Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : BCLLatlas (Horizon 2020, appel 2018, Synergy grants)
Entité participante : Fundació Clínic per a la Recerca Biomèdica — Pays : Espagne — Rôle : PI
Acronyme de l'entité : FCRB;FCRB-CERCA
Type d'entité : Recherche
Financement ERC de l'entité : 2582787.5 €

Unbiased analyses of the molecular make up of single cells are revolutionizing our understanding of cell differentiation and cancer. Over the last years, our groups have characterized the molecular features of normal B-cell subpopulations and of pools of leukemic cells from chronic lymphocytic leukemia (CLL), the most frequent leukemia in the Western world. These analyses have revealed that CLL subtypes are related to different B-cell maturation stages, and that they can show a complex subclonal architecture. Such subclonality is dynamically modulated during the course of the disease, and has deep implications in CLL biology, clinical aggressiveness and treatment responses. In this scenario, BCLL@las aims at deciphering the origin and molecular anatomy of CLL during the entire life history of the disease by generating genetic, transcriptional and epigenetic maps of hundred-thousands of single cells across locations, time points and individuals. We plan to fulfill four major objectives: 1) To generate a comprehensive atlas of normal B-cell maturation, 2) To understand the initial steps of neoplastic transformation through the analysis of minute B-cell monoclonal proliferations in healthy individuals, 3) To decipher the cellular diversity and clonal architecture of CLL at diagnosis, and 4) To characterize the single-cell subclonal dynamics of CLL during disease evolution and treatment response. To reach these goals, BCLL@las gathers together four teams with complementary expertise in B-cell biology, clinics and pathology of CLL, genomics, transcriptomics, epigenomics, sequencing technologies, single-cell profiling and computational biology. This, together with the richness of the available CLL samples and the technical and analytical depth of BCLL@las shall lead to unprecedented insights into the origin and evolution of cancer in the precision medicine era.

Mots-clés : single cell genomics,chronic lymphocyic leukemia,b cell,clonal heterogeneity
Projet ERC : BCLLatlas (Horizon 2020, appel 2018, Synergy grants)
Entité participante : Hospital Clínic de Barcelona — Pays : Espagne — Rôle : Partner
Type d'entité : Recherche
Financement ERC de l'entité : 299312.5 €

Unbiased analyses of the molecular make up of single cells are revolutionizing our understanding of cell differentiation and cancer. Over the last years, our groups have characterized the molecular features of normal B-cell subpopulations and of pools of leukemic cells from chronic lymphocytic leukemia (CLL), the most frequent leukemia in the Western world. These analyses have revealed that CLL subtypes are related to different B-cell maturation stages, and that they can show a complex subclonal architecture. Such subclonality is dynamically modulated during the course of the disease, and has deep implications in CLL biology, clinical aggressiveness and treatment responses. In this scenario, BCLL@las aims at deciphering the origin and molecular anatomy of CLL during the entire life history of the disease by generating genetic, transcriptional and epigenetic maps of hundred-thousands of single cells across locations, time points and individuals. We plan to fulfill four major objectives: 1) To generate a comprehensive atlas of normal B-cell maturation, 2) To understand the initial steps of neoplastic transformation through the analysis of minute B-cell monoclonal proliferations in healthy individuals, 3) To decipher the cellular diversity and clonal architecture of CLL at diagnosis, and 4) To characterize the single-cell subclonal dynamics of CLL during disease evolution and treatment response. To reach these goals, BCLL@las gathers together four teams with complementary expertise in B-cell biology, clinics and pathology of CLL, genomics, transcriptomics, epigenomics, sequencing technologies, single-cell profiling and computational biology. This, together with the richness of the available CLL samples and the technical and analytical depth of BCLL@las shall lead to unprecedented insights into the origin and evolution of cancer in the precision medicine era.

Mots-clés : single cell genomics,chronic lymphocyic leukemia,b cell,clonal heterogeneity
Projet ERC : BIOUNCERTAINTY (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Cultures and cultural production
Entité participante : Jagiellonian University — Pays : Pologne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499625.0 €

Uncertainty is everywhere, as the saying goes, but rarely considered in ethical reflections. This project aims to reinterpret ethical discussions on current advances in biomedicine: instead of understanding bioethical positions as extensions of classical normative views in ethics (consequentialism, deontologism, contractualism etc.), my project interprets them more accurately as involving various normative approaches to decision making under uncertainty. The following hard cases in bioethics provide the motivation for research: 1) Regulating scientific research under uncertainty about the ontological/moral status (e.g. parthenogenetic stem cells derived from human parthenotes) in the context of meta-reasoning under normative uncertainty. 2) The value of preventive medicine in healthcare (e.g. vaccinations) in the context of decision-making under metaphysical indeterminacy. 3) Population or reproductive decisions (e.g. preimplantation genetic diagnosis) in the context of valuing mere existence. The main drive behind this project is the rapid progress in biomedical research combined with new kinds of uncertainties. These new and “deep” uncertainties trigger specific forms of emotions and cognitions that influence normative judgments and decisions. The main research questions that will be addressed by conceptual analysis, new psychological experiments, and case studies are the following: how do the heuristics and biases (H&B) documented by behavioral scientists influence the formation of normative judgments in bioethical contexts; how to demarcate between distorted and undistorted value judgments; to what extent is it permissible for individuals or policy makers to yield to H&B. The hypothesis is that many existing bioethical rules, regulations, practices seem to have emerged from unreliable reactions, rather than by means of deliberation on the possible justifications for alternative ways to decide about them under several layers and types of uncertainty.

Mots-clés : philosophy,ethics,bioethics,uncertainty,risk,social psychology,decision making,research ethics,medical ethics,healthcare ethics,reproductive ethics
Projet ERC : INTRASTEM (Horizon 2020, appel 2014, Proof of concept grants)
Entité participante : University of Nottingham — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 147489.0 €

Under an ERC Advanced Grant, Professor Shakesheff's team have invented a new intracellular delivery system that overcomes a problem in pluripotent stem cell culture as well as being applicable to many other mammalian cell types. The system, called GAG-binding enhanced transduction (GET), enables intracellular delivery of proteins, nucleic acids and particles into cells that resist other non-viral strategies. The work under ERC Advanced Grant funding has allowed exemplification of the delivery of proteins that promote pluripotency or differentiation, delivery and expression of mRNA and high yield delivery of nano and microparticles. This Proof-of-Concept Application will achieve 6 deliverables that together will generate a robust business plan for commercialisation of GET. We begin by performing, via a European marketing company, a comprehensive market analysis to test our view that GET could be used to replace lentiviral transfection, or as an in vivo reprogramming tool or for other challenngng pharmaceutical applications. Next we take account of the market analysis to refine our technical work resulting in a report that provides robust evidence of market required advantages of GET over competitor products. This technical work will include a consideration of manufacturing routes and costs of goods. In parallel with the technical work we will commission an independent freedom-to-operate report. Finally, we will initiate confidential discussions with potential partners and customers via face-to-face meetings in Europe and the US. The final business plan will establish the technical and commercial feasibility of our approaches in one or more of our target markets. We envisage that at the end of the ERC PoC grant we will attract substantial funding to rapidly progress product launches and licenses.

Mots-clés : regenerative medicine,intracellular delivery,protein therapeutics,nucleic acids,nanoparticles
Projet ERC : SPADE (Horizon 2020, appel 2016, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : Hebrew University of Jerusalem — Pays : Israël — Rôle : PI
Acronyme de l'entité : HUJI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

Understanding and quantifying the impacts of climate change at the regional and hemispheric scales are particularly difficult with respect to changes in rainfall and temperature patterns that lead to extended droughts and flooding events. Isotopic records in speleothems are increasingly used to determine climate variability on land and for data-model comparisons. However, transferring speleothem records into quantitative climate parameters suffers from a major limitation: speleothem formation processes result in geochemical disequilibrium and there is currently no way to correct for it in paleoclimate data. SPADE will shift the treatment of paleoclimate archives from regarding them as recorders of slow geological processes to consideration of geological material as recording much faster chemical reactions. As such, they cannot be assumed to form at equilibrium. SPADE will create a new framework, based on one classic and two novel isotopic tracers in carbonates (δ18O-Δ17O-Δ47) to quantify disequilibrium in cave records and overcome this underlying limitation. SPADE’s unique approach is based first on laboratory experiments that isolate chemical processes of speleothem formation, to test their respective effects on isotopic disequilibrium. Then speleothem analog experiments and modern cave material are combined to create speleothem specific calibrations for these isotopic proxies. These SPADE results will then be applied to classic paleoclimate records of dryland hydrology, such as Soreq Cave (Israel) and Devils Hole (Nevada). SPADE will address long standing climatic hypotheses regarding the interplay between temperature, amount of rainfall, surface evaporation, moisture sources, and regional climate connections in these drought vulnerable regions, and will make these records much more useful. A detailed understanding of disequilibrium will enable the use of these innovative geochemical tools in speleothems and more broadly, in other paleoclimate carbonate archives.

Mots-clés : clumped isotopes,speleothems
Projet ERC : proteoRAGE (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
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 : 498668.37 €

Understanding how different environmental cues influence cellular physiology is critical but challenging. Small molecule metabolites such as nutrients and signalling molecules carry information about the external and internal state of the cell. Proteins sense these environmental signals through direct physical interactions with metabolites that trigger rapid variations of protein activities as response. Those events where protein and metabolites interact leading to functional consequences are called allosteric interactions. Allosteric interactions are classically studied in the context of enzymatic reactions, but much less is known regarding their potential ability to control gene expression. I propose to test the hypothesis that metabolites can, in some cases, bypass classical signaling pathways and act directly on gene expression. To address this question, I will study systematically the proteins that regulate gene expression (i.e. transcription and translation) and that can be directly activated (or inhibited) by interactions with metabolites. Building on my previous work studying metabolite-protein interactions using limited proteolysis, I will apply novel mass spectrometry-based proteomics approaches to investigate the gene expression allosterome. I will couple the measurement of structural changes caused by protein-metabolite interactions with their direct effects on chromatin accessibility and mRNA-protein associations. By measuring those effects in vivo, I will link allosteric interactions with gene expression activity. Finally, I will validate their functional role by integrating structural information with deep mutagenesis and cellular phenotyping in multiple environments. In summary, my research aims to establish a novel interdisciplinary approach to functionally characterize the complexity of the allosterome, to identify novel entry points for its modulation using small molecules and to refine our understanding of gene expression.

Mots-clés : allosterome,gene expression regulation,limited proteolysis coupled to mass spectrometry,metabolite binding domains,proteomics,protein metabolite interactions,chromatin
Projet ERC : proteoRAGE (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Karolinska Institutet — Pays : Suède — Rôle : Partner
Acronyme de l'entité : KI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1185925.63 €

Understanding how different environmental cues influence cellular physiology is critical but challenging. Small molecule metabolites such as nutrients and signalling molecules carry information about the external and internal state of the cell. Proteins sense these environmental signals through direct physical interactions with metabolites that trigger rapid variations of protein activities as response. Those events where protein and metabolites interact leading to functional consequences are called allosteric interactions. Allosteric interactions are classically studied in the context of enzymatic reactions, but much less is known regarding their potential ability to control gene expression. I propose to test the hypothesis that metabolites can, in some cases, bypass classical signaling pathways and act directly on gene expression. To address this question, I will study systematically the proteins that regulate gene expression (i.e. transcription and translation) and that can be directly activated (or inhibited) by interactions with metabolites. Building on my previous work studying metabolite-protein interactions using limited proteolysis, I will apply novel mass spectrometry-based proteomics approaches to investigate the gene expression allosterome. I will couple the measurement of structural changes caused by protein-metabolite interactions with their direct effects on chromatin accessibility and mRNA-protein associations. By measuring those effects in vivo, I will link allosteric interactions with gene expression activity. Finally, I will validate their functional role by integrating structural information with deep mutagenesis and cellular phenotyping in multiple environments. In summary, my research aims to establish a novel interdisciplinary approach to functionally characterize the complexity of the allosterome, to identify novel entry points for its modulation using small molecules and to refine our understanding of gene expression.

Mots-clés : allosterome,gene expression regulation,limited proteolysis coupled to mass spectrometry,metabolite binding domains,proteomics,protein metabolite interactions,chromatin
Projet ERC : TF-Dynamics (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : Royal Netherlands Academy of Arts and Sciences — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : KNAW
Type d'entité : Recherche
Financement ERC de l'entité : 1330400.0 €

Understanding how genomic regulatory elements encode when and where genes are expressed in development remains one of the most important open questions in biology. Despite intense study, this knowledge gap persists because technological limitations have obscured an important degree of freedom: time. Recent discoveries made with live cell imaging have defied the textbook view of how transcription is regulated. Hence, the time is ripe to introduce a new paradigm for studying transcription in development—one based on how genes are regulated in living animals as development is actually taking place. Excitingly, we can now exploit the cutting-edge live imaging technology and quantitative approaches that I previously developed in order to visualize transcription factor (TF) concentration dynamics, transcription, and even single TF molecules in live Drosophila embryos to uncover how enhancer sequence regulates transcription in vivo. This ambitious work will span multiple length scales, from examining changes in TF concentration at the single-nucleus level, to measuring the formation of local clusters of TFs at the locus level, to watching individual protein-protein interactions as they drive transcription at the molecular level. First, we will understand how TF concentration dynamics regulate gene expression. Second, we will uncover how recently discovered dynamic TF clusters or condensates regulate transcription and how their properties are shaped by enhancer sequence. Finally, we will overcome one of the most daunting technical challenges facing the field of transcription by developing a method to directly visualize the transient protein-protein interactions that drive transcription in vivo. Simultaneously visualizing protein-protein interactions and tracking transcription will make it possible to address the most pressing questions about transcription mechanisms in vivo, by revealing precisely when they occur and how they modulate transcription.
Projet ERC : EMERGE (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
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 : 1859375.0 €

Understanding how the Milky Way arrived at its present state requires a large volume of precision measurements of our Galaxy’s current makeup, as well as an empirically based understanding of the main processes involved in the Galaxy’s evolution. Such data are now about to arrive in the flood of quality information from Gaia and SDSS-V. The demography of the stars and of the compact stellar remnants in our Galaxy, in terms of phase-space location, mass, age, metallicity, and multiplicity are data products that will come directly from these surveys. I propose to integrate this information into a comprehensive picture of the Milky Way’s present state. In parallel, I will build a Galactic chemical evolution model, with input parameters that are as empirically based as possible, that will reproduce and explain the observations. To get those input parameters, I will measure the rates of supernovae (SNe) in nearby galaxies (using data from past and ongoing surveys) and in high-redshift proto-clusters (by conducting a SN search with JWST), to bring into sharp focus the element yields of SNe and the distribution of delay times (the DTD) between star formation and SN explosion. These empirically determined SN metal-production parameters will be used to find the observationally based reconstruction of the Galaxy’s stellar formation history and chemical evolution that reproduces the observed present-day Milky Way stellar population. The population census of stellar multiplicity with Gaia+SDSS-V, and particularly of short-orbit compact-object binaries, will hark back to the rates and the element yields of the various types of SNe, revealing the connections between various progenitor systems, their explosions, and their rates. The plan, while ambitious, is feasible, thanks to the data from these truly game-changing observational projects. My team will perform all steps of the analysis and will combine the results to obtain the clearest picture of how our Galaxy came to be.

Mots-clés : supernovae,binary systems,explosive nucleosynthesis,chemical evolution,white dwarfs
Projet ERC : 3DSCAN (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : University of London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. London
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Understanding how the brain processes information is one of the unsolved grand challenges in science. Moreover, neurological disorders, which disrupt information processing, have an enormous societal and economic impact. Studying information processing in the brain requires measurements of signals as they flow through neural circuits. However, the 3D nature of brain circuits and the speed of information transfer makes it difficult for neuroscientists to measure their properties with sufficiently high spatial and temporal resolution. During the NEUROGAIN ERC project, we developed a novel type of Acousto-Optic Lens (AOL)-based high-speed 3D laser scanner. This technology enables the focusing and scanning of a laser beam at 20-40 kHz. This scanning technology can be added to existing two-photon microscopes to enable 3D imaging of neurons and circuits with unprecedented spatio-temporal resolution. Moreover, it also automatically corrects for brain movement in real-time providing sharper images. This ERC PoC will facilitate commercialization of this 3D scanning technology by providing support to explore the markets in biosciences and beyond, protect the IP and facilitate early stage manufacture and assembly of AOL 3D scanners to supply biomedical researchers.

Mots-clés : two photon imaging,brain function,laser scanning,circuit,neuron,synapse