laboratoire de physique statistique
laboratoire de physique statistique


Fluctuating fitness shapes the clone-size distribution of immune repertoires - Desponds, Jonathan and Mora, Thierry and Walczak, Aleksandra M.

Abstract : The adaptive immune system relies on the diversity of receptors expressed on the surface of B-and T cells to protect the organism from a vast amount of pathogenic threats. The proliferation and degradation dynamics of different cell types (B cells, T cells, naive, memory) is governed by a variety of antigenic and environmental signals, yet the observed clone sizes follow a universal power-law distribution. Guided by this reproducibility we propose effective models of somatic evolution where cell fate depends on an effective fitness. This fitness is determined by growth factors acting either on clones of cells with the same receptor responding to specific antigens, or directly on single cells with no regard for clones. We identify fluctuations in the fitness acting specifically on clones as the essential ingredient leading to the observed distributions. Combining our models with experiments, we characterize the scale of fluctuations in antigenic environments and we provide tools to identify the relevant growth signals in different tissues and organisms. Our results generalize to any evolving population in a fluctuating environment.
Different Buckling Regimes in Direct Electrospinning: A Comparative Approach to Rope Buckling - Shariatpanahi, S. P. and Etesami, Z. and Zad, A. Iraji and Bonn, D. and Ejtehadi, R.

Abstract : Understanding the dynamics of direct electrospinning is the key to control fiber morphologies that are critical for the development of new electrospinning methods and novel materials. Here, we propose the theory for direct electrospinning based on theories for (liquid) ``rope coiling'' and experimentally test it. For the experiments, the buckling of microscale liquid ropes formed from polymer solutions is studied systematically using three different electrospinning setups and for different polymer concentrations. We show that different buckling regimes exist, whose dynamics are governed by an interplay of electrical, inertial, and viscous forces, and that three different buckling regimes emerge depending on the dominant forces. For low polymer concentrations, we observe an inertial regime similar to that observed for viscous liquid ropes at high velocities. By increasing the polymer concentration and consequently decreasing the rope velocity, we enter an inertial-electrical regime for which discontinuities occur in the buckling frequency as a function of applied voltage. These observations can be accounted for quantitatively by replacing the gravitational forces in viscous rope coiling theory with the electrical forces of our electrospinning experiment. Finally, for the highest polymer concentration, we observe a purely electrical regime for a solidified rope; this regime is well described by ``elastic'' rope coiling theory. (c) 2015 Wiley Periodicals, Inc.
Snapshot of sequential SNARE assembling states between membranes shows that N-terminal transient assembly initializes fusion - Wang, Yong Jian and Li, Feng and Rodriguez, Nicolas and Lafosse, Xavier and Gourier, Christine and Perez, Eric and Pincet, Frederic

Abstract : Many prominent biological processes are driven by protein assembling between membranes. Understanding the mechanisms then entails determining the assembling pathway of the involved proteins. Because the intermediates are by nature transient and located in the intermembrane space, this determination is generally a very difficult, not to say intractable, problem. Here, by designing a setup with sphere/plane geometry, we have been able to freeze one transient state in which the N-terminal domains of SNARE proteins are assembled. A single camera frame is sufficient to obtain the complete probability of this state with the transmembrane distance. We show that it forms when membranes are 20 nm apart and stabilizes by further assembling of the SNAREs at 8 nm. This setup that fixes the intermembrane distance, and thereby the transient states, while optically probing the level of molecular assembly by Forster resonance energy transfer (FRET) can be used to characterize any other transient transmembrane complexes.
Electrical bending instability in electrospinning visco-elastic solutions - Shariatpanahi, S. Peyman and Bonn, Daniel and Ejtehadi, Mohammad R. and Zad, Azam Iraji

Abstract : The electrical bending instability in charged liquid jets is the phenomenon determining the process of electrospinning. A model of this phenomenon is lacking however, mostly due to the complicated interplay between the viscosity and elasticity of the solution. To investigate the bending instability, we performed electrospinning experiments with a solution of polyethylene oxide in water/ethanol. Using a fast camera and sensitive multimeter, we deduced an experimental dispersion relation describing the helix pitch length as a function of surface charge. To understand this relation, we developed a theoretical model for the instability for a wide range of visco-elastic materials, from conducting to nonconducting. The theoretical dispersion relation shows good agreement with the experimental results. Using the new model, we find that the elastic tension in the visco-elastic threads plays an important role in triggering the instability. (c) 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2016, 54, 1036-1042
Structure and Permeability of Porous Silicon Investigated by Self-Diffusion NMR Measurements of Ethanol and Heptane - Puibasset, J. and Porion, P. and Grosman, A. and Rolley, E.

Abstract : The adsorption and phase transitions of confined fluids in nanoporous materials have been studied intensely because of both their fundamental interest and their crucial role in many technologies. Questions relating to the influence of the confinement of fluids, and the disorder or elastic deformation of porous solids on the liquid-gas phase transition are still under debate. Model systems are needed to understand the adsorption phenomenon. In this context, Porous Silicon (PoSi), which is a single crystal obtained by etching a (100) silicon wafer is an excellent candidate. Indeed, it consists of non-connected tubular pores running parallel to the [100] axis perpendicular to the wafer surface, with transverse sections with a polygonal shape of nanometric size whose areas are widely distributed. Once detached from the wafer, free PoSi membranes can be considered a nanoscale disordered honeycomb. Adsorption/desorption experiments have been performed to characterize the structure: they have shown that evaporation occurs collectively, an intriguing observation generally associated with a disordered pore structure with many interconnections through narrow necks. The characterization of fluid mobility inside the pores should give complementary information about the pore structure and topology. This paper focuses on the dynamics of a fluid confined inside the structure of porous silicon, and in particular the self-diffusion measurements (pulsed field gradient spin echo Nuclear Magnetic Resonance (NMR)). The results show a strong anisotropy of the self diffusion tensor, as expected in this highly anisotropic structure. However, a non-zero self-diffusion in the directions perpendicular to the pore axis is observed. In order to interpret these puzzling results, molecular and Brownian dynamics calculations are underway.
Diversity of immune strategies explained by adaptation to pathogen statistics - Mayer, Andreas and Mora, Thierry and Rivoire, Olivier and Walczak, Aleksandra M.

Abstract : Biological organisms have evolved a wide range of immune mechanisms to defend themselves against pathogens. Beyond molecular details, these mechanisms differ in how protection is acquired, processed, and passed on to subsequent generations-differences that may be essential to long-term survival. Here, we introduce a mathematical framework to compare the long-term adaptation of populations as a function of the pathogen dynamics that they experience and of the immune strategy that they adopt. We find that the two key determinants of an optimal immune strategy are the frequency and the characteristic timescale of the pathogens. Depending on these two parameters, our framework identifies distinct modes of immunity, including adaptive, innate, bet-hedging, and CRISPR-like immunities, which recapitulate the diversity of natural immune systems.
Kinetic barriers to SNAREpin assembly in the regulation of membrane docking/priming and fusion - Li, Feng and Tiwari, Neeraj and Rothman, James E. and Pincet, Frederic

Abstract : Neurotransmission is achieved by soluble NSF attachment protein receptor (SNARE)-driven fusion of readily releasable vesicles that are docked and primed at the presynaptic plasma membrane. After neurotransmission, the readily releasable pool of vesicles must be refilled in less than 100 ms for subsequent release. Here we show that the initial association of SNARE complexes, SNAREpins, is far too slow to support this rapid refilling owing to an inherently high activation energy barrier. Our data suggest that acceleration of this process, i.e., lowering of the barrier, is physiologically necessary and can be achieved by molecular factors. Furthermore, under zero force, a low second energy barrier transiently traps SNAREpins in a half-zippered state similar to the partial assembly that engages calcium-sensitive regulatory machinery. This result suggests that the barrier must be actively raised in vivo to generate a sufficient pause in the zippering process for the regulators to set in place. We show that the heights of the activation energy barriers can be selectively changed by molecular factors. Thus, it is possible to modify, both in vitro and in vivo, the lifespan of each metastable state. This controllability provides a simple model in which vesicle docking/priming, an intrinsically slow process, can be substantially accelerated. It also explains how the machinery that regulates vesicle fusion can be set in place while SNAREpins are trapped in a half-zippered state.
Surfactant adsorption kinetics in microfluidics - Riechers, Birte and Maes, Florine and Akoury, Elias and Semin, Benoit and Gruner, Philipp and Baret, Jean-Christophe

Abstract : Emulsions are metastable dispersions. Their lifetimes are directly related to the dynamics of surfactants. We design a microfluidic method to measure the kinetics of adsorption of surfactants to the droplet interface, a key process involved in foaming, emulsification, and droplet coarsening. The method is based on the pH decay in the droplet as a direct measurement of the adsorption of a carboxylic acid surfactant to the interface. From the kinetic measurement of the bulk equilibration of the pH, we fully determine the adsorption process of the surfactant. The small droplet size and the convection during the droplet flow ensure that the transport of surfactant through the bulk is not limiting the kinetics of adsorption. To validate our measurements, we show that the adsorption process determines the timescale required to stabilize droplets against coalescence, and we show that the interface should be covered at more than 90\% to prevent coalescence. We therefore quantitatively link the process of adsorption/desorption, the stabilization of emulsions, and the kinetics of solute partitioning-here through ion exchange-unraveling the timescales governing these processes. Our method can be further generalized to other surfactants, including nonionic surfactants, by making use of fluorophore-surfactant interactions.
Neural assemblies revealed by inferred connectivity-based models of prefrontal cortex recordings - Tavoni, G. and Cocco, S. and Monasson, R.

Abstract : We present two graphical model-based approaches to analyse the distribution of neural activities in the prefrontal cortex of behaving rats. The first method aims at identifying cell assemblies, groups of synchronously activating neurons possibly representing the units of neural coding and memory. A graphical (Ising) model distribution of snapshots of the neural activities, with an effective connectivity matrix reproducing the correlation statistics, is inferred from multi-electrode recordings, and then simulated in the presence of a virtual external drive, favoring high activity (multi-neuron) configurations. As the drive increases groups of neurons may activate together, and reveal the existence of cell assemblies. The identified groups are then showed to strongly coactivate in the neural spiking data and to be highly specific of the inferred connectivity network, which offers a sparse representation of the correlation pattern across neural cells. The second method relies on the inference of a Generalized Linear Model, in which spiking events are integrated over time by neurons through an effective connectivity matrix. The functional connectivity matrices inferred with the two approaches are compared. Sampling of the inferred GLM distribution allows us to study the spatio-temporal patterns of activation of neurons within the identified cell assemblies, particularly their activation order: the prevalence of one order with respect to the others is weak and reflects the neuron average firing rates and the strength of the largest effective connections. Other properties of the identified cell assemblies (spatial distribution of coactivation events and firing rates of coactivating neurons) are discussed.
Stability, folding dynamics, and long-range conformational transition of the synaptic t-SNARE complex - Zhang, Xinming and Rebane, Aleksander A. and Ma, Lu and Li, Feng and Jiao, Junyi and Qu, Hong and Pincet, Frederic and Rothman, James E. and Zhang, Yongli

Abstract : Synaptic soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) couple their stepwise folding to fusion of synaptic vesicles with plasma membranes. In this process, three SNAREs assemble into a stable four-helix bundle. Arguably, the first and rate-limiting step of SNARE assembly is the formation of an activated binary target (t)-SNARE complex on the target plasma membrane, which then zippers with the vesicle (v)-SNARE on the vesicle to drive membrane fusion. However, the t-SNARE complex readily misfolds, and its structure, stability, and dynamics are elusive. Using single-molecule force spectroscopy, we modeled the synaptic t-SNARE complex as a parallel three-helix bundle with a small frayed C terminus. The helical bundle sequentially folded in an N-terminal domain (NTD) and a C-terminal domain (CTD) separated by a central ionic layer, with total unfolding energy of similar to 17 k(B)T, where kB is the Boltzmann constant and T is 300 K. Peptide binding to the CTD activated the t-SNARE complex to initiate NTD zippering with the v-SNARE, a mechanism likely shared by the mammalian uncoordinated-18-1 protein (Munc18-1). The NTD zippering then dramatically stabilized the CTD, facilitating further SNARE zippering. The subtle bidirectional t-SNARE conformational switch was mediated by the ionic layer. Thus, the t-SNARE complex acted as a switch to enable fast and controlled SNARE zippering required for synaptic vesicle fusion and neurotransmission.
Optimal permeability of aquaporins: a question of shape? - Gravelle, Simon and Joly, Laurent and Detcheverry, Francois and Ybert, Christophe and Cottin-Bizonne, Cecile and Bocquet, Lyderic
M S-MEDECINE SCIENCES 31174-179 (2015)

Abstract : Aquaporins are transmembrane proteins, ubiquitous in the human body. Inserted into the cell membranes, they play an important role in filtration, absorption and secretion of fluids. However, the excellent compromise between selectivity and permeability of aquaporins remains elusive. In this review, we focus on the hourglass shape of aquaporins, and we investigate its influence on water permeability, using numerical calculations and a simple theoretical model. We show that there is an optimum opening angle that maximizes the hydrodynamic permeability, and whose value is close to the angles observed in aquaporins.
Inferring epigenetic dynamics from kin correlations - Hormoz, Sahand and Desprat, Nicolas and Shraiman, Boris I.

Abstract : Populations of isogenic embryonic stem cells or clonal bacteria often exhibit extensive phenotypic heterogeneity that arises from intrinsic stochastic dynamics of cells. The phenotypic state of a cell can be transmitted epigenetically in cell division, leading to correlations in the states of cells related by descent. The extent of these correlations is determined by the rates of transitions between the phenotypic states. Therefore, a snapshot of the phenotypes of a collection of cells with known genealogical structure contains information on phenotypic dynamics. Here, we use a model of phenotypic dynamics on a genealogical tree to define an inference method that allows extraction of an approximate probabilistic description of the dynamics from observed phenotype correlations as a function of the degree of kinship. The approach is tested and validated on the example of Pyoverdine dynamics in Pseudomonas aeruginosa colonies. Interestingly, we find that correlations among pairs and triples of distant relatives have a simple but nontrivial structure indicating that observed phenotypic dynamics on the genealogical tree is approximately conformal-a symmetry characteristic of critical behavior in physical systems. The proposed inference method is sufficiently general to be applied in any system where lineage information is available.
Neuronal Morphology Generates High-Frequency Firing Resonance - Ostojic, Srdjan and Szapiro, German and Schwartz, Eric and Barbour, Boris and Brunel, Nicolas and Hakim, Vincent
JOURNAL OF NEUROSCIENCE 357056-7068 (2015)

Abstract : The attenuation of neuronal voltage responses to high-frequency current inputs by the membrane capacitance is believed to limit single-cell bandwidth. However, neuronal populations subject to stochastic fluctuations can follow inputs beyond this limit. We investigated this apparent paradox theoretically and experimentally using Purkinje cells in the cerebellum, a motor structure that benefits from rapid information transfer. We analyzed the modulation of firing in response to the somatic injection of sinusoidal currents. Computational modeling suggested that, instead of decreasing with frequency, modulation amplitude can increase up to high frequencies because of cellular morphology. Electrophysiological measurements in adult rat slices confirmed this prediction and displayed a marked resonance at 200 Hz. We elucidated the underlying mechanism, showing that the two-compartment morphology of the Purkinje cell, interacting with a simple spiking mechanism and dendritic fluctuations, is sufficient to create high-frequency signal amplification. This mechanism, which we term morphology-induced resonance, is selective for somatic inputs, which in the Purkinje cell are exclusively inhibitory. The resonance sensitizes Purkinje cells in the frequency range of population oscillations observed in vivo.
How a well-adapted immune system is organized - Mayer, Andreas and Balasubramanian, Vijay and Mora, Thierry and Walczak, Aleksandra M.

Abstract : The repertoire of lymphocyte receptors in the adaptive immune system protects organisms from diverse pathogens. A well-adapted repertoire should be tuned to the pathogenic environment to reduce the cost of infections. We develop a general framework for predicting the optimal repertoire that minimizes the cost of infections contracted from a given distribution of pathogens. The theory predicts that the immune system will have more receptors for rare antigens than expected from the frequency of encounters; individuals exposed to the same infections will have sparse repertoires that are largely different, but nevertheless exploit cross-reactivity to provide the same coverage of antigens; and the optimal repertoires can be reached via the dynamics of competitive binding of antigens by receptors and selective amplification of stimulated receptors. Our results follow from a tension between the statistics of pathogen detection, which favor a broader receptor distribution, and the effects of cross-reactivity, which tend to concentrate the optimal repertoire onto a few highly abundant clones. Our predictions can be tested in high-throughput surveys of receptor and pathogen diversity.
Inferring processes underlying B-cell repertoire diversity - Elhanati, Yuval and Sethna, Zachary and Marcou, Quentin and Callan, Jr., Curtis G. and Mora, Thierry and Walczak, Aleksandra M.

Abstract : We quantify the VDJ recombination and somatic hypermutation processes in human B cells using probabilistic inference methods on high-throughput DNA sequence repertoires of human B-cell receptor heavy chains. Our analysis captures the statistical properties of the naive repertoire, first after its initial generation via VDJ recombination and then after selection for functionality. We also infer statistical properties of the somatic hypermutation machinery (exclusive of subsequent effects of selection). Our main results are the following: the B-cell repertoire is substantially more diverse than T-cell repertoires, owing to longer junctional insertions; sequences that pass initial selection are distinguished by having a higher probability of being generated in a VDJ recombination event; somatic hypermutations have a non-uniform distribution along the V gene that is well explained by an independent site model for the sequence context around the hypermutation site.
Thermodynamics and signatures of criticality in a network of neurons - Tkacik, Gasper and Mora, Thierry and Marre, Olivier and Amodei, Dario and Palmer, Stephanie E. and Berry, II, Michael J. and Bialek, William

Abstract : The activity of a neural network is defined by patterns of spiking and silence from the individual neurons. Because spikes are (relatively) sparse, patterns of activity with increasing numbers of spikes are less probable, but, with more spikes, the number of possible patterns increases. This tradeoff between probability and numerosity is mathematically equivalent to the relationship between entropy and energy in statistical physics. We construct this relationship for populations of up to N = 160 neurons in a small patch of the vertebrate retina, using a combination of direct and model-based analyses of experiments on the response of this network to naturalistic movies. We see signs of a thermodynamic limit, where the entropy per neuron approaches a smooth function of the energy per neuron as N increases. The form of this function corresponds to the distribution of activity being poised near an unusual kind of critical point. We suggest further tests of criticality, and give a brief discussion of its functional significance.
Spontaneous Flows in Suspensions of Active Cyclic Swimmers - Brotto, Tommaso and Bartolo, Denis and Saintillan, David

Abstract : Many swimming cells rely on periodic deformations to achieve locomotion. We introduce in this work a theoretical model and numerical simulations in order to elucidate the impact of these cyclic strokes on the emergence of mesoscale structures and collective motion in swimmer suspensions. The model extends previous kinetic theories for populations of identical swimmers to the case of self-propelled particles undergoing transitions between pusher and puller states, and is applied to quantify how the unsteadiness of the hydrodynamic velocity field, to which each swimmer population contributes, affects the onset and characteristics of spontaneous flows. A linear stability analysis reveals that the sign of the population-averaged dipole determines the stability of the uniform isotropic state, with suspensions dominated by pushers being subject to growing nematic bend fluctuations. Stochastic transitions, however, are also seen to provide an additional damping mechanism. To investigate the population dynamics above the instability threshold, we also perform direct particle simulations based on a slender-body model, where the growth or decay of the active power generated by the swimmers is found to be a robust measure of the structural and dynamical instability.
Distinguishing the immunostimulatory properties of noncoding RNAs expressed in cancer cells - Tanne, Antoine and Muniz, Luciana R. and Puzio-Kuter, Anna and Leonova, Katerina I. and Gudkov, Andrei V. and Ting, David T. and Monasson, Remi and Cocco, Simona and Levine, Arnold J. and Bhardwaj, Nina and Greenbaum, Benjamin D.

Abstract : Recent studies have demonstrated abundant transcription of a set of noncoding RNAs (ncRNAs) preferentially within tumors as opposed to normal tissue. Using an approach from statistical physics, we quantify global transcriptome-wide motif use for the first time, to our knowledge, in human and murine ncRNAs, determining that most have motif use consistent with the coding genome. However, an outlier subset of tumor-associated ncRNAs, typically of recent evolutionary origin, has motif use that is often indicative of pathogen-associated RNA. For instance, we show that the tumor-associated human repeat human satellite repeat II (HSATII) is enriched in motifs containing CpG dinucleotides in AU-rich contexts that most of the human genome and human adapted viruses have evolved to avoid. We demonstrate that a key subset of these ncRNAs functions as immunostimulatory ``self-agonists'' and directly activates cells of the mononuclear phagocytic system to produce proinflammatory cytokines. These ncRNAs arise from endogenous repetitive elements that are normally silenced, yet are often very highly expressed in cancers. We propose that the innate response in tumors may partially originate from direct interaction of immunogenic ncRNAs expressed in cancer cells with innate pattern recognition receptors, and thereby assign a previously unidentified danger-associated function to a set of dark matter repetitive elements. These findings potentially reconcile several observations concerning the role of ncRNA expression in cancers and their relationship to the tumor microenvironment.
Modeling quantum fluid dynamics at nonzero temperatures - Berloff, Natalia G. and Brachet, Marc and Proukakis, Nick P.

Abstract : The detailed understanding of the intricate dynamics of quantum fluids, in particular in the rapidly growing subfield of quantum turbulence which elucidates the evolution of a vortex tangle in a superfluid, requires an in-depth understanding of the role of finite temperature in such systems. The Landau two-fluidmodel is the most successful hydrodynamical theory of superfluid helium, but by the nature of the scale separations it cannot give an adequate description of the processes involving vortex dynamics and interactions. In our contribution we introduce a framework based on a nonlinear classical-field equation that is mathematically identical to the Landau model and provides a mechanism for severing and coalescence of vortex lines, so that the questions related to the behavior of quantized vortices can be addressed self-consistently. The correct equation of state as well as nonlocality of interactions that leads to the existence of the roton minimum can also be introduced in such description. We review and apply the ideas developed for finite-temperature description of weakly interacting Bose gases as possible extensions and numerical refinements of the proposed method. We apply this method to elucidate the behavior of the vortices during expansion and contraction following the change in applied pressure. We show that at low temperatures, during the contraction of the vortex core as the negative pressure grows back to positive values, the vortex line density grows through a mechanism of vortex multiplication. This mechanism is suppressed at high temperatures.
Quantitative theory of entropic forces acting on constrained nucleotide sequences applied to viruses - Greenbaum, Benjamin D. and Cocco, Simona and Levine, Arnold J. and Monasson, Remi

Abstract : We outline a theory to quantify the interplay of entropic and selective forces on nucleotide organization and apply it to the genomes of single-stranded RNA viruses. We quantify these forces as intensive variables that can easily be compared between sequences, outline a computationally efficient transfer-matrix method for their calculation, and apply this method to influenza and HIV viruses. We find viruses altering their dinucleotide motif use under selective forces, with these forces on CpG dinucleotides growing stronger in influenza the longer it replicates in humans. For a subset of genes in the human genome, many involved in antiviral innate immunity, the forces acting on CpG dinucleotides are even greater than the forces observed in viruses, suggesting that both effects are in response to similar selective forces involving the innate immune system. We further find that the dynamics of entropic forces balancing selective forces can be used to predict how long it will take a virus to adapt to a new host, and that it would take H1N1 several centuries to adapt to humans from birds, typically contributing many of its synonymous substitutions to the forcible removal of CpG dinucleotides. By examining the probability landscape of dinucleotide motifs, we predict where motifs are likely to appear using only a single-force parameter and uncover the localization of UpU motifs in HIV. Essentially, we extend the natural language and concepts of statistical physics, such as entropy and conjugated forces, to understanding viral sequences and, more generally, constrained genome evolution.