Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : TransfoPneumo (Horizon 2020, appel 2016, Consolidator grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: Biological Mechanisms, Structures and Functions
Entité participante : Université de Bordeaux — Pays : France — Rôle : Partner
Acronyme de l'entité : UBx
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 103418.74 €

Natural genetic transformation, first discovered in Streptococcus pneumoniae by Griffith in 1928, is observed in many Gram-negative and Gram-positive bacteria. This process promotes genome plasticity and adaptability. In particular, it enables many human pathogens such as Streptococcus pneumoniae, Staphylococcus aureus or Neisseria gonorrhoeae to acquire resistance to antibiotics and/or to escape vaccines. For natural transformation to occur, bacteria must develop a highly regulated physiological state called competence, during which a multiprotein machinery, designated as the transformasome, is specifically expressed. The transformasome drives the uptake of extracellular DNA and its subsequent integration into the bacterial genome. This intricate system can be divided into three functional entities: the transformation pilus, the DNA entry pore and the recombination apparatus. The architecture and function of the transformasome remains largely elusive. We propose to dissect the structure and function of this system in the human pathogen Streptococcus pneumoniae. We will combine four complementary approaches to attain our goal: (1) Molecular biology and biochemical studies in vitro (2) Structural biology on purified proteins or protein complexes using X-ray crystallography and cryo-electron microscopy (3) Structure-function studies in vitro and in vivo (4) Structural biology in situ using cryo-tomography. Overall, we believe this ambitious project will provide major insights to understand the molecular basis of bacterial transformation, a fundamental process in bacterial physiology. In addition, this project may provide new strategies to reduce pneumococcal adaptation during infection.

Mots-clés : membrane protein complexes
Projet ERC : DALI (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : University of Essex — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 302303.8 €

Natural language expressions are supposed to be unambiguous in context. Yet more and more examples of use of expressions that are ambiguous in context, yet felicitous and rhetorically unmarked, are emerging. In my own work, I demonstrated that ambiguity in anaphoric reference is ubiquitous, through the study of disagreements in annotation, that I pioneered in CL. Since then, additional cases of ambiguous anaphoric reference have been found; and similar findings have been made for other aspects of language interpretation, including wordsense disambiguation, and even part-of-speech tagging. Using the Phrase Detectives Game-With-A-Purpose to collect massive amounts of judgments online, we found that up to 30% of anaphoric expressions in our data are ambiguous. These findings raise a serious challenge for computational linguistics (CL), as assumptions about the existence of a single interpretation in context are built in the dominant methodology, that depends on a reliably annotated gold standard. The goal of the proposed project is to tackle this fundamental issue of disagreements in interpretation by using computational methods for collecting and analysing such disagreements, some of which already exist but have never before been applied in linguistics on a large scale, some we will develop from scratch. Specifically, I propose to develop more advanced games-with-a-purpose to collect massive amounts of data about anaphora from people playing a game. I propose to use Bayesian models of annotation, widely used in epidemiology but not in linguistics, to analyse such data and identify genuine ambiguities; doing this for anaphora will require novel methods. Third, I propose to use these data to revisit current theories about anaphoric expressions that do not seem to cause infelicitousness when ambiguous. Finally, I propose to develop the first supervised approach to anaphora resolution that does not require a gold standard as a blueprint for other areas.

Mots-clés : semantics,discourse,anaphora resolution,coreference,ambiguity,corpus annotation,games with a purpose,crowdsourcing,bayesian models of annotation
Projet ERC : ABLASE (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed matter physics
Entité participante : University of Cologne — Pays : Allemagne — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 63812.5 €

Naturally occurring optical phenomena attract great attention and transform our ability to study biological processes, with “the discovery and development of the green fluorescent protein (GFP)” (Nobel Prize in Chemistry 2008) being a particularly successful example. Although found only in very few species in nature, most organisms can be genetically programmed to produce the brightly fluorescent GFP molecules. Combined with modern fluorescence detection schemes, this has led to entirely new ways of monitoring biological processes. The applicant now demonstrated a biological laser – a completely novel, living source of coherent light based on a single biological cell bioengineered to produce GFP. Such a laser is intrinsically biocompatible, thus offering unique properties not shared by any existing laser. However, the physical processes involved in lasing from GFP remain poorly understood and so far biological lasers rely on bulky, impractical external resonators for optical feedback. Within this project, the applicant and his team will develop for the first time an understanding of stimulated emission in GFP and related proteins and create an unprecedented stand-alone single-cell biolaser based on intracellular optical feedback. These lasers will be deployed as microscopic and biocompatible imaging probes, thus opening in vivo microscopy to dense wavelength-multiplexing and enabling unmatched sensing of biomolecules and mechanical pressure. The evolutionarily evolved nano-structure of GFP will also enable novel ways of studying strong light-matter coupling and will bio-inspire advances of synthetic emitters. The proposed project is inter-disciplinary by its very nature, bridging photonics, genetic engineering and material science. The applicant’s previous pioneering work and synergies with work on other lasers developed at the applicant’s host institution provide an exclusive competitive edge. ERC support would transform this into a truly novel field of research.

Mots-clés : laser,micro laser,biophotonics,fluorescent protein,f rster transfer,biocompatibility,strong coupling,biologically inspired photonics,biologically produced photonics,biolaser,bionic
Projet ERC : MatEnSAP (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : University of Cambridge — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. Cambridge
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1960289.0 €

Nature has been harnessing solar energy to drive endergonic life-sustaining reactions such as photosynthesis for billions of years. However, the overall biological processes are inefficient despite the evolution of efficient enzymes for carrying out specific reactions. Currently, there is an urgent need to develop superior strategies for the large scale conversion of solar energy into a renewable chemical fuel through artificial photosynthesis, which uses the same fundamental science as natural photosynthesis. Here we integrate the strengths of both natural and artificial photosynthesis to explore novel pathways for efficient solar-to-chemical conversion, which are otherwise inaccessible to either field alone. In aim 1, we develop advanced materials and strategies for the rational integration of photosynthetic enzymes into photoelectrochemical cells. A platform will be established in which enzymes can be artificially coupled to light absorbers, and also be wired together to perform novel chemical reactions. In aim 2, we adapt advanced analytical techniques, including scanning electrochemical microscopy and time-resolved spectroscopy, to gain mechanistic insights into the nature, extent, and mechanism of the enzyme-material interaction. This will aid rational cell design and shed light into reaction bottlenecks. In aim 3, we wire the enzyme-electrodes together in rational combinations to arrive at novel and efficient pathways for performing solar-to-fuel conversions. We will demonstrate the efficient coupling of solar energy harvesting with water oxidation and proton/carbon dioxide reduction. This integrated approach will lead the emergent field of semi-artificial photosynthesis beyond conventional solar fuels research. It will probe into the strengths and weaknesses of biological processes, and be used to explore how other processes (e.g. nitrogen fixation, C–H bond activation) can be more efficiently re-wired or be coupled to photochemistry.
Projet ERC : DYNAPOL (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : University of Applied Sciences and Arts of Southern Switzerland — Pays : Suisse — Rôle : Partner
Acronyme de l'entité : SUPSI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

Nature uses self-assembly to build fascinating supramolecular materials, such as microtubules and protein filaments, that can self-heal, reconfigure, adapt or respond to specific stimuli in dynamic way. Building synthetic (polymeric) supramolecular materials possessing similar bioinspired properties via the same self-assembly principles is interesting for many applications. But their rational design requires a detailed comprehension of the molecular determinants controlling the assembly (structure, dynamics and properties) that is typically very difficult to reach experimentally. The aim of this project is to obtain structure-dynamics-property relationships to learn how to control the dynamic bioinspired properties of supramolecular polymers. I propose to unravel the molecular origin of the bioinspired behavior through massive multiscale modeling, advanced simulations and machine learning. First, we will develop ad hoc molecular models to study monomer assembly and the supramolecular structure of various types of self-assembled materials on multiple scales. Second, using advanced simulation approaches we will characterize the supramolecular dynamics of these materials (dynamic exchange of monomers) at high (submolecular) resolution. We will then study bioinspired properties such as the ability of various supramolecular materials to self-heal, adapt or reconfigure dynamically in response to specific stimuli. Our models will be systematically validated by comparison with the experimental evidence from our collaborators. Finally, we will use machine learning approaches to analyze our high-resolution simulations and to identify the key monomer features that control and determine the structure, dynamics and dynamic properties of a supramolecular material (i.e., structure-dynamics-property relationships). This research will produce unprecedented insight and fundamental models for the rational design of artificial dynamic materials with controllable bioinspired properties.

Mots-clés : molecular simulation,multiscale modeling,self assembly,bioinspired,dynamic materials,supramolecular polymer,coarse graining,structure property relationships,responsive,adaptive materials
Projet ERC : EMERG-ANT (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1439893.0 €

Navigation is one of the most crucial and most challenging problems animals face. Behavioural analyses have shown that animals make use of a number of different mechanisms to navigate, but very little is known of how spatial information is processed and integrated by the brain. This project will exploit the stunning ability of ants in learning long visual routes to investigate the mechanisms of navigation in a brain numerically much simpler than vertebrate. We will combine an ecological approach with state-of-the-art technologies to enable a thorough control of sensory-motor cues while the ant is navigating in virtual-reality reconstructions of its natural environments. This new and powerful method will enable us to dissect the mechanisms underlying the emergence of navigational behaviours by performing straightforward manipulations. The results will be modelled in the light of insect neurobiology and integrated into an increasingly complete neural architecture. This neural architecture will be embedded into an agent navigating in the same virtual-reality environment as the real ants for testing. The advantage of such an inter-disciplinary approach is that failures of our agent will help us identify gaps in our knowledge and thus fuel new experimentation. Reciprocally, our agent will become increasingly refined in the light of incoming experimental results. This will create a positive feedback towards a complete, multi-level understanding of navigation in the wild. The findings will inspire new robust solutions for navigational problems that can be applied to bio-robotics.
Projet ERC : QuinaWorld (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1620711.5 €

Neanderthals disappeared ~40 000 years ago; although they have received significant public and academic attention, their evolution and behavioural diversity remain little known. Quina Mousterian designates a singular Neanderthal lithic industry; it is often associated with specific, large game seasonal hunting (herds of reindeer). Particular mobility patterns and elaborate carcass processing suggest an image of a complex, intriguing cultural entity. Outside its core area (SW France), Quina Mousterian is also mentioned in different parts of Europe. My project will first aim at testing the hypothesis that a Quina cultural entity existed, i.e. that the occurrences of Quina Mousterian correspond to a short period of time and can thus be attributed to affiliated or connected groups of Neanderthals. A widely interdisciplinary consortium will then aim at defining the characteristics of the assumed Quina entity, how it evolved in time and potentially diffused in space across Europe. High-resolution OSL dating, based on new Bayesian models allowing cutting-edge uncertainties (~2-3%) for periods beyond the radiocarbon dating range, will be implemented to obtain a tight chronological framework and tie the archaeological record with palaeo-environments. Tool production and use, as a function of raw material availability and procurement, will be studied based on a technological and techno-functional approach. The influence of varying climates and environments on the Quina subsistence strategies – approached in terms of both food acquisition and storage – will be deciphered. Palaeo-anthropological and genetic studies will aim at defining the biological identity of the makers of Quina Mousterian, and possible human migrations associated with its diffusion. Eventually, the Quina World project will allow discussing the potentially oldest regionalisation and cultural diffusion patterns of Europe, and shed new light on the array and complexity of Neanderthal behaviours.

Mots-clés : luminescence dating,middle paleolithic,neanderthal,subsistence strategies,bayesian modelling
Projet ERC : EARLY-ADAPT (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : CERCA Institution — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CERCA;I-CERCA
Type d'entité : Recherche
Financement ERC de l'entité : 1999999.0 €

Nearly 8% of deaths are attributable to ambient temperatures, but little is known about the future impact in a warming world. I conducted studies in high-impact journals showing that this death toll can be largely reduced if a substantial degree of adaptation to ambient temperatures takes place. Adaptation strategies have been increasingly implemented in Europe in recent years, but the last IPCC report indicated that evidence of their effectiveness is still lacking. I postulate that adaptation measures are starting to generate positive benefits for the wellbeing of societies, including an adaptive response to climate change, but the degree to which they are effectively reducing human vulnerability is largely heterogeneous among and within European societies. I aim to describe the major sources of vulnerability, and if, which and to what extent societies have already started to adapt to changing conditions. Towards this aim, I will use predictive models to quantify the potential beneficial effect of early adaptation strategies through the attribution of temporal changes in human vulnerability. For that purpose, I will generate a massive database with daily counts of death for different subdomains and spatial resolutions, including data for countries, regions, cities and neighbourhoods, together with the best available climate, air pollution, influenza, socioeconomic and demographic datasets. In addition, I will combine the best epidemiological techniques with weather and climate forecasts and climate change simulations to perform an integrated predictability assessment of mortality risks and provide a realistic re-estimation of the likely range of future heat- and cold- attributable mortality. Expected results will provide a better understanding of the real impact of adaptation measures, which is key for decision-making and the design of strategies minimizing the negative impacts of future temperature rises in Europe.

Mots-clés : global warming,climate impact and predictability,temperature,urban heat island effect,air pollution,risk factors,attributable mortality,vulnerability,early adaptation,resilience,europe
Projet ERC : NeuralCellTypeEvo (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : European Molecular Biology Laboratory — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : EMBL
Type d'entité : Recherche
Financement ERC de l'entité : 2500000.0 €

Nervous system evolution involved multiple cellular innovations, enabling fast synaptic transmission, novel sensory modalities, and complex forms of neural connectivity. These innovations were distributed to an ever-increasing number of neural cell types, each specified and maintained by the combinatorial activity of transcription factors. When, where, and how did this complexity arise? This proposal aims at resolving the history of cell type diversification that led to this complexity, from the birth of the first neurons to the many families of neuron types that exist today. Our emphasis will be on reconstructing the cellular diversity in the ancestor of bilaterian animals and finding the key molecular innovations that drove early nervous system complexity. Towards this aim, we will first use whole-body single-cell RNAseq, in combination with a spatial expression atlas at cellular resolution, to comprehensively characterise cell types in the model annelid Platynereis dumerilii, a genetically tractable, slow-evolving bilaterian. We will then generate and compare similar datasets from diverse bilaterians and non-bilaterian outgroups to map the history of neuronal cell type diversification and infer the key regulatory and functional innovations that gave rise to the first bilaterian nervous system. For several such regulatory innovations, we will experimentally validate transcription factor binding to effector gene loci via superresolution microscopy and chromatin immunoprecipitation. We will also investigate neuron family-specific protein complexes, their subcellular localization, and neural functions via biochemical and proteomics approaches, correlative microscopy and loss-of-function analyses. This analysis of neuronal cell type diversity will for the first time trace the evolutionary history of nervous system complexity, unravelling when, where and how key neuronal innovations have driven the success of bilaterian nervous systems.

Mots-clés : evo devo,cell type evolution,single cell genomics,nervous system evolution
Projet ERC : MemoryDynamics (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Friedrich Miescher Institute — Pays : Suisse — Rôle : PI
Acronyme de l'entité : FMI
Type d'entité : Recherche
Financement ERC de l'entité : 2499604.0 €

Nervous systems produce adaptive behavior, arguably their most important function, through learning and memory. Memories ensure that what is learned will be available for later retrieval. Upon the initial learning process, synaptic plasticity important for memory consolidation is triggered within minutes, but whether, and in which form memories will be retained more permanently can be influenced by information and insights gained after the initial trigger. Learning and memory have been studied extensively, but we still know very little about the mechanisms through which memories are shaped after acquisition. Here we hypothesize that instead of simply reflecting requirements to produce long-term memory traces, cascades of plasticity processes induced at the time of acquisition might also reflect systems requirements for updating of new relevant information, as well as selection of potentially useful memories that need to enter the process of long-term consolidation. Recent advances in neuroscience have provided powerful novel means to reveal, analyze and manipulate memory traces in the living brain, from single neurons to systems, and to interrogate their function. This research program will address the functional roles of learning-related plasticity processes unfolding subsequent to acquisition in learning and memory. We will investigate how hippocampal memories are shaped during several hours after acquisition through network activity and addition of new information through experience, and how these processes involve unique roles for dorsal hippocampus, and for dedicated neuronal circuits. Furthermore, we will study how shaped memories are then long-term consolidated, including the key role of ventral hippocampal circuitry, and how memories are further modified through subsequent learning. This research will produce fundamentally novel insights into how learning leads to adaptive behavior through writing and editing of memories.

Mots-clés : memory consolidation,plasticity,neuronal circuits,genetic control,cell identity,learning