Reading the T cell receptor code Abstract »

The specificity of adaptive immune responses relies on the binding of hyper-variable receptors to diverse ligands. Advances in the depth at which the hyper-variable receptor loci can be sequenced provide unprecedented resolution into the many-to-many mapping between receptors and ligands. What does this data reveal about the sequence determinants of specific binding? In my talk, I will discuss some of our recent progress in addressing this question: First, I will introduce a population genetics approach to infer correlation functions of specificity on sequence space. Second, I will present our initial attempts at using metric learning to learn which receptors recognize common targets. I will conclude with some thoughts on how an ability to read the T cell receptor code will change the way we track immune responses to infection, vaccinations and cancer.

Non-equilibrium antigen recognition in acute infections Abstract »

The immune response to an acute primary infection is a coupled process of antigen proliferation, molecular recognition by naive B cells, and their subsequent proliferation and antibody shedding. This process contains a fundamental problem: the recognition of an exponentially time-dependent antigen signal. Here we show that B cells can efficiently recognise new antigens by a tuned kinetic proofreading mechanism, where the molecular recognition machinery is adapted to the complexity of the immune repertoire. This process produces potent, specific and fast recognition of antigens, maintaining a spectrum of genetically distinct B cell lineages as input for affinity maturation. We show that the proliferation-recognition dynamics of a primary infection is a generalised Luria-Delbrück process, akin to the dynamics of the classic fluctuation experiment. This map establishes a link between signal recognition dynamics and evolution. We derive the resulting statistics of the activated immune repertoire: antigen binding affinity, expected size, and frequency of active B cell clones are related by power laws. Their exponents define the class of generalised Luria-Delbrück processes; they depend on the antigen and B cell proliferation rate, the number of proofreading steps, and the lineage density of the naive repertoire. Our model predicts key clinical characteristics of acute infections, including the emergence of elite neutralisers and the effects of immune ageing. More broadly, our results establish acute infections as a new probe into the global architecture and functional principles of immune repertoires.

Robust membrane processing for automatic protein sampling in cryo-electron tomograms with TomoCHAMPS at nanoscale Abstract »

Cryo-electron tomography (cryo-ET) allows visualisation of molecular structures in their native states and context at near-atomic resolution. Due to technical restrictions in image acquisition such as the low intrinsic contrast of biological materials and minimised electron dose to prevent radiation damage in exposed sample, sophisticated computational methods are required to accurately extract and enhance signal of target objects. In particular, small membrane proteins (< 150 kDa) exhibit weak signal. To obtain high- resolution structural information of such proteins, increasingly large datasets are acquired and mined. While existing softwares demand extensive manual curation in handling membrane protein cryo-ET data, we present TomoCHAMPS (tomography-based characterisation and analysis of membranes for protein sampling): an automatic image processing workflow dedicated to cryo-ET based characterisation and analysis of membranes for resolving membrane protein structures. By integrating improved open- source tools/methods and in-house scripts in a configurable manner, TomoCHAMPS is expected to support efficient processing of large in vitro and cellular transmembrane and membrane-binding protein cryo-ET datasets up until subtomogram averaging with minimised manual input required. Main features of TomoCHAMPS include pre-processing, tilt series alignment, 3D reconstruction, membrane segmentation within user-defined regions of interest, geometric analysis of membranes, and membrane protein sampling. Here, we showcase the application of TomoCHAMPS to three in vitro reconstituted membrane contact site cryo-ET datasets aiming at resolving small membrane protein structures (present as dimers, size range: ~55-80 kD).

The nanocaterpillar's random walk: or how to move precisely with random sticky feet? Abstract»

Particles with sticky feet - or nanoscale caterpillars - in biological or artificial systems, beat the paradigm of standard diffusion to achieve complex functions. Some cells (like leucocytes) use ligand-receptor contacts (sticky feet) to crawl and roll along vessels. Sticky DNA (another type of sticky feet) is coated on colloids to design programmable interactions and self-assembly. Predicting the dynamics of such sticky motion is challenging since sticky events (attaching/detaching) often occur on very short time scales compared to the overall motion of the particle. Even understanding the equilibrium statistics of these systems (how many feet are attached in average) is largely uncharted. Yet, controlling the dynamics of such particles is critical to achieve these advanced functions -- for example facilitating motility is critical for long-range alignment of DNA coated-colloids crystals. Here we present advanced theory and experimental results on a model system. We rationalize what parameters control average feet attachment and how they can be compared to other existing systems. We investigate furthermore how various motion modes (rolling, sliding or skipping) may be favored over one another.

Hydrodynamics of active cells migrating under mesoscopic confinement Abstract »

When interacting in large ensembles, cells can undergo collective cell migration, reminiscent of the motions observed in fish schools or sheep herds. The importance of collective migration in various biological processes such as morphogenesis or cancer progression has been pointed out in recent years. In vivo, cells migrate in effective channels defined by the local environment. Such a situation can be recapitulated in well-defined synthetic mesoscale structures or patterns. Physical models of interacting particles can then be proposed to explain the experimental observations. These interpretations allow measuring physical properties of the system (diffusion, viscosity, ect), leading to a better understanding of its dynamics.

Designing molecular RNA switches with Restriced Boltzmann machines Abstract »

Riboswitches are structured allosteric RNA molecules capable of switching between competing conformations in response to a metabolite binding event, eventually triggering a regulatory response. Computational modelling of these molecules is complicated by complex tertiary contacts, conditioned to the presence of their cognate metabolite. In this work, we show that Restricted Boltzmann machines (RBM), a simple two-layer machine learning model, capture intricate sequence dependencies induced by secondary and tertiary structure, as well as the switching mechanism, resulting in a model that can be successfully used for the design of allosteric RNA. As a case study we consider the aptamer domain of SAM- I riboswitches. To validate the functionality of designed sequences experimentally by SHAPE-MaP, we develop a tailored analysis pipeline adequate for high-throughput probing of diverse homologous sequences. We find that among the probed 84 RBM designed sequences, showing up to 20% divergence from any natural sequence, about 28% (and 47% of the 45 among them having low RBM effective energies), are correctly structured and undergo a structural allosteric in response to SAM. Finally, we show how the flexibility of the molecule to switch conformations is connected to fine energetic features of its structural components.

Record-ages of non-Markovian Scale Invariant Random Walks Abstract »

How long is needed for an observable to exceed its previous highest value and establish a new record? This time, known as the age of a record plays a crucial role in quantifying record statistics. Until now, general methods for determining record age statistics have been limited to observations of either independent random variables or successive positions of a Markovian (memoryless) random walk. Here we develop a theoretical framework to determine record age statistics in the presence of memory effects for continuous non-smooth processes that are asymptotically scale-invariant. Our theoretical predictions are confirmed by numerical simulations and experimental realisations of diverse representative non-Markovian random walk models and real time series with memory effects, in fields as diverse as genomics, biology, climatology, hydrology, geology and computer science. Our results reveal the crucial role of the number of records already achieved in time series and change our view on analysing record statistics.

Optimal foraging in Caenorhabditis elegans: A simple rule from a complex dataset Abstract »

Evolution is supposed to produce near-optimal organisms, but this optimality is often hidden behind the high complexity of biology. Optimal animal behavior is particularly hard to study, given the extreme complexity of the nervous system and the diversity of environmental cues it can face. We address this challenge on a simple and powerful model organism, the nematode Caenorhabditis elegans. Combining high-throughput experimental techniques, data analysis and modeling, we aim to test the optimality of behavior with unprecedented accuracy, breadth and detail.

Emergent bistability and mutualistic behavior: How interations and dispersal rescue diverse ecosystems from extinction Abstract »

How diversity is maintained in natural ecosystems is a long-standing question in Theoretical Ecology. By studying a system that combines ecological dynamics, heterogeneous interactions and spatial structure, we uncover a new mechanism for the survival of diversity-rich ecosystems in the presence of demographic fluctuations. While the single species case and the case of constant interactions boil down to the well-studied Directed Percolation model, we show that the heterogeneity of the interaction network can lead to qualitatively new behavior: global bistability emerges, accompanied by sudden tipping points and the development of mutualism.

Incorporating structure into models of ecological community stability Abstract »

Many models of complex ecosystems (with many species) use random numbers to represent the interactions between species. The justification for this is that it is only the statistics of the interactions that determine the stability of the community, if the system has sufficiently many species. However, in such models, the species are typically taken to be statistically equivalent, whereas a more realistic model would incorporate a hierarchy or structure to the interactions between species. In this talk, I will present some simple formulae for stability, derived from random matrix theory, that demonstrate the effect of including structure in the model. The results, which are derived treating the additional structure as perturbation, are very general yet elementary. It is thus made transparent what kinds of statistical structure are stabilising/destabilising for an ecological community.

Demixing fluorescence time traces transmitted by multimode fibers: a new minimally invasive deep brain endoscope Abstract »

Fiber photometry is a significantly less invasive method compared to other deep brain imaging microendoscopy approaches due to the use of thin multimode fibers (MMF diameter < 500 µm). Nevertheless, the transmitted signals get scrambled upon propagation within the MMF, thus limiting the technique s potential in resolving temporal readouts with cellular resolution. Here, we demonstrate how to separate the time trace signals of several fluorescent sources probed by a thin (approximately 200 µm) MMF with typical implantable length in a mouse brain. We disentangled several spatio-temporal fluorescence signals by using a general unconstrained non-negative matrix factorization (NMF) algorithm directly on the raw video data. Furthermore, we show that commercial and low-cost open-source miniscopes display enough sensitivity to image the same fluorescence patterns seen in our proof of principle experiment, suggesting that a whole new avenue for novel minimally invasive deep brain studies with multimode fibers in freely-behaving mice is possible.

Coarsening Kinetics of Chemically-Active Emulsions Abstract »

Droplets form via phase separation and coexist with a dilute phase. After nucleation and growth of droplets, the resulting emulsion of many droplets undergoes coarsening kinetics to reach its thermal equilibrium state. Ostwald ripening describes the coarsening kinetics of emulsions for which the total droplet material is conserved. During Ostwald ripening, the droplet number density decreases, the average radius increases, and the droplet size distribution function broadens in a universal manner. Phase separation and kinetics of emulsions are relevant for the spatial organization of cells and for synthetic chemical systems. In these systems, droplet material is often not conserved due to the active production of droplet building blocks by fuel-driven chemical reaction cycles. In this talk, I will introduce the theoretical framework for coarsening in emulsions with matter supply, which comprises diffusion limited and interface-kinetics limited growth regimes. I will discuss the effect of matter supply on the statistics of droplet sizes and the universality of the droplet size distribution function. We find that matter supply can transiently decouple emulsions and lead to new scaling behaviors. The importance of this work is in understanding how matter supply can lead to size control in chemically-active emulsions, which can be a possible regulatory mechanism mediated by biomolecular condensates in living cells.

Interplay of nanoparticles transport and gel rheology through Vide Abstract »

Despite the increasing significance of extracellular vesicles (EVs) as nanocarriers in medical treatments and their role in disease (e.g. cancer) progression, their transportation remains a critical concern. To gain a better understanding of the correlation between vesicles transport and the rheology of the surrounding environment, the use of suitable instruments becomes crucial. In this research summary, we present the application of the Videodrop built and commercialized by the French company Myriad, which not only enables the analysis of nanoparticle concentration and size distribution but also provides valuable insights into the properties of their immediate surroundings. Indeed, this instrument allows the physical characterization of bio-nanoparticles not only in aqueous solution but also in challenging medium with relatively high viscosity. By exploration of the functionality of the instrument and addition of calibration procedures using synthetic nanoparticles of various known sizes, we successfully obtained information about the local viscosity of a gel that encapsulates EVs. It also facilitated the characterization of EVs in suspension in unconventional medium. Leveraging the outcomes of this investigation, we not only highlight the advantages but also acknowledge the limitations of the instrument. A better understanding of EVs transport in viscous matrices can pave the way to the development of optimized biological carriers for targeted drug delivery and therapeutic applications.

Two-fluid dynamics and micron-thin boundary layers shape cytoplasmic flows in early drosophila embryos Abstract »

Cytoplasmic flows are widely emerging as key functional players in development. In early Drosophila embryos, flows drive the spreading of nuclei across the embryo. Here, we combine hydrodynamic modeling with quantitative imaging to develop a two-fluid model that features an active actomyosin gel and a passive viscous cytosol. Gel contractility is controlled by the cell cycle oscillator, the two fluids being coupled by friction. In addition to recapitulating experimental flow patterns, our model explains observations that remained elusive and makes a series of predictions. First, the model captures the vorticity of cytosolic flows, which highlights deviations from Stokes’ flow that were observed experimentally but remained unexplained. Second, the model reveals strong differences in the gel and cytosol motion. In particular, a micron-sized boundary layer is predicted close to the cortex, where the gel slides tangentially while the cytosolic flow cannot slip. Third, the model unveils a mechanism that stabilizes the spreading of nuclei with respect to perturbations of their initial positions. This self-correcting mechanism is argued to be functionally important for proper nuclear spreading. Fourth, we use our model to analyze the effects of flows on the transport of the morphogen Bicoid and the establishment of its gradients. Finally, the model predicts that the flow strength should be reduced if the shape of the domain is more round, which is experimentally confirmed in Drosophila mutants. Thus, our two-fluid model explains flows and nuclear positioning in early Drosophila, while making predictions that suggest novel future experiments.

Actin cortex multi-scale mechanics Abstract »

The cell cortex is a thin acto-myosin layer underlying the plasma membrane of eukaryotic cells. This structure confers a mechanical resistance to the cell, an essential role for metazoan cells lacking of cell wall. However, as an active gel, the cell cortex in not a simple passive shell. On the contrary, it is a dynamic structure involved in cell migration, cell shape and polarization. Cortex mechanics is tightly regulated by actin cross-linker proteins that dynamically bind and unbind actin filaments. However, this interplay is still poorly understood lacking of quantitative approaches. We faced this challenge by quantification of i) piconewton forces felt by actin cross-linkers thanks to FRET-based biosensor and ii) actin cortex thickness nanometric fluctuations using magnetic pinchers. The combination of the theses techniques in the same cell offers a unique description of the cortex multi-scale mechanics. We explored this coupling across scales in an epithelium monolayer to understand how it underlies physiological processes such as migration, polarization and regulation of cell density.