Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : EVOIMMECH (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : University of Otago — Pays : Nouvelle-Zélande — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 62500.0 €

Bacteria have a range of immune mechanisms, but it is unclear why this diverse armamentarium evolved. The most important immune mechanisms are (1) Surface Modification (SM) (2) Abortive infection (Abi) (3) Restriction Modification (R-M) (4) CRISPR-Cas and (5) prokaryotic Argonaute (pAgo), all of which can occur as stand-alone mechanisms or in combination. The individual mechanisms differ in key aspects, such as their fitness costs (constitutive versus inducible), specificity (indiscriminate versus specific), the recipient of the benefits (individual versus group), the speed of de novo resistance evolution (rapid versus slow), and heritability of immunity. Here I will take a combined in vitro and in vivo approach to tease apart the variables that drive the evolution of these diverse stand-alone and integrated bacterial immune strategies in nature, and examine their associated co-evolutionary dynamics. I focus on three ecological variables that are consistently important in host-symbiont co-evolution: (1) force of infection (2) spatial structure (3) presence of mutualists (plasmids). First, I will perform in vitro manipulations using Pseudomonas aeruginosa PA14 variants that carry either single or multiple immune mechanisms. Next, I will sequence metagenomes, transcriptomes and viromes of microbial communities from environments that differ in ecological variables that are important in vitro, to examine their importance in vivo. Key ecological mechanisms identified in the first two parts of the project will be used to guide mesocosm experiments to experimentally confirm that these mechanisms are the drivers of the observed patterns of resistance and co-evolution in nature. Finally, I will share my data with mathematical biologists to generate theoretical models to predict and manipulate the evolution of bacterial immune mechanisms, which will facilitate tailored species protection in agriculture and industry.

Mots-clés : bacteria,phage,plasmid,surface modification,restriction modification,crispr cas,prokaryotic argonaute,abortive infection
Projet ERC : MIX-Effectors (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Life Science
Panel : Immunity, Infection and Immunotherapy
Entité participante : Tel Aviv University — Pays : Israël — Rôle : PI
Acronyme de l'entité : TAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1484375.0 €

Bacteria use various mechanisms to combat competitors and colonize new niches. The Type VI Secretion System (T6SS), a contact-dependent protein delivery apparatus, is a widespread, recently discovered machine used by Gram-negative bacteria to target competitors. Its toxicity is mediated by secreted proteins called effectors, yet the identity of many effectors, the mechanism of secretion of different effector classes, and their toxic activities remain largely unknown. I recently uncovered a widespread class of T6SS effectors that share a domain called MIX. MIX-effectors are polymorphic proteins carrying various toxin domains, many of which with unknown activities. Many bacterial pathogens have acquired resistance to contemporary antibiotic treatments, becoming a public health threat and necessitating the development of novel antibacterial strategies. Thus, as a relatively untapped antibacterial system, studying the T6SS and its MIX-effectors presents a double incentive: 1) previously uncharacterized antibacterial activities of MIX-effectors can illuminate novel cellular targets for antibacterial drug development; 2) the T6SS machinery can be used as a novel toxin delivery platform to combat multi-drug resistant bacterial infections, using polymorphic MIX-effectors. In this proposal, I will focus on T6SS MIX-effectors and elucidate their activities, mechanism of secretion, and utilization as antibacterial agents, by combining microbiology, molecular biology, genetic, biochemical, and proteomic approaches. Specifically, the goal of this proposal is to utilize T6SSs and MIX-effectors to develop a novel T6SS-based, antibacterial therapeutic platform in which a nonpathogenic bacterium will be engineered to carry a T6SS that can secrete a diverse repertoire of polymorphic antibacterial MIX-effectors. This innovative platform has several advantages over current antibacterial strategies, and can be used as an adjustable tool to combat multi-drug resistant bacteria.

Mots-clés : type vi secretion system,effector proteins,antibacterial toxins,protein delivery platform,bacterial infection treatment
Projet ERC : BioMatrix (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: Biological Mechanisms, Structures and Functions
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1499901.0 €

Bacterial biofilm formation is a paramount developmental process in both Gram-positive and Gram-negative species and in many pathogens has been associated with processes of horizontal gene transfer, antibiotic resistance development and pathogen persistence. Bacterial biofilms are collaborative sessile macrocolonies embedded in complex extracellular matrix that secures both mechanical resistance and a medium for intercellular exchange. Biogenesis platforms for the secretion of biofilm matrix components - many of which controlled directly or indirectly by the intracellular second messenger c-di-GMP - are important determinants for biofilm formation and bacterial disease, and therefore present compelling targets for the development of novel therapeutics. During my Ph.D. and post-doctoral work I studied the structure and function of c-di-GMP-sensing protein factors controling extracellular matrix production by DNA-binding at the transcription initiation level or by inside-out signalling mechanisms at the cell envelope, as well as membrane exporters involved directly in downstream matrix component secretion. Here, I propose to apply my expertise in microbiology, protein science and structural biology to study the structure and function of exopolysaccharide secretion systems in Gram-negative species. Using Pseudomonas aeruginosa, Vibrio spp. and Escherichia coli as model organisms, my team will aim to reveal the global architecture and individual building components of several expolysaccharide-producing protein megacomplexes. We will combine X-ray crystallography, biophysical and biochemical assays, electron microscopy and in cellulo functional studies to provide a comprehensive view of extracellular matrix production that spans the different resolution levels and presents molecular blueprints for the development of novel anti-infectives. Over the last year I have laid the foundation of these studies and have demonstrated the overall feasibility of the project.

Mots-clés : biofilm formation,exopolysaccharide secretion,bacterial secretion systems,macromolecular complex assembly,c di gmp signaling
Projet ERC : lending (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : University of Zurich — Pays : Suisse — Rôle : PI
Acronyme de l'entité : UZH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2103440.0 €

Banking crises are thought to be recurrent phenomena that generally come on the heels of strong credit growth. Their damaging real effects have generated a broad agreement among academics and policymakers that financial regulation needs to tighten and to obtain a macroprudential dimension that aims to lessen the negative externalities from the financial to the macro real sector. Among the main ingredients that are often mentioned to have played a role in the explosive growth of credit in the run-up to the latest financial crisis are the financial innovations by financial institutions, in particular loan securitization, the boom in mortgage lending and prices of real estate, the lack of information about prospective borrowers, and the high leverage (and corresponding low capital ratios) of financial institutions. Yet, despite the singling out of these ingredients by policymakers, decisive empirical evidence about their role and relevancy is lacking. However, given the magnitude and complexity of the global banking system and the lack of encompassing micro-level data, it is currently impossible to confidently study the impact of all ingredients jointly. This project therefore analyses pertinent settings where we can empirically identify the correspondence between the aforementioned individual ingredients and the credit granting by financial institutions. The objective of the project is to advance identification and estimation of the impact of each respective factor on loan growth by combining the appropriate methodology with an exceptional set of micro-level datasets. When missing in the literature a theoretical framework will be provided. The project further aims to assess how potential combinations of these ingredients may have interacted in spurring credit growth. While the identification of the impact of each ingredient on credit growth is paramount, the individual setting of the studied datasets and employed methodologies will ensure maximum external validity.
Projet ERC : NEURAL-PROB (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Commissariat à l’énergie atomique et aux énergies alternatives — Pays : France — Rôle : PI
Acronyme de l'entité : CEA
Type d'entité : Recherche
Financement ERC de l'entité : 1499963.0 €

Bayesian inference optimally estimates probabilities from limited and noisy data by taking into account levels of uncertainty. I noticed that human probability estimates are accompanied by rational confidence levels denoting their precision; I thus propose here that the human sense of probability is Bayesian. This Bayesian nature constrains the estimation, neural representation and use of probabilities, which I aim to characterize by combining psychology, computational models and neuro-imaging. I will characterize the Bayesian sense of probability computationally and psychologically. Human confidence as Bayesian precision will be my starting point, I will test other formalizations and look for the human algorithms that approximate Bayesian inference. I will test whether confidence depends on explicit reasoning (with implicit electrophysiological measures), develop ways of measuring its accuracy in a learning context, test whether it is trainable and domain-general. I will then look for the neural codes of Bayesian probabilities, leveraging encoding models for functional magnetic resonance imaging (fMRI) and goal-driven artificial neural networks to propose new codes. I will ask whether the confidence information is embedded in the neural representation of the probability estimate itself, or separable. Last, I will investigate a key function of confidence: the regulation of learning. I will test the implication of neuromodulators such as noradrenaline in this process, using both within and between-subject variability in the activity of key neuromodulatory nuclei (with advanced fMRI), the cortical release of noradrenaline during learning and its receptor density (with positron-emission tomography) and test for causality with pharmacological intervention. Characterizing the sense of probability has broad implications: it should improve our understanding of the way we represent our world with probabilistic internal models, the way we learn and make decisions.

Mots-clés : bayesian inference,computations,multi modal neuroimaging,neuromodulation  metacognition
Projet ERC : Water-Cultures (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : Ca' Foscari University of Venice — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2433520.25 €

Behind this project lies a paradox: water, although vital for life, has historically had little intrinsic value. Considered base and common as a drink, it was nevertheless the most symbolically charged of the elements; of limited monetary value in and of itself, access to it was in fact hard-fought, the foundation and driving force of society. The Water Cultures project aims to create a new field of study, based around the social and cultural history of a people’s polyvalent interactions with water, applicable to a wide range of places and times. The project proposes an epistemological method of structuring, analysing and presenting the diverse range of findings and approaches into a new holistic understanding. The Water Cultures concept is based on the synergistic braiding of five key 'Streams': the symbolic beliefs and practices associated with water; the circulation and evolution of knowledge about water and disease and its effects; the water management systems of large cities and demands on them; the changing hydraulic landscape of rural areas; and the occupations of water, exploring the professions and trades associated with water and its delivery and uses. Italy has been chosen as the case study—for its rich archives and social, political and geographical variety. The Italian history of water, from the 1500s to the end of the 19th century, is a story of authority and conflict, social hierarchy and material realities, changing medical and scientific knowledge and technological expertise, and religious beliefs and practices. Yet Italian historians have undervalued water and its uses. This transformative project conceptualises a new way of writing history, with water at its core. It proposes the history and culture of a given society, the construction of identities and forms of self-representation based on relationships and interactions with water: the ways of controlling, using and conceiving it, and the symbolic, creative and material dimensions it assumed.

Mots-clés : water and the sacred,thermal springs,mineral waters,water and health,disease,cholera,sanitation,hydraulic systems and infrastructure,water supply management,water access,irrigation and land reclamation,water related occupations,circulation of hydrological knowledge and expertise,social and cultural history,environmental history,architectural history,history of medicine,science and technology,hydraulic archaeology,landscape archaeology,social and cultural his
Projet ERC : Outside-In (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : Ghent University — Pays : Belgique — Rôle : PI
Acronyme de l'entité : UGent
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1494044.0 €

Being bullied is a major stressor for many adolescents and it is recognized as a public health concern worldwide. Adolescents who are exposed to bullying are at increased risk for mental and physical health problems, which could even perpetuate into adulthood. Unfortunately, current understandings of how bullying can pose such deleterious effects remain poor, thus limiting our ability to inform prevention and intervention efforts. This project addresses this fundamental gap and substantially extends prior research in two unique ways. First, I will examine fine-grained processes as they occur within adolescents in real-time in their real-life as a crucial pathway for uncovering mechanisms underlying the negative effects of bullying. Second, I will adopt a multilevel perspective to examine the dynamic interplay between multiple psychological and biological processes and how they unfold over time. In this regard, I will examine the possibility that bullying influences gene expression processes resulting in a gene expression profile that increases risk for health problems. In a first study, I will use a longitudinal measurement burst design, allowing me to examine how bullying exposure can influence within-person processes over time at the daily level. I will assess psychological (e.g., emotional) and physiological (e.g., HPA-axis) functioning in situ, and I will use transcriptional profiling to examine how gene expression changes over adolescence as a function of bullying. In a second study, I will utilize data from the Netherlands Twin Register to identify monozygotic twins who differ from each other in their history of victimization in adolescence and examine their gene expression profiles in early adulthood, while accounting for genetic confounds. Together, this research will offer unprecedented insights about short- and long-term interplays between psychological, physiological and molecular processes through which bullying may get into the mind and under the skin.

Mots-clés : peer relations,bullying victimization,adolescence,psychophysiology,experience sampling method,gene expression profiling,biological embedding
Projet ERC : MEMEB (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : BRIQ Institute on Behavior and Inequality — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : BRIQ
Type d'entité : Recherche
Financement ERC de l'entité : 1279361.0 €

Beliefs and expectations play a major role in economic analysis. In the proposed research, I seek to advance our empirical understanding of belief and expectation formation processes by incorporating memory patterns. Intuitively, memory plays a crucial role in the process of belief formation and the evolution of belief distortions, as large parts of the information used when forming beliefs is retrieved from memory. While recent theoretical work has begun to recognize the important role of memory for belief formation, empirical research is virtually non-existent. Accordingly, this research sets out to study the role of memory for belief formation in a set of key domains of behavioral economics. In parts 1a and 1b, I propose to study the role of associative recall in expectation formation. The principle of associative recall posits that current cues trigger the recall of past news that are mentally associated with the cue. Two central predictions that emerge from this principle are: (i) context-cued associative recall can lead to overreaction; (ii) context-cued associative recall can create belief spillovers. I plan to test both predictions in tailored lab experiments. In part 2a, I seek to study the implications of memory for reference-dependent behavior. Reference-dependent preferences are at the heart of many behavioral theories. Yet, the nature and determinants of reference points remains an open issue. I plan to experimentally study how memory shapes reference points. Memory patterns can endogenize the reference point and will deliver precise conditions as to when reference points can be expected to be determined by rational expectations, and when they are more likely to be backward-looking. In the final part of this proposal, I plan to study a key puzzle in behavioral economics. Why are so many people naïve about their present bias? In this project, I propose to experimentally study the role (imperfect) memory plays in generating and maintaining naïveté.

Mots-clés : behavioural economics,experimental economics,belief formation,expectation formation,memory
Projet ERC : FUN POLYSTORE (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Uppsala University — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1950732.0 €

Besides the need for large-scale implementation of renewable energy sources, there is an equivalent need for new energy storage solutions. This is not least true for the transport sector, where electric vehicles are expanding rapidly. The rich flora of battery chemistries – today crowned by the Li-ion battery – is likewise expected to expand in upcoming years. Novel types of batteries, “post-lithium ion”, will challenge the Li-ion chemistries by advantages in cost, sustainability, elemental abundance or energy density. This requires significant improvements of the materials, not least regarding the electrolyte. The conventional liquid battery electrolytes pose a problem already for the mature Li-ion chemistries due to safety and cost, but are particularly destructive for future battery types such as Li-metal, organic electrodes, Li-S, Li-O2, Na- or Mg-batteries, where rapid degradation and loss of material are associated with incompatibilities with the electrolytes. In this context, solid state polymer electrolytes (SPEs) could provide a considerable improvement. The field of solid polymer electrolytes (SPEs) is dominated by polyethers, particularly poly(ethylene oxide) (PEO). This application regards moving out of the established PEO-paradigm and exploring alternative polymer hosts for SPEs, primarily polycarbonates and polyesters. These ‘alternative’ polymers are comparatively easy to work with synthetically, and their possible functionalization is straightforward. The work aims at exploring functionalized alternative polymer host for mechanically robust block-copolymer systems, for alternative cation chemistries (Na, Mg, etc.), for extremely high and low electrochemical potentials, and for unstable and easily dissolved electrode materials (sulfur, organic). Moreover, since the ion transport processes in the host materials are fundamentally different from polyethers, there is a need for investigating the conduction mechanisms using simulations.

Mots-clés : energy storage,li battery,na battery,polymer electrolyte,polymer functionalization,molecular dynamics simulation,block copolymer,polycarbonates