24 June 2022: Adrienne Fairhall (Washington)

From neurons to behavior in Hydra

Hydra is a fascinating model organism for neuroscience. It is transparent; new genetic lines allow one to image activity in both neurons and muscle cells; it exhibits quite rich behavior; and it continually rebuilds itself. Hydra’s fairly simple physical structure as a two-layered fluid-filled hydrostat and the accessibility of information about neural and muscle activity open the possibility of a complete model of neural control of behavior. Toward that end, we have developed a biophysical and biomechanical model of Hydra’s body that allows us to transform measured neural activity into behavior.

17 June 2022: Ila Fiete (MIT)

From smooth gradients to discrete modules: a topologically robust model of structure emergence

Modular structures in the brain are hypothesized to play a central role in intelligence by permitting compositional representations, but the general mechanisms driving discrete structure emergence from more-continuous genetically specified morphogens have remained elusive. Grid cells represent self-location during navigation in 2D spaces with spatially periodic codes of a small number of discrete periodicities. They present a paradigmatic example of the computational advantages of modular representations– permitting exponential representational capacity and strong intrinsic error-correction by representing a continuous euclidean variable (location), with a modular set of position-encoding phases. Underlying this discrete modular coding, which emerges rapidly postnatally, are biophysical gradients that vary smoothly. I will consider how smooth gradients can give rise to globally discrete function through self-organization in the context of this system. We show that two purely local lateral interactions, one with a smoothly graded parameter in the brain and another without a spatial gradient can simultaneously give rise to local pattern formation and global modularity. We show that this mechanism of modularity emergence is highly generic, robust, and almost completely insensitive to parameters because it is a topological process. The model makes predictions for the relationships between modules that furnish the most accurate match to data to date. Abstractly, the mechanism involves dynamics on the sum of two energy landscapes, one of which is a shallow global minimum that smoothly moves with the spatial parametric variation, and the other of which is a static landscape with multiple narrow minima. We believe this is a novel self-organization mechanism by which simple local interactions and smooth gradients may interact to induce macroscopic modular organization.

3 June 2022: Gabriel Popescu (UIUC)

Artificial confocal microscopy for deep label-free imaging

Widefield microscopy methods applied to optically thick specimens are faced with reduced contrast due to “spatial crosstalk”, in which the signal at each point in the field of view is the result of a superposition from neighboring points that are simultaneously illuminated. In 1955, Marvin Minsky proposed confocal microscopy as a solution to this problem. Today, laser scanning confocal fluorescence microscopy is broadly used due to its high depth resolution and sensitivity, which come at the price of photobleaching, chemical, and photo-toxicity. Here, we present artificial confocal microscopy (ACM) to achieve confocal-level depth sectioning, sensitivity, and chemical specificity, on unlabeled specimens, nondestructively. Thus, we augmented a commercial laser scanning confocal instrument with a quantitative phase imaging module, which provides optical pathlength maps of the specimen in the same field of view as the fluorescence channel.

Using pairs of phase and fluorescence images, we trained a convolution neural network to translate the former into the latter. The training to infer a new tag is very practical as the input and ground truth data are intrinsically registered, and the data acquisition is automated. Remarkably, the ACM images present significantly stronger depth sectioning than the input (phase) images, enabling us to recover confocal-like tomographic volumes of microspheres, hippocampal neurons in culture, and 3D liver cancer spheroids. By training on nucleus-specific tags, ACM allows for segmenting individual nuclei within dense spheroids for both cell counting and volume measurements. Furthermore, taking the estimated fluorescence volumes, as annotation for the phase data, we extracted dry mass information for individual nuclei. In sum, ACM can provide quantitative, dynamic data, nondestructively, from both thin and thick samples, while chemical specificity is recovered computationally.

20 May 2022: Philippe Brunet (MSC)

Nonlinear phototaxis and instabilities in suspensions of light-seeking algae

13 May 2022:  Silvia de Monte & Mathieu Forget (IBENS)

Aggregation and behavioural strategies in the 'social' amoeba Dictyostelium discoideum

The ‘social’ amoeba D. discoideum is facultatively multicellular. Starvation triggers a life cycle where single cells come together to form multicellular fruiting bodies, essential for efficient dispersal and long-term survival. In this process, part of the cells die while promoting the survival of the spores. The evolution of self-sacrificial behaviour is more easily understood when all cells in the body share the same genome. It is therefore puzzling to observe that in natural conditions multicellular aggregates tend to be genetic chimeras, so that genetic conflicts are unavailable. Theory predicts that the spread of genotypes that reap more than their fair share of benefits from the group — the so-called cheaters — should prevent cooperative behaviour to be evolutionary stable. We compared the social performance in chimeras composed of isogenic cells harvested at different phases of population growth, and found that social behavior is modulated by phenotypic plasticity as well as genetic background. By tracing the origin of spore biases to the process of aggregation from single cells, we explored the single-cell determinants of differences in social behaviour. Finally, we show that biases due to non-genetic sources of phenotypic variation are comparable to genetic effects, and can dominate over genetic differences, overturning classical definitions of social behaviour. Our observations suggest that inevitable heterogeneity in cell-level physical properties may act – by breaking heritability of social behaviour – as a hindrance to the evolutionary success of cheaters, and this even when social interactions within the multicellular body are neglected.

22 April 2022, 12:30

Leonid Mirny (MIT)

Chromosomes as memory machines

One of the hallmarks of nuclear organization in eukaryotes is the spatial segregation of transcriptionally active (euchromatin) and inactive (heterochromatin) genomic regions. Recently we found that such compartmentalization is driven by affinity between heterochromatin regions (Falk et al Nature 2019) through microphase separation. Despite the widespread of such compartmentalized organization in nature, its functional roles remain elusive. Here we examine the role of compartmentalization in the maintenance of epigenetic memory, i.e. maintenance of pattern of histone marks for hundreds of generations. We modeled joint dynamics of chromatin and histone marks: loss and spreading of marks, and refolding of chromosomes through the cell cycle. A surprinting analogy between the spreading of histone marks and the spreading of a disease in a pandemic helped to identify factors that provide robust memory. We further found a parallel between epigenetic memory and an associative memory in the neural network. Our analysis shows that operation of chromatin as a memory device requires enzyme limitation and spatial spreading of the marks in the dense and spatial segregated heterochromatin, suggesting a functional role for this hallmark of nuclear organization.

15 April 2022, 1PM

Olivia du Roure (PMMH)

Pinching the cortex of living cells to assess its biophysics

The cell cortex is a contractile actin meshwork, which determines cell shape and is essential for cell mechanics, migration and division. Because the cortical thickness is below optical resolution, it has been generally considered as a thin uniform elastic and contractile layer. Using two mutually attracted magnetic beads, one inside the cell and the other in the extracellular medium, we pinch the cortex of live dendritic cells and provide an accurate and time resolved measure of its thickness. Our observations draw a new picture of the cell cortex as a highly dynamic layer, harboring large fluctuations in its third dimension due to actomyosin contractility. We propose that the cortex dynamics might be responsible for the fast shape changing capacity of highly contractile cells that use amoeboid-like migration. Depending on time I will also describe some recent results on the mechanics of cell cortex.

8 April 2022, 1PM

Ulisse Ferrari (Institut de la vision)

Collective behavior in neuronal networks: Maximum Entropy Principle in Neuroscience

The Maximum Entropy principle is an inference framework that allows for finding the discrete Boltzmann distribution that reproduces at best the empirical statistics of a chosen data set. In this talk I will present some applications of this strategy to the spiking activity of real neurons recorded during experiments, either in the retina or in the cortex.
At first I will build the framework and explain how we can solve the inference problem by taking advantage of our stat. phys. knowledge of spin systems. Then I will discuss an application of this method to the prefrontal cortex of behaving rats and how it allows for identifying cell assemblies that undergo memory reply. I will then show how maximum entropy models account well for the system collective behaviour when the input stimuli have short-ranged correlations, but fail for inputs with long-ranged ones. This happens, for example, in the cortex during sleep, or in the retina for full-field visual stimuli. In the latter case, to solve this issue we apply a previously developed framework that, in addition to network effects, accounts for external stimuli that drive the system in time. In this case, the inferred model is not anymore a disordered Ising model, but it takes the form of a random field Ising model with short-ranged ferromagnetic couplings, and disordered magnetic fields.

1 April 2022, 1PM

Hervé Turlier (Collège de France)

Hydraulic and osmotic control of biological cavity formation and maintenance

Fluid-filled biological cavities, or lumens, are ubiquitous in tissues and embryos (1), and have been widely studied experimentally. But their collective dynamics and the control of their size has remained largely unexplored from a physical perspective. First, we focus on a particular type of lumens, which are located at the adhesive side of cells and can therefore interact directly through the intercellular space, as recently observed in the very first stages of mouse embryogenesis (2). Based on these experimental observations, we propose a generic model to describe the hydraulic and osmotic exchanges between lumens themselves, and with the surrounding cellular medium (3). Lumens are pressurized by a surface tension, which leads naturally to their coarsening into a single final cavity through hydraulic exchanges. With extensive numerical simulations and a mean-field theory we predict that such coarsening dynamics follows a robust scaling law, that barely depends on concentration heterogeneities between lumens. On the contrary, active osmotic pumping largely influences the collective dynamics by favoring lumen coalescence and by biasing the position of the final cavity. Then, we propose a generic model to describe the control of cavity size by osmotic gradients, starting from the classical pump-leak mechanism for a single cell, and that applies indifferently to basal or apical lumens. We predict that mechanics plays generally no role on the volume of a single cavity, that the presence of impermeants in the cavity is essential to ensure the existence of a stable state, and we study the impact of paracellular transport on lumen growth. Our theoretical work provides a generic theoretical framework for hydraulic and electro-osmotic control of biological cavity formation and maintenance, that shall find further applications in embryo and tissue morphogenesis.

1. Le Verge-Serandour, M., Turlier*, H. Blastocoel morphogenesis: a biophysics perspective. (2021) In revision.
2. Dumortier, J., Le Verge-Serandour, M., Tortorelli, A. F., Mielke, A., de Plater, L., Turlier*, H., & Maitre*, J.L. (2019) Hydraulic fracturing and active coarsening position the lumen of the mouse blastocyst. Science, 365, 465-468.
3. Le Verge-Serandour, M., Turlier*, H. A hydro-osmotic coarsening theory of biological cavity formation. (2021) PLoS Computational Biology, 17(9): e1009333. https://doi.org/10.1371/journal.pcbi.1009333
4. Le Verge-Serandour, M., Turlier*, H. Electro-osmotic control of lumen size. In preparation.

25 March 2022, 4PM, on zoom

William Gilpin (Harvard)

Chaos and predictability in statistical forecasting models

Chaotic systems are traditionally thought to be dynamical systems that are quantifiably difficulty to predict. However, the striking fractal geometry of strange attractors underscores the generative nature of chaos: like probability distributions, repeated measurements of chaotic systems produce arbitrarily-detailed information about the underlying attractor. Chaotic systems thus pose a unique challenge to modern statistical forecasting models, requiring representations that correctly encode their fractal geometry while capturing their underlying mathematical properties. I will describe my recent work on representing and forecasting chaotic systems. Using a collection of hundreds of known chaotic dynamical systems spanning fields such as astrophysics, climatology, and biochemistry, I show that chaoticity and empirical predictability are only weakly coupled. Instead, contemporary machine learning algorithms uncover structural properties of chaotic attractors, such as dominant orbits, hidden variables, and latent symmetries. I will show how tools from chaos can assist in general machine learning problems, such as time series classification, importance sampling, and symbolic regression.

18 March 2022, 1PM, room 306

 Victor Luria (Yale)

Novel genes enable protein structural innovation and function in the brain

How genuinely new protein-coding genes originate is a central question in biology. Long thought impossible to arise from non-coding sequence, novel genes arising de novo from genomic “junk” DNA or from long non-coding RNA were recently found in eukaryotic genomes. Novel genes are taxon-restricted and may encode structurally novel proteins with new protein domains. To understand how novel genes arise, we built a mathematical model based on gene and genome parameters and dynamic factors such as mutation. We combined phylostratigraphy and proteogenomics to identify novel genes in 25 eukaryotic genomes and evaluated their predicted biophysical properties. Compared to ancient proteins, novel proteins are shorter, more fragile, disordered and promiscuous, yet less prone to aggregate or to form toxic prions. We performed biophysical experiments comparing novel and ancient proteins, showed that novel genes function in vivo in zebrafish brains, and found novel genes are expressed in human brains at multiple ages. Genomic sequence turnover generates many novel genes encoding short proteins, of which some are maintained and encode proteins with distinct structural features and expressed in the brain. Thus, genomic variation continuously generates new protein structures and new functions.

11 March 2022, 1PM

Christian Vestergaard (Pasteur)

Identifying neural microcircuits in the brains of small animals

Behavior and decision-making are determined by physical processes taking place in the complex environment of the brain. Experimental techniques have reached the point where it is now possible to map the complete wiring diagram (the physical connectome of synaptic connections between neurons) of the brain of simple model organisms at the level of single synapses, and to manipulate individual neuron activity in freely moving animals and observe the resulting behavior. Together this lets us investigate how the structure of the connectome constrains an organism’s capability to process information and generate behavior.

I will discuss how we can combine knowledge of an animal’s connectome with large-scale behavioral experiments to link neural circuits to decision making and specific behavioral sequences. I will mainly focus on how to extract the statistical regularities (i.e., “motifs”) of a connectome of an animal. Relying on a restricted set of statistically regular circuit motifs, optimized for specific functions, may provide an animal with biologically advantageous inductive biases for efficient learning and help encode innate behaviors. Information theory furthermore tells us that the presence of statistically regularities would make the connectome compressible, and circuit motifs would thus provide a means to encode the neural wiring information in the limited storage space of the genome.

Identifying motifs in a connectome is a challenging inverse problem since we have access to only a single experimental realization (i.e., a single graph). To circumvent problems with classic null-model-based analysis linked to multiple testing and the ill-posed problem of defining a proper null model against which statistical significance is defined, we have developed methods combining hierarchies of microcanonical random graph null models and graph compression techniques. We applied our methods to uncover circuit motifs in different brain regions of adult and larval Drosophila as well as C elegans in different developmental stages. Our preliminary results show more compressible yet more complex brain structure in larger brains. By comparing typical circuit structures in different brains regions and animals, we may furthermore formulate hypotheses linking circuit structure to function that can be tested in behavioral experiments. I will finally discuss how we can build generative models of neural connectomes.

18 February 2022, 1PM

Andrea Cavagna (Sapienza – on zoom)

Collective behaviour is found in a startling variety of biological systems, from clusters of bacteria and colonies of cells, up to insect swarms, bird flocks, and vertebrate groups. A unifying ingredient is the presence of strong correlations: experiments in bird flocks, fish schools, mammal herds, insect swarms, bacterial clusters and proteins, have found that the correlation length is significantly larger than the microscopic scales. In the case of natural swarms of insects another key hallmark of statistical physics has been verified, namely dynamic scaling: spatial and temporal relaxation are entangled into one simple law, so that the relaxation time scales as a power of the correlation length, thus defining the dynamical critical exponent, z. Within statistical physics, strong correlations and scaling laws are the two stepping stones leading to the Renormalization Group (RG): when we coarse-grain short-scale fluctuations, the parameters of different models flow towards one common fixed point ruling their large-scale behaviour. RG fixed points therefore organize into few universality classes the macroscopic behaviour of strongly correlated systems, thus providing parameter-free predictions of the collective behaviour. Biology is vastly more complex than physics, but the widespread presence of strong correlations and the validity of scaling laws can hardly be considered a coincidence, and they rather call for an exploration of the correlation-scaling-RG path also in collective biological systems. However, to date there is yet no successful test of an RG prediction against experimental data on living systems. In this talk I will apply the renormalization group to the dynamics of natural swarms of insects. Swarms of midges in the field are strongly correlated systems, obeying dynamic scaling with an experimental exponent z~1.2, significantly smaller than the naive value z = 2 of equilibrium overdamped dynamics. I will show that this anomalous exponent can indeed be reproduced by an RG calculation, provided that off-equilibrium activity *and* inertial dynamics, are both taken into account; the theory gives z=1.3, a value closer to the experimental exponent than any previous theoretical determination. This successful result is a significant step towards testing the core idea of the RG even at the biological level, namely that integrating out the short-scale details of a strongly correlated system impacts on its large-scale behaviour by introducing anomalies in the dimensions of the physical quantities. In the light of this, it is fair to hope that the renormalization group, with its most fruitful consequence — universality — may have indeed an incisive impact also in biology.

11 February 2022, 1PM

Feng-Tching Tsai (PCC)

Mechanisms of curved membrane protein IRSp53 driven actin-rich membrane protrusion initiation and stabilization

4 February 2022, 1PM

Pierre Ronceray (Centuri – on Zoom)

What can we learn from the stochastic trajectories of biological systems?

14 January 2022, 3PM

Oliver Hobert (Columbia – on zoom)

Gene regulatory logic of neuronal cell type diversification and neuronal circuit assembly

The enormous diversity of cell types in any animal model system is defined by neuron type-specific gene batteries that endow distinct cells with distinct anatomical and functional properties. Based on my laboratory’s work in Caenorhabditis elegans as well as recent gene expression studies in vertebrates and flies, I propose that the diversity of neuronal cell types can be reduced to a simpler descriptor, the combinatorial expression of a specific class of transcription factors, encoded by homeobox genes. Functional studies in multiple animal model systems have corroborated the importance of homeobox genes in specifying neuronal identity and perhaps also neuronal circuit assembly. I propose that the preponderance of homeobox genes in neuronal identity control is a reflection of an evolutionary trajectory in which an ancestral neuron type was specified by an ancestral homeobox genes and that this functional linkage then duplicated and diversified to generate distinct cell types and neuronal assemblies in an evolving nervous system.

7 January 2022, 1PM

Laure Bally-Cuif (Pasteur)

Single cell and population mechanisms controlling adult neural stem cell maintenance

We are interested in understanding how single cell and population events combine to ensure the maintenance of neural stem cell (NSC) pools in the adult brain. We focus on the dorsal telencephalon (pallium), which hosts NSCs in all adult vertebrates. In teleost fish such as the zebrafish, the pallial NSC pool consists of a monolayer of tightly juxtaposed radial glial cells. NSCs are mostly quiescent, but can transiently activate (i.e. enter the cell cycle and divide) to divide and generate other NSCs and/or neurons. The NSC decision to activate, and the fate choices it makes at division, are two key events that condition NSC maintenance. These events are controlled at both the single-cell and the population levels, and we are taking quantitative and dynamic approaches to understand these processes in time and space.

For this, we developed an intra-vital imaging method to directly record, over weeks and with single cell resolution, the behavior of NSCs in their niche (> 1,000 cells per pallial hemisphere). With this method, we generated a 4D map of NSC activation and division events. Using spatial statistics and mathematical modeling in an NSC lattice, we showed that NSC activation events are spatiotemporally correlated by local and temporally delayed interactions that occur between brain germinal cells and generate self-propagating dynamics. We also observed that NSC apical size is highly predictive of NSC fate decisions at division, and are analyzing the mechanisms involved and their cell- and non-cell-autonomous impact. Together, this work will highlight how NSCs across the germinal sheet coordinate their state and fate decisions for the harmonious and long-lasting maintenance of the NSC pool.

17 December 2022, 1PM

Andrea Mazzolini (LPENS)

Generous resource sharing in animals: a reinforcement learning approach

Resource sharing outside the kinship bonds is rare. Besides humans, it occurs in chimpanzees, wild dogs and hyenas as well as in vampire bats. Resource sharing is an instance of animal cooperation, where an animal gives away part of the resources that it owns for the benefit of a recipient. Taking inspiration from blood-sharing in vampire bats, here we show the emergence of generosity in a Markov game, which couples the resource sharing between two players with the gathering task of that resource. At variance with the classical evolutionary models for cooperation, the optimal strategies of this game can be potentially learned by animals during their life-time. The players act greedily, that is, they try to individually maximize only their personal income. Nonetheless, the analytical solution of the model shows that three non trivial optimal behaviors emerge depending on conditions. Besides the obvious case when players are selfish in their choice of resource division, there are conditions under which both players are generous. Moreover, we also found a range of situations in which one selfish player exploits another generous individual, for the satisfaction of both players. Our results show that resource sharing is favored by three factors: a long time horizon over which the players try to optimize their own game, the similarity among players in their ability of performing the resource-gathering task, as well as by the availability of resources in the environment. These concurrent requirements lead to identifying necessary conditions for the emergence of generosity.

10 December 2021, 1pm

Julie Plastino (LPENS)

Forces drive basement membrane invasion in Caenorhabditis elegans

Invasion of cells through basement membrane (BM) extracellular matrix barriers is an important process during organ development and cancer metastasis. Much has been understood concerning the cell biology of invasion, but the role of cell mechanics in the invasive process is little studied. During invasion cells breach BM barriers with actin-rich protrusions. It remains unclear, however, if actin polymerization applies pushing forces to help break through BM, or if actin filaments play a passive role as scaffolding for targeting invasive machinery. Here using the developmental event of anchor cell (AC) invasion in Caenorhabditis elegans, we observe that the AC deforms the BM just prior to invasion, exerting forces in the tens of nN range. BM deformation is driven by actin polymerization nucleated by the Arp2/3 complex and its activators, while formins, crosslinkers and myosin motor activity are dispensable. Delays in invasion upon actin regulator loss are not caused by defects in AC polarity, trafficking or secretion, as appropriate markers are correctly localized in the AC even when actin is reduced and invasion is disrupted. In addition our preliminary results indicate that the AC nucleus is deformed during invasion, and the role played by the nucleus in AC invasion is currently under investigation. Overall cell and nuclear mechanics emerge from this study as important considerations in BM disruption by invading cells.

3 December 2021, 1PM

Xiaowen Chen (LPENS)

Inferring collective behavior and control principles in a small brain

In large neuronal networks, functions emerge through the collective behavior of many interconnected neurons. Recent technical development of whole brain imaging in Caenorhabditis elegans – a nematode with 302 neurons, allowed us to ask if such emergence reaches down to even the smallest brains. In the first part of this talk, I will discuss how we use the maximum entropy principle to construct pairwise probabilistic models for the collective activity of 50+ neurons in C. elegans. These models successfully predict higher order statistical structure in the data, the topological features of the structural connectome, and show signatures of collective behavior. In the second part, I will present two ways of how perturbing the inferred model of neuronal activity can shed light on the control principles in the brain, which in turn facilitates future perturbation experiments. Firstly, by ablating and clamping neurons, we discover that the worm brain is both robust against damages and efficient in transmitting information. Secondly, by examining the local information geometry of the model, we find that a few, “pivotal” neurons account for most of the system’s sensitivity, suggesting a sparse mechanism for control of the collective behavior. Finally, if time allows, I will briefly describe my current work at ENS on inferring statistical models with long memory kernel for collective dynamics in a group of social animals.

26 November 2021, 1pm

Giovanni Cappello (LIPhy, Grenoble)

The mechanical and biological role of extracellular matrix in multicellular aggregates

Biological tissues are composite materials, made of cells, extracellular matrix and interstitial fluid. As cells continuously proliferate, migrate, and secrete new extracellular matrix, biological tissues also build up an intrinsic stress during their growth. This complexity gives the tissues emerging rheological and biological properties, which cannot be merely traced back to those of the constitutive cells.

In this work, we characterized the mechanical and biological reaction of a model tissue in response to an external mechanical perturbation. In particular, we used multicellular aggregates as a proxy of avascular and homogeneous tissues, we compressed them via osmotic shocks and modeled the experimental results with an active poroelastic material.

We concluded that both the mechanical and the biological response are mainly determined by the presence of the extracellular matrix and by its mechanical state, as well as by the flows of the interstitial fluid.

19 November 2021, 1pm

Florence Élias (Matière et Systèmes Complexes)

Marine foams described using a model system: trapping bi-flagellated algae in a foam

A massive formation of stable sea foam is regularly observed on certain shores. These foams, of natural origin, are concomitant with a loss of phytoplankton biomass and biodiversity. Besides, liquid foams are known to act as filters for solid particles, due to the complex network of internal channels through which the liquid flows. We therefore hypothesise that a relevant part of the phytoplankton, advected in the foam during the foam formation, could be trapped in the foam.

Among phytoplanktonic organisms, many are flagellated and therefore motile. In this talk, I will present experiments performed in the laboratory on a model system to investigate the sedimentation of microswimmers in a liquid foam: the unicellular bi-flagellate alga Chlamydomonas reinhardtii (CR) was incorporated into a liquid foam stabilized with biocompatible proteins. Over time, the liquid contained in the foam flows downward by gravity drainage, advecting the solid particles suspended in the liquid, which then escape from the foam and reach the underlying liquid. We measured the dynamics of escape of CR cells from the foam, and compared the case of living and of dead cells. While the dead cells are totally advected by the liquid flow, as expected for passive solid particles of similar size, the living cells sediment much more slowly, and a significant amount remains trapped in the foam at long times. I will ultimately discuss the microscopic mechanisms that can lead to this trapping.

1 October 2021, 1pm

Joseph d’Alessandro (Institut Jacques Monod)

Local cell-cell interactions and large-scale coordination in moving cell groups

In living tissues, cells exhibit various degrees of mobility and coordination of their movements. These motions are powered by the self-propulsion of individual cells, which also interact with their neighbours and their environment. In particular, the physical contacts between cells are known to mediate the transmission of information, which is further processed to alter the dynamics – e.g. speed, direction – of their motion. With a physicist’s view, a cell colony could thus be viewed as a collection of polar active particles with interactions between their positions – forces – and their polarities – akin to spin interactions. Yet, the actual validity of this view and its detailed features still remain elusive.

In this talk, I will show how one can make use of micropatterned adhesive tracks to bridge the scales in that matter. Indeed, by following epithelial cells on such tracks we could characterise both the properties of collective motion and the cell-cell pair interactions. Including our observations into a lowest-order particle-based model allowed us to explain how local interactions that apparently favour disorder may not prevent large-scale order in particular situations. I will then discuss the possibilities offered by this set-up to a finer understanding of the cell-cell interactions.

24 September 2021, 1pm

Julien Berro (Yale University)

Force production and force sensing during clathrin-mediated endocytosis

Clathrin-mediated endocytosis (CME) consists of the formation of a vesicle out of a flat membrane in eukaryotes. When membrane tension and/or turgor pressure are high, actin dynamics is required to produce the forces required to invaginate the membrane and pinch it off into a vesicle. However, how the actin meshwork produces forces at the molecular level has remained elusive, because endocytic structures are intrinsically transient, out of equilibrium, and diffraction limited. In this seminar, I will present results from mathematical modeling and experiments in yeast demonstrating that actin polymerization alone cannot produce sufficient force to invaginate the plasma membrane. I will also present new force production mechanisms by the actin meshwork that are not exclusively based on polymerization, and are relevant to other subcellular processes involving actin and membranes.

21 May 2021, 1pm

Peter Swain (University of Edinburgh)

Using a push-pull system of repressors to match glucose transporters to extracellular glucose

A common cellular task is to match gene expression dynamically to a range of concentrations of a regulatory molecule. Studying glucose transport in budding yeast, we determine mechanistically how such matching occurs for seven hexose transporters. By combining time-lapse microscopy with mathematical modelling, we find that levels of transporters are history-dependent and are regulated by a push-pull system comprising two types of repressors. I will argue that matching is favoured by a rate-affinity trade-off and that the regulatory system allows yeast to import glucose rapidly enough to starve competitors.

7 May 2021, 4pm

Thierry Emonet (Yale University)

Information processing and decision making during chemical navigation

During chemical navigation organisms must detect molecules, process that information, and make decision (e.g. turn or not to turn), which affects the signal they will encounter next. I will report on recent experiments in our lab that examine different aspects of this process.
In the first part of the talk, I will discuss experiments that quantified the strategy used by walking fruit flies to navigate complex odor plumes, when the location and timing of odor packets are uncertain.
In the second part of the talk, I will use the simpler and better characterized E. coli chemotaxis system to quantify how information puts a bound on maximal navigational performance, and how efficient a bacterium is at using the information it gathers in order to navigate.

30 April 2021, 1pm

Renaud Poincloux (Institut de Pharmacologie et Biologie Structurale, Toulouse)

Nanoscale architecture and mechanics of macrophage podosomes

Podosomes are macrophage adhesion structures devoted to the proteolysis of the extracellular matrix that are constitutively formed by monocyte/macrophage-derived cells. We have shown that they are crucial for the capability of macrophages to perform macrophage protease-dependent mesenchymal migration in vivo. Therefore, podosomes are emerging as specific targets to limit the deleterious macrophage infiltration in tumors. Podosomes are composed of a core of F-actin surrounded by adhesion complexes. We have shown that podosomes are capable of applying protrusive forces onto the extracellular environment, thanks to the development of a method called Protrusion Force Microscopy, which consists in measuring by Atomic Force Microscopy the nanometer deformations produced by macrophage podosomes on a compliant formvar membrane. We estimated the protrusive force generated at podosomes and showed that it oscillates with a constant period and requires combined acto-myosin contraction and actin polymerization. We have demonstrated that talin, vinculin and paxillin sustain protrusion force generated at the podosome core, and related force generation to the molecular extension of talin within the podosome ring, indicating that the ring sustains mechanical tension. We are now investigating the organization and regulation of actin filaments in podosomes and the precise localization of actin cross-linkers. Next to the demonstration that the ring is a site of tension balancing protrusion at the core, we are now determining how actin filaments in the core are collectively organized to generate podosome protrusive forces. Using in situ cryo-electron tomography, we have recently unveiled how the nanoscale architecture of macrophage podosomes enables basal membrane protrusion. In particular, we could show that the sum of the actin polymerization forces at the membrane is not sufficient to explain podosome protrusive forces, but that it can be rather explained by the elastic energy that is accumulated inside podosome actin filaments.

9 April 2021, 4pm

Mikhail Tikhonov (Washington University in St. Louis)

A spin-glass model for the interplay of ecology, and evolution, and biochemistry

The spin glass is a paradigmatic example of a difficult optimization problem arising from simple pairwise interactions, and unsurprisingly recurs in many contexts. One such context is the study of evolution, where spin-glass-like models are extensively used to simulate the complex “fitness landscape” experienced by the organisms as they evolve and interact. I will describe a class of eco-evolutionary models focusing on the simplest case of the interaction between organisms and their environment, namely competition for limited resources. In this class of models, the glassy landscape acquires the meaning of specifying the (complex, idiosyncratic) biochemistry. Focusing on the ecosystem response to external perturbations, I will argue that the spin-glass intuition allows us to expect several parameter regimes with distinct behaviors. In particular, the intuitive regime (“what the community is doing depends on the species it contains”) is flanked by two regimes where ecosystem response is predictable: one where this predictability emerges in spite of biochemical details, and another where it arises because of them.

2 April 2021, 1pm

Pauline Durand-Smet (Laboratoire MSC)

Plant cells under confinement: impact of geometrical cues on the cytoskeleton organization

Specific cell and tissue form is essential to support many biological functions of living organisms. During development, the creation of different shapes fundamentally requires the integration of genetic, biochemical and physical inputs.

In plants, it is well established that the cytoskeletal microtubule network plays a key role in the morphogenesis of the plant cell wall by guiding the organisation of new cell wall material. The cell cytoskeleton is thus a major determinant of plant cell shape. What is less clear is how cell geometry in turn influences the cytoskeletal organization.

To explore the relative contribution of geometry to the final organization of actin and microtubule cytoskeletons in single plant cells, we developed an experimental approach combining confinement of plant cells into micro-niches of controlled geometry with imaging of the cytoskeleton. A model of self-organizing microtubules in 3D predicts that severing of microtubules is an important parameter controlling the anisotropy of the microtubules network. We experimentally confirmed the model predictions by analysis of the response to shape change in plant cells with altered microtubule severing dynamics. This work is a first step towards assessing quantitatively how cell geometry controls cytoskeletal organization in plants.

26 March 2021, 1pm

Annafrancesca Rigato (Institut Fresnel, Marseille)

Growth-associated constraints and mechanical instabilities during epidermal morphogenesis in Drosophila

Cells in growing tissues are continuously subjected to and exerting active and passive forces. In fact, growth rate variations or changes in the spatial orientation of growth produce stress. To release the produced stress, the balance between growth and cell division is fundamental. Here we investigate the consequences on cell morphology when this balance is not present. A perfect model system is Drosophila abdominal epidermis, a continuous cell layer formed of two cell types: larval epithelial cells (LECs), and adult epidermis precursors (histoblasts). Histoblasts are organized in nests surrounded by LECs. Interestingly, histoblasts grow without dividing throughout the whole larval life. At the same time, LECs grow at a faster rate than histoblasts. Such imbalance causes an amazing morphological change in histoblasts, with cell junctions changing from straight to deeply folded. Such transition is reminiscent of buckling instabilities. We hypothesize that growing LECs compress histoblasts, causing junctional buckling. Live imaging observations of larvae in which we genetically altered cell cycle or growth of either cell type support this idea. Hence, we show that altering the balance between cell growth and divisions leads to unexpected morphological and mechanical regimes.

19 March 2021, 1pm

Alexandre Kabla (Cambridge University)

Rheology of cells and tissues

Cell migration and cell mechanics play a crucial role in a number of key biological processes, such as embryo development or cancer metastasis. It is therefore important to characterise the material properties of cells and tissues and the way they mechanically interact with their environment.

In this talk, I will present recent work we did to address these questions at the single-cell and tissue level. In particular, experimental studies on the mechanical response of in-vitro epithelial monolayers show that the material exhibits a strong time-dependent response over a broad range of timescales. In this situation, it is challenging to capture the response of the system with a few parameters without losing some of the material’s characteristic features. I will show that rheological models based on fractional calculus are effective empirical tools to summarize such complex data and highlight similarities across a broad range of systems.

5 March 2021, 1pm

Sigolène Meilhac (Institut Imagine – Institut Pasteur)

Looping of a tube : an asymmetric process to establish the double blood circulation in the heart

Left-right partitioning of the heart underlies the double blood circulation : pulmonary circulation in the right heart, systemic circulation in the left heart. Asymmetric heart morphogenesis is initiated in the embryo, when the tubular primordium acquires a rightward helical shape during the process of heart looping. This shape change determines cardiac chamber alignment and thus heart partitioning. Impairment of the left-right patterning of mesoderm precursor cells leads to the severe heterotaxy syndrome, including complex cardiac malformations and failure to establish the double blood circulation. Whereas the molecular cascade breaking the symmetry has been well characterised, how asymmetric signalling is sensed by precursor cells to generate asymmetric organogenesis has remained largely unknown.

Heart looping had been previously analysed as a binary parameter (left/right) of the helix direction, taken as a readout of the symmetry-breaking event. However, this is too reductionist to describe a 3D shape. We have developed a novel framework to quantify and simulate the fine heart loop shape in the mouse, as a readout of asymmetric morphogenesis. This has led us to propose a model of heart looping centred on the buckling of the tube growing between fixed poles. We have re-analysed the role of the major left determinant Nodal in this context. We have traced the contribution of Nodal expressing cells to regions of the heart tube poles. By manipulating Nodal signalling in time and space, we show that it is not involved in the buckling, but that it biases it. Nodal is required transiently in heart precursors, to amplify and coordinate opposed asymmetries at the heart tube poles and thus generate a robust helical shape.

Ongoing work aims at further dissecting the dynamics of left-right patterning, beyond Nodal signaling. Thus, we provide novel insight into the mechanisms of asymmetric heart morphogenesis relevant to complex congenital heart defects.

12 February 2021, 1pm

Marco Polin (University of Warwick)

Dial-a-Plume: Localised Photo-Bio-Convection on Demand

Microorganismal motility is often characterised by complex responses to environmental physico-chemical stimuli. Although the biological basis of these responses is often not well understood, their exploitation already promises novel avenues to directly control the motion of living active matter at both the individual and collective level. Here we leverage the phototactic ability of the model microalga Chlamydomonas reinhardtii to precisely control the timing and position of localised cell photo-accumulation, leading to the controlled development of isolated bioconvective plumes. This novel form of photo-bio-convection allows a precise, fast and reconfigurable control of the spatio-temporal dynamics of the instability and the ensuing global recirculation, which can be activated and stopped in real time. A simple continuum model accounts for the phototactic response of the suspension and demonstrates how the spatio-temporal dynamics of the illumination field can be used as a simple external switch to produce efficient bio-mixing.

5 February 2021, 1pm

Venkatesh Murthy (Harvard University)

Sensing the chemical world and making sense of it

The olfactory system senses chemicals in the environment to guide behavior in animals. Fluctuating mixtures of chemicals, transported in fluid environments, are detected by an array of olfactory sensors and parsed by neural circuits to recognize odor objects, which then inform behavioral decisions. Some key questions for chemical sensing systems include how they can detect relevant molecules that are embedded in a sea of distractors, and how they use sparse intermittent stimuli to navigate. We work with theorists to frame these questions quantitatively and use experiments in mice to address them. I will present some examples from our recent and ongoing work.

29 January 2021, 1pm

Michael Rera (CRI)

Ageing: what the Smurf?

Ageing is a complex process, broadly affecting living organisms in extremely various ways, ranging from the negligible senescence of some trees and arthropods, through the sudden post-reproduction death of salmon and desert organisms, to our human ageing with what has long been described as a time dependent exponential increase of the mortality risk.

Drosophila melanogaster and Mus musculus, the fruit fly and mouse, are two broadly used model organisms for studying ageing mostly because they show an apparent exponential increase of their mortality risk, same as
in humans. Using the first model system, about 10 years ago I identified a physiological marker preceding death – fruit flies would turn blue when fed a non-toxic food dye. This simple visual cue allows us to identify individuals at a different stage of their life amongst a cohort of individuals and study aging and progress towards death.

We use this tool to question our knowledge regarding ageing, showed the broad conservation of this end-of-life phenotype in different drosophila subspecies, nematodes, zebrafish and killifish as well as develop a
novel mathematical model for ageing allowing the experimental quantification of various “ageing parameters”.

15 January 2021, 1pm

Claire Wyart (ICM)

Tasting from within in the vertebrate spinal cord? A novel sensory interface controlling development, posture and innate immunity

The cerebrospinal fluid (CSF) is a complex solution circulating around the brain and spinal cord. Multiple evidence indicate that the activity and the development of the nervous system can be influenced by the content and flow of the CSF. Yet, it is not known how neuronal activity changes as a function of the physico-chemical properties of the CSF.

We identify throughout vertebrate species, ciliated neurons at the interface between the CSF and the nervous system that are in ideal position to sense CSF cues, to relay information to local networks and to regulate CSF content by secretion.

By combining electrophysiology, optogenetics and calcium imaging in vivo in larval zebrafish, we demonstrate that neurons contacting the CSF detect local bending of the spinal cord and in turn feedback GABAergic inhibition to multiple interneurons driving locomotion and posture in the spinal cord and hindbrain. Such inhibitory feedback modulates neuronal target in a state-dependent manner, depending on the fact that the animal is at rest or actively moving at a define speed.

Behavioral analysis of animals deprived of this sensory pathway reveals differential effects on speed for slow and fast regimes, as well as impairments in the control of posture during active locomotion. Our work first sheds light on the cellular and network mechanisms enabling sensorimotor integration of mechanical and chemical cues from the CSF onto motor circuits controlling locomotion and posture in the spinal cord.

We will present converging evidence that this interoceptive sensory pathway is involved in guiding a straight body axis throughout life, as well as innate immunity via the detection and combat of pathogens intruding the CSF.

17 December 2020, 11am

Jonathan Fouchard (IBPS)

Curling and buckling of epithelial monolayers, some experimental insights

Epithelial monolayers are soft thin sheets which shape the body and organs of many multi-cellular organisms. Competition between stretching and bending characterizes shape transitions of thin elastic sheets. While stretching dominates the mechanical response in tension, bending dominates in compression after an abrupt buckling transition. As opposed to inert materials, the morphogenesis of epithelial monolayers is largely influenced by endogenous ATP-dependent forces, which generate in-plane tension and active torques due to the polarization of myosin II molecular motors. Here, we address the dialog between in-plane and out-of-plane forces in vitro, in epithelial monolayers devoid of substrate and suspended between parallel plates. I will show that curls of high curvature form spontaneously at the free edge of these monolayers, which we use to estimate the active torques and the bending modulus of the tissue. I will also show that these tissues buckle in response to compression in a time-dependent and myosin II-dependent manner.

3 December 2020, 11am

Ramiro Godoy-Diana (PMMH, ESPCI)

The burst-and-coast regime in fish swimming

Body and caudal fin undulations are a widespread locomotion strategy in fish, and their swimming kinematics is usually described by a characteristic frequency and amplitude of the tail-beat oscillation. In some cases, fish use intermittent gaits, where a single frequency is not enough to fully describe their kinematics. Energy efficiency arguments have been invoked in the literature to explain this so-called burst-and-coast regime but well controlled experimental data are scarce. I will discuss our recent results on an experiment with burst-and-coast swimmers and a numerical model based on the observations showing that the observed burst-and-coast regime can be understood as obeying a minimization of cost of transport.

Ref: Li et al. (2020) Burst-and-coast swimmers optimize gait by adapting unique intrinsic cycle arXiv:2002.09176

26 November 2020, 11am

António Carlos Costa (LPENS)

Physics of Behavior Across Scales

Behavior exhibits multiple spatio-temporal scales: from fast control of the body posture by neural activity, to the slower neuromodulation of exploratory strategies all the way to ageing. How can we bridge these scales? We leverage the interplay between microscopic variability and macroscopic order, fundamental to statistics physics, to extract predictive coarse-grained dynamics from data. We reconstruct the state space as a sequence of measurements, partition the resulting space as to maximize entropy, and choose the sequence length to maximize predictive information. We approximate the dynamics of densities in the partitioned state space through transfer operators, providing an accurate statistical model on multiple scales. The operator spectrum provides a principled means of timescale separation and coarse-graining. We illustrate our approach using high-resolution posture measurements of the nematode C. elegans, and show that long-time changes in exploratory strategies (10’s of minutes) can be extracted from fine scale posture samples (10’s of milliseconds).

19 November 2020, 11am

Efe Ilker (Institut Curie)

Disentangling the effect of metabolic costs in selection

Metabolism and evolution are closely connected: if a mutation incurs extra energetic costs for an organism, there is a baseline selective disadvantage that may or may not be compensated for by other adaptive effects. A long-standing, but to date unproven, hypothesis [1] is that this disadvantage is equal to the fractional cost relative to the total resting metabolic expenditure. I will present our recent work [2] which validates this hypothesis from physical principles through a general growth model and show that it holds to excellent approximation for experimental parameters drawn from a wide range of species. We will also overview the significance of this contribution from metabolic expenditures in the course of evolution, by considering the elements of population dynamics. As an example, I will demonstrate that a close inspection on the thermodynamic costs, noise suppression performance and selection shows intriguing aspects about the evolution of microRNA regulated gene networks which play a critical role by controlling developmental processes of complex organisms and related diseases.

[1] L. E. Orgel and F. H. Crick, Nature 284, 604 (1980)

[2] E. Ilker and M. Hinczewski, Phys. Rev. Lett. 122, 238101 (2019)

5 November 2020, 4pm

Paul François (McGill University)

Phenotypic models of immune response : from single cells to cytokine code

T cells have to make life-or-death immune decisions based on sensitive and specific interactions with self and/or foreign peptides. On a longer time scale, T cells have to coordinate with one another to trigger a properly balanced immune response. Modeling this process is a daunting task because of the multiplicity of molecular and cellular interactions. I will show how phenotypic models can be built to describe those processes in a simple and predictive way. At the single cell level, we propose an « adaptive kinetic proofreading » model, detecting ligand strength irrespective of ligand concentrations. This model predicts experimental features such as ligand antagonism, which, interestingly, can be related to adversarial problems in artificial neural networks. At the cell population level, I will introduce a data driven approach to build phenomenological models of collective response, suggesting the existence of a simple cytokine code.

15 October 2020, 11am

Georges Debrégeas (Laboratoire Jean Perrin)

Persistent activities in the brain: from behavior to data-driven network models

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.

8 October 2020, 11am

David Lacoste (Physico-Chimie Théorique, ESPCI)

Inequalities constraining fluctuations and fitness on lineage trees

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.

[1] Linking lineage and population observables in biological branching processes, R. Garcia-Garcia, A. Genthon and D. Lacoste, Phys. Rev. E, 042413 (2019).

[2] Fluctuation relations and fitness landscapes of growing cell populations, Scientific Reports, 10, 11889 (2020).