Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : VitruVius (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
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 : 2338519.0 €

Body size is an intrinsic property of living organisms that is intimately linked to the developmental program to produce fit individuals with proper proportions. Final size is the result of both genetic determinants and sophisticated mechanisms adapting size to available resources. Classical regeneration and transplantation experiments have established that different body parts grow according to autonomous programs, challenging the concept of systemic and harmonious growth. Therefore, coordination mechanisms must ensure that all parts have reached appropriate final size before animals stop growing. The main objective of this program is to tackle the mechanisms ensuring growth coordination and size determination. To tackle these questions, we propose to bring together physiology, genetics, advanced imaging and modelling approaches in an unprecedented integrated project. We will develop these approaches on the Drosophila model where we gained expertise, and will develop the vertebrate model Ambystoma mexicanum (axolotl) well adapted for limb growth and regeneration studies. Three major aims will be addressed: 1- We will explore the mechanisms coupling the developmental clock with organ growth. 2- We will dissect the mechanisms allowing inter-organ growth coordination both in response to abnormal growth (injury/neoplasm) and in the course of normal development (control of developmental instability). 3- We will use our knowledge acquired on insect models to develop Ambystoma mexicanum (axolotl) as a vertebrate model for organ growth coordination. We believe this project brings together novel and complementary expertise that will contribute to broader understanding of the fascinating question of body growth and final size assessment.

Mots-clés : growth control,developmental timing,insulin,igf signaling,ecdysone signaling
Projet ERC : ZeoMemRx (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Utrecht University — Pays : Pays-Bas — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Both methane (CH4) and carbon dioxide (CO2) are greenhouse gases, but are available in large supply, and are often flared or vented. A promising strategy to efficiently utilize these abundant molecules is their transformation to easily transported liquid chemicals, which is particularly attractive because this conversion not only reduces emissions of the greenhouse gases into the atmosphere, but also produces commodity chemicals that can be either used as fuels or as precursors for many industrial processes. We propose the fabrication of a prototype membrane reactor, containing catalytically active, highly oriented zeolite ZSM-5 thin-films for the conversion of CO2 and CH4. We have recently demonstrated a method for fabricating catalytically active, highly oriented thin-films of zeolite ZSM-5 on various dense substrates. In this Proof of Concept proposal, we will develop the fabrication of zeolite ZSM-5 thin-films on porous substrates to serve as membranes for catalysis and to convert CH4 and CO2 into liquid commodity chemicals, especially aromatics. The membranes will be incorporated into a prototype reactor, to be designed and implemented as part of the proposal, for reaction testing and optimization. Along with the experimental work we will create a market analysis and seek potential industrial partners, key to this will be pursuing intellectual property coverage through a patent application.

Mots-clés : zeolites,zeolite films,heterogeneous catalysis,membrane reactor,ch4 upgrading,co2 conversion
Projet ERC : ShipShape (Horizon 2020, appel 2017, Proof of concept grants)
Entité participante : Sofia University — Pays : Bulgarie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 127412.5 €

Bottom-up Energy-Efficient Emulsification and Structured Materials Fabrication Building on the novel platform technology we have recently pioneered for the bottom-up bulk generation of shapes, as well as for self-emulsification from liquid droplets, we are developing pre-commercialization activities. The existing method creates, without the use of lithography, applied fields, or other expensive techniques, micro- and nanoparticles of regular geometric shapes, including fibers. By cycling temperature in the range of only a few degrees, it can also efficiently break up rough emulsions into micro- and nano-scale droplets. Last year our process was featured in Nature and we have filed a patent to protect the IP. Since, we have a published several papers on the detailed mechanisms of the transformations and classified over 60 systems of different compounds and surfactants exhibiting this general phenomenon. We have submitted other papers and have several in preparation on further novel physical phenomena and potential uses of the technology. We have received significant interest from existing active industrial collaborators, detailed in the support letters from 3 of the largest chemical and consumer product companies in Europe. In this POC grant we will explore the commercial viability of our technology in order to take it to a pilot plant stage test. We will clarify the IP position in talks with companies that could potentially license it, and cover the initial expenses for establishing a company if the best route turns out to be commercialization via a start-up. This energy- and material-effficient process may become a new bottom-up method for manufacturing.

Mots-clés : emulsions,self emulsification,shape change,elastocapillarity,bottom up fabrication
Projet ERC : NANOCELL (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : Imperial College London — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 609989.35 €

Bottom-up synthetic biology aims to artificially replicate the emerging behaviours of cellular life but struggles to do so without relying on poorly controllable machinery borrowed from biological cells. DNA nanotechnology enables ab-initio design of nanoscale objects with fully programmable structure and dynamic response, making them ideal to mimic the complex functionalities of biological machinery in a truly bottom-up fashion. NANOCELL will establish a fully modular and integrated platform that utilises DNA nanotechnology to prescribe structure and functionality of artificial cells. I will design a library of micron-scale DNA-based objects that mimic cell organelles in their ability to perform specific tasks in response to chemical and environmental stimuli including signal detection and amplification, the capture and release of cargoes, and the construction of structural elements. These “membrane-less organelles” will self-assemble from a new class of amphiphilic DNA building blocks I recently introduced, which enable unprecedented control over the morphology and response of nanostructured frameworks. Interaction between organelles will lead to the emergence of collective effects, and their encapsulation in lipid-bilayer compartments will enable the modular construction of artificial cells displaying a range of complex behaviours such as remote communication, dynamic adaptation, and spatiotemporal patterning in multicellular systems. NANOCELL will consist of three Work Packages reflecting its hierarchical approach: WP1: Mapping the self-assembly behaviour of amphiphilic DNA nanostructures. WP2: Embedding different functionalities in amphiphilic DNA frameworks to produce artificial organelles. WP3: Creating artificial cells by encapsulating DNA organelles in compartmentalised systems. The full programmability afforded by NANOCELL will ultimately unlock long-awaited applications of artificial cells, spanning from biosensing to smart therapeutics.

Mots-clés : structural dna nanotechnology,dynamic dna nanotechnology,artificial cells,bottom up synthetic biology,encapsulation,self assembly,amphiphilic molecules,phase behaviour
Projet ERC : HumanNeuronScreen (Horizon 2020, appel 2020, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Amsterdam University Medical Centers — Pays : Pays-Bas — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

Brain disorders present a staggering health-care burden, costing around 800 billion euros per year in the EU and affecting almost 180 million people. Currently, development of treatments for these disorders is very unsuccessful. Of all currently prescribed drugs, >30% target G-protein coupled receptors, that are typically activated by neuromodulators. Neuromodulators are signaling molecules secreted by most neurons, which regulate many processes in our brain and body. Dysregulation of neuromodulator secretion is firmly associated with many neuropsychiatric disorders, but no screening assay for neuromodulator secretion is currently available to test drug candidates. We have developed a human-based neuromodulator screening assay for preclinical testing of compounds for neuropsychiatric disorders. This assay, the HumanNeuronScreen, uses human neurons derived from somatic patient cells (e.g. skin), to maximally approach the situation in the patients’ CNS and thereby greatly enhancing target validation and lead optimization in preclinical research. It delivers in depth knowledge on the mechanism, potency and selectivity of drug candidates, supporting a higher success rate for clinical trials. Therefore, the value proposition of our product consists of a drastic reduction of costs in drug-development for pharmaceutical and biotech companies, and potentially impacts on 180 million patients in Europe. This proof-of-concept project aims to prove the commercial potential for the HumanNeuronScreen by measuring a reference library of compounds that establishes the resolution, reproducibility and dynamic range of the screen. An IP strategy will be developed to ensure a market position and business strategy will be created and validated. Together, this maximizes the value of the research conducted in the ERC Advanced grant DCV fusion.

Mots-clés : drug discovery,human neurons,neuromodulator assays
Projet ERC : SynLink (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Forschungsverbund Berlin — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : FVB
Type d'entité : Recherche
Financement ERC de l'entité : 1499243.0 €

Brain function crucially depends on chemical neurotransmission at synapses, while, conversely, synaptic dysfunction underlies neurological and psychiatric disorders. Synapses are composed of more than 2,000 distinct proteins, spatially organized into specialized molecular machineries. During decades of efforts, researchers have acquired a wealth of knowledge on individual key components of the synapse. However, the overall picture of the spatial arrangement, molecular architecture and interaction network of the synaptic proteome remains largely uncharted. Furthermore, innovative methods that allow system-wide profiling of these organizational aspects of synaptic proteins are in great demand. I propose to develop a highly sensitive cross-linking mass spectrometry (XL-MS) pipeline to analyze structural and organizational features of the synaptic proteome at an unprecedented depth and comprehensiveness. In parallel, I also plan to establish quantitative XL-MS strategies to reveal global network rearrangements and complex-specific alterations during long-term potentiation, which arguably is the most attractive cellular model for learning and memory. Importantly, it is foreseeable that numerous novel insights can be discovered, for which I will use complementary approaches and tools, such as biochemistry, super-resolution imaging, structural modelling and network analysis to validate and interrogate their molecular details and network principles. These studies will yield groundbreaking insights into the molecular architecture of the synapse and thereby fill a crucial knowledge gap in neuroscience. Furthermore, they will provide a framework to gain a deeper understanding of the dynamic regulation in synaptic plasticity and synaptic dysfunction in neurological disorders.

Mots-clés : cross linking mass spectrometry,synapse,protein structure,protein interaction
Projet ERC : ENSEMBLE (Horizon 2020, appel 2020, Synergy grants)
Entité participante : Université de Bordeaux — Pays : France — Rôle : PI
Acronyme de l'entité : UBx
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499525.0 €

Brain research has made tremendous progress over the last few decades in nearly all areas of investigation with the exception of one: the extracellular space (ECS). It is however a key compartment defined as the web-like space between brain cells, filled with a myriad of molecules that enable brain functions and homeostasis. How molecules navigate in the ECS is a very important, yet unsolved, challenge that precludes conceptual advance in brain science and innovation in therapeutics (e.g. immunotherapy). The lack of knowledge is mainly due to the absence of dedicated investigation strategies for such a complex and finely structured biological entity. Our ground-breaking project (ENSEMBLE) will shed light on the conceptual and methodological roadblocks that have prevented us from understanding the fine architecture of the ECS and how molecules navigate within it throughout the brain. We posit that molecular diffusion in the ECS is locally regulated by the properties of the ECS, which is essential for brain functions. Four world-class scientists, L. Groc (molecular neuroscience, CNRS), E. Bezard (systems neuroscience, INSERM), L. Cognet (optics & nanoscience, CNRS), and U.V. Nägerl (neurophotonics, Univ. Bordeaux), team up to develop and apply unconventional investigation approaches, based on original nano-imaging strategies (super-resolution microscopy and carbon nanotube/nanoparticle tracking), to the in vivo brain. Yet, to consider and achieve such an experimental and multidisciplinary tour de force a side-by-side and daily interactive effort is necessary. Thanks to our complementary expertise and geographical proximity, ENSEMBLE will provide a unique opportunity to unveil in vivo the structure and functions of this crucial brain compartment and will offer a new theoretical and experimental framework to manipulate molecule navigation. The ENSEMBLE project will also cross-fertilize the fields of nanoscience, optical imaging, organ pathophysiology and immunotherapy.

Mots-clés : brain,extracellular space,superresolution microscopy,single molecule imaging,single nanoparticle tracking,immunoglobulin,neuronal communication
Projet ERC : C-MORPH (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Capital Region of Denmark — Pays : Danemark — Rôle : PI
Acronyme de l'entité : RH
Type d'entité : Organismes publics (hors enseignement & recherche)
Financement ERC de l'entité : 1498811.0 €

Brain structure determines function. Disentangling regional microstructural properties and understanding how these properties constitute brain function is a central goal of neuroimaging of the human brain and a key prerequisite for a mechanistic understanding of brain diseases and their treatment. Using magnetic resonance (MR) imaging, previous research has established links between regional brain microstructure and inter-individual variation in brain function, but this line of research has been limited by the non-specificity of MR-derived markers. This hampers the application of MR imaging as a tool to identify specific fingerprints of the underlying disease process. Exploiting state-of-the-art ultra-high field MR imaging techniques, I have recently developed two independent spectroscopic MR methods that have the potential to tackle this challenge: Powder averaged diffusion weighted spectroscopy (PADWS) can provide an unbiased marker for cell specific structural degeneration, and Spectrally tuned gradient trajectories (STGT) can isolate cell shape and size. In this project, I will harness these innovations for MR-based precision medicine. I will advance PADWS and STGT methodology on state-of-the-art MR hardware and harvest the synergy of these methods to realize Cell-specific in-vivo MORPHOMETRY (C-MORPH) of the intact human brain. I will establish novel MR read-outs and analyses to derive cell-type specific tissue properties in the healthy and diseased brain and validate them with the help of a strong translational experimental framework, including histological validation. Once validated, the experimental methods and analyses will be simplified and adapted to provide clinically applicable tools. This will push the frontiers of MR-based personalized medicine, guiding therapeutic decisions by providing sensitive probes of cell-specific microstructural changes caused by inflammation, neurodegeneration or treatment response.
Projet ERC : BRAIN-MATCH (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : German Cancer Research Center — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : DKFZ
Type d'entité : Recherche
Financement ERC de l'entité : 1999875.0 €

Brain tumors represent an extremely heterogeneous group of more than 100 different molecularly distinct diseases, many of which are still almost uniformly lethal despite five decades of clinical trials. In contrast to hematologic malignancies and carcinomas, the cell-of-origin for the vast majority of these entities is unknown. This knowledge gap currently precludes a comprehensive understanding of tumor biology and also limits translational exploitation (e.g., utilizing lineage targets for novel therapies and circulating brain tumor cells for liquid biopsies). The BRAIN-MATCH project represents an ambitious program to address this challenge and unmet medical need by taking an approach that (i) extensively utilizes existing molecular profiles of more than 30,000 brain tumor samples covering more than 100 different entities, publicly available single-cell sequencing data of normal brain regions, and bulk normal tissue data at different times of development across different species; (ii) generates unprecedented maps of normal human CNS development by using state-of-the art novel technologies; (iii) matches these molecular portraits of normal cell types with tumor datasets in order to identify specific cell-of-origin populations for individual tumor entities; and (iv) validates the most promising cell-of-origin populations and tumor-specific lineage and/or surface markers in vivo. The expected outputs of BRAIN-MATCH are four-fold: (i) delivery of an unprecedented atlas of human normal CNS development, which will also be of great relevance for diverse fields other than cancer; (ii) functional validation of at least three lineage targets; (iii) isolation and molecular characterization of circulating brain tumor cells from patients´ blood for at least five tumor entities; and (iv) generation of at least three novel mouse models of brain tumor entities for which currently no faithful models exist.

Mots-clés : brain tumor,tumor biology,molecular characterization,liquid biopsies,single cell sequencing,neurodevelopment
Projet ERC : BrainConquest (Horizon 2020, appel 2016, 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 : 1498751.25 €

Brain-Computer Interfaces (BCIs) are communication systems that enable users to send commands to computers through brain signals only, by measuring and processing these signals. Making computer control possible without any physical activity, BCIs have promised to revolutionize many application areas, notably assistive technologies, e.g., for wheelchair control, and human-machine interaction. Despite this promising potential, BCIs are still barely used outside laboratories, due to their current poor reliability. For instance, BCIs only using two imagined hand movements as mental commands decode, on average, less than 80% of these commands correctly, while 10 to 30% of users cannot control a BCI at all. A BCI should be considered a co-adaptive communication system: its users learn to encode commands in their brain signals (with mental imagery) that the machine learns to decode using signal processing. Most research efforts so far have been dedicated to decoding the commands. However, BCI control is a skill that users have to learn too. Unfortunately how BCI users learn to encode the commands is essential but is barely studied, i.e., fundamental knowledge about how users learn BCI control is lacking. Moreover standard training approaches are only based on heuristics, without satisfying human learning principles. Thus, poor BCI reliability is probably largely due to highly suboptimal user training. In order to obtain a truly reliable BCI we need to completely redefine user training approaches. To do so, I propose to study and statistically model how users learn to encode BCI commands. Then, based on human learning principles and this model, I propose to create a new generation of BCIs which ensure that users learn how to successfully encode commands with high signal-to-noise ratio in their brain signals, hence making BCIs dramatically more reliable. Such a reliable BCI could positively change human-machine interaction as BCIs have promised but failed to do so far.

Mots-clés : brain computer interfaces,electroencephalography,training,learning