Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : MitoMethylome (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: Biological Mechanisms, Structures and Functions
Entité participante : Karolinska Institutet — Pays : Suède — Rôle : PI
Acronyme de l'entité : KI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499999.25 €

Mitochondria and mitochondrial function have gained increased attention within a wide range of clinical and scientific specialities, but exactly how mitochondria impact the rest of the cell is less well understood. Not only are mitochondria implicated in a range of rare genetic disorders, but dysfunction of mitochondria or reduced bioenergetic capacity has been associated with common diseases including cancer, heart failure, neurodegeneration and diabetes mellitus, as well as natural ageing. It is becoming increasingly clear that mitochondrial dysfunction is not only a downstream event in these conditions, but plays an important role in disease progression and pathology. S-adenosylmethionine (SAM) is the dominant methyl group donor within our cells, required for a diverse set of post-translational modifications, nucleotide methylations or the synthesis of co-factors and metabolites. Mitochondria play an important part in SAM synthesis, and mitochondrial function has recently been shown to influence cellular methylation. Approximately 30% of the cellular SAM pool is located within mitochondria, advocating a central role for mitochondria in cellular methylation. The advancements in genome sequencing techniques, unprecedented depth of modern mass spectrometry analyses and our possibility to efficiently generate model systems, provides a rare opportunity to comprehensively study the role of both SAM and mitochondria in health and disease. This project plan describes the genetic, molecular, metabolic and proteomic analysis of fruit fly and mouse models with mitochondrial dysfunction and disrupted intra-mitochondrial SAM levels to identify the mitochondrial methylome, its relevance towards other cellular functions and its impact on the epigenetic control of gene regulation. My extensive research on mitochondrial function, as well as working as a physician with patients suffering from inborn errors of metabolism gives me a unique perspective in this project.

Mots-clés : inborn errors of metabolism,mitochondria,methylation,s adenosylmethionine,drosophila melanogaster,mouse,molecular biology,proteomics,mitochondrial disease,metabolism,bioenergetics
Projet ERC : MITOsmORFs (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: Biological Mechanisms, Structures and Functions
Entité participante : University of Freiburg — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1094166.25 €

Mitochondria are essential organelles with crucial roles in cellular energy metabolism, Fe-S cluster biogenesis, signaling and apoptosis. Mitochondrial dysfunction causes encephalomyopathy and neurodegenerative diseases. Mitochondria possess a remarkably high content of small proteins compared to other cellular compartments. About one third of the cellular proteins ≤15 kDa characterized to date are located in mitochondria. Functional examples of such small proteins cover the whole mitochondrial biology like cristae morphology, Fe-S cluster formation, metabolite transport, protein biogenesis and respiration. However, the intracellular localization and function of most small proteins is unknown. These small proteins constitute one third of the uncharacterized open reading frames and even three quarters of the dubious open reading frames in the model organism budding yeast. Taken together we predict that more than 10% of the mitochondrial proteome deserves to be discovered. In an initial study we demonstrated the mitochondrial localization of several uncharacterized small open reading frame (smORF) proteins. MITOsmORFs aims to identify over 100 novel small mitochondrial proteins. MITOsmORFs will determine the submitochondrial localization and the functional role of the novel mitochondrial proteins by genetic, proteomic, metabolomic and lipidomic analysis, including interaction mapping and characterization of mitochondrial activities in vivo and in organello to explore the unknown biology of smORF proteins localized to mitochondria.

Mots-clés : mitochondrial biogenesis,mitochondrial function,mitochondrial proteins
Projet ERC : UPRmt (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Board of the Swiss Federal Institutes of Technology — Pays : Suisse — Rôle : PI
Acronyme de l'entité : ETH Zurich
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

Mitochondria—organelles specialized in energy harvesting through oxidative phosphorylation (Oxphos)—critically influence metabolism, health and lifespan. Evolved from endosymbiotic proteobacteria, mitochondria retained the vestige of the bacterial genome, the mitochondrial DNA, which encodes 13 subunits of the Oxphos complexes, while the remaining ~80 Oxphos components and the rest of the mitochondrial proteome are encoded on nuclear DNA, translated in the cytoplasm and imported in the mitochondria. The control of the mitochondrial proteome by two genomes exposes these organelles to proteotoxic stress in case of an imbalance between the nuclear- and mitochondrial-encoded proteins. Upon such stress, several mitochondrial protein quality control (mtPQC) pathways, including the mitochondrial unfolded protein response (UPRmt), will sense, transmit and re-establish mitochondrial proteostasis through mitonuclear regulatory circuits. Although a robust UPRmt circuit improves health and lifespan in C. elegans, much less is known about mtPQC in vertebrates. We propose here to characterize UPRmt pathways across 3 species by: (1) mapping mammalian UPRmt genes and networks in vivo after the induction of the UPRmt in a large murine genetic reference population at 3 different times throughout life with 2 different inducers; (2) integrating these UPRmt networks with a wide set of clinical, mitochondrial, and molecular phenotypes collected throughout life to establish links between UPRmt mechanisms and health- and lifespan; (3) mechanistically validating the most important UPRmt pathways, using loss-of-function studies in cells, worms and mice; and (4) clinically translating promising UPRmt hits, using genetic association studies in human cohorts. The insight gained will mechanistically define the UPRmt networks from worms to humans and will provide the next step in translating the benefits of activating the UPRmt—initially observed in invertebrates—into targeted human therapies.

Mots-clés : bioenergetics,mitochondria,stress response,complex trait genetics,proteostasis,uprmt,genetic reference populations
Projet ERC : RESOLVENCY (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : Freie Universität Berlin — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : FU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1492348.0 €

Modern capitalism is essentially built on the institution of debt. The unlimited conception of debt reinforces an infinite growth logic and drives economic, political, cultural and ecological unsustainability. A crucial research question is how to constitute debt as more sustainable socio-economic medium. The RESOLVENCY project aims to shape a new (socially) reflexive debt paradigm by rethinking insolvency law as reflexive (democratic) debt deliberation. The project intends to set up a global theory of debt deliberation (for firms, consumers and states), which outlines a new RESOLVENCY paradigm for insolvency law reintegrating over-burdened debtors into the economic system (making them ‘re-solvent’) and incorporating other social (political, cultural, ecological) perspectives. ‘Resolving’ debt conflicts requires a collective procedure including debtor, creditors and all other private (employees, inhabitants) and public (communities, environment) interests involved. Advancing PI’s novel ‘discursive normative grammar’ (DNG) methodology and combining it with empirical methods, the project has four main objectives: (A) to reconstruct a universal argumentative frame (an insolvency DNG) for debt deliberation integrating normative principles (values) from corporate, consumer and sovereign insolvency theories across different jurisdictions; (B) to newly classify insolvency laws worldwide with a global comparative insolvency law theory based on this DNG; (C) to model and experiment with legal designs of reflexive debt deliberation procedures (RESOLVENCY law); and (D) to outline a model of reflexive debt (RE:DEBT) and analyse its ex ante effects on credit markets. The project does not only impact any legal and economic research on insolvency, but also debt theory in all social and sustainability sciences. In advancing PI’s DNG method, it enhances general understanding of deep normative architectures of legal reasoning and its constitutional effects for society at large.

Mots-clés : comparative insolvency law,debt theory,discourse theory,discourse analysis,systems theory,legal institutionalism,varieties of capitalism,law and development,heterodox economics,critical legal studies,sustainability science,sustainable debt
Projet ERC : HEAT (Horizon 2020, appel 2018, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
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 : 148728.0 €

Modern electronic devices have flourished because of the relentless development of new lithographic processes that result in ever higher and more compact computing power. However, this increases the amount of heat generated in a decreasing volume. As a result the computing power of many modern processors is truncated to avoid thermal damage. The preferred cooling technology for portable electronic devices are heat pipes. While this technology allows for impressive cooling performances, heat pipes have essentially remained unchanged for the past four decades, and are unable to satisfy the cooling requirements of modern processors. This project seeks to maximize the performance of heat pipes made using a new ultra-fast co-electroplating process that allows for the fabrication of an entirely new type of heat pipe material. Specifically, the developed process allows fabrication of 3D foams with microscale geometries (microfoams) that are made out of a carbon nanotube-copper composite. These foams exhibit capillary driven flowrates 250% that of commercial heat pipe foams, which is expected to provide a similar step-change improvement in heat pipe cooling power. The fabrication process itself is also disruptive because it enables an unprecedented control over the metal foam porosity and leverages the ultra-high thermal conductivity of the used nanoparticles. Further, our process is more energy efficient than current thermal sintering processes and it potentially allows for a continuous fabrication process. Because of the combined advantages in cooling performance and efficiency of the manufacturing process, this developed technology could displace current heat pipes. However, to take this technology forward, it requires support from this ERC-POC project to study the scale-up of the manufacturing process as well as to develop heat pipe demonstrators.

Mots-clés : heat pipes,thermal management,hierarchical materials,nanotechnology,carbon nanotubes
Projet ERC : HBIS (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Vrije Universiteit Amsterdam — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : VU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499482.5 €

Modern innovations such as soap, condoms, and indoor plumbing have allowed billions of people to reduce their contact with viruses and bacteria and, as a result, dramatically increase length and quality of life. But how did members of the genus homo avoid pathogens for the two million years that preceded these technological innovations and, more broadly, discoveries that infectious disease is caused by microbes? And, importantly, how do any natural behavioral defenses against pathogens impact our behavior in the modern world? Recent research and theory in the field of evolutionary psychology suggests that natural selection has shaped a human behavioral immune system (HBIS)—a suite of psychological mechanisms, ranging from aspects of our olfactory systems (e.g., that detect specific chemical compounds) to our emotion systems (e.g., the emotion disgust) and our learning systems (e.g., conditioned aversions to foods) that are coordinated for a common function: to detect and motivate the avoidance of pathogens. Given that myriad universal human behaviors connote some pathogen risk—including interpersonal contact, mating, and eating—gaining a holistic understanding of the HBIS has the potential to offer critical new insights into multiple fundamental aspects of human nature. Here, I utilize an interdisciplinary approach to answer three foundational, yet currently opaque questions concerning the nature of the HBIS, including: (1) Where does trait variation in HBIS activation come from? (2) What effect does the HBIS have on behavior when cues to pathogens are detected? and (3) How does the HBIS facilitate learning of avoidance and rejection? To answer these questions, I propose an array of methodologically diverse studies to investigate how trait HBIS activation shapes rejection versus acceptance of innovations, how state HBIS activation can be harnessed to promote the use of health-promoting technologies, and how the HBIS can be leveraged for shaping dietary behavior.

Mots-clés : evolutionary psychology,personality,emotion,health,behavioral genetics
Projet ERC : STREAMLINE (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
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 : 1495625.0 €

Modern photonic systems increasingly rely on complex nonlinear optical processes at the foundation of demanding applications spanning advanced light source development, metrology and imaging. Importantly, current flagship imaging systems are based on nonlinear light-matter interactions provided by specialized lasers requiring complex operation and lacking tunability: means of controlling nonlinear phenomena and interactions are restricted, and reaching the ideal settings for a specific application can prove extremely challenging. In this context, optical excitations can be inefficient (with e.g. excessive power or spectral coverage) and versatile means to drive coherent control of light properties are highly sought-after, for they provide the main building blocks for advanced imaging techniques. However, such control is currently constrained to few degrees of freedom provided by complex components ultimately hindering the accessible optical parameter space. The realization of versatile, efficient and practical optical sources in compact forms would thus represent a fundamental revolution. STREAMLINE constitutes an ambitious multidisciplinary program aiming to push forwards the development of 'smart photonic sources' for the creation of a promising new research field merging ultrafast nonlinear optics and computational imaging. The envisioned architecture, combining integrated and fibered components, will explore new multimode and input-dependent nonlinear dynamics via dedicated machine-learning schemes. Together with suitable monitoring techniques, fully reconfigurable and tailored optical wavepackets (with ‘on-demand’ spectral, temporal and spatial properties), will be exploited towards disruptive nonlinear imaging and metrology techniques. Besides providing user-friendly operation with improved performances, blueprint dynamical imaging with custom light-matter interactions will unlock access to novel deep-learning strategies towards biological sample histology.

Mots-clés : nonlinear optics,ultrafast photonics,integrated optics,fibre optics,solitons,complexity,nonlinear dynamics,smart systems,beam shaping,optoelectronics,machine learning,imaging,metrology
Projet ERC : SVIS (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Tel Aviv University — Pays : Israël — Rôle : PI
Acronyme de l'entité : TAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499528.0 €

Modern society relies more and more on computing for managing complex safety-critical tasks (e.g., in medicine, avionics, economy). Correctness of computerized systems is therefore crucial, as incorrect behaviors might lead to disastrous outcomes. Still, correctness is a big open problem without satisfactory theoretical or practical solutions. This has dramatic effects on the security of our lives. The current practice in industry mainly employs testing which detects bugs but cannot ensure their absence. In contrast, formal verification can provide formal correctness guarantees. Unfortunately, existing formal methods are still limited in their applicability to real world systems since most of them are either too automatic, hindered by the undecidability of verification, or too manual, relying on substantial human effort. This proposal will introduce a new methodology of supervised verification, based on which, we will develop novel approaches that can be used to formally verify certain realistic systems. This will be achieved by dividing the verification process into tasks that are well suited for automation, and tasks that are best done by a human supervisor, and finding a suitable mode of interaction between the human and the machine. Supervised verification represents a conceptual leap as it is centered around automatic procedures but complements them with human guidance; It therefore breaks the classical pattern of automated verification, and creates new opportunities, both practical and theoretical. In addition to opening the way for developing tractable verification algorithms, it can be used to prove lower and upper bounds on the asymptotic complexity of verification by explicitly distilling the human's role. The approaches developed by this research will significantly improve system correctness and agility. At the same time, they will reduce the cost of testing, increase developers productivity, and improve the overall understanding of computerized systems.

Mots-clés : formal verification,model checking
Projet ERC : HToMS (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
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 : 974526.0 €

Moduli spaces are spaces which describe all mathematical objects of some type. This proposal concerns the study of certain moduli spaces via techniques from homotopy theory, from several different points of view. The main moduli spaces in which we are interested are moduli spaces of manifolds, or equivalently classifying spaces of diffeomorphism groups of manifolds. We are also interested in spaces of positive scalar curvature metrics on smooth manifolds, which we study by relating them to moduli spaces of smooth manifolds. The study of moduli spaces of manifolds via homotopy theory has seen a great deal of development in the last 20 years, the breakthrough result being Madsen and Weiss' calculation of the stable homology of moduli spaces of surfaces. More recently, Galatius and I have established analogous results for manifolds of higher dimension. A main goal of this proposal is to study the homology of moduli spaces from a multiplicative point of view. This leads to higher-order forms of the phenomenon of homological stability in which the failure of ordinary homological stability is itself stable. Remarkably, our methods developed to handle moduli spaces of manifolds are sufficiently general to yield deep new results when applied to other moduli spaces in algebra and topology, such as moduli spaces of modules (equivalently, classifying spaces of general linear groups) or moduli spaces of graphs (equivalently, classifying spaces of automorphism groups of free groups). In each case our methods give new information about their homology outside of the traditional stable range. Other goals of this proposal are to form new connections between spaces of Riemannian metrics of positive scalar curvature and infinite loop spaces, and to investigate the structure of tautological subrings of the cohomology of moduli spaces of manifolds, especially in relation to the tautological rings of moduli spaces of Riemann surfaces studied in algebraic geometry.

Mots-clés : homotopy theory,moduli space,mapping class group,general linear group,automorphism group of free group,e n algebra,homological stability,algebraic k theory,positive scalar curvature,cobrdism
Projet ERC : iGLURs - A NEW VIEW (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : University of Bergen — Pays : Norvège — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Molecular biology strives for the prediction of function, based on the genetic code. Within neuroscience, this is reflected in the intense study of the molecular basis for ligand recognition by neurotransmitter receptors. Consequently, structural and functional studies have rendered a profoundly high-resolution view of ionotropic glutamate receptors (iGluRs), the archetypal excitatory receptor in the brain. But even this view is obsolete: we don’t know why some receptors recognize glutamate yet others recognize other ligands; and we have been unable to functionally test the underlying chemical interactions. In other words, our view differs substantially from nature’s own view of ligand recognition. I plan to lead a workgroup attacking this problem on three fronts. First, bioinformatic identification and electrophysiological characterization of a broad and representative sample of iGluRs from across the spectrum of life will unveil the diversity of ligand recognition in iGluRs. Second, phylogenetic analyses combined with functional experiments will reveal the molecular changes that nature employed in arriving at existing means of ligand recognition in iGluRs. Finally, chemical-scale mutagenesis will be employed to overcome previous technical limitations and dissect the precise chemical interactions that determine the specific recognition of certain ligands. With my experience in combining phylogenetics and functional experiments and in the use of chemical-scale mutagenesis, the objectives are within reach. Together, they form a unique approach that will expose nature’s own view of ligand recognition in iGluRs, revealing the molecular blueprint for protein function in the nervous system.

Mots-clés : glutamate receptors,ion channels,ligand recognition,evolution,ancestral reconstruction