Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : PREVENT-2024 (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Lund University — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

Increasing occurrence of obesity and diabetes is the major threat to cardiovascular health of our century. Whereas the field is saturated with “omics” strategies aimed at improving prediction of cardiometabolic disease (CMD), mechanism-orientated prevention strategies, which is what the population calls for, are lacking. We here propose three completely new and high-risk strategies to prevent CMD in large subsets of the population, who have elevated risk due to measurable endocrine abnormalities. SUBPROJECT 1: We test if the increased CMD risk linked to high levels of the intestinal fat absorption and storage promoting hormone neurotensin (NTS), can be improved by: (A) blockade of NTS using monoclonal antibodies in mice and (B) inhibition of NTS secretion and intestinal fat uptake with the drug orlistat in humans. SUBPROJECT 2: High plasma levels of vasopressin (VP) (present in 25% of the population) is a strong risk factor for later CMD and the dominating cause of high VP is low water intake. We therefore test if the elevated CMD risk in subjects with high VP can be reduced by increasing water intake in a large 12-month randomized trial of 1.5 L water supplementation vs control therapy. SUBPROJECT 3: Aderenomedullin (ADM), whose endothelial secretion is enhanced in obesity, has beneficial effects on the intravascular wall but in the extravascular space, to which it diffuses freely, it may promote diabetes. We investigate how long-term increase and decrease of levels of bioactive ADM in the intra- and extravascular compartments, respectively, affect atherosclerosis and glucose metabolism in mice. In humans we test if a monoclonal antibody, which traps ADM in the circulation (while still allowing it to bind to its endothelial receptors) and drains it from the extravascular space, improves vascular function and glucose metabolism. We provide completely novel, mechanism-orientated and near-future applicable strategies for primary prevention of CMD.

Mots-clés : prevention,cardiometabolic disease,diabetes,obesity,cardiovascular disease,vasopressin,neurotensin,adrenomedullin
Projet ERC : LOCAL KNOWLEDGE (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Cultures and cultural production
Entité participante : Wageningen University & Research — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : WUR
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499934.0 €

Indigenous and other local communities possess complex biological knowledge that is increasingly recognized in collaborative approaches in the agricultural, environmental, and health sciences. However, collaborations between local communities and academically trained scientists are commonly challenged by deep differences in epistemologies, ontologies, and value systems. For example, an Indigenous fisher may be an expert on a local marine ecosystem but rely on spiritual fishing norms and metaphysical assumptions that raise questions about compatibility with academic ecology. This project will develop “philosophy of ethnobiology” as an interdisciplinary meeting ground for addressing foundational methodological issues in cross-cultural negotiations of biological and ecological knowledge. As there has been almost no interaction between academic philosophy and ethnobiology, the project develops an equally ambitious and original program. It provides a framework for approaching cross-cultural collaborations despite deep philosophical differences and for expanding current philosophical debates through global and applied considerations. While I am trained as a philosopher of science, the project will develop an interdisciplinary research methodology that integrates philosophical analysis and empirical collaboration with three ethnobiological research teams in Brazil and Mexico. Furthermore, I have already shown the possibility of bringing these fields together in flagship journals of both philosophy of science and ethnobiology. The unique interdisciplinary methodology and published proofs of concept therefore clearly demonstrate the feasibility of developing “philosophy of ethnobiology” as a meeting ground between foundational and applied concerns of global challenges in the life sciences.

Mots-clés : ethnobiology,ethnoscience,philosophy of biology,philosophy of ecology,philosophy of anthropology,traditional ecological knowledge,knowledge diversity
Projet ERC : YEAST-TRANS (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
Entité participante : Technical University of Denmark — Pays : Danemark — Rôle : PI
Acronyme de l'entité : DTU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1423357.5 €

Industrial biotechnology employs synthetic cell factories to create bulk and fine chemicals and fuels from renewable resources, laying the basis for the future bio-based economy. The major part of the wanted bio-based chemicals are not native to the host cell, such as yeast, i.e. they are xenobiotic. Some xenobiotic compounds are readily secreted by synthetic cells, some are poorly secreted and some are not secreted at all, but how does this transport occur? Or why does it not occur? These fundamental questions remain to be answered and this will have great implications on industrial biotechnology, because improved secretion would bring down the production costs and enable the emergence of novel bio-based products. YEAST-TRANS will fill in this knowledge gap by carrying out the first systematic genome-scale transporter study to uncover the transport mechanisms of small xenobiotic molecules by synthetic yeast cells and to apply this knowledge for engineering more efficient cell factories for bio-based production of fuels and chemicals.

Mots-clés : transport proteins,xenopus oocytes expression,saccharomyces cerevisiae transportome,bio based chemicals
Projet ERC : CHAT-Opt (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : KU Leuven — Pays : Belgique — Rôle : PI
Acronyme de l'entité : KUL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1893125.0 €

Industry and society are increasingly automating processes, which requires solving constrained optimisation problems. This includes vehicle routing problems in transportation, scheduling of tasks in electricity demand-response programs, rostering of personnel and more. However, the solutions found by state-of-the-art constraint programming solvers are often found to not match user expectations. Solutions are regularly critiqued by domain experts as impractical, frustrating for people involved or creating unfair situations that a human planner would never propose. As a result, the technology is not accepted or workarounds like manual processing is done which reduces its potential. This project is based on the idea that we must shift away from the concept of the optimal solution, and must move to that of the desired solution. To make the solutions more humane, we must make the solution process more human-aware. The key to this is to integrate techniques from machine learning that can learn about the context of the environment and user. This can move the problem formulation process from a one-shot model + solve paradigm to a dialogue-based conversation paradigm between the end-user and the solver. The focus here is not on the use of natural language, but rather on making the constrained programming technology ready for such interactions. This project aims to fundamentally advance it on three fronts: 1) to learn from the environment and integrate the learning and the predictive models into the optimisation; 2) to learn the implicit preferences form the user by letting her/him interact with the solutions; and ultimately 3) to develop a conversational constraint solver that can answer unambiguous questions of the users in terms of explanations and alternatives. The end goal is a system that lets the user co-create a solution that she/he desires, and that system can adapt to changing needs and preferences over time.

Mots-clés : combinatorial optimisation,machine learning,constraint solving
Projet ERC : iAML-lncTARGET (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Goethe University Frankfurt — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 605645.0 €

Infant acute myeloid leukemia (AML) has a dismal prognosis, with a high prevalence of unfavorable features and increased susceptibility to therapy-related toxicities, highlighting the need for innovative treatment approaches. Despite the discovery of an enormous number and diversity of transcriptional products arising from the previously presumed wastelands of the non-protein-coding genome, our knowledge of non-coding RNAs is far from being incorporated into standards of AML diagnosis and treatment. I hypothesize that the highly developmental stage- and cell-specific expression of long non-coding RNAs shapes a chromatin and transcriptional landscape in fetal hematopoietic stem cells that renders them permissive towards transformation. I predict this landscape to synergize with particular oncogenes that are otherwise not oncogenic in adult cells, by providing a fertile transcriptional background for establishing and maintaining oncogenic programs. Therefore, the non-coding transcriptome, inherited from the fetal cell of origin, may reflect a previously unrecognized Achilles heel of infant AML, which I will identify with my expertise to understand and edit the AML genome and transcriptome. I will apply recent breakthroughs from various research areas to i) create a comprehensive transcriptomic atlas of infant AML and fetal stem cells, ii) define aberrant or fetal stage-specific non-coding RNAs that drive leukemia progression, and iii) resolve their features to probe the oncogenic interactome. After iv) establishing a biobank of patient-derived xenografts, I will v) evaluate preclinical RNA-centered therapeutic interventions to overcome current obstacles in the treatment of infant AML. Targeting the vulnerable fetal stage-specific background of infant AML inherited from the cell of origin may set a paradigm shift for cancer treatment, by focusing on the permissive basis required by the oncogene for inducing and sustaining cancer, rather than on the oncogene itself.

Mots-clés : infant,long non coding rna
Projet ERC : PATHOCOM (Horizon 2020, appel 2020, Synergy grants)
Entité participante : New York University — Pays : Etats-Unis — Rôle : PI
Acronyme de l'entité : NYU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 3857659.0 €

Infectious disease is often the major selective agent in nature, and we cannot understand how populations evolve without understanding their pathogenic microbes. Beyond host immunity, an important factor determining the ability of pathogens to invade and proliferate in a host is the resident microbiota, but we are only beginning to glimpse its multifarious impacts. We know even less about interactions among pathogenic microbes themselves. Any effort to explain how pathogen communities, or pathobiota, develop within a host requires knowledge about the extent to which pathogens engage in competition, commensalism and cooperation, both with other pathogens and the rest of the microbiota. To date, studies of plant-pathogen interactions in the lab and descriptive work in the field have focused on pairwise interactions between one plant host and one pathogen, leaving a large gap in our understanding of how different types of interactions between microbes, and especially pathogens, determine the outcome of host-pathogen interactions in the real world. In PATHOCOM, we will implement a program that integrates large-scale field observations of microbes in the plant Arabidopsis thaliana with ultra-high-throughput experimental tests of host-dependent interactions among microbes, allowing experiment-informed modeling of pathogenic microbe-microbe interactions. These models, which will be improved through an iterative process of data collection with synthetic communities, will illuminate how interactions, from pairwise to higher-order, shape microbial community composition and structure. In the final step, the resulting models will be tested against and refined with field data. Together, these efforts will transform the study of plant pathogens by applying deep analyses of microbial interactions in an ecological context to explain patterns in nature. Ultimately, PATHOCOM will play an essential role in refashioning plant-pathogen-microbiome studies into a predictive science.

Mots-clés : arabidopsis thaliana,ecological genomics,pathogen pathogen interactions,host microbiota interactions,ecology community structure,community modeling
Projet ERC : Micro-GIFT (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Leibniz Association — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LG
Type d'entité : Recherche
Financement ERC de l'entité : 1499967.0 €

Infertility is a worldwide problem affecting ~11% of the reproductive-age population. Severe cases are currently treated by in vitro fertilization (IVF) and intracytoplasmic injection techniques (ICSI) with high fertilization rates (~95%). However, embryo transfer is still the critical stage with only 32% of the cases resulting in clinical pregnancies. Moreover, the implantation rates per embryo remain very low (~17%) and often the procedure needs to be repeated several times with no success implying a high economic and social cost. Among the different methods used to overcome this issue, gamete or zygote ntrafallopian transfer (GIFT or ZIFT) seems more promising offering appropriate physiological environment for zygote/embryo development at an optimal synchronization between embryonic and endometrial preparation. However, these methods are invasive and involve surgical procedures and anaesthesia to introduce macroscopic imaging and manipulation tools into the female body, increasing the risk of injury and ectopic pregnancies. The goal of Micro-GIFT is to seek for novel approaches to non-invasively transport and release high-quality gametes/zygotes in the fallopian tube in vivo (mice model). For that multifunctional untethered microrobots (~100 µm size) will be developed making use of smart materials and advanced microtechnologies. However, there are major challenges that need to be overcome to bring this technology close to the clinic, such as the in vivo imaging and control of such microrobots, and their removal after use. The project will also provide deeper insights on the contribution of the fallopian tube on the natural embryo development and implantation, being crucial to create more natural procedures with high success rates. The PI has contributed significantly to the field of sperm-based microbots for assisted fertilization and targeted drug delivery as well as developed a variety of novel microbiosensors for molecular and cellular analysis.

Mots-clés : medical microrobots,remote gametes,zygotes transport,gametes,zygote selection,magnetic microrobots,in vivo imaging,assisted fertilization,microfabrication,lab on a chip,artificial oviduct,ultrasensitive single cell sensors
Projet ERC : Bat Flu (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Life Science
Panel : Immunity, Infection and Immunotherapy
Entité participante : University of Freiburg — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499637.5 €

Influenza A viruses (IAVs) are zoonotic pathogens that frequently cross the species barrier into humans, often causing severe morbidity and even global pandemics. This cross-species transmission is facilitated in large part by alterations in the interaction between the viral surface proteins hemagglutinin (HA) and neuraminidase (NA) and sialic acid, a ubiquitous glycan that serves as the cellular entry receptor. Although avian hosts have generally been thought to be the primary reservoir for all influenza A viruses, this dogma has recently been challenged by the identification of two novel IAV subtypes in bats, H17N10 and H18N11. Despite an otherwise high degree of functional homology to conventional IAVs, the surface proteins of bat IAVs demonstrate several unprecedented characteristics. Specifically, these proteins are unable to interact with sialic acid; rather, we recently showed that bat IAVs use the major histocompatibility complex class II (MHC-II) protein to gain entry into host cells. Unexpectedly, we observed that N11 downregulates surface expression of MHC-II, suggesting that it potentially harbors a receptor-destroying function. Most surprisingly, bat IAV could replicate to even higher titers the absence of functional NA, a capability which has never been observed among influenza viruses. These findings suggest that the surface glycoproteins of bat IAV may possess a structural plasticity that is much broader than that of conventional IAV. In light of the critical importance of the surface proteins for cross-species transmission of IAV, the goal of this project will be to probe this plasticity, first by determining the mode of interaction between H17/H18 and MHC-II and elucidating the mechanism of N10/N11-dependent downregulation of MHC-II, but most importantly by using forced evolution to explore the plasticity of IAV for new cellular entry factors. The insights from these studies will have a major impact on our understanding of influenza virus tropism.

Mots-clés : bat influenza viruses,receptor,mhc ii
Projet ERC : ModVaccine (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Helmholtz Centre for Infection Research — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : GBF;HZI
Type d'entité : Recherche
Financement ERC de l'entité : 1499871.0 €

Influenza is a significant public health threat and vaccines are crucial for preventing infections at population-level. The efficacy of vaccination per individual, however, is highly variable. The causes for this broad variability in vaccine response between individuals remain poorly understood. In this proposal, I hypothesize that genetic variants and their downstream pathways underlie the heterogeneity in vaccine response between individuals. This ERC project aims to for the first time, systematically investigate the interactions between genetic, non-genetic host and environmental factors, and the response to vaccination in order to build reliable models for predicting vaccine efficacy. The outcomes of this research will pinpoint key deterministic factors and identify modulators that can be used to improve vaccination strategies. This project is based on the expertise that my research group has built up for identifying the downstream consequences of genetic variants, and for predictive modelling through integration of large cross-omics datasets. Given the rapid evolution of influenza virus, I will use seasonal trivalent inactivated influenza vaccines as prototype responses within two cohorts of 500 individuals from the Netherlands and 200 individuals from Germany. I will systematically generate, analyse, and integrate the cross-omics data (six layers of information from genome, epigenome, transcriptome, proteome, metabolome, and microbiome) with immune phenotypes (e.g. antibody titers, an important indicator of protection) using novel computational methods. This research will reveal the previously unknown cell-types, molecules, and pathways involved in vaccine-induced immune response and provide mathematical models for predicting individual variation in immune response, a crucial first step towards personalized prevention. The key molecules I identify will provide leads for pharmacological modulators for improving vaccine efficacy.

Mots-clés : systems genetics,multi omics,vaccination,predictive modelling,modulators
Projet ERC : INSTRUCT (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : University of Oxford — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 778395.35 €

Information flows are fundamental to how well markets work for consumers and firms. Consumers get different deals depending on (a) how much they know about the offerings of different firms and, conversely, (b) how much firms know about consumer preferences. The internet is transforming both (a) and (b), allowing consuInformation flows are fundamental to how well markets work for consumers and firms. Consumers get different deals depending on (a) how much they know about the offerings of different firms and, conversely, (b) how much firms know about consumer preferences. The internet is transforming both (a) and (b), allowing consumers to discover and evaluate products with greater ease and enabling firms to personalise prices and target their advertising. Economic understanding currently lags behind what is needed for robust policy formulation in the areas of consumer privacy, price discrimination, and the costs of search and advertising. This project aims to fill that gap. How does the structure of information in consumer markets affect market performance, and which kinds of information should be stimulated or controlled? I propose four lines of enquiry to address this over-arching theme: (1) to develop innovative modeling techniques to understand how the structure of information about consumer preferences (possessed by firms and by consumers themselves) affects overall surplus and how that surplus is divided between firms and consumers; (2) to develop methods to study how the structure of consideration sets (i.e., the set of firms a consumer is able or willing to consider for her purchase) affects market outcomes; (3) to analyse how the information channels of advertising by firms and search by consumers interact and which is more important for the efficient functioning of markets, and (4) to investigate which aspects of their preferences consumers are willing to share with firms and thereby understand better how to solve difficult but important pricing problems.