Paris Biological Physics
Community Day 2021

Impact of population spatial structure on mutant fixation probabilities, from models on graphs to the gut

Microbial populations often have complex spatial structures, with homogeneous competition holding only at a local scale. Population structure can strongly impact evolution, in particular by affecting the fixation probability of mutants. I will first discuss a general model for describing structured populations on graphs. Then I will show that the specific structure of the gut with gradients of food and bacterial concentrations can increase the fixation probability of neutral mutants, which can have consequences for the diversity of the microbiota.

Synaptic scaling to maintain neuronal dynamics and propagate information

There are many seminal theories on the conditions for propagating information faithfully while maintaining stability in neuronal networks. Testing these theories is difficult as it requires accurate information about network architecture and precise control of the input. To overcome these limitations, we used cultures of cortical neurons and stimulated the network using a novel optogenetic stimulation technique. Theories suggest that the appropriate scaling of synaptic strengths with network size is crucial to preserve stability and generate in-vivo like dynamics. In a first study, we showed that synaptic strength varies nearly as 1/﹟K (K = number of connections), close to the ideal theoretical value. This result is important because this scaling law was assumed by major theoretical models but lacked any experimental demonstration. Using optogenetics, we delivered high spatiotemporal resolution stimuli to neurons within the network to show that the neuronal dynamics predicted by theory hold even under conditions far from the ideal limits. These results obtained in cultures, predicted by theory and observed in the brain suggest that the synaptic scaling rule and resultant dynamics are emergent properties of networks in general. Information contained in neuronal activity can be represented as the neuronal firing rate or as the precise timing of action potentials. To study what information is propagated in networks composed of several connected layers, we combined microfabrication techniques with neuronal culture to build multilayer networks in vitro. We optogenetically activated neurons from the first layer and identified the conditions to transmit the input. Brief stimuli with different temporal precisions resulted in a firing rate modulation. Whereas temporal information was better preserved in low density networks, dense networks could propagate firing rate. These results indicate that both temporal and rate information can be propagated in multilayer networks, depending not only on the input but also on network architecture and cell density.

Collective contact guidance triggers polar laning of turbulent epithelial monolayers

Collective cell flows within tissues are central in biological processes such as morphogenesis, wound healing, or cancer progression. In vivo, cell behaviors are controlled by their surrounding environment such as oriented bundles of extra cellular matrix proteins. These fibrillar structures can be recapitulated in vitro with grooved substrates allowing to study the cell response to such cues by “contact guidance”. Up to now, contact guidance has been mostly studied on single cell migration. However, little is known about cell collective response to such cues. Here, we show that, when plated on subcellular grooves, a confluent monolayer of human bronchial epithelial cells (HBECs) spontaneously organizes into wide alternating polar lanes that migrate in antiparallel directions. These lanes can be few millimeters in length and coarsen with time reaching widths of several hundred micrometers before cells jam. Within a lane, cell displacements are described by a plug flow with a well-defined polarity at the tissue scale. Our results are well captured by a hydrodynamic description of an active polar fluid that undergoes a disordered-to-flocking transition favored by friction anisotropy via the damping of fluctuations in the transverse direction. More microscopically, particle based simulations encapsulating a friction anisotropy identify polarity-velocity coupling and excluded volume interactions as key ingredients of the laning transition.

Looking for fibers : Frustrated self-assembly of 3D printed colloids

Self-assembly manifests in a multitude of systems of varying complexities. However, our understanding of the process of self-assembly is limited to that in simple systems with elementary interactions. To exploit self-assembly for mitigation of diseases such as Alzheimer’s, Parkinson’s, Prions and sickle cell anaemia or to understand protein aggregation, it is essential to generate understanding of a generalized physical mechanism governing self-assembly of complex systems where the building blocks do not fit together perfectly, resulting in geometric frustration. Recent theoretical investigations stipulates that when ill-fitting particles are brought together, geometric frustration builds up, limiting the growth of aggregates thereby determining the final structure of the 'product of self-assembly' [1]. Our focus is to experimentally investigate the self-assembly of various colloidal shapes fabricated through a sophisticated 3D nanoprinting technique based on two-photon polymerization in order to derive a general physical understanding of frustrated self-assembly. I will discuss the experimental strategies used to fabricate colloids of various geometries and their self-assembly under depletion mediated attractive interaction. During the talk I will discuss the experimental techniques, challenges and some solutions we have identified. Some interesting effects of depletion interaction on the diffusion of colloids, which we learned from our failed experimental trials will also be discussed.

Finding the interaction rules behind C. elegans aggregation and swarming

The model organism C. elegans has recently emerged as a system to study collective behaviour at the mesoscopic scale. We have recently identified a set of three behavioural rules that individual worms follow to give rise to starkly contrasting aggregation phenotypes. We further extended the model to show that aggregation and swarming are related behaviours, with the latter driven by food depletion. We have since imaged the aggregation behaviour of 197 wild C. elegans strains sampled world-wide, and found natural variation in the behaviour. We now ask: can the same set of behavioural rules apply to these wild strains to capture all of the observed variations, or are new interactions required.

Intracellular rheology of red blood cells

Characterizing the rigidity of red blood cells (RBCs) and their heterogeneity in a blood sample is a key parameter in understanding erythrocyte diseases. We propose a method of intracellular rheology based on molecular rotors, viscosity sensitive fluorescent probes. Experiments were conducted on RBCs whose rigidity was varied with temperature. We show that the DASPI molecular rotor can detect variations in their overall rigidity, with a fluorescence signal that increases with cell stiffness. A simple RBC model was developed to separate the cytosol and membrane contributions, allowing a qualitative comparison of the cytosol viscosity variation with independent viscosity measurements of hemoglobin solutions. These experiments show that the rotor is able to detect stiffness heterogeneity at the cellular level within a sample and open up the possibility of new diagnostic techniques, especially in the case of sickle cell disease in which hemoglobin polymerization is directly related to the stiffening of RBCs and to the development of painful vaso-occlusive crises.

The topology of DNA knots and catenanes by Atomic Force Microscopy

The topology of DNA is crucial across diverse cellular processes which target topological signatures (e.g., supercoiling, knotting, catenation), these processes then enzymatically drive major topological changes into the DNA. In recent years Atomic Force Microscopy (AFM) imaging has matured into a powerful technique for the investigation of DNA structure, as it is capable of the examination of uncoated DNA molecules in hydrated conditions. However, the direct examination of DNA knots and catenanes (links) by AFM was unexplored. During my PhD thesis at the University of Glasgow (UK) we utilised an E. coli DNA recombination system for the generation of topologically complex knotted or catenated DNA circles. While these DNA recombination products had been investigated using biochemical techniques, they had not yet been verified on a single-molecule level using microscopy. We used high resolution AFM to investigate the topological assignment of these DNA molecules in comparison to our models and the previous biochemical evidence. This work validated the use of AFM as a highly practical and scalable method of single-molecule DNA topology investigations.

An active-gel theory of multicellular migration in tissue

Cells may migrate collectively in tissues in a fluid-like manner. We propose that the tissue can be regarded as a two-component, active, permeating gel, with the cells acting as an active, polar solvent. Our new theory identifies the internal forces of each component (cells and environment) and the interaction forces between components, which orient the solvent (“permeation alignment") and deform the network (“permeation deformation"). These mechanisms drive novel, finite-wavelength instabilities, unique to active, permeating polar gels. Our theory opens an avenue to study cell-matrix interactions during multicellular migration.

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

Stochastic differential equations are often used to model the dynamics of living systems, from Brownian motion at the molecular scale to the dynamics of cells and animals. How does one learn such models from experimental data? This task faces multiple challenges, from information-theoretical limitations to practical considerations. I will present my recent and ongoing effort to develop principled methods to reconstruct stochastic dynamical models from experimental data, with a focus on robustness and data efficiency. This provides a generic means to quantify complex behavior and unfold the underlying mechanisms of an apparently erratic trajectory.

Kinetics of stator recruitment and release in the bacterial flagellar motor

The Bacterial Flagellar Motor (BFM) is the molecular machine responsible for the torque generation that produces the rotational movement of flagella in bacteria, allowing them to move through aqueous media. Thanks to its mechano-sensitivity, the motor is capable of adapting to external forces by a system of active association and dissociation of stators, which are ion channels that consume the proton motive force to generate the torque that allows the motor to turn. Despite being one of the most studied nano-machines, the BFM possesses dynamical features that have not yet been fully explained within the framework of statistical physics. We aim to explain the stochastic behaviour of the recruitment and release processes of stators from the BFM by considering effects such as stator cooperativity and the small size of the system. We use theoretical (lattice gas) and numerical (Monte Carlo simulations) tools to investigate these processes and evaluate the importance of these effects.

Vibrio cholerae motility in aquatic and mucus-mimicking environments

Vibrio cholerae swimming motility increases the bacteria’s pathogenicity by an unknown mechanism, thought to involve aiding the bacteria in crossing the intestinal mucus barrier to reach sites of infection. The cell can be either pushed or pulled by its single polar flagellum, but there is no consensus on the resulting repertoire of motility behaviors. We use high-throughput 3D bacterial tracking to observe _V. cholerae_ swimming in buffer, in viscous solutions of the synthetic polymer PVP, and in mucin solutions that may mimic the host mucosal environment. We perform a statistical characterization of its motility behavior based on automated analysis of tens of thousands of 3D individual trajectories. We reveal that _V. cholerae_ performs a run-reverse-flick motility, consisting of a sequence of forward swimming, reversal, and backward swimming, followed by a turn of approximately 90° (a flick) preceding the next forward swimming segment. Forward runs are, on average, more than three times longer than backward ones, an asymmetry that results in an 85% increase in the effective diffusion coefficient compared to the symmetric scenario observed in other species. Surprisingly, the turning frequency decreases with increasing macroscopic viscosity, indicating mechanosensing and adaptation of either the flagellar motor itself or of its physiological inputs.

Maximal Diversity and Zipfs Law

Zipf law describes the empirical size distribution of the components of many natural and artificial complex systems. Diversity, on the other hand, is a central concept in ecology, economics, information theory, and other natural and social sciences and can be quantified by diversity indices which characterize the system under study from different angles. I will discuss the co-occurrence of Zipf’s law with the maximization of the diversity of the component sizes, understanding here the number of different sizes rep-resented. I will present the law ruling the increase of such diversity with the total dimension of the system and its relation with Heaps’ law. As an example, I will compare analytical results with linguistics and urbanistic datasets. Future directions include the study of biological scenarios, such as gene expression in cells.