Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : HERDPATH (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Life Science
Panel : Environmental B iology, Ecology  and E volution
Entité participante : Université Paris 1 - Panthéon Sorbonne — Pays : France — Rôle : Partner
Acronyme de l'entité : Paris 1
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 40000.0 €

Palaeogenomics has transformed our understanding of the genetic consequences of domestication, particularly for livestock species, first brought into the anthropological sphere ~10,000 years ago in Southwest Asia. However, we know little of how domestication shaped the evolution and frequency of pathogens affecting livestock. Moreover, the evolution and occurrence of zoonoses - pathogens infecting both animals and humans - in Neolithic and later societies has been debated, but studies have focused on human remains to obtain ancient pathogen genomes, neglecting animal sources.  HERDPATH will address this deficit through large-scale palaeogenomic screening of faunal remains from Eurasia across 10,000 years. Focusing on sheep and goats, two of our oldest domesticates and which share a high number of common diseases with humans, HERDPATH will analyse both pathogen and ruminant genomes to reveal the dynamic between ancestry, husbandry-induced inbreeding, immune gene variation, and pathogen occurrence through time. Bioinformatic screening will produce a temporal, multi-species archive of pathogen-positive livestock, providing the first molecular baseline of infectious disease presence in domestic herds. Time-stamped pathogen genomes will permit the timing of key evolutionary events such as host adaptation and the origin of lineages circulating today. Using data derived from multiple livestock species, HERDPATH will explore the co-evolutionary trajectory of pathogens and immune genes since domestication.  Exploiting temporal genomes from underexplored sources will reveal how domestication shaped pathogen evolution towards increasing host adaptation, helping us to model the evolutionary dynamics of future livestock disease, zoonosis outbreaks, and food security. HERDPATH will be a step-change in our understanding of the consequences of domestication; how it drove pathogen evolution and the genetic makeup of our herds, shaped animal health, and our own health in return.

Mots-clés : goat genomics,sheep genomics,livestock pathogens,pathogen palaeogenomics,domestication palaeogenomics
Projet ERC : BridgingScales (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and Communication Engineering
Entité participante : Institut national de recherche en sciences et technologies du numérique — Pays : France — Rôle : PI
Acronyme de l'entité : Inria
Type d'entité : Recherche
Financement ERC de l'entité : 1497790.0 €

A key turning point in the evolution of life was the transition from single-cell to multicellular organisms and the optimization of fitness via division of labour and specialization. Similarly, microorganisms have evolved equivalent strategies by forming communities or consortia. Division of labour in isogenic microbial populations is often implemented by mechanisms that create or act upon population heterogeneity to diversify functionality. Rational design in synthetic biology, on the other hand, is focused on the engineering of gene circuits with deterministically predictable functionality within single cells. While synthetic biology has certainly come a long way, predictable functionality of circuits in growing microbial populations still remains elusive or limited to tightly constrained operating conditions. We will develop novel mathematical methods to characterize and control the dynamics of synthetic gene circuits within growing microbial populations. We will develop a modelling framework and novel computational methods that take both stochasticity of single-cell processes and consequences of heterogeneity for population dynamics into account. On the mathematical side, this necessitates coupling single-cell stochastic processes to state dependent population processes such as growth or selection. We will develop methods for parameter inference, experimental design and control for such models. This will enable the construction of models that can be used to design synthetic circuits that function as specified within growing populations and that can be deployed to regulate single-cell processes such that desirable dynamics emerge at the scale of populations and consortia. We will apply the methodology for bioproduction problems in which proteins that are hard to fold need to be produced. Overproducing such proteins impairs cellular growth, which creates couplings between single-cell and population processes and raises the need to feedback control production.

Mots-clés : stochastic chemical kinetics,continuous time markov chains,parameter inference,optimal experimental design,population dynamics,optogenetics,synthetic biology,cybergenetics
Projet ERC : DANCINGFOOL (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Condensed Matter Physics
Entité participante : Institut national de recherche en sciences et technologies du numérique — Pays : France — Rôle : PI
Acronyme de l'entité : Inria
Type d'entité : Recherche
Financement ERC de l'entité : 833775.0 €

A physical system implementing a quantum bit (qubit) is never perfectly isolated from an uncontrolled environment. The system dynamics is thus noisy, modifying randomly the qubit state. This phenomenon of decoherence is the main roadblock to build a stable quantum computing platform. In order to mitigate decoherence, quantum error correction employs only a few code states within a much larger informational space, so that noise-induced dynamics can be detected and corrected before the encoded information gets corrupted. Unfortunately, most known protocols require to control dauntingly complex systems, with a degree of coherence currently out of reach. Our project is to build autonomously error-corrected qubits encoded in high-impedance superconducting circuits. In our protocol, a qubit is encoded in the vast phase-space of the quantum oscillator implemented by each circuit, in the form of Gottesman-Kitaev-Preskill (GKP) states. The novelty is that the GKP states are fully stabilized by a modular dissipation, induced by the coherent tunneling of charges through a stroboscopically biased Josephson junction. The coherence of the encoded qubit is expected to exceed that of existing superconducting qubits by orders of magnitude. Furthermore, we propose to perform protected logical gates between encoded qubits by varying adiabatically the parameters of the modular dissipation, paving the way toward fault-tolerant quantum computing. The major experimental challenge of our protocol resides in the exquisite level of control needed over a wide band in the microwave range. We propose to address this challenge by developing novel on-chip filters, tunable couplers and isolators based on periodically modulated, high-impedance, transmission lines. These on-chip components would find a wide range of applications in quantum technologies, and favor the advent of large-scale quantum computing platforms.

Mots-clés : quantum error correction superconducting circuits reservoir engineering microwave engineering gkp
Projet ERC : MEKanics (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Life Science
Panel : Cell Biology, Development, Stem Cells and R egeneration
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 : 1497550.0 €

Homeostatic platelet counts are crucial for vascular integrity and vital to life. Megakaryocytes (MEKs) are giant hematopoietic cells forming large protrusions that fragment to constantly replenish the circulating platelet pool. Nevertheless, severe blood loss, sepsis and aggressive cancer therapies, often cause critically low platelet levels - a major public health problem in Europe's aging population. Despite the unmet clinical need to control platelet production, there is a major lack of knowledge about the mechanistic cell biology of MEKs, hampering the development of innovative therapies. MEKanics will go beyond the state of the art and proposes a combined cell biological and biophysical approach to study MEKs in physiological tissue environments to uncover the mechanical principles that drive platelet formation. I will use quantitative microscopy to characterize cytoskeletal dynamics of MEKs confined in 3D environments of controlled adhesiveness, geometry and stiffness to reveal the mechanisms of force generation and transmission critical for MEK protrusion formation. Further, I will explore how protrusion mechanics affect cytoplasmic transport and partitioning of organelles required for functional platelets. Using super-resolution intravital imaging, I will investigate these processes in their physiological bone marrow niche. By integrating scRNAseq and live-cell microscopy, I will map morpho-dynamics with transcriptomics to identify the gene signature initiating protrusion formation of MEKs in response to mechanical stimuli. A novel MEK cell-system with optimized access to genetic manipulations will allow high-throughput screening of candidate genes. Together, the unique combination of genetics, engineering, quantitative microscopy and intravital tools will provide a holistic cell mechanical model of MEKs in 3D tissues paving the way for new therapeutic approaches to control platelet formation and to advance devices for large-scale platelet production.

Mots-clés : cell motility,force transmission,actin dynamics,platelets,thrombopoiesis,megakaryopoiesis,cellular confinement
Projet ERC : ARISE (Horizon Europe, appel 2024, Starting grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
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 : 1499979.0 €

The brain exhibits remarkable capacities to initiate self-repair mechanisms after brain injury as a prerequisite for the recovery of lost functions. ARISE will unveil fundamental, yet not understood principles how brain repair mechanisms are orchestrated and how they can be further enhanced. Due to technical constraints, it was previously impossible to uncover 1) how individual neurons rewire and reconnect after CNS injury, 2) why some surviving neurons participate in repair processes and others do not, and 3) how neuronal rewiring could be further stimulated to promote the restoration of impaired functions. But now, with technological advances at hand, I am in a unique position to tackle these major questions by examining causal relationships between neuronal rewiring and behavioral outcome. I have recently developed a mouse model for vascular dementia that enables the monitoring of the same neurons in the hippocampus over several weeks under healthy conditions and after induction of multiple microstrokes in relation to the spatial memory of the animal. Using sophisticated closed-loop experiments, combining chronic 2photon imaging in-vivo with optogenetics and machine learning, I will characterize neuronal recoding in relation to the behavioural performance of the animal. I hypothesize that principles of learning are key to understand how surviving cells are recruited to participate in new neuronal ensembles to restore lost memory engrams. Using local light stimulation I will manipulate surviving neurons to unveil their role in rewiring network dynamics and repair processes and to enhance their engagement in restorative operations. With ARISE I will establish a novel experimental pipeline to identify the cellular mechanisms of neuronal repair that are linked to distinct behavioural outcome parameters. This approach will also allow me to train generalized linear models (GLMs) to assess the efficiency and predict the outcome of novel restorative therapies in stroke.

Mots-clés : neuronal repair,stroke,vascular dementia,neuronal circuit rewiring,hippocampal plasticity
Projet ERC : 2P-BRAINSCOPY (Horizon Europe, appel 2023, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and Communication Engineering
Entité participante : Institute for Bioengineering of Catalonia — Pays : Espagne — Rôle : PI
Acronyme de l'entité : IBEC
Type d'entité : Recherche
Financement ERC de l'entité : 1666199.62 €

Understanding how neuronal circuits process information is a major scientific challenge, which demands new tools to address the complexity of the brain in animals during natural functioning. Two-photon (2P) microscopy, combined with optogenetics, has revolutionized neuroscience thanks to the possibility to image and photostimulate neuronal activity with light, but suffers from important limitations. To determine how perception and behaviour arise, we need to record and manipulate at will the activity of every neuron in a circuit in freely behaving animals. 2P microscopy is on the contrary mainly performed in head-fixed animals, which poses a clear limitation to the study of natural behaviour. At the same time, understanding how different brain areas exchange information requires to maintain single cell spatial resolution (~ 15 μm) and temporal resolutions compatible with the propagation of neuronal signals (~ 1 ms) over ultra large spatial scales (5 mm), which is today completely out of reach for 2P microscopy. In this project I will overcome these limitations and develop the 2P compound fiberscope, a new optical technique based on the unique combination of multiple optical fibers and optimal spatial and temporal beam shaping approaches, which will completely change the way we study neuronal circuits thanks to two main technologies. 1) A flexible 2P micro-endoscope to image and photostimulate neurons in freely moving animals, which will give access to entire brain regions with the highest imaging and manipulation efficiency and the fastest acquisition speed. 2) The first 2P mesoscope specifically conceived to image and manipulate neuronal activity with single cell resolution across the majority of the mouse cortex on temporal scales compatible with the propagation of neuronal signals. These technologies will pave the way for a real understanding of how neuronal circuits drive behaviour, and how different brain regions communicate to process neuronal information

Mots-clés : two photon microscopy,optical fibers,micro endoscopy,optogenetic photostimulation,computer generated holography,calcium and voltage imaging,large field of view microscopy,kilohertz imaging,brain circuits,all optical study of the brain,wavefront shaping
Projet ERC : DynamHet (Horizon Europe, appel 2022, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Fundació Clínic per a la Recerca Biomèdica — Pays : Espagne — Rôle : PI
Acronyme de l'entité : FCRB
Type d'entité : Recherche
Financement ERC de l'entité : 1775190.0 €

Cancer-associated fibroblasts (CAFs) are one of the most abundant and versatile cell types in the tumour microenvironment (TME), where they crosstalk with stromal cells and actively participate in tumour development. Because of their assumed pro-tumourigenic functions, CAFs have long been considered an attractive therapeutic target. However, recent evidence indicates that multiple CAF subpopulations showing inflammatory, myofibroblastic, vascular, antigen-presenting, and immunosuppressive phenotypes co-exist within the same tumour, – with some promoting and other restricting tumour growth; thus, making their targeting challenging. How CAFs change dynamically as cancers evolve, and how this may affect the overall tumour heterogeneity, remains unaddressed. Therefore, the main goal of DynamHet is to elucidate the origin and evolution of CAF heterogeneity and to decipher the mediators and mechanisms that regulate CAF plasticity as the tumour advances. This is crucial for the development of effective therapies aimed at reprogramming CAFs towards therapeutically favourable phenotypes and will constitute a great breakthrough in the field of oncology. Hence, DynamHet aims to 1) decipher the origin of CAF heterogeneity by performing clonal tracing and by generating and characterising CAF subtypes starting from human induced pluripotent stem cells; 2) dissect CAF-TME crosstalk by generating 3D patient-derived organoids and spheroids and by analysing their secretome and transcriptomic profiles using high throughput technologies and computational analysis; and 3) reprogramme CAFs by genetic manipulation in favour of therapeutically advantageous subpopulations as a novel therapeutic approach. DynamHet is an ambitious and feasible project that stands as a pioneer in the new concept of deciphering the origin and reprogramming the dynamic heterogeneity of CAFs towards the development of innovative precision medicine approaches in cancer.

Mots-clés : cancer associated fibroblasts,tumour microenvironment,heterogeneity,cell plasticity,cell crosstalk,target therapy,cholangiocarcinoma
Projet ERC : VeNiss (Horizon Europe, appel 2021, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Texts and Concepts
Entité participante : Université Harvard — Pays : Etats-Unis — Rôle : Partner
Type d'entité : Recherche
Financement ERC de l'entité : 0.0 €

In the historical tradition, Venice is a city without walls and gates, and hence lacking suburbs. VeNiss reverses this trope by examining the urban, political, and cultural patterns connecting the capital with the chain of over sixty islands forming its lagoon fringes. Investigation of their integral role in Venice's spatial practices establishes a ground-breaking approach for the study of historic cities' margins as connective tissues, a subject seldom tackled by urban scholars. Reframing Venice within its archipelago, this project addresses that gap and explores the impact of urban edges on city planning, economic dependence, social responsiveness, and artistic production. From the 16th century, Venice became critically conscious of the granular nature of its hinterland, constructing a governance that involved the islands. Lagoon sites were systematically included in the network of capillary infrastructures for the city's supply, defence, and healthcare as well as civic rituals. Cultural entanglements sometimes bypassed the city, as novel lagoon architectural solutions permeated the Italian Peninsula through the agency of religious communities. Maps, atlases, and books of islands published on and in Venice helped consolidate the capital's archipelagic thinking into a coherent framework. VeNiss sheds light on this physical and theoretical construct –abruptly interrupted by the fall of the Venetian Republic (1797)– through a holistic project which combines social history, architecture, art and literary studies with advanced digital technologies. Coupling close archival readings with modelling systems, it proposes a pioneering methodology to reconstruct the islands' transformations alongside their interwoven relationships in a geographically- and temporally-based digital environment. VeNiss will constitute a crucial contribution to Venetian history while providing a valuable model for future urban studies seeking to visualise dispersed places through time and space.

Mots-clés : urban history history of venice digital heritage reconstruction digital knowledge representation
Projet ERC : OUTLIERS (Horizon Europe, appel 2025, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe Sciences
Entité participante : Institut d'astrophysique des Canaries — Pays : Espagne — Rôle : PI
Acronyme de l'entité : IAC
Type d'entité : Recherche
Financement ERC de l'entité : 1500000.0 €

The number of identified primitive low-metallicity stars has steadily grown. Today, we know of stars with less than one ten-millionth of the solar iron content, but no stars completely devoid of metals —known as Population III (Pop III)— have been identified so far. It was commonly accepted that only massive, short-lived Pop III stars formed from metal-free clouds, but recent simulations suggest that their low-mass counterparts (<1M☉) could also form and may still survive today. However, the mass distribution of these first stars remains unknown, though most are expected to be massive, reaching up to 1000M☉. The first supernova (SN) enriched the medium with heavy elements, enabling the formation of long-lived Population II (Pop II) stars from this processed material. These stars exhibit distinct chemical peculiarities that are key to understanding their Pop III progenitors, including mass and SN explosion energy. However, identifying and characterising these exceedingly rare chemically peculiar stars poses significant challenges. Finding long-lived Pop III stars or second-generation stars polluted by very massive Pop III SNe will revolutionise modern astronomy.  With OUTLIERS I propose a novel approach that combines an unprecedented observational effort, encompassing my large program with the 10.4m GTC, privileged access to the latest spectroscopic surveys (DESI, 4MOST, WEAVE), and Gaia BP/RP data. Together with state-of-the-art models and my advanced analysis tools (FESWI, PISN-explorer), this approach will increase the number of chemically peculiar stars by over an order of magnitude, allowing us, for the first time, to:  -Search for Pop III stars within the largest spectroscopic dataset ever compiled -Identify and characterise second-generation stars to reconstruct the mass and energy of their progenitors  Achieving these objectives will shed light on a critical issue in astrophysics: the formation of the first stars as evidenced by their Pop II descendants.

Mots-clés : population iii,population ii,stellar spectroscopy,chemical evolution