Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : ReceptorPAINT (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: Biological Mechanisms, Structures and Functions
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 750000.0 €

Targeting cell surface proteins to alter cellular behavior is a major aim of many therapeutics. Recently approved immunotherapeutic drugs trigger anti-tumor immunity by disrupting key cell surface proteins that guide immune cell interactions. Despite the cell surface representing a major site of drug action, its nanoscale organization remains poorly characterized. The main reason for this is largely due to technical limitations of current fluorescence and super-resolution imaging approaches, which do not allow high-throughput measurements of the spatial localization and interaction of hundreds of proteins with true single-protein- resolution on cell surfaces. We here propose to develop exactly such a disruptive capability by advancing recently developed DNA-PAINT microscopy to enable the visualization and quantification of all relevant cell surface proteins at single-protein-resolution. We will achieve this by innovating DNA-PAINT to enable isotropic 1-nm-resolution, develop DNA-based protein binders against all cell surface proteins, and devise multiplexing capabilities to resolve them with single-protein-resolution over large fields of view, reaching the ultimate goal of enabling Imaging Receptomics. We will then apply this to test the central hypothesis that surface protein architecture and patterning on immune and tumor cells dictates the outcome of their interactions. We will map the nanoscale organization of hundreds of key immunomodulatory surface proteins and their corresponding ligands on key interacting pairs of immune cells relevant to current immunotherapy approaches (dendritic cells and T cells), as well as tumor cells. This will yield fundamental insights into the molecular architecture of their interactions and potentially enable the future development of more refined “pattern”-based immunotherapeutics. Collectively, this highly multidisciplinary and novel approach has the potential to be ground-breaking across a range of research fields.

Mots-clés : super resolution microscopy,dna nanotechnology,cell surface receptors,receptor tyrosine kinases,immune checkpoints
Projet ERC : CAREER (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : University of Amsterdam — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : UvA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499422.0 €

Technological changes and the automation of occupational tasks present societies with a challenge: Is it still sensible to provide students with occupation-specific (vocational) education? Or are students with general educational qualifications better equipped for the future, given that what is demanded in the labor market is under rapid change? While a large literature has shown that graduates with vocational training have a comparatively smooth transition from school to work, it has exclusively focused on the early career. We do not know how and why labor market outcomes vary over the life course, or how careers are affected by changing labor markets. CAREER investigates how labor market demands change, and how these changes in the macro context affect individual workers. It takes an innovative career perspective to study how and why labor market returns to vocational and general education vary over the life cycle. Its core hypothesis is that vocational graduates have a late-career disadvantage because their occupation-specific skills hinder labor market mobility, particularly when labor market demands alter quickly. CAREER is a comparative project, and studies six countries: Germany, the Netherlands, Poland, Sweden, Switzerland, and the United Kingdom. Using computational methods on unique data of millions of historical job vacancy texts, we describe how labor markets are changing. Relying on high quality panel data we map how careers of vocational and general graduates develop in changing labor markets. Using interviews, and factorial experiments we expose the theoretical mechanisms that drive career effects. By extending the observation window from the early to the full career, CAREER shows how workers with specific or general qualifications perform in rapidly changing labor markets. This will not only enrich our understanding of the link between education and the labor market, it will also inform policy makers on a future-proof education system.

Mots-clés : social stratification,education,occupations,labor market
Projet ERC : Scale-FreeBack (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Institut national de recherche en sciences et technologies du numérique — Pays : France — Rôle : Partner
Acronyme de l'entité : Inria
Type d'entité : Recherche
Financement ERC de l'entité : 31511.0 €

Technology achievements were typically built upon fundamental theoretical findings, but nowadays technology seems to be evolving faster than our ability to develop new concepts and theories. Intelligent traffic systems benefit from many technical innovations, for example. Mobile phones, radars, cameras and magnetometers can be used to measure traffic evolution and provide large sets of valuable data. Vehicles can communicate with the network infrastructure, as well as each other. However, these huge technological advances have not been used to the full so far. Traffic lights are far from functioning optimally and traffic management systems do not always prevent the occurrence of congestions. So what is missing? Such systems affect our daily life; why aren’t them on pace with technology advances? Possible because they have become far more complex than the analytical tools available for managing them. Systems have many components, communicate with each other, have self-decision-making mechanisms, share an enormous amount of information, and form networks. Research in control systems has challenged some of these features, but not in a very concerted way. There is a lack of “glue” relating the solutions to each other. In the Scale-FreeBack project, it is proposed to approach this problem with a new holistic vision. Scale-FreeBack will first investigate appropriate scale-free dynamic modeling approaches breaking down system’s complexity, and then develop control and observation algorithms which are specifically tailored for such models. Scale-FreeBack will also investigate new resilient issues in control which are urgently required because of the increasing connectivity between systems and the external world. Road traffic networks will be used in proof-of-concept studies based on field tests performed at our Grenoble Traffic Lab (GTL) and in a large-scale microscopic simulator.
Projet ERC : TelMetab (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : The Francis Crick Institute — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 2118431.0 €

Telomeres are specialised nucleoprotein structures that protect chromosome ends from degradation and promiscuous DNA repair activities. Critically short telomeres give rise to Dyskeratosis Congenita and Hoyeraal-Hreidarrson Syndrome (HHS), highlighting the clinical importance of maintaining telomeres. Telomeres also progressively shorten with each cell division, eventually triggering cellular senescence. Although telomerase is able to extend telomeres to solve the “end replication problem”, its re-expression is a major route to cancer cell immortalization. Hence, telomeres and telomerase must be subject to exquisite regulation to maintain telomere homeostasis and organismal function. We have previously implicated the Fe-S helicase RTEL1 in maintaining vertebrate telomeres, which is frequently mutated in HHS. In this ERC proposal, we will employ proteomic methods, super-resolution microscopy, biochemistry and genetic approaches to: i) investigate why telomerase is the cause of telomere dysfunction in the absence of Rtel1, ii) how RTEL1 is controlled during the cell cycle, and iii) how this process is compromised by Rtel1 mutations in HHS. By establishing quantitative PICh to interrogate telomere composition in unprecedented detail, we have uncovered an unappreciated compensation between RTEL1 and ATRX at telomeres and also identified SLX4IP as a key regulator of telomere recombination, which we will characterize at a mechanistic level. We will extend our expertise in quantitative PICh and genome-wide CRISPR screens to identify novel factors that respond to or are lost from telomeres as a result of: i) induction of DNA damage at telomeres, ii) inhibition of p97 segregase, and iii) the onset of senescence. Our proposal will lead to a greater understanding of the causes/consequences of telomere dysfunction in multiple contexts, the factors that mitigate these effects to maintain telomere homeostasis and how these processes are compromised in human diseases.

Mots-clés : telomeres,dna repair,homologous recombination
Projet ERC : ThermalMR (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Max Delbrück Center for Molecular Medicine — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MDC
Type d'entité : Recherche
Financement ERC de l'entité : 2043804.98 €

Temperature is a physical parameter with diverse biological implications and crucial clinical relevance. With an ever increasing interest in thermal applications, non-invasive in vivo methods to modulate temperature and characterize subsequent effects are imperative. Magnetic resonance (MR) is a mainstay of diagnosis but lacks inherent means for focal thermal modulation. Ultrahigh field (UHF) MR employs higher radio frequencies (RF) than conventional MR and has unique potential to provide focal temperature manipulation and high resolution imaging (ThermalMR). Our simulations show that we can adapt an UHF- MR device to generate heat in highly focused regions of tissue by using high-density RF transmitter arrays. This new instrument will provide a revolutionary method for precise in vivo temperature manipulations. To establish high-fidelity thermal dosimetry, we will investigate pioneering strategies that exploit electrical and heat transfer tissue properties. For thermal dosage control, novel methods of MR thermometry will be developed. The capacity of ThermalMR for thermal intervention will be demonstrated in model systems. Its efficacy for drug release will be explored using new thermo-responsive nanocarriers loaded with fluorinated probes, exquisitely quantifiable with 19F MR. The applicability and safety of ThermalMR will be demonstrated in animal models followed by a feasibility study in healthy subjects. To link thermal responses of MR contrasts with molecular signatures, gene expression profiling will be performed. The aim is to understand the thermal properties of healthy and pathological tissues and explore the use of temperature modulation as a therapeutic tool. ThermalMR will eradicate the main barriers to the study and use of temperature - a critical dimension of life that is of intense clinical interest, but so far very poorly understood. This approach opens an entirely new research field of thermal phenotyping: where physics, biology and medicine meet.

Mots-clés : biomedical imaging,magnetic resonance imaging  mri,ultrahigh field magnetic resonance,radiofrequency antennae
Projet ERC : FluctEvol (Horizon 2020, appel 2015, 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 : 1499665.0 €

Temporal environmental variation in natural systems includes a large component of random fluctuations, the magnitude and predictability of which is modified under current climate change. The need for predicting eco-evolutionary impacts of plastic and evolutionary responses to changing environments is still hampered by lack of strong experimental evidence. FluctEvol aims at shedding a new light on population responses to stochastic environments, and facilitating their prediction, using a unique combination of approaches. First, theoretical models of evolution and demography under a randomly changing optimum phenotype will be designed and analysed, producing new quantitative predictions. Second, statistical methodologies will be developed, and employed in meta-analyses of long-term datasets from natural populations. And third, large-scale and automated experimental evolution in stochastic environments will be carried out with the micro-alga Dunaliella salina, an extremophile that thrives at high and variable salinities. We will manipulate the magnitude and predictability of fluctuations in salinity, and use high-throughput phenotyping and candidate-gene sequencing to analyse the evolution of plasticity for traits involved in salinity adaptation in this species: glycerol and carotene content. We will thus combine the benefits of experimental evolution in microbes (short generations, ample replication) with a priori knowledge of ecologically relevant adaptive traits, allowing for hypothesis-driven experiments. The success of this project in increasing our predictive power about eco-evolutionary dynamics is warranted by the experience of the PI, at the interface between theoretical and empirical approaches. Our experiments will have relevance beyond academia, as we will modify through evolution the plasticity of traits (accumulation of energetic cell metabolites) that are direct targets for bioindustry, thus potentially overcoming current limitations in productivity.

Mots-clés : evolutionary theory,experimental evolution,contemporary evolution,phenotypic plasticity,genetics of adaptation
Projet ERC : lncImpact (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Weizmann Institute of Science — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

Tens of thousands of loci in mammalian genomes produce long RNAs that do not go on to produce functional proteins, and are collectively called long noncoding RNAs (lncRNAs). A growing number of these have been shown to be important in various biological processes and human diseases. How lncRNA genes function and, specifically, how their production, maturation, or RNA products affect other gene regulatory processes remains poorly understood and is the focus of this proposal. We will build on a rich arsenal of tools from molecular biology, computational biology, high-throughput screens, cell biology, and mouse genetics, develop new methodologies, and dissect the rules underlying the functions of three lncRNA circuit classes that we identified as representatives of large groups of lncRNAs. Namely, lncRNAs that: (i) regulate gene expression in cis at a distance; (ii) affect the activity of proximal promoters; or (iii) modulate the function of RNA binding proteins that regulate mRNAs post-transcriptionally. We propose a roadmap in which we will use minimal synthetic systems to build on the insights from the representative circuits, identify yet uncharacterized lncRNAs with similar modes of action, and derive a codebook of how lncRNA gene loci impact gene regulatory networks and sculpt gene expression in mammalian cells. The proposed research has the potential of producing conceptual breakthroughs including: (1) Understanding how RNA production poises genomic loci for timely gene activation upon cues for neuroregeneration and learning. (2) Recipes for therapeutic perturbations that will tune promoter activity for balancing gene expression in haploinsufficient or over-producing cells. (3) Decoding how a single lncRNA species can disrupt a network of post-transcriptional control by RNA binding proteins.

Mots-clés : long noncoding rnas,enhancers,post transcriptional regulation,crispr screens
Projet ERC : THRESHOLD (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : Swedish University of Agricultural Sciences — Pays : Suède — Rôle : PI
Acronyme de l'entité : SLU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2167635.0 €

Terrestrial ecosystems are important in providing key services to humankind, but under global warming the provisioning of such ecosystem services is at risk. However, there is little consensus on how the functioning of terrestrial ecosystems will change under projected scenarios of global warming, or when we will reach or surpass thresholds and tipping points. This is largely because most studies have failed to unravel ecosystem responses to increasing temperatures in terms of the underlying non-linear responses of plants, soil organisms, and their communities. Since plants and their associated soil organisms (i.e., pathogens, mutualists, and decomposers) can vary in their responses to temperature change, global warming may disrupt or decouple interactions among coexisting and co-evolved species. This may have unforeseen consequences for key ecosystem functions, such as carbon and nutrient cycling. THRESHOLD will use a novel cross-disciplinary approach to advance our fundamental knowledge of how non-linear temperature responses transcend different levels of ecological organization. Specifically, this project aims to: 1) Establish a global network of forest-tundra and forest-alpine ecotone sites, to assess how responses of ecosystem carbon and nutrient cycling to global warming will be pushed across thresholds and tipping points. 2) Perform mesocosm experiments under different temperatures, to estimate how ecosystem process responses to global warming can be predicted from the reordering of plant and soil communities, as well as from the functional traits that they possess and express. 3) Reveal how community responses to warming and extreme temperatures can be predicted from the physiological responses of their component species. To achieve these aims, this work will utilize a powerful approach that harnesses an array of cutting-edge tools, and it will advance our conceptual understanding in an area of urgent importance for ecology and society.

Mots-clés : ecotone,extreme temperature,global network,global warming,non linearity,plant soil interactions,threshold,tipping point
Projet ERC : REALM (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : Imperial College London — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499615.0 €

Terrestrial ecosystems respond to changes in climate and the atmospheric environment, which they in turn help to regulate. As global change has become an international concern, high expectations have been laid on Earth system models with embedded ecosystem and biophysical land-surface components to deliver reliable, quantitative predictions of large-scale changes in ecosystems and their feedbacks to the climate system. But the lack of established quantitative theory for many fundamental processes – such as the long-term effects of temperature on primary production and carbon allocation, the sustainability and nutrient requirements of CO2 ‘fertilization’, and the regulation of green vegetation cover and its water use – has made such expectations impossible to fulfil. As a result, numerical models of land ecosystem processes continue stubbornly to disagree both with one another, and with benchmark data sets. This impasse can be overcome, but not without re-thinking modelling practice. Theory must be re-instated as the required link between observations and models. Multidisciplinary data resources now available should be used far more extensively and creatively. Observational and experimental results should be integral to model development, not merely used for ‘end-of-pipe’ testing of complex, poorly constrained models. I propose to develop a comprehensive, next-generation vegetation model using eco-evolutionary optimality hypotheses to generate testable predictions, and multiple data sources to provide tests. Initial results have demonstrated the remarkable power of this ‘strong inference’ approach to explain patterns seen in nature. The project will transform the practice of global vegetation and land-surface modelling and in doing so, establish the foundations of a more robust, quantitative understanding of the role of terrestrial ecosystems in Earth System dynamics.

Mots-clés : dynamic global vegetation model,earth system model,plant functional traits,optimality,carbon cycle,acclimation,ecohydrology,land surface model,primary production,biome distributions,carbon allocation
Projet ERC : DOC (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : Partner
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 101085.0 €

Terrestrial life is based on organic chemistry, on the complex combination of relatively small molecules containing less than 50 atoms of carbon and other elements in smaller quantities. Some of these bricks, notably amino acids, are found in meteoritic and cometary material, a fact (among others) which led the Nobel laureate C. de Duve to conclude that “the seeds of life are universal” and “life is an obligatory manifestation of matter, written into the fabric of the Universe”. The objective of the DOC project is to understand the dawn of organic chemistry, namely the start of organic chemistry in systems similar to the progenitor of the Solar System, with the ultimate goal to understand how organic chemistry builds up and evolves in these systems and, consequently, to understand how universal the chemical seeds of life are. To achieve this objective, I propose to build a reliable theory for the organic chemistry in nascent Solar type systems, by combining in a tightly coordinated way new ground-breaking astronomical observations, quantum chemistry computations, astrochemical/chemi-physical models and sophisticated analysis tools. The DOC project is based on (i) a mine of first-class data from already awarded Large Programs at IRAM and from a plethora of smaller proposals at IRAM, ALMA and APEX, (ii) new state-of-the-art quantum chemistry computations to understand astrochemistry reactions at the molecular level, and (iii) models and tools to fully exploit the new data and computations. My ambition is to provide a reliable theory not only for the astrochemical and the star and planet formation communities, but also for the extragalactic one. Indeed, the new highly sensitive spectral observations from facilities like IRAM, ALMA and, in the future, SKA will inevitably contain lines from many organic molecules. DOC ambition is to ultimately allow us to understand how organic chemistry unfolds in the Universe.