Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : DOG-AMP (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Helmholtz Zentrum München — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : HMGU
Type d'entité : Recherche
Financement ERC de l'entité : 1599261.0 €

The DOG-AMP project will develop cutting-edge methods for Deep Optimized Generation (DOG), and use them to transform the emerging field of AntiMicrobial Peptide (AMP) discovery.  Continuous overuse of antibiotics fuels the outgrowth and spread of multi-drug resistant microbial strains. Increasing antimicrobial resistance is already now a major health and economic hazard, and is expected to account for 10 million deaths globally per year by 2050, exceeding deaths caused by cancer.  AMPs are short peptides that can actively and selectively kill antibiotic-resistant pathogens, and as such are considered the most promising strategy for fighting antimicrobial resistance. Still, intensive research on AMP did not translate to their success in the clinic, mostly due to their lower activity and safety compared to existing antibiotics. Deep optimized generation has the potential to radically advance AMP discovery, but only once unsolved problems are attacked and open research directions in this area are further explored to reach three major objectives of the DOG-AMP project:  i) develop a novel model, geared for deep optimized generation, combining the variational autoencoder framework with probabilistic modeling and algorithms for Pareto (conflicting multi-target) optimization, dealing with data scarcity and bias, generation diversity, and model interpretability;  ii) combine the deep optimized generation model into a framework tailored for the specific needs of AMP design, e.g., accounting for AMP clustering, or conflicting features that make AMPs active or toxic;  iii) apply the newly developed framework to explore and navigate the space of peptides to select and experimentally validate the best candidates that will supersede existing AMPs and antibiotics in their activity against hazardous microbes and safety.  DOG-AMP has the potential to bring breakthroughs in the broad research areas of deep generative modeling, sequence optimization, and AMP discovery.

Mots-clés : deep generative models,antimicrobial peptide design
Projet ERC : NOD-AOL (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : Université norvégienne pour les sciences de la vie — Pays : Norvège — Rôle : PI
Acronyme de l'entité : NMBU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999858.0 €

In the riparian zone of eutrophic lakes and in field denitrification beds, microbial communities degrade lignocellulose, in anoxia, while maintaining a denitrifying lifestyle. During this process nitrate is converted to nitrogen gases via a series of reactions and intermediate products, fueled by the degradation of lignocellulosic biomass. The microbial interactions, metabolic pathways, and enzymatic mechanisms, underlining this remarkable process remain largely unknown. Intriguingly, in these anoxic habitats, enzymes involved in O2-driven oxidative lignocellulose conversion are found and expressed, yet their source of O2, their potential use of other oxidants, and their catalytic mechanism in anoxia remain unknown. Exploring this knowledge gap is a high-risk endeavor with potential to discover yet undescribed enzymes or enzyme systems capable of anaerobic oxidation of lignocellulose (AOL).  I hypothesize that oxidative cleavage of lignocellulose under denitrifying conditions follows aerobic routes including lytic polysaccharide monooxygenases (LPMOs) and lignin-active oxidases, and further, that the activity of nitric oxide dismutases (NODs) provides a source of O2 for LPMOs and lignin-active enzymes. This is conceptually high risk, linking together biological processes in a new way. Herein I will scrutinize my key hypotheses by in-depth characterization of both LPMOs, lignin-active enzymes and NODs to a depth never done before. I will study whether LPMOs can employ relevant non-conventional denitrification-linked electron acceptors and use novel approaches for characterizing the enigmatic NODs.  NOD-AOL is highly interdisciplinary and addresses questions central for understanding the global carbon and nitrogen cycles, which may ultimately help counteracting climate change.

Mots-clés : denitrification,agriculture,eutrophication,enzymes,anaerobic lignocellulose degradation
Projet ERC : DOG-AMP (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Université de Varsovie — Pays : Pologne — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 399210.0 €

The DOG-AMP project will develop cutting-edge methods for Deep Optimized Generation (DOG), and use them to transform the emerging field of AntiMicrobial Peptide (AMP) discovery.  Continuous overuse of antibiotics fuels the outgrowth and spread of multi-drug resistant microbial strains. Increasing antimicrobial resistance is already now a major health and economic hazard, and is expected to account for 10 million deaths globally per year by 2050, exceeding deaths caused by cancer.  AMPs are short peptides that can actively and selectively kill antibiotic-resistant pathogens, and as such are considered the most promising strategy for fighting antimicrobial resistance. Still, intensive research on AMP did not translate to their success in the clinic, mostly due to their lower activity and safety compared to existing antibiotics. Deep optimized generation has the potential to radically advance AMP discovery, but only once unsolved problems are attacked and open research directions in this area are further explored to reach three major objectives of the DOG-AMP project:  i) develop a novel model, geared for deep optimized generation, combining the variational autoencoder framework with probabilistic modeling and algorithms for Pareto (conflicting multi-target) optimization, dealing with data scarcity and bias, generation diversity, and model interpretability;  ii) combine the deep optimized generation model into a framework tailored for the specific needs of AMP design, e.g., accounting for AMP clustering, or conflicting features that make AMPs active or toxic;  iii) apply the newly developed framework to explore and navigate the space of peptides to select and experimentally validate the best candidates that will supersede existing AMPs and antibiotics in their activity against hazardous microbes and safety.  DOG-AMP has the potential to bring breakthroughs in the broad research areas of deep generative modeling, sequence optimization, and AMP discovery.

Mots-clés : deep generative models,antimicrobial peptide design
Projet ERC : OpiO (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Institut national de la santé et de la recherche médicale — Pays : France — Rôle : PI
Acronyme de l'entité : Inserm
Type d'entité : Recherche
Financement ERC de l'entité : 1997915.0 €

Type 2 diabetes (T2D) and obesity are leading causes of morbidity and mortality, becoming a major burden on public health. Failure to understand their pathophysiology has frustrated efforts to develop improved therapeutic strategies. T2D and obesity are complex polygenic disorders. Genome-wide association studies have identified hundreds of loci associated with metabolic traits, but they have not led to promising new drug targets, so far. In contrast, the identification and characterization of rare mutations causing monogenic metabolic disorders have been instrumental in repositioning or developing drugs. Beyond this proof of concept, the challenge is to use genomic medicine for innovative molecules restoring impaired insulin secretion that characterizes T2D. OπO has stemmed from the old but forgotten correlation between opioids consumption and metabolic trait abnormalities. Opioids classically act through delta opioid receptor (DOP encoded by OPRD1), kappa and mu opioid receptors. Based on my preliminary data that include large-scale human functional genetics of OPRD1 mutations, my hypothesis is that DOP is a major link between opioids and metabolism in humans. More specifically, I propose that DOP and opioid signaling have a crucial direct role in insulin secretion from pancreatic β cells; making DOP a promising new drug target against T2D. In this context, I suggest four tasks in OπO: the first two tasks will decipher the role of DOP and opioid signaling in metabolism with a specific focus on islets and β cells, while the two following tasks will decipher the systemic contribution of opioids and opioid receptors to metabolism. The methodologies that I proposed are truly comprehensive and innovative as they combine preclinical animal studies (with a humanized mouse model), deep phenotyping of islets, pharmacology, multi-omic analyses, genome editing, functional genetics, genetic epidemiology (including Mendelian randomization) and clinical intervention study.

Mots-clés : insulin secretion,pancreatic beta cell,type 2 diabetes,opioid,opioid receptor,obesity
Projet ERC : WATER-X (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and Analytical Chemical Sciences
Entité participante : Helmholtz-Zentrum Berlin für Materialien und Energie — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : HZB
Type d'entité : Recherche
Financement ERC de l'entité : 1998125.0 €

Photocatalytic water splitting using transition metal oxides (TMOs) has the potential to play a key role in the sustainable large-scale production of hydrogen. Due to their activity, cost-effectiveness, and stability TMOs are viewed as attractive materials to catalyze water splitting by harnessing solar energy. A major challenge is effectively preventing the recombination of electrons and holes in the TMOs produced upon (solar) light absorption. While these charge recombination processes occur on the pico-to-nanosecond timescale, the whole water splitting process is almost 12 orders of magnitude slower! This huge difference urgently demands a better understanding of the underlying mechanisms and charge-driven chemical reactions involving electron transfer (reduction reaction) or hole transfer (oxidation reaction) that take place at the TMO semiconductor–liquid interface. In my WATER-X project I will investigate these sub-10-picoseconds processes at the interface of TMO nanoparticles in bulk water by using time-resolved femtosecond laser photoelectron spectroscopy by applying liquid microjet setup. The objective is to measure the early-time molecular intermediates and their associated electronic-structures, their lifetimes, energetics, photoelectron angular distributions, and decay mechanisms of the short-lived molecular intermediates. With this knowledge we can determine the exact mechanisms of light-induced water dissociation and will pave the way to manipulating light-induced interactions to the solid-aqueous interface for improving the efficiency of light-to-energy conversion. These novel experiments will be performed for four nanoparticle photocatalysts, hematite, titanium dioxide, cerium oxide, and nickel-iron-oxyhydroxide with manifold electronic-structure properties (bandgap, charge carrier dynamics, and energetics), which make them attractive for future applications.

Mots-clés : photoelectron spectroscopy,solid liquid interface,transient species,
Projet ERC : INSTant CARMA (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and Processes Engineering
Entité participante : Université de Liège — Pays : Belgique — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 938885.0 €

Osteoarthritis (OA) is a highly prevalent disease, affecting 1 in 8 adults worldwide and is projected to increase by 60% in the next two decades. Due to the intricate interplay between multiple influencing factors such as mechanical loading and inflammation playing out over multiple length scales and tissue compartments, currently no disease-modifying drugs are available on the market. The INSTAnt CARMA project aims to harness the power of in silico trials to study OA onset and progression, as well as design endogenous (drugs) and exogenous (tissue engineered) therapies. A multiscale multifactorial in silico model of the knee joint will be established and validated with dedicated in vitro and in vivo experiments. A continuous effort following targeted and untargeted approaches will take place to explore biological hypotheses and implement relevant model extensions. In parallel, computational upscaling tools will be implemented to prepare the model for execution of in silico trial simulations on virtual patient cohorts. The first in silico trial will investigate the effect of model-predicted drug combinations after experimental confirmation in a rodent model. The second trial will seek to optimize tissue engineered constructs for deep osteochondral defect regeneration, followed by experimental validation in a small and large animal model. To realize its goals, INSTAnt CARMA can build on the well-received and published work on a wide range of in silico, in vitro and in vivo tools developed by the applicant and her team. Additionally, the work will benefit from the applicant’s extensive network and involvement in regulatory science for in silico medicine. This project will further accelerate the uptake of in silico testing strategies in the development of medical therapies in general and osteoarthritis in particular.

Mots-clés : in silico medicine,osteoarthritis,tissue engineering,advanced therapy medicinal product,computer modeling and simulation
Projet ERC : ANICOM (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Soci al World and Its Interactions
Entité participante : Université de Liège — Pays : Belgique — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2270511.0 €

As the ‘social’ in social sciences is rethought beyond the human, multispecies research across disciplines increasingly asks how to speak with and for non-human others. I pose that intuitive interspecies communication (IIC), a strategy practiced by successful animal communicators to engage in explicit, detailed, two-way communication with non-human animals, holds uncharted resources for doing research with rather than on animals. Research on IIC has been curtailed to specific domains and mythologized, while the worldwide boom in professional animal communicators has been ignored. ANICOM’s unique engagement with animal communicators’ practical strategies for relating across nature/culture and mind/body dichotomies is ground-breaking in the often largely theoretical discussions of the ontological and species turns. It simultaneously unsettles continued divides between humans and animals as well as dominant and subjugated ways of knowing. The project triangulates participant observation, Q method, interviews and audio-visual methods (including video-diaries and video-elicitations) with natural science approaches, to collaboratively work with six expert animal communicators and a variety of animals in Europe and Africa. It addresses unexplored possibilities for cross-fertilization between new materialism and posthumanism on the one hand, and Indigenous studies and knowledge systems on the other, while relying on the latest insights in biosemiotics and animal cognition. It thus develops transdisciplinary innovations that include non-human animals as full research participants, while achieving a deeper reflexivity on the limitations of humans thinking animals outside the human-animal relationship. It’s ultimate objective is to establish the resources and foundation for dialogic multispecies methods (DMM), a dynamic set of conceptual, theoretical and methodological approaches and tools to engage with the views, experiences and knowledges of non-human animals in academia.

Mots-clés : multispecies ethnography animal turn interspecies methods human animal communication ontological turn posthumanism
Projet ERC : PROGRESS (Horizon Europe, appel 2021, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth System Science
Entité participante : Université Babeș-Bolyai — Pays : Roumanie — Rôle : PI
Acronyme de l'entité : UBB
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2657500.0 €

Quantitative provenance analysis studies are instrumental in understanding the tectonic and climatic processes that are shaping Earth`s landscape. Although the most abundant mineral in the sedimentary system is quartz, almost all studies in provenance analysis investigate accessory minerals. Quartz crystals contain a vast number of point defects, intrinsic or due to impurities. Although our understanding on the formation and dynamics of these defects is far from complete, a few of these defects in quartz are used for dating Quaternary sediments by luminescence (thermoluminescence (TL) or optically stimulated luminescence (OSL)) or by electron spin resonance (ESR). PROGRESS aims at proving that point defects in quartz have also the capacity to carry genetic information and their modifications can provide evidence for antiquity, metamorphism (or lack thereof) as well as knowledge on weathering, transport, or recycling. This information can be unravelled by ESR and luminescence methods in combination with microscopic techniques such as scanning electron microscopy coupled with cathodoluminescence (CL) wavelength resolved spectroscopy. To understand changes that are occurring at atomic level in quartz in nature in geological time, PROGRESS will investigate quartz grains extracted from independently dated old to young quartz-bearing continental crustal sources, metamorphosed rocks versus their unmetamorphosed equivalents, fresh versus highly weathered samples, as well as intrusive versus volcanic rocks, besides conducting experiments in laboratory environments. To tackle nature`s complexity during sediment movement in space and time the effect of physical and chemical changes that occur during transport of quartz grains will be investigated by the study of river sediments that drain different lithologies. These investigations will allow a simple quartz based fingerprinting method to be developed, that will have a significant impact on quantitative provenance studies.

Mots-clés : provenance,quartz,defects,luminescence,electron spin resonance
Projet ERC : ACQUA (Horizon Europe, appel 2022, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer Science and Informatics
Entité participante : Université Ben Gourion du Néguev — Pays : Israël — Rôle : Partner
Acronyme de l'entité : BGU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 400000.0 €

Project ACQUA brings together two of the most important trends in modern cryptographic study, with the aim of maximizing their combined benefit. One is the emergence of quantum computing as a realistic computational model, and the other is the accelerated development of advanced cryptographic tools for the remote processing and control of private data.  As we aspire to a world where quantum computing is prevalent, it is necessary to prepare the proper cryptographic tools for users to utilize their data in such a world. This includes protection against quantum attackers (known as post-quantum security), ways for classical users to securely maintain and process data stored on a remote quantum device, and methods to utilize quantum powers to exceed classically achievable capabilities. Recent developments in quantum cryptographic research gave us a glimpse of the possibilities that such a world holds, but they are still few and far between. We are still far from understanding even the theoretical possibilities and limitations. Project ACQUA is a concentrated effort, drawing from the theory of quantum computing and from the theory of cryptography, towards establishing advanced cryptography in a quantum world as a viable construct and unleashing its full potential.  The project objectives consist of studying the effect of quantum computing on the foundations of cryptography, constructing relevant classical building blocks, and developing new quantum-cryptographic tools that are needed for an advanced quantum-cryptographic future.

Mots-clés : theoretical cryptography,quantum computing,foundations of cryptography
Projet ERC : CATACLIS (Horizon Europe, appel 2023, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention,  Diagnosis and T reatment of Human Diseases
Entité participante : Université Louis-et-Maximilien de Munich — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : LMU
Type d'entité : Organismes publics (hors enseignement & recherche)
Financement ERC de l'entité : 2000000.0 €

Cellular therapies are commonly used to treat hematological cancers but have yet to be established in solid oncology. Their evolution has been fuelled by hypotheses derived from cell biological observations in cancer models. Most approaches, however, will either never enter clinical development or fail clinical testing, often due to inadequate models of disease and their lack of relevance to human biology.  In CATACLIS, I propose the first unbiased development of cellular products based on patient characteristics in order to address this enormous translational gap and ultimately provide more effective cell therapies to patients with solid cancers. CATACLIS will herald a paradigm shift in cell therapy by reversing conventional model-to-patient innovation ("forward translation") to patient-generated ideas tested in patient-derived models into clinical trials ("reverse translation").  I have discovered novel approaches to improve T cell function, which resulted in a clinical trial and established me as a leader in the field of cellular therapies. The challenge I will now face is to move beyond model bias and integrate cancer heterogeneity across patients and entities. In CATACLIS, I will use single cell data sets from patients to inform the design of next generation cellular therapies capable of overcoming current limitations in solid cancers, namely 1) access to tumor tissue, 2) target antigen(s) selection, and 3) immune suppression. To maximize clinical relevance, CATACLIS will use patient-derived materials from hypothesis generation to in vivo testing. This will enable me to create cellular products tailored to the patient´s cancer  My research will not only result in novel cellular products for further testing and development toward clinical trials, but it will also serve as a resource for the development of innovative therapies based on patient data, contribute to the European open science objectives, and reduce the burden of animal experimentation.

Mots-clés : computational analysis car t cells chemokine receptors fusion proteins synthetic biology reverse translation