Active matter, a term coined by physicists to describe a large number of agents consuming energy to move or exert mechanical forces, has become a major field of research in biological physics. A colony of motile bacteria is a good example of growing active matter: each cell can grow and divide, and it can move around thanks to its flagella. Growing active matter with microswimmers raises specific questions: What is the contribution of growth in long-range ordering patterns that are typically obtained in dense bacterial suspension? What is the influence of swimming modes, namely the pusher and puller mode used to describe two types of microswimmers, in tetratic and nematic alignement? How do physical effects translate across scales? This project proposes to use the bacterium Pseudomonas aeruginosa as an experimental model system to answer these questions. I will use a suite of imaging devices and methods across all scales, from single-cell to the whole colony, and with transmission, reflection, and fluorescence imaging. I will also use genetic engineering to modulate motility as an experimental variable. The tasks presented in the project are ordered in increasing length and time scales: from the hydrodynamics of P. aeruginosa single cells to 2D and 3D orderings, the physics of spreading of active fluid, the dynamics of layered organization, the dynamics of binary mixtures of cells with different motility properties, and, for much longer time scales, evolutionary dynamics of motility.

The gastrointestinal tract involves many biological, chemical and physical phenomena to secure the absorption of nutrients from our food. Also, specific sites of the digestive mucosa are gateways to our immunologic system which pave the way for the development of innovative oral therapeutic strategies. These strategies are based on the encapsulation of drugs in nano- or micro- particles or the administration of bacteria, which would target these sites in order to induce an immune response. However, a major scientific barrier is to be able to predict the flow of these "micro-particles" and thus control the dose absorbed by our body. The objective of TransportGut is to develop a predictive and comprehensive modelling of the transport of microparticles in the gastrointestinal system. The challenge of such a model is to account for the different specificities of the physical environment of the digestive tract on the phenomena of transport and mixing. On the one hand, transport and mixing are controlled by the mechanical activity of the smooth muscles of the intestinal mucosa, on both macroscopic and microscopic scales. On the other hand, this activity varies according to the time scales considered. Several scales are thus relevant: the microstructures of the mucosa, the isolated organ and along the digestive system. Mixing at large scales are probably controlled by mixing at small scales. There is currently no particle transport model that takes into account these different scales. TransportGut is an integrated and interdisciplinary project that draws on the complementary expertise of three teams in biorheology, theoretical biophysics and physiology. The team of the Laboratoire Rhéologie et Procédés (LRP) has significant experience in the development of experiments in complex fluid mechanics at macroscopic and microscopic scales, as well as in numerical modeling of flows in the gastrointestinal tract. The team of the Laboratoire Jean Perrin (LJP) has expertise in theoretical modeling of the transport of bacteria and their interactions with the immune system of the digestive tract. Finally, the team from Techniques de l’Ingénierie Médicale et de la Complexité (TIMC-IMAG) develops experimental systems and original technologies for understanding the physiology of smooth muscles. Based on experiments at the interface of physiology and fluid mechanics and numerical simulations of flows, we propose to develop an analytical model of transport connecting these different scales. We will develop experiments on animal models to study the transport of particles along the digestive system and in the vicinity of microstructures of the intestinal mucosa. These experiments will be used to simulate numerically the coupling between flows at microscopic and macroscopic scales in order to understand the role of active and microstructured interfaces on the transport and mixing of microparticles. All of these data from experiments and numerical simulations will make it possible to build analytical and simplified models of the transport and mixture of particles at different spatial and temporal scales. This model would predict the spatiotemporal dispersion of particles in order to be a decision-making tool for the pharmaceutical industry, but also to understand the fundamental mechanisms that govern the spatial structure of the intestinal microbiota.

In the digestive tract, there are commensal bacteria which are beneficial to the host, but also pathogenic bacteria that can invade. How does the host control its microbiota? One of the tools for the host is its immune system. The main effector of the adaptive immune response in the gut is a type of antibodies, secreted Immunoglobulin A (sIgA). This molecule bind very specifically a target, for instance a pattern on the surface of a bacterial strain, but once bound to bacteria, sIgA do not kill nor prevent bacteria from replicating, but can bind them together. This system can also be seen as a physico-chemical system, with a complex hydrodynamic flow, and spatially varying concentration of reactive molecules and their targets. There are many open questions about sIgA, but they are hard to tackle quantitatively, because there is so far no spatial model of sIgA concentration along the digestive tract, taking into account how antibodies are transported from one part of the digestive tract to the next. Such a model must also take into account which proportion of antibodies are free and which proportion of antibodies are attached to their target, in particular when antibodies’target are bacteria, which concentration varies widely along the digestive tract. Our hypothesis is that the physical description of this system, a system with a flow and complex mixing, inhomogeneous antibody production, and reaction with targets, will enable to understand the profile of antibody concentration, and how they interact with bacteria. The main barrier is to build an approximate spatial representation of the digestive tract and the transport of the gut contents, simple enough for efficient numerical study and analytical approximations, and enabling to understand which are the important mechanisms at play, while retaining the important properties of the real system. The project is articulated around 3 main aims. The first aim is building a first spatial model, representing the complex gut transport unidimensionally, with a mean velocity and an effective diffusion, representing mixing. After a systematic review of the literature, we will start from a preliminary model, study it more systematically numerically, extend it in several directions, attempt to find analytical approximations for this model, and compare with experimental data. The second aim consists in developing a better approximation of gut transport, which would be tractable enough to be included in this model of antibody concentration, while being closer to realistic transport at different scales. For finding analytical approximations, we will use results from computational fluid dynamics simulations, confronted to experiments. The third aim will be to combine the model developed in aim 1 with the better approximation of transport of aim 2, and exploit it for different uses, for answering different questions about antibody dynamics in the digestive tract, their interaction with bacteria and structuration of the bacterial population, as well as modeling bacterial evolution in the gut. This project benefits from existing collaborations with a biologist expert in the interaction of bacteria and the immune system in the gut, a specialist of gut fluid dynamics (both experimental and computational), and a biophysicist who models the impact of population structure on evolution. The expected results are a better understanding of the interaction of antibodies and bacteria in the gut, and additionally, spatial models of the gut and approximate transport operators that could be reused for other projects.

Understanding how the perception of an environment emerge from the collective dynamics of the massive assembly of neurons that constitutes the vertebrate brain is arguably one of the most challenging scientific question of our time. The multi-scale nature of the brain allows for several complex processing, among which the integration of sensory inputs plays a central role. Each sensory system transduces a different form of energy and provides the brain with an independent picture of the environment, which has two major consequences: (i) animals are subjected to a barrage of information for which the brain must continuously evaluate the relative priorities, and (ii) the brain can use the information from different sensory channels to enhance event detection. The aim of this proposal is to build a set of experimental and analytical tools that will allow, for the first time, to record brain-wide neuronal activity during multi-modal integration tasks and to decipher the complex neural processes involved. To this aim, we plan to use a specific animal model, zebrafish larvae. Zebrafish, which was originally developed as a model for embryo development and tissue regeneration, has recently emerged as a similarly important model system for neuroscience. The rapid development of calcium imaging – tightly related to the progress of genetics – has led to remarkable improvements on the number of neurons whose activity can be simultaneously recorded. Recently, Single-Plane Illumination Microscopy (SPIM) approaches yielded even more spectacular progress allowing to record simultaneously the activity of approximately 85% of the neurons of an intact zebrafish larva, yet with cellular resolution. These groundbreaking advances in the field of functional imaging allow us to reconsider long-standing question in neurosciences with a fresh perspective. Here, we propose to study some fundamental issues related to multi-sensory integration with brain-wide neuronal activity recordings during a simple stimulation paradigm. In the framework of a collaboration with experienced theoreticians, we will test and develop models of network inference on extensive datasets, and explore to what extent the zebrafish brain uses probabilistic approaches to handle the intrinsic variability of sensory inputs. We believe that the convergence between new experimental and theoretical tools convey great promises to unveil fundamental mechanisms of multi-sensory integration in the vertebrate brain.

The project aims at discovering the fundamental principles governing the adaptation of multi-species communities to disturbance on a 4-species (4S) bacterial biofilm of natural origin. In the nature, these systems play a crucial role in the biogeochemical cycles of carbon, nitrogen and water. The disturbance of their balance can only come along with striking consequences at a global scale. However, we currently ignore how these communities will respond to climate change. The examination of this question at the natural ecosystem scale is hardly feasible due to the impossibility to rationally vary and control the environmental conditions. Besides the laboratory studies are mostly mono-species while it is increasingly becoming obvious that the inter-species interactions are crucial for the assembly and the development of these communities. To better understand the factors which support the adaptation of these communities to disturbances, we propose gathering biophysicists and microbiologists who will examine the global and molecular responses of the model 4S community to controlled environmental changes. In a first phase, we will build a quantitative phenotypic and genetic description of the 4S biofilm established in a microfluidic platform enabling to control the applied physical and chemical conditions as well as to monitor in real time the development of the community. Through a combinatorial approach — all biofilms from mono- to 4-species will be examined in parallel — we will first identify interspecies interactions and their environmental and genetic background in a reference state. Then, in a second phase, we will carry out the perturbation program consisting in completing series of controlled disturbances of various natures — chemical, physical and social — to detect characteristic adaptive trajectories (resistance, resilience or redundancy) and select remarkable time-points — climax or plateau — which will then be studied from a genetic point of view in the third phase. In this third phase, we will study the transcriptional and genomic alterations having occurred at the selected time points of the adaptive trajectory. Through this approach, we aim at identifying the genes and the interspecies interactions involved in the adaptation to a given perturbation, and isolate potentially emerging mutants. On the other hand, we will conduct a theoretical analysis to model the population dynamics induced by disturbances. This program holds several methodological and technological challenges such as the development of a quantitative method for describing the community phenotype, the development of the experiment automation required by the combinatorial approach and the disturbance screening step; as well the genetic analyses that will be performed in the multi-species context, thus needing the implementation of the latest technical advances in the field. Our approach aims at overcoming the difficulty in linking phenotypic and genetic information. Our strategy is to pre-select a limited number of relevant trajectories and to perform correlated analyses — phenotypic and genetic — on defined time points of the adaptive path to bring over adaptation mechanism features in this 4S adherent community. The completion of our program should provide a first clarification on the role of interspecies interactions in the specific architecture of the mixed community and its capacity to adapt to a given stress. We also expect other benefits such as the advance of new experimental tools to analyze adherent bacterial communities and new strategies to control bacterial biofilms, potentially new avenues to artificially assemble useful multispecies communities with defined function. Finally, our work will allow to evaluate the potential of multispecies simplified models, grown in the laboratory conditions for understanding and predicting the dynamics of natural systems.