Antimicrobial resistance is a major threat worldwide that requires a strong investment in fundamental studies. Resistance, as well as transient tolerance (persistence) to antibiotics, involve a network of intracellular stress responses: e.g., the stringent response, the SOS response, and the RpoS-regulated general stress response. We and others have shown that these stress responses are induced by antibiotic (AB) doses below the minimum inhibitory concentration (sub-MIC) and that they can accelerate acquisition of heritable AB resistance through increased mutagenesis and horizontal gene transfer (HGT). Although low concentrations of antibiotics do not kill bacteria, they can have a major impact on bacterial populations. In particular, it was shown that AB concentrations as low as hundred-fold below the MIC can lead to mutations and the selection of AB resistant cells. Most of the studies describing how bacteria acquire resistance or become persisters are based on experiments dealing with populations of cells. Such measurements yield average quantities for the whole population but they cannot provide a distribution of responses, nor can they follow the temporal evolution of individuals within the population. By contrast, there is mounting evidence that cells within a given population can display widely heterogeneous responses to an AB stress. This project aims at describing precisely individual cell fate during stress responses to low doses of antibiotics, and understanding the emergence of antibiotic resistance on the level of a single cell. We propose to address the profile of induction of four stress responses at the single-cell level: SOS, stringent response, RpoS general stress response and oxidative stress response, in response to three ABs from different families (fluoroquinolones, aminoglycosides, ß-lactams). To this end, we will use a microfluidic platform to culture bacteria, while submitting them to controlled AB stresses to assess heterogeneity and growth on chip. We will develop the theoretical description of bacterial growth dynamics taking into account the AB stress through mathematical modelling relating large-scale heterogeneity to the variability on the scale of individual cells. We will then isolate and extract cells that show phenotypic diversity. The large statistics will allow us to get access to rare events. The extracted cells will be subjected to analysis (NGS, dPCR) in order to detect horizontal gene transfers, mutations or changes of protein expression that can explain the behavior of these cells. This will first require the development of technological tools to genotype the small number of bacterial cells that can be recovered from the microchannel. The second step will be to explore different conditions that lead to the emergence of antibiotic resistance in order to gain insight into the underlying mechanisms and devise strategies to counter them. The impact of this project will be threefold: (i) Concerning the fundamental biological knowledge it will bring, (ii) the technological and quantitative developments that accompany it, and (iii) in understanding the emergence of resistance mechanisms and their implications for the development of new therapeutic strategies.

How do tissues and organs grow to reach well-defined shapes? For instance, thin tissues, such as animal epithelia and plant leaves, are typically flat, whereas the default state of a growing thin sheet is curved. How is flat shape achieved? Here we address this question in Arabidopsis leaves, a system amenable to live-imaging of growth, biophysical experiments, and genetic manipulation. We hypothesize that cell-to-cell growth heterogeneity enables cells to sense variations in leaf curvature and maintain flatness. We aim to test this hypothesis using experimental and theoretical biophysics with cell biology. We will (i) characterize the relationship between cell-to-cell heterogeneity, cell mechanics, and leaf flatness, (ii) build a theoretical framework to model a thin active growing sheet in 3D space, and (iii) characterize the combinatorial regulation of flatness through model predictions and experimental tests. Altogether, we expect to shed light on the robustness of morphogenesis.

SCALP considers complex systems being governed by non-linear multiscale dynamics with non-local interactions between scales. These systems present extreme events in their dynamics as well as long-range dependences. Some examples of this kind of processes are fluid turbulence, ocean and atmosphere dynamics, stock markets, avalanche processes. They usually resist traditional analytical/simulation approaches, lacking a reliable and tractable physical model needed to perform any forecasting tasks. High dimensional chaotic systems may display a dynamics so intricated that no analytical theory is available, and the building of an explainable minimal model should provide insights. ML approaches are appealing in this context but require the design of new ML architectures exhibiting specific physics informed properties such as scales symmetries and conservation laws. Furthermore, observations are often scarce, eliminating de-facto too large architectures. Our aim is to develop deep but interpretable models with relevant scale symmetries and respecting physical conservations laws. As study cases we will be focusing on various multiscale dynamical models of turbulence (shell models, wave turbulence, fluid turbulence), chaotic models of atmospheric dynamics, and avalanche processes. Then, real data from observations, experiments and direct numerical simulations will be studied. The long-term impacts of SCALP concern contexts not limited to physics, where bigger non-interpretable networks is not the answer.

MIMETUBE aims at providing new types of tubular biomaterials to address unmet clinical needs in vascular and thoracic surgery, and to serve as platforms for fundamental investigations of graft integration and tissue regeneration. The consortium gathers materials scientists, physicists, physiologists and surgeons sharing a strong interest for bioengineering. The processing strategy relies on ice-templating of highly concentrated type I collagen materials coupled with topotactic fibrillogenesis – recently reported by the LCMCP. The resulting hierarchical materials display biomimetic assembly of collagen fibres as well as stabilization of the macroscopic features required for surgical application. By providing on-demand tissues with precisely modulated properties, including geometrical and mechanical features, MIMETUBE aims at dramatically increasing the availability of grafts for both treatment of peripheral arterial disease and airway transplantation.

Understanding the shear stress-driven cellular activities is crucial to develop innovative diagnoses, therapies, and medical devices. Because there exists no method to measure the rapidly varying shear stress (e.g. pulsatile blood flow) near cells, our knowledge of how flow regulates such a variety of cell functions is highly limited. We will develop a micro-tomographic shearmetry that allows 3D-mapping and monitoring of the time-dependent shear stress profile with unprecedented spatio-temporal resolution. This constitutes a breakthrough from the conventional approaches based on particle tracking methods within microfluidic chambers. We propose to develop a highly novel shearmetry technique through a radically different methodology based on capturing the shear-induced orientation behavior of luminescent nanorods. As a case study using the new shearmetry, we will investigate important mechanobiological questions in endothelial cells (ECs) lining the inner surfaces of blood vessels. The flow-induced intracellular calcium mobilization and the flow-induced endothelial wound healing will be examined. A successful pursuit of this project will provide the new shearmetry platform as a universal experimental solution to measure, monitor, and analyze the dynamic shear stress distribution in a wide range of micro- and bio-fluidic systems and environments.