ERC FUNDED PROJECTS

Although we have extensive knowledge of many important processes in cell biology, including information on many of the molecules involved and the physical interactions among them, we still do not understand most of the dynamical features that are the essence of living systems. This is particularly true for the actin cytoskeleton, a major component of the internal architecture of eukaryotic cells. In living cells, actin networks constantly assemble and disassemble filaments while maintaining an apparent stable structure, suggesting a perfect balance between the two processes. Such behaviors are called “dynamic steady states”. They confer upon actin networks a high degree of plasticity allowing them to adapt in response to external changes and enable cells to adjust to their environments. Despite their fundamental importance in the regulation of cell physiology, the basic mechanisms that control the coordinated dynamics of co-existing actin networks are poorly understood. In the AAA project, first, we will characterize the parameters that allow the coupling among co-existing actin networks at steady state. In vitro reconstituted systems will be used to control the actin nucleation patterns, the closed volume of the reaction chamber and the physical interaction of the networks. We hope to unravel the mechanism allowing the global coherence of a dynamic actin cytoskeleton. Second, we will use our unique capacity to perform dynamic micropatterning, to add or remove actin nucleation sites in real time, in order to investigate the ability of dynamic networks to adapt to changes and the role of coupled network dynamics in this emergent property. In this part, in vitro experiments will be complemented by the analysis of actin network remodeling in living cells. In the end, our project will provide a comprehensive understanding of how the adaptive response of the cytoskeleton derives from the complex interplay between its biochemical, structural and mechanical properties.

2 349 898 €

Start date: 2017-09-01, End date: 2022-08-31

Parameterized mathematical models have been central to the understanding and design of communication, networking, and radar systems. However, they often lack the ability to model intricate interactions innate in complex systems. On the other hand, data-driven approaches do not need explicit mathematical models for data generation and have a wider applicability at the cost of flexibility. These approaches need labelled data, representing all the facets of the system interaction with the environment. With the aforementioned systems becoming increasingly complex with intricate interactions and operating in dynamic environments, the number of system configurations can be rather large leading to paucity of labelled data. Thus there are emerging networks of systems of critical importance whose cognition is not effectively covered by traditional approaches. AGNOSTIC uses the process of exploration through system probing and exploitation of observed data in an iterative manner drawing upon traditional model-based approaches and data-driven discriminative learning to enhance functionality, performance, and robustness through the notion of active cognition. AGNOSTIC clearly departs from a passive assimilation of data and aims to formalize the exploitation/exploration framework in dynamic environments. The development of this framework in three applications areas is central to AGNOSTIC. The project aims to provide active cognition in radar to learn the environment and other active systems to ensure situational awareness and coexistence; to apply active probing in radio access networks to infer network behaviour towards spectrum sharing and self-configuration; and to learn and adapt to user demand for content distribution in caching networks, drastically improving network efficiency. Although these cognitive systems interact with the environment in very different ways, sufficient abstraction allows cross-fertilization of insights and approaches motivating their joint treatment.

2 499 595 €

Start date: 2017-10-01, End date: 2022-09-30

The project ARTHUS aims at determining the physical origin of Dark Energy: in addition to the energy sources of the standard model of cosmology, effective terms arise through spatially averaging inhomogeneous cosmological models in General Relativity. It has been demonstrated that these additional terms can play the role of Dark Energy on large scales (but they can also mimic Dark Matter on scales of mass accumulations). The underlying rationale is that fluctuations in the Universe generically couple to spatially averaged intrinsic properties of space, such as its averaged scalar curvature, thus changing the global evolution of the effective (spatially averaged) cosmological model. At present, we understand these so- called backreaction effects only qualitatively. The project ARTHUS is directed towards a conclusive quantitative evaluation of these effects by developing generic and non-perturbative relativistic models of structure formation, by statistically measuring the key-variables of the models in observations and in simulation data, and by reinterpreting observational results in light of the new models. It is to be emphasized that there is no doubt about the existence of backreaction effects; the question is whether they are even capable of getting rid of the dark sources (as some models discussed in the literature suggest), or whether their impact is substantially smaller. The project thus addresses an essential issue of current cosmological research: to find pertinent answers concerning the quantitative impact of inhomogeneity effects, a necessary, worldwide recognized step toward high-precision cosmology. If the project objectives are attained, the results will have a far-reaching impact on theoretical and observational cosmology, on the interpretation of astronomical experiments such as Planck and Euclid, as well as on a wide spectrum of particle physics theories and experiments.

2 091 000 €

Start date: 2017-09-01, End date: 2023-08-31

The immune system is a complex ensemble of diverse lineages. Studies on in-vivo-hematopoiesis have until now largely rested on transplantation. More physiological experiments have been limited by the inability to analyze hematopoietic stem (HSC) and progenitor cells in situ without cell isolation and other disruptive manipulations. We have developed mouse mutants in which a fluorescent marker can be switched on in HSC in situ (inducible fate mapping), and traced HSC lineage output under unperturbed conditions in vivo. These experiments uncovered marked differences comparing in situ and post-transplantation hematopoiesis. These new developments raise several important questions, notably on the developmental fates HSC realize in vivo (as opposed to their experimental potential), and on the structure (routes and nodes) of hematopoiesis from HSC to peripheral blood and immune lineages. Answers to these questions (and in fact the deconvolution of any tissue) require the development of non-invasive, high resolution barcoding systems. We have now designed, built and tested a DNA-based barcoding system, termed Polylox, that is based on an artificial recombination locus in which Cre recombinase can generate several hundred thousand genetic tags in mice. We chose the Cre-loxP system to link high resolution barcoding (i.e. the ability to barcode single cells and to fate map their progeny) to the zoo of tissue- or stage-specific, inducible Cre-driver mice. Here, I will present the principles of this endogenous barcoding system, demonstrate its experimental and analytical feasibilities and its power to resolve complex lineages. The work program addresses in a comprehensive manner major open questions on the structure of the hematopoietic system that builds and maintains the immune system. This project ultimately aims at an in depth dissection of unique or common lineage pathways emerging from HSC, and at resolving relationships within cell lineages of the immune system.

2 500 000 €

Start date: 2017-07-01, End date: 2022-06-30