 Jul 11;113(2):028302.  Nuclear pore complex plasticity during developmental process as revealed by super-resolution microscopy. Sci Rep. 2017 Nov 7;7(1):14732. Sellés J, Penrad-Mobayed M, Guillaume C, Fuger A, Auvray L, Faklaris O, Montel F.
Embryo morphogenesis relies on highly coordinated movements of different tissues as well as cell differentiation and patterning. However, remarkably little is known about how tissues coordinate their movements to shape the embryo and whether and how dynamic changes in signalling and tissue rheology affect tissue morphogenesis. In zebrafish embryogenesis, coordinated tissue movements first become apparent during "doming," when the blastoderm begins to spread over the yolk sac, a process involving coordinated epithelial surface cell layer expansion and deep cell intercalations. In this talk, I will first present how using a combination of active-gel theory and experiments (performed by Dr. Hitoshi Morita, Yamanashi University, Japan) shows that active surface cell expansion represents the key process coordinating tissue movements during doming. I will then talk about the analysis of the intrinsic mechanical properties of the blastoderm at the onset of doming and how, by the aid of a simpler toy model and experiments (performed by Dr. Nicoletta Petridou, IST Austria), blastoderm movement relies on a rapid, pronounced and spatially patterned tissue fluidisation which is found to be linked to local activation of non-canonical Wnt signalling mediating cell cohesion.
Fitness landscapes have moved from theoretical constructions to observable data in last decades, while several experimental fitness landscapes were partially or completely resolved. We have developped few metrics to get a better sense on what are these highly dimensionnal objects. We are now trying to infer what class of models can generate the observed experimental fitness landscapes: clearly none of the ones that were proposed so far. We however found some clues on what to search and where to garden in these landscapes.
The overdamped Langevin equation describes the inertialess motion of a particle under deterministic drift and thermal noise. The deterministic drift is the result of the combined action of active forces and the diffusivity gradient (the “spurious” force). For biological applications, it is important to distinguish between the two components, because the former indicates specific interactions, while the latter is due to a heterogeneous environment, in which these interactions take place. The spurious force is always proportional to the diffusivity gradient, but the proportionality coefficient is only known for equilibrium systems. This leads to a range of possible spurious force values in out-of-equilibrium systems and leads to ambiguity in the interpretation of the observed drift. This ambiguity is known as the Itô-Stratonovich dilemma. In this work, we do not try to resolve the dilemma, but analyze the information that can be extracted about the active forces in an a priori unknown out-of-equilibrium system. To this end, we propose a Bayesian method that marginalizes over all possible values of the spurious force and allows robust identification of active forces in both equilibrium and out-of-equilibrium setups. Under certain assumptions, the main result can be obtained in a closed form. The method has a significantly decreased false positive rate of active force detection as compared to conventional approaches. We illustrate the practical value of the method by integrating it into the open-source software project TRamWAy and applying it to both numerical trajectories and experimental single-biomolecule tracks (HIV capsids assembly) recorded on the cell membrane.
Spatially growing populations are ubiquitous across scales, ranging from the human migration out of Africa to the spreading of diseases. In contrast to well-mixed populations where an individual’s chance to survival is only determined by its fitness, in spatially growing populations the physical location of an individual is determinant for its survival: the individuals at the edge of the expanding front benefit from having access to virgin territory and giving their offspring the same advantage. The emerging population dynamics results in an evolutionary dynamics dominated by noise, with extreme consequences such as the accumulation of deleterious mutations at the front of the population. To explore experimentally how spatial constraints affect evolutionary dynamics, we employ bacteriophage T7, an E. coli virus that allows to cover many generations in short periods of times while controlling the underlying resource constraints, i.e., the bacterial host. In an evolutionary experiment lasting only 7 days, we were able to evolve a T7 strain that more than doubled its spreading speed on a bacterial lawn compared to its ancestor. The results from the experiments pointed out specific properties that are under strong selection in viral expansions and uncovered new remarkable properties of phage spreading dynamics that we believe are shared across viruses and pathogens in general.
Understanding how groups of species diversified, and how species phenotypes evolved during evolutionary history, is key to our understanding patterns of biodiversity as we see them around us today. Phylogenetic comparative methods have been developed to study diversification and phenotypic evolution from present-day data. I will present recent developments that allow testing the effect of past environmental changes on rates of speciation, extinction and phenotypic evolution, as well as models that allow testing the role of species interactions -- such as competitive, mutualistic, and antagonistic interactions – on phenotypic evolution. Empirical applications of these new phylogenetic comparative methods to large empirical datasets demonstrate the pervasive effect of past environmental changes on evolutionary rates across diverse clades spanning micro and macroorganims. They also demonstrate a distinct effect of interspecific competition in traits involved in resource use versus social signaling. Past environmental changes and species interactions have been key in driving the heterogeneity of evolution rates repeatedly observed across the tree of life.
The migration of immune cells is guided by specific chemical signals, such as chemokine gradients. Their trajectories can also be diverted by physical cues and obstacles imposed by the cellular environment, such as topography, rigidity, adhesion, or hydraulic resistance. On the example of hydraulic resistance, it was shown that neutrophils preferentially follow paths of least resistance, a phenomenon referred to as barotaxis. We here combined quantitative imaging and physical modeling to show that barotaxis results from a force imbalance at the scale of the cell, which is amplified by the actomyosin intrinsic polarization capacity. Strikingly, we found that macropinocytosis specifically confers to immature dendritic cells a unique capacity to overcome this physical bias by facilitating external fluid transport across the cell, thereby enhancing their space exploration capacity and promoting their tissue-patrolling function both in silicoand in vivo. Conversely, mature dendritic cells, which down-regulate macropinocytosis, were found to be sensitive to hydraulic resistance. Theoretical modeling suggested that barotaxis, which helps them avoid dead-ends, might accelerate their migration to lymph nodes, where they initiate adaptive immune responses. We conclude that the physical properties of the microenvironment of moving cells can introduce biases in their migratory behaviors but that specific active mechanisms such as macropinocytosis have emerged to diminish the influence of these biases, allowing motile cells to reach their final destination and efficiently fulfill their functions.
My colleague Sunil Laxman has observed the spontaneous emergence of subpopulations of cells in different metabolic states in growing populations of budding yeast. I'll talk about two situations - one where the yeast is in a well-mixed chemostat, and the other where it grows on agar plates. The chemostat produces incredibly regular oscillations between quiescence and proliferation which can sustain for days. I'll spend most time in the talk discussing a simple mathematical model that we think captures many aspects of this oscillation. The model helped us deduce that the the key metabolites triggering the switch from quiescence to proliferation are probably Acetyl-CoA and NADPH. If there is time, I'll also discuss the results of experiments and modelling of the spatial colonies where cells in two different metabolic states self-organize into a complex intermingled spatial pattern, with one state dependent on the other for metabolic raw material.
Our understanding of bacterial cell size control is based mainly on stress-free growth conditions in the laboratory. In the real-world however, bacteria are routinely faced with stresses that produce long filamentous cell morphologies. E. coli is observed to filament in response to DNA damage, antibiotic treatment, host immune systems, temperature, starvation, and more; conditions which are relevant to clinical settings and food preservation. This shape plasticity is considered a survival strategy. Size control in this regime remains largely unexplored. Here we report that E. coli cells use a dynamic size ruler to determine division locations combined with an adder-like mechanism to trigger divisions. As filamentous cells increase in size due to growth, or decrease in size due to divisions, its multiple Fts division rings abruptly reorganize to remain one characteristic cell length away from the cell pole, and two such length units away from each other. These rules can be explained by spatio-temporal oscillations of Min proteins. Upon removal of filamentation stress, the cells undergo a sequence of division events, randomly at one of the possible division sites, on average after the time required to grow one characteristic cell size. These results indicate that E. coli cells continuously keep track of absolute length to control size, suggest a wider relevance for the adder principle beyond the control of normally sized cells, and provide a new perspective on the function of the Fts and Min systems.
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