Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : FIT2GO (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : University of Bern — Pays : Suisse — Rôle : PI
Acronyme de l'entité : UB
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1121811.25 €

A major challenge in evolutionary biology is to quantify the processes and mechanisms by which populations adapt to new environments. In particular, the role of epistasis, which is the genetic-background dependent effect of mutations, and the constraints it imposes on adaptation, has been contentious for decades. This question can be approached using the concept of a fitness landscape: a map of genotypes or phenotypes to fitness, which dictates the dynamics and the possible paths towards increased reproductive success. This analogy has inspired a large body of theoretical work, in which various models of fitness landscapes have been proposed and analysed. Only recently, novel experimental approaches and advances in sequencing technologies have provided us with large empirical fitness landscapes at impressive resolution, which call for the evaluation of the related theory. The aim of this proposal is to build on the theory of fitness landscapes to quantify epistasis across levels of biological organization and across environments, and to study its impact on the population genetics of adaptation and hybridization. Each work package involves classical theoretical modelling, statistical inference and method development, and data analysis and interpretation; a combination of approaches for which my research group has strong expertise. In addition, we will perform experimental evolution in Escherichia coli and influenza to test hypotheses related to the change of fitness effects across environments, and to adaptation by means of highly epistatic mutations. We will specifically apply our methods to evaluate the potential for predicting routes to drug resistance in pathogens. The long-term goal lies in the development of a modeling and inference framework that utilizes fitness landscape theory to infer the ecological history of a genome, which may ultimately allow for a prediction of its future adaptive potential.

Mots-clés : evolutionary theory,mathematical modeling,statistical population genetics,viral evolution
Projet ERC : FIT2GO (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : Calouste Gulbenkian Foundation — Pays : Portugal — Rôle : Partner
Type d'entité : Recherche
Financement ERC de l'entité : 244438.75 €

A major challenge in evolutionary biology is to quantify the processes and mechanisms by which populations adapt to new environments. In particular, the role of epistasis, which is the genetic-background dependent effect of mutations, and the constraints it imposes on adaptation, has been contentious for decades. This question can be approached using the concept of a fitness landscape: a map of genotypes or phenotypes to fitness, which dictates the dynamics and the possible paths towards increased reproductive success. This analogy has inspired a large body of theoretical work, in which various models of fitness landscapes have been proposed and analysed. Only recently, novel experimental approaches and advances in sequencing technologies have provided us with large empirical fitness landscapes at impressive resolution, which call for the evaluation of the related theory. The aim of this proposal is to build on the theory of fitness landscapes to quantify epistasis across levels of biological organization and across environments, and to study its impact on the population genetics of adaptation and hybridization. Each work package involves classical theoretical modelling, statistical inference and method development, and data analysis and interpretation; a combination of approaches for which my research group has strong expertise. In addition, we will perform experimental evolution in Escherichia coli and influenza to test hypotheses related to the change of fitness effects across environments, and to adaptation by means of highly epistatic mutations. We will specifically apply our methods to evaluate the potential for predicting routes to drug resistance in pathogens. The long-term goal lies in the development of a modeling and inference framework that utilizes fitness landscape theory to infer the ecological history of a genome, which may ultimately allow for a prediction of its future adaptive potential.

Mots-clés : evolutionary theory,mathematical modeling,statistical population genetics,viral evolution
Projet ERC : QSIMCORR (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : Ludwig-Maximilians-Universität München — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LMU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

A major challenge in theoretical physics is to develop novel methods without systematic errors. The scope of this proposal is the numerical control over strongly correlated phases in the thermodynamic limit through two main developments: First, for bosonic systems, we aim to obtain reliable phase diagrams for optical flux lattices, combining topology with interactions. In particular, we study the competition between superfluid order and (fractional) Chern insulators, which may harbor (non-)abelian anyonic excitations. This is achieved by a major improvement on our current selfenergy-based cluster methods through non-local interactions, vertex corrections and momentum cluster extensions. This also enables access to out-of-equilibrium dynamics, relevant to study quench-type experiments. In the presence of disorder, we can then answer whether many-body-localization exists in higher dimensions and address the fundamental puzzle of how and when systems thermalize. Second, for fermionic systems with long-range interactions, such as warm dense matter, the electron gas, and cold gases with Rydberg interactions, the diagrammatic Monte Carlo method is uniquely situated to compute thermal exchange correlation energies over the entire density range, essential to any calculation in condensed matter physics, astro physics and plasma physics. It employs a universal language but needs further algorithmic refinements for improving its convergence and sign properties. Extensions are towards (frustrated) spin systems, providing an alternative route to the realization of strongly correlated phases. At all stages analytical derivations must be supplemented with coding and large-scale computation. We address what new types of quantum systems can efficiently be computed on a classical computer, and how. Simultaneously, we seek to extend the paradigm of quantum simulation by comparing the results of our novel methods with cold gas experiments in challenging regimes, where possible.

Mots-clés : quantum monte carlo,strong correlations,quantum simulations,topology,many body localization,warm dense matter,electron gas,high performance computing,algorithms
Projet ERC : KiloNeurons (Horizon 2020, appel 2020, Synergy grants)
Entité participante : Norwegian University of Science and Technology — Pays : Norvège — Rôle : CO-PI
Acronyme de l'entité : NTNU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 7211875.0 €

A major goal in neuroscience is to understand neural computation in the mammalian cortex. Since the 1950s, we have learnt how cells respond to changes in the environment but the cells have largely been observed one at a time. However, single-cell recording cannot access the complexity of distributed processing and coding in the large, intermixed cell populations of the cortex. To understand this complexity, we need population-wide activity measurements, at single-cell resolution, as well as theoretical models to interpret the data. In this project, we shall combine experiments and theory to enable a paradigmatic shift from single-cell to population analysis for a prototypical high-level cortical system, the navigation system of the mammalian medial entorhinal-hippocampal region. In this system, spatial firing correlates of individual cells are so evident that they have been given simple, descriptive names – such as place cells, grid cells, and head direction cells. The wealth of information on the phenomenology of these cells, and the existence of theoretical frameworks that offer strong predictions on their population-wide activity patterns, renders the system perfect for population-level analyses of cortical computation. We shall introduce experimental tools to obtain the amount and specificity of multi-neuron data required to decipher neural population codes in freely navigating rodents. Guided initially by theory on attractor network dynamics, we shall identify regularities in firing and connectivity patterns of thousands of simultaneously monitored neurons and use the data to test, refine and develop theoretical models. This exercise will be extended to less-understood high-end systems such as lateral entorhinal cortex, where computational operations have remained elusive due to the lack of similar single-cell correlates. The project is transformative in that it will uncover fundamental and general mechanisms of high-end cortical population coding in mammals.

Mots-clés : computational neuroscience,entorhinal cortex,hippocampus,attractor networks,continuous attractors,grid cells,head direction cells,cortex,neural networks,spatial computation
Projet ERC : APPROAcH (Horizon 2020, appel 2014, Proof of concept grants)
Entité participante : University of Groningen — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : RUG
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

A major problem in dental care restorations is bacterial infiltration. Bacteria between the tooth and the restoration is a potential cause of postoperative sensitivity, pulp inflammation, and necrosis. In orthodontics, the formation of biofilms during treatment bears the risk of enamel decalcification, cavity formation, and gingival inflammation due to the fact that colonized bacteria are extremely hard to remove in presence of orthodontic appliances. Another related problem is that the current fabrication of dental restorations and braces is labor intensive, requiring highly skilled technicians. Recently, steps have been taken to change the traditional workflow and introduce 3D printing (3DP) technology in this field. 3DP enables a more patient specific way of working, increasing the quality of dental care on the one hand and reducing the costs on the other hand. To address both problems, a highly innovative 3DP antimicrobial polymer system for applications in dentistry and orthodontics will be developed in this proposal. Since the materials will be in contact to or incorporated into the body, attention needs to be paid to render these systems non-toxic and biocompatible. Second, the commercial, IPR and business opportunities of these novel materials will be investigated.

Mots-clés : antimicrobial,3d printable,oral health,polymer,resin,chemistry
Projet ERC : NutrientSensingVivo (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : Spanish National Cancer Research Centre — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CNIO
Type d'entité : Recherche
Financement ERC de l'entité : 1846494.0 €

A major role of metabolic alterations in the development of several human diseases, as diabetes, cancer and in the onset of ageing is becoming increasingly evident. This has a deep impact for human health due to the alarming increase in nutrient intake and obesity in the last decades. Fundamental aspects of how aberrant nutrient fluctuations trigger deregulated hormone levels and endocrine signals have been elucidated, being a prime example the phenomenon of insulin resistance. In contrast, how changes in nutrient levels elicit direct cell-autonomous signal transduction cascades and the consequences of these responses in physiology are less clear. The signalling circuitry of direct nutrient sensing converges with that of hormones in the regulation of the mechanistic target of rapamycin (mTOR) kinase, a driver of anabolism, cell growth and proliferation. Deregulation of mTORC1 activity underlies the pathogenesis of cancer and diabetes, and its inhibitor rapamycin is approved as an anti-cancer agent and delays ageing from yeast to mammals. In spite of its importance for human disease, our understanding of the nutrient sensing signalling pathway and its impact in physiology is largely incomplete, as only a few years ago the direct molecular link between nutrients and mTORC1 activation, the Rag GTPases, were identified. The present proposal aims to determine how the nutrient sensing signalling pathway affects mammalian physiology and metabolism, and whether its deregulation contributes to cancer, insulin resistance and aging. In particular, the objectives are: 1) To identify novel regulators of the Rag GTPases with unbiased and candidate-based approaches. 2) To establish the consequences of deregulated nutrient-dependent activation of mTORC1 in physiology, by means of genetically engineered mice. 3) To determine the impact of the nutrient sensing pathway in the effects of dietary restriction and nutrient limitation in glucose homeostasis and cancer.

Mots-clés : mouse models,signal transduction,mtorc1,nutrients,aging,physiology,rag gtpases
Projet ERC : EXTREMA (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Politecnico di Milano — Pays : Italie — Rôle : PI
Acronyme de l'entité : POLIMI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1972837.0 €

A new space era is fast approaching. A multitude of miniaturised probes will soon permeate the inner solar system. The abundantly variegated minor bodies will be the destinations of numerous missions driven by exploration and exploitation needs. Missions to rocky planets will feature networks of artificial satellites to support science and operations. Yet, the state-of-the-art is to pilot deep-space probes from ground. Although this is reliable, ground control slots will saturate soon, thus hampering the current momentum in space exploration. EXTREMA enables self-driving spacecraft: machines able to travel in the deep space free of human-driven instructions. We take the challenge to make these systems a reality, and fundamental research is conducted to lay down their foundations. The ambition of EXTREMA is to prove that minor bodies and inner planets can be reached in a totally autonomous fashion with highly constrained platforms. These systems are used to engineer ballistic capture, an extremely rare event observed in highly sensitive regimes. To reinforce this logic, a new approach in orbit validation is introduced, which excels pure computer simulations. Erected over three pillars, the project forges a Simulation Hub, which reproduces on ground the spacecraft-environment interaction. While the pillars enable intermediate milestones, such as inferring the spacecraft position by exploiting the surrounding environment (autonomous navigation), self-determining a nominal plan without a-priori knowledge (autonomous guidance), and targeting the corridors that conduce to ballistic capture, it is the activity performed in the Simulation Hub that allows achieving the objectives via dedicated case studies. A successful outcome will boost access to outer space. The impact is to favour settlements in the inner solar system on a large-scale basis. Located at the fringe of research, EXTREMA can determine a paradigm shift in the way we conceive and conduct deep-space mission.

Mots-clés : astrodynamics,space trajectory design and optimisation,optical navigation,orbit control,autonomous guidance,navigation,and control,interplanetary cubesat,space engineering
Projet ERC : EpiRibo (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Weizmann Institute of Science — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

A remarkable diversity of post-transcriptional modifications adorn the ribosomal RNA (rRNA) throughout all domains of life. While initially conceptualized as a constitutive component of the ribosome, recent evidence demonstrates that some modifications are only present on a fraction of cellular ribosomes, and our lab recently revealed unprecedented environmentally-mediated dynamics of an rRNA modification. This suggests that some rRNA modification may serve as a tunable layer for regulation of ribosome properties, facilitating adaptation to a new environment, stress or pathological state. Here we aim to systematically explore the extent to which rRNA modifications are tunable across evolution and highly diverse growth conditions, and to understand the consequences thereof. We seek to understand which rRNA modifications are subject to regulation, to uncover the contexts in which such regulation occurs, and to unravel the underlying mechanisms. Dissecting these questions requires an approach allowing systematic measurement of diverse rRNA modifications. We propose to establish a streamlined workflow, allowing multiplexed, precise, robust and cost-efficient systematic profiling of 19 distinct rRNA modifications in dozens of samples in a single experiment (Aim 1). In Aim 2, we will systematically measure rRNA modifications across the three domains of life, focusing on species that can thrive across two widely different physical/chemical gradients, where the potential for tunable rRNA modifications is particularly high. In Aim 3, we will combine gain- and loss-of-function approaches to systematically explore the functions RNA modifications can bestow on ribosomes. Collectively, EpiRibo addresses a fundamental open question regarding the extent of plasticity and regulatory potential present within the ribosome itself and encoded via its epitranscriptome, setting the stage for investigations in other RNA species, and in more complex and disease-related contexts.

Mots-clés : epitranscriptome,rna modifications,post transcriptional regulation,rrna modifications
Projet ERC : DINA (Horizon 2020, appel 2019, Synergy grants)
Entité participante : University of California System — Pays : Etats-Unis — Rôle : PI
Acronyme de l'entité : UC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1400000.0 €

A renovated approach to the measurement of economic inequality consistent with macro aggregates should rebuild the bridges between distributional data available from micro sources and national accounts aggregates in a systematic way. This is the main goal pursued through DINA-Distributional National Accounts. The aim is to provide annual estimates of the distribution of income and wealth using concepts that are consistent with the macroeconomic national accounts. In this way, the analysis of growth and inequality can be carried over in a coherent framework. This endeavour also involves the production of synthetic micro-files (i.e. individual level data that are not necessarily the result of direct observation but rather through estimations that reproduce the observed distribution of the underlying data, including the joint distribution of age, gender, numbers of dependent children, income and wealth between adult individuals) providing information on income and wealth, which will also be made available online. The global aim is to release income and wealth synthetic DINA micro-files for all countries on an annual basis. Such data will certainly play a critical role in the public debate, and will be used as a resource for further analysis by various actors in civil society and in the academic, business and political communities.

Mots-clés : distribution  income  wealth  inequality  national accounts  returns
Projet ERC : CABUM (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : University of Ljubljana — Pays : Slovénie — Rôle : PI
Acronyme de l'entité : UL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1609065.0 €

A sudden decrease in pressure triggers the formation of vapour and gas bubbles inside a liquid medium (also called cavitation). This leads to many (key) engineering problems: material loss, noise and vibration of hydraulic machinery. On the other hand, cavitation is a potentially a useful phenomenon: the extreme conditions are increasingly used for a wide variety of applications such as surface cleaning, enhanced chemistry, and waste water treatment (bacteria eradication and virus inactivation). Despite this significant progress a large gap persists between the understanding of the mechanisms that contribute to the effects of cavitation and its application. Although engineers are already commercializing devices that employ cavitation, we are still not able to answer the fundamental question: What precisely are the mechanisms how bubbles can clean, disinfect, kill bacteria and enhance chemical activity? The overall objective of the project is to understand and determine the fundamental physics of the interaction of cavitation bubbles with different contaminants. To address this issue, the CABUM project will investigate the physical background of cavitation from physical, biological and engineering perspective on three complexity scales: i) on single bubble level, ii) on organised and iii) on random bubble clusters, producing a progressive multidisciplinary synergetic effect. The proposed synergetic approach builds on the PI's preliminary research and employs novel experimental and numerical methodologies, some of which have been developed by the PI and his research group, to explore the physics of cavitation behaviour in interaction with bacteria and viruses. Understanding the fundamental physical background of cavitation in interaction with contaminants will have a ground-breaking implications in various scientific fields (engineering, chemistry and biology) and will, in the future, enable the exploitation of cavitation in water and soil treatment processes.

Mots-clés : cavitation,exploitation,bacteria,viruses,water treatment