Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : ArtMotor (Horizon 2020, appel 2020, Synergy grants)
Entité participante : UNSW Sydney — Pays : Australie — Rôle : PI
Acronyme de l'entité : UNSW
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 3273207.0 €

Molecular motors and machines are essential for all cellular processes that together enable life. Built from proteins, with a wide range of properties, functionalities and performance characteristics, biological motors perform complex tasks and can transduce chemical energy into mechanical work more efficiently than human-made combustion engines. Sophisticated studies of biological protein motors have led to much structural and biophysical information and the development of models for motor function. However, from the study of highly evolved, biological motors it remains difficult to discern detailed mechanisms, for example about the relative role of different force generation mechanisms, or how information is communicated across a protein to achieve the necessary coordination. A promising, complementary approach to answering these questions is to build synthetic protein motors from the bottom up. Indeed, much effort has been invested in functional protein design, but so far, the ‘holy grail’ of designing and building a functional synthetic protein motor has not been realized. The purpose of ArtMotor is to design and build functional, synthetic protein motors capable of moving and transducing energy, based on existing, non-motor protein modules of known molecular function. Harnessing the synergy of expertise in computational protein design, structural and molecular biology, and single-molecule detection, we will use a two-pronged approach to (a) construct relatively simple protein motors that will require external control, while (b) construct, step by step, an autonomous protein motor capable of moving along a track. Such a functional, synthetic protein will constitute a ground-breaking advance in synthetic biology, physics and engineering. In addition to gaining new insights into mechanisms of energy transduction in proteins, we will also inspire other, complex protein designs that may lead to advances in fields from enzyme design to nano-engineering.

Mots-clés : protein design,protein engineering,artificial molecular motor,molecular motor,molecular machine,synthetic biology,single molecule approaches
Projet ERC : EMC2 (Horizon 2020, appel 2018, Synergy grants)
Entité participante : École nationale des ponts et chaussées — Pays : France — Rôle : PI
Acronyme de l'entité : ENPC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2133294.0 €

Molecular simulation has become an instrumental tool in chemistry, condensed matter physics, molecular biology, materials science, and nanosciences. It will allow to propose de novo design of e.g. new drugs or materials provided that the efficiency of underlying software is accelerated by several orders of magnitude. The ambition of the EMC2 project is to achieve scientific breakthroughs in this field by gathering the expertise of a multidisciplinary community at the interfaces of four disciplines: mathematics, chemistry, physics, and computer science. It is motivated by the twofold observation that, i) building upon our collaborative work, we have recently been able to gain efficiency factors of up to 3 orders of magnitude for polarizable molecular dynamics in solution of multi-million atom systems, but this is not enough since ii) even larger or more complex systems of major practical interest (such as solvated biosystems or molecules with strongly-correlated electrons) are currently mostly intractable in reasonable clock time. The only way to further improve the efficiency of the solvers, while preserving accuracy, is to develop physically and chemically sound models, mathematically certified and numerically efficient algorithms, and implement them in a robust and scalable way on various architectures (from standard academic or industrial clusters to emerging heterogeneous and exascale architectures). EMC2 has no equivalent in the world: there is nowhere such a critical number of interdisciplinary researchers already collaborating with the required track records to address this challenge. Under the leadership of the 4 PIs, supported by highly recognized teams from three major institutions in the Paris area, EMC2 will develop disruptive methodological approaches and publicly available simulation tools, and apply them to challenging molecular systems. The project will strongly strengthen the local teams and their synergy enabling decisive progress in the field.

Mots-clés : high performance algorithms,mathematics of molecular simulations,error analysis in numerical simulations
Projet ERC : EMC2 (Horizon 2020, appel 2018, Synergy grants)
Entité participante : Sorbonne Université — Pays : France — Rôle : CO-PI
Acronyme de l'entité : Sorbonne U
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 5578050.0 €

Molecular simulation has become an instrumental tool in chemistry, condensed matter physics, molecular biology, materials science, and nanosciences. It will allow to propose de novo design of e.g. new drugs or materials provided that the efficiency of underlying software is accelerated by several orders of magnitude. The ambition of the EMC2 project is to achieve scientific breakthroughs in this field by gathering the expertise of a multidisciplinary community at the interfaces of four disciplines: mathematics, chemistry, physics, and computer science. It is motivated by the twofold observation that, i) building upon our collaborative work, we have recently been able to gain efficiency factors of up to 3 orders of magnitude for polarizable molecular dynamics in solution of multi-million atom systems, but this is not enough since ii) even larger or more complex systems of major practical interest (such as solvated biosystems or molecules with strongly-correlated electrons) are currently mostly intractable in reasonable clock time. The only way to further improve the efficiency of the solvers, while preserving accuracy, is to develop physically and chemically sound models, mathematically certified and numerically efficient algorithms, and implement them in a robust and scalable way on various architectures (from standard academic or industrial clusters to emerging heterogeneous and exascale architectures). EMC2 has no equivalent in the world: there is nowhere such a critical number of interdisciplinary researchers already collaborating with the required track records to address this challenge. Under the leadership of the 4 PIs, supported by highly recognized teams from three major institutions in the Paris area, EMC2 will develop disruptive methodological approaches and publicly available simulation tools, and apply them to challenging molecular systems. The project will strongly strengthen the local teams and their synergy enabling decisive progress in the field.

Mots-clés : high performance algorithms,mathematics of molecular simulations,error analysis in numerical simulations
Projet ERC : EMC2 (Horizon 2020, appel 2018, Synergy grants)
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 : 54142.0 €

Molecular simulation has become an instrumental tool in chemistry, condensed matter physics, molecular biology, materials science, and nanosciences. It will allow to propose de novo design of e.g. new drugs or materials provided that the efficiency of underlying software is accelerated by several orders of magnitude. The ambition of the EMC2 project is to achieve scientific breakthroughs in this field by gathering the expertise of a multidisciplinary community at the interfaces of four disciplines: mathematics, chemistry, physics, and computer science. It is motivated by the twofold observation that, i) building upon our collaborative work, we have recently been able to gain efficiency factors of up to 3 orders of magnitude for polarizable molecular dynamics in solution of multi-million atom systems, but this is not enough since ii) even larger or more complex systems of major practical interest (such as solvated biosystems or molecules with strongly-correlated electrons) are currently mostly intractable in reasonable clock time. The only way to further improve the efficiency of the solvers, while preserving accuracy, is to develop physically and chemically sound models, mathematically certified and numerically efficient algorithms, and implement them in a robust and scalable way on various architectures (from standard academic or industrial clusters to emerging heterogeneous and exascale architectures). EMC2 has no equivalent in the world: there is nowhere such a critical number of interdisciplinary researchers already collaborating with the required track records to address this challenge. Under the leadership of the 4 PIs, supported by highly recognized teams from three major institutions in the Paris area, EMC2 will develop disruptive methodological approaches and publicly available simulation tools, and apply them to challenging molecular systems. The project will strongly strengthen the local teams and their synergy enabling decisive progress in the field.

Mots-clés : high performance algorithms,mathematics of molecular simulations,error analysis in numerical simulations
Projet ERC : PREMOL (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : Heinrich Heine University Düsseldorf — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : HHU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

Molecules have an enormous potential in the field of frequency metrology-based fundamental physics, yet have so far not played an important role, due to difficult experimental challenges. The goal of this project is to overcome these difficulties by developing new techniques, thus opening a new chapter in precision molecular spectroscopy. Furthermore, it will have far-reaching impact in fundamental physics: (1) A 500-fold improved limit to the existence of a “fifth force” with range on the 0.1 nm scale. (2) An independently determined set of the fundamental constants me/mp, me/md, and the Rydberg constant R∞. Their uncertainties will be reduced compared to CODATA2014 by up to a factor of 23 for me/mp, 4 for me/md, and 2 for R∞; (3) A test of the current muonic atom discrepancies of proton and deuteron charge radii rp and rd at the 30% and 50% level, respectively; (4) Achieve a precision 1×10-16 in molecular ion spectroscopy, thus exploring the feasibility of using, in the future, molecular ions for testing the time-dependence of me/mp and mp/md. Molecular hydrogen ions (MHIs) are the systems in principle suitable for providing these results: indeed, the required ab initio theory has made outstanding advances, reaching the 8×10-12 inaccuracy level. To date, experimental results are orders of magnitude less precise. In order to achieve an accuracy surpassing the theoretical one, this project shall develop new quantum optical techniques, including: - Doppler-free spectroscopy, rotational and ro-vibrational; - preparation of a single molecular ion in a single internal quantum state; - resolution and control of systematic shifts at levels from 1×10-12 to 1×10-16; - novel spectroscopy laser systems. These techniques will be of general applicability in the field of molecular ion spectroscopy. The proposed work is based on the wide experience of the PI in precision measurements and will make a strong and overdue contribution to spectroscopy and fundamental physics.

Mots-clés : ion trap,laser cooling,sympathetic cooling,quantum three body problem,molecular hydrogen ion,fundamental constants,rydberg constant,electron mass,deuteron mass,proton mass
Projet ERC : MOPPEX (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
Entité participante : Leiden University — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2461503.0 €

Molecules pervade the cooler, denser parts of our Universe, in particular the reservoirs of the matter that forms stars and planets, and the gas in the centres of galaxies. In the Milky Way we routinely use molecules to discover and explore these regions and the more complex the chemistry, the more details of the gas the molecules reveal. There are one hundred billion galaxies in the observable Universe. About 200 or so are our neighbours. However, due to their distance, we are still not able to zoom in and observe individual clouds of dense gas. Nevertheless with the advent of ever more sensitive telescopes such as ALMA, we are discovering that chemistry in external galaxies is as complex as in our own Milky Way. Molecules, it seems, are universal and widespread. In MOPPEX I use molecules to shed light on the physical and chemical structure of our local galaxies, namely (i) what the energetic processes that determine their appearance are and (ii) where the matter that will form stars or fuels black holes is, with the ultimate goal to understand how galaxies form, evolve and interact with each other. To achieve this objective I propose a multi-faceted program that combines state of the art chemical and statistical models in conjunction with interferometric observations. More specifically, the success of MOPPEX relies on (i) in-house and open source suites of chemical models and an in-house line radiative transfer model, (ii) a new suite of tools comprising of modular statistical and machine learning algorithms, and (iii) large datasets of observational data on two nearby galaxies differing in types. My ultimate objective is to fundamentally change the way molecular observations are interpreted for external galaxies and thus to cause a paradigm shift in the use of molecules as tools to determine the chemistry and physics of galaxies.

Mots-clés : astrochemistry,molecules
Projet ERC : Self-Control (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : Collège de France — Pays : France — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 280688.5 €

Morphogenesis seeks to understand how information and mechanics emerge from molecular interactions and how they are regulated in space and time. Two parallel legacies are now intertwined: the conceptual framework of developmental patterning that explains how cells acquire positional information during development and control cell behaviors, and the description of biological processes in physical terms. The current framework explains how genetic and biochemical information controls cellular mechanics, in particular contractility mediated by actomyosin networks, and thus cell and tissue shape changes. However, newly reported contractile dynamics, namely pulses, flows and waves, cannot be explained in this framework: they are self-organized in that they depend on local mechano-chemical interactions and feedback that cannot be accounted for by upstream genetic control. This project will explore the interplay between genetic control and self-organization in Drosophila embryos. We will study the emergence of multicellular flow and the mechanism of newly characterized tissue-level trigger wave dynamics associated with endoderm invagination, a poorly studied process. We will ask: 1) how do patterns of apical and basal contractility drive cell dynamics; 2) what is the contribution of geometrical feedback, e.g. tissue curvature, in amplifying the effect of contractile asymmetries; and 3) what is the nature of mechanical feedback and cell spatial coupling underlying trigger wave dynamics in the tissue? We will use an interdisciplinary approach, combining live imaging, capturing the 3D shape of cells/tissues, genetic/optogenetic/mechanical perturbations and theoretical/computational methods to model mechanics and geometry. We expect to unravel how organized multicellular dynamics emerge from genetic, mechanical and geometric “information”, and feedback during morphogenesis. This work will shed new light on a variety of morphogenetic processes occurring during development.

Mots-clés : morphogenesis,mechanics
Projet ERC : Self-Control (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
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 : 2581882.5 €

Morphogenesis seeks to understand how information and mechanics emerge from molecular interactions and how they are regulated in space and time. Two parallel legacies are now intertwined: the conceptual framework of developmental patterning that explains how cells acquire positional information during development and control cell behaviors, and the description of biological processes in physical terms. The current framework explains how genetic and biochemical information controls cellular mechanics, in particular contractility mediated by actomyosin networks, and thus cell and tissue shape changes. However, newly reported contractile dynamics, namely pulses, flows and waves, cannot be explained in this framework: they are self-organized in that they depend on local mechano-chemical interactions and feedback that cannot be accounted for by upstream genetic control. This project will explore the interplay between genetic control and self-organization in Drosophila embryos. We will study the emergence of multicellular flow and the mechanism of newly characterized tissue-level trigger wave dynamics associated with endoderm invagination, a poorly studied process. We will ask: 1) how do patterns of apical and basal contractility drive cell dynamics; 2) what is the contribution of geometrical feedback, e.g. tissue curvature, in amplifying the effect of contractile asymmetries; and 3) what is the nature of mechanical feedback and cell spatial coupling underlying trigger wave dynamics in the tissue? We will use an interdisciplinary approach, combining live imaging, capturing the 3D shape of cells/tissues, genetic/optogenetic/mechanical perturbations and theoretical/computational methods to model mechanics and geometry. We expect to unravel how organized multicellular dynamics emerge from genetic, mechanical and geometric “information”, and feedback during morphogenesis. This work will shed new light on a variety of morphogenetic processes occurring during development.

Mots-clés : morphogenesis,mechanics
Projet ERC : FungalTolerance (Horizon 2020, appel 2020, Synergy grants)
Entité participante : Charité - Universitätsmedizin Berlin — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 4989668.0 €

Mortality from invasive fungal infections approaches 50%, despite the use of available antifungal drugs. While bacterial studies have focused on drug resistance, the rare appearance of antifungal drug resistance does not explain these treatment failures. Antifungal tolerance is a poorly understood property that is expressed to different degrees in different non-resistant isolates, yet has not been measured routinely in the clinic or in most research studies. We do not know how tolerance differs between isolates, what biological mechanisms drive it, how it affects only some cells in a single isolate, or whether it can be inhibited to improve treatment outcomes. Recently, the Berman lab found that tolerance is an intrinsic property, in which some cells of a non-resistant isolate continue growing in the presence of the drug that has the potential to explain antifungal treatment failures. In parallel, the Ralser lab found that inhibitors of metabolic pathways affect the stress survival of some cells and the Berman lab found that these inhibitors can clear tolerance and convert an antifungal drug from fungistatic to fungicidal, thereby killing the cells and halting their adaptation. Together, we combine expertise in pathogenic fungi (Berman) and metabolic systems (Ralser) to reach fundamental understandings of tolerance across the range of its biological scales by: 1) capturing the diversity of tolerance in a genomic and proteomic data resource of >1000 isolates; 2) identifying metabolic pathways and molecular mechanisms that drive tolerance within isolates; and 3) probing processes and compounds that affect phenotypic heterogeneity between cells and suppress tolerance. By elucidating the mechanisms that drive tolerance and fungal single-cell diversity, we propose to render tolerance targetable, providing a paradigm shift in anti-fungal treatment strategies.

Mots-clés : phenotypic heterogeneity,metabolic communities,stress tolerance,integrated biomolecular responses
Projet ERC : GHOSTS (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 523926.25 €

Most biological tissues are optically opaque, largely precluding access by light microscopy. In stark contrast, some living tissues and organisms are highly transparent. Examples include many deep-sea fish, your retina, and cells that we exposed to directed evolution. Here we propose to uncover the genetic basis of tissue transparency, such that living cells and tissue cultures can be optically cleared by precision genetics. For this we will combine insights into origins of retina transparency, and a set of unique methods, to answer the question how genetically cells become more transparent during directed evolution. Specifically, we will use a three-fold approach to find transparency genes that do not compromise cellular integrity. For this we will use i) directed evolution towards transparency while co-selecting for cell fitness, ii) extensive phenotyping of transparent cells, both optically and functionally, and iii) use of transcriptomics to rule out stressed cells, and those that deviate too much from wildtype gene expression profiles. Knowing about physiological transparency genes will allow unprecedented insights into living tissues. If model tissues in the lab were just 1% as transparent as some glass-like fish found in the deep sea, optical microscopes could unleash their full potential, and enable high resolution views into developmental processes in their native environment. We see further transformative potential especially in the fields of organotypic tissue models, functional brain imaging, as well as pharmaceutical screens in 3D tissue cultures.