Project acronym 3DCellPhase-
Project In situ Structural Analysis of Molecular Crowding and Phase Separation
Researcher (PI) Julia MAHAMID
Host Institution (HI) EUROPEAN MOLECULAR BIOLOGY LABORATORY
Call Details Starting Grant (StG), LS1, ERC-2017-STG
Summary This proposal brings together two fields in biology, namely the emerging field of phase-separated assemblies in cell biology and state-of-the-art cellular cryo-electron tomography, to advance our understanding on a fundamental, yet illusive, question: the molecular organization of the cytoplasm.
Eukaryotes organize their biochemical reactions into functionally distinct compartments. Intriguingly, many, if not most, cellular compartments are not membrane enclosed. Rather, they assemble dynamically by phase separation, typically triggered upon a specific event. Despite significant progress on reconstituting such liquid-like assemblies in vitro, we lack information as to whether these compartments in vivo are indeed amorphous liquids, or whether they exhibit structural features such as gels or fibers. My recent work on sample preparation of cells for cryo-electron tomography, including cryo-focused ion beam thinning, guided by 3D correlative fluorescence microscopy, shows that we can now prepare site-specific ‘electron-transparent windows’ in suitable eukaryotic systems, which allow direct examination of structural features of cellular compartments in their cellular context. Here, we will use these techniques to elucidate the structural principles and cytoplasmic environment driving the dynamic assembly of two phase-separated compartments: Stress granules, which are RNA bodies that form rapidly in the cytoplasm upon cellular stress, and centrosomes, which are sites of microtubule nucleation. We will combine these studies with a quantitative description of the crowded nature of cytoplasm and of its local variations, to provide a direct readout of the impact of excluded volume on molecular assembly in living cells. Taken together, these studies will provide fundamental insights into the structural basis by which cells form biochemical compartments.
Summary
This proposal brings together two fields in biology, namely the emerging field of phase-separated assemblies in cell biology and state-of-the-art cellular cryo-electron tomography, to advance our understanding on a fundamental, yet illusive, question: the molecular organization of the cytoplasm.
Eukaryotes organize their biochemical reactions into functionally distinct compartments. Intriguingly, many, if not most, cellular compartments are not membrane enclosed. Rather, they assemble dynamically by phase separation, typically triggered upon a specific event. Despite significant progress on reconstituting such liquid-like assemblies in vitro, we lack information as to whether these compartments in vivo are indeed amorphous liquids, or whether they exhibit structural features such as gels or fibers. My recent work on sample preparation of cells for cryo-electron tomography, including cryo-focused ion beam thinning, guided by 3D correlative fluorescence microscopy, shows that we can now prepare site-specific ‘electron-transparent windows’ in suitable eukaryotic systems, which allow direct examination of structural features of cellular compartments in their cellular context. Here, we will use these techniques to elucidate the structural principles and cytoplasmic environment driving the dynamic assembly of two phase-separated compartments: Stress granules, which are RNA bodies that form rapidly in the cytoplasm upon cellular stress, and centrosomes, which are sites of microtubule nucleation. We will combine these studies with a quantitative description of the crowded nature of cytoplasm and of its local variations, to provide a direct readout of the impact of excluded volume on molecular assembly in living cells. Taken together, these studies will provide fundamental insights into the structural basis by which cells form biochemical compartments.
Max ERC Funding
1 228 125 €
Duration
Start date: 2018-02-01, End date: 2023-01-31
Project acronym ABCTRANSPORT
Project Minimalist multipurpose ATP-binding cassette transporters
Researcher (PI) Dirk Jan Slotboom
Host Institution (HI) RIJKSUNIVERSITEIT GRONINGEN
Call Details Starting Grant (StG), LS1, ERC-2011-StG_20101109
Summary Many Gram-positive (pathogenic) bacteria are dependent on the uptake of vitamins from the environment or from the infected host. We have recently discovered the long-elusive family of membrane protein complexes catalyzing such transport. The vitamin transporters have an unprecedented modular architecture consisting of a single multipurpose energizing module (the Energy Coupling Factor, ECF) and multiple exchangeable membrane proteins responsible for substrate recognition (S-components). The S-components have characteristics of ion-gradient driven transporters (secondary active transporters), whereas the energizing modules are related to ATP-binding cassette (ABC) transporters (primary active transporters).
The aim of the proposal is threefold: First, we will address the question how properties of primary and secondary transporters are combined in ECF transporters to obtain a novel transport mechanism. Second, we will study the fundamental and unresolved question how protein-protein recognition takes place in the hydrophobic environment of the lipid bilayer. The modular nature of the ECF proteins offers a natural system to study the driving forces used for membrane protein interaction. Third, we will assess whether the ECF transport systems could become targets for antibacterial drugs. ECF transporters are found exclusively in prokaryotes, and their activity is often essential for viability of Gram-positive pathogens. Thus they could turn out to be an Achilles’ heel for the organisms.
Structural and mechanistic studies (X-ray crystallography, microscopy, spectroscopy and biochemistry) will reveal how the different transport modes are combined in a single protein complex, how transport is energized and catalyzed, and how protein-protein recognition takes place. Microbiological screens will be developed to search for compounds that inhibit prokaryote-specific steps of the mechanism of ECF transporters.
Summary
Many Gram-positive (pathogenic) bacteria are dependent on the uptake of vitamins from the environment or from the infected host. We have recently discovered the long-elusive family of membrane protein complexes catalyzing such transport. The vitamin transporters have an unprecedented modular architecture consisting of a single multipurpose energizing module (the Energy Coupling Factor, ECF) and multiple exchangeable membrane proteins responsible for substrate recognition (S-components). The S-components have characteristics of ion-gradient driven transporters (secondary active transporters), whereas the energizing modules are related to ATP-binding cassette (ABC) transporters (primary active transporters).
The aim of the proposal is threefold: First, we will address the question how properties of primary and secondary transporters are combined in ECF transporters to obtain a novel transport mechanism. Second, we will study the fundamental and unresolved question how protein-protein recognition takes place in the hydrophobic environment of the lipid bilayer. The modular nature of the ECF proteins offers a natural system to study the driving forces used for membrane protein interaction. Third, we will assess whether the ECF transport systems could become targets for antibacterial drugs. ECF transporters are found exclusively in prokaryotes, and their activity is often essential for viability of Gram-positive pathogens. Thus they could turn out to be an Achilles’ heel for the organisms.
Structural and mechanistic studies (X-ray crystallography, microscopy, spectroscopy and biochemistry) will reveal how the different transport modes are combined in a single protein complex, how transport is energized and catalyzed, and how protein-protein recognition takes place. Microbiological screens will be developed to search for compounds that inhibit prokaryote-specific steps of the mechanism of ECF transporters.
Max ERC Funding
1 500 000 €
Duration
Start date: 2012-01-01, End date: 2017-12-31
Project acronym ABRSEIST
Project Antibiotic Resistance: Socio-Economic Determinants and the Role of Information and Salience in Treatment Choice
Researcher (PI) Hannes ULLRICH
Host Institution (HI) DEUTSCHES INSTITUT FUR WIRTSCHAFTSFORSCHUNG DIW (INSTITUT FUR KONJUNKTURFORSCHUNG) EV
Call Details Starting Grant (StG), SH1, ERC-2018-STG
Summary Antibiotics have contributed to a tremendous increase in human well-being, saving many millions of lives. However, antibiotics become obsolete the more they are used as selection pressure promotes the development of resistant bacteria. The World Health Organization has proclaimed antibiotic resistance as a major global threat to public health. Today, 700,000 deaths per year are due to untreatable infections. To win the battle against antibiotic resistance, new policies affecting the supply and demand of existing and new drugs must be designed. I propose new research to identify and evaluate feasible and effective demand-side policy interventions targeting the relevant decision makers: physicians and patients. ABRSEIST will make use of a broad econometric toolset to identify mechanisms linking antibiotic resistance and consumption exploiting a unique combination of physician-patient-level antibiotic resistance, treatment, and socio-economic data. Using machine learning methods adapted for causal inference, theory-driven structural econometric analysis, and randomization in the field it will provide rigorous evidence on effective intervention designs. This research will improve our understanding of how prescribing, resistance, and the effect of antibiotic use on resistance, are distributed in the general population which has important implications for the design of targeted interventions. It will then estimate a structural model of general practitioners’ acquisition and use of information under uncertainty about resistance in prescription choice, allowing counterfactual analysis of information-improving policies such as mandatory diagnostic testing. The large-scale and structural econometric analyses allow flexible identification of physician heterogeneity, which ABRSEIST will exploit to design and evaluate targeted, randomized information nudges in the field. The result will be improved rational use and a toolset applicable in contexts of antibiotic prescribing.
Summary
Antibiotics have contributed to a tremendous increase in human well-being, saving many millions of lives. However, antibiotics become obsolete the more they are used as selection pressure promotes the development of resistant bacteria. The World Health Organization has proclaimed antibiotic resistance as a major global threat to public health. Today, 700,000 deaths per year are due to untreatable infections. To win the battle against antibiotic resistance, new policies affecting the supply and demand of existing and new drugs must be designed. I propose new research to identify and evaluate feasible and effective demand-side policy interventions targeting the relevant decision makers: physicians and patients. ABRSEIST will make use of a broad econometric toolset to identify mechanisms linking antibiotic resistance and consumption exploiting a unique combination of physician-patient-level antibiotic resistance, treatment, and socio-economic data. Using machine learning methods adapted for causal inference, theory-driven structural econometric analysis, and randomization in the field it will provide rigorous evidence on effective intervention designs. This research will improve our understanding of how prescribing, resistance, and the effect of antibiotic use on resistance, are distributed in the general population which has important implications for the design of targeted interventions. It will then estimate a structural model of general practitioners’ acquisition and use of information under uncertainty about resistance in prescription choice, allowing counterfactual analysis of information-improving policies such as mandatory diagnostic testing. The large-scale and structural econometric analyses allow flexible identification of physician heterogeneity, which ABRSEIST will exploit to design and evaluate targeted, randomized information nudges in the field. The result will be improved rational use and a toolset applicable in contexts of antibiotic prescribing.
Max ERC Funding
1 498 920 €
Duration
Start date: 2019-01-01, End date: 2023-12-31
Project acronym ACCENT
Project Unravelling the architecture and the cartography of the human centriole
Researcher (PI) Paul, Philippe, Desiré GUICHARD
Host Institution (HI) UNIVERSITE DE GENEVE
Call Details Starting Grant (StG), LS1, ERC-2016-STG
Summary The centriole is the largest evolutionary conserved macromolecular structure responsible for building centrosomes and cilia or flagella in many eukaryotes. Centrioles are critical for the proper execution of important biological processes ranging from cell division to cell signaling. Moreover, centriolar defects have been associated to several human pathologies including ciliopathies and cancer. This state of facts emphasizes the importance of understanding centriole biogenesis. The study of centriole formation is a deep-rooted question, however our current knowledge on its molecular organization at high resolution remains fragmented and limited. In particular, exquisite details of the overall molecular architecture of the human centriole and in particular of its central core region are lacking to understand the basis of centriole organization and function. Resolving this important question represents a challenge that needs to be undertaken and will undoubtedly lead to groundbreaking advances. Another important question to tackle next is to develop innovative methods to enable the nanometric molecular mapping of centriolar proteins within distinct architectural elements of the centriole. This missing information will be key to unravel the molecular mechanisms behind centriolar organization.
This research proposal aims at building a cartography of the human centriole by elucidating its molecular composition and architecture. To this end, we will combine the use of innovative and multidisciplinary techniques encompassing spatial proteomics, cryo-electron tomography, state-of-the-art microscopy and in vitro assays and to achieve a comprehensive molecular and structural view of the human centriole. All together, we expect that these advances will help understand basic principles underlying centriole and cilia formation as well as might have further relevance for human health.
Summary
The centriole is the largest evolutionary conserved macromolecular structure responsible for building centrosomes and cilia or flagella in many eukaryotes. Centrioles are critical for the proper execution of important biological processes ranging from cell division to cell signaling. Moreover, centriolar defects have been associated to several human pathologies including ciliopathies and cancer. This state of facts emphasizes the importance of understanding centriole biogenesis. The study of centriole formation is a deep-rooted question, however our current knowledge on its molecular organization at high resolution remains fragmented and limited. In particular, exquisite details of the overall molecular architecture of the human centriole and in particular of its central core region are lacking to understand the basis of centriole organization and function. Resolving this important question represents a challenge that needs to be undertaken and will undoubtedly lead to groundbreaking advances. Another important question to tackle next is to develop innovative methods to enable the nanometric molecular mapping of centriolar proteins within distinct architectural elements of the centriole. This missing information will be key to unravel the molecular mechanisms behind centriolar organization.
This research proposal aims at building a cartography of the human centriole by elucidating its molecular composition and architecture. To this end, we will combine the use of innovative and multidisciplinary techniques encompassing spatial proteomics, cryo-electron tomography, state-of-the-art microscopy and in vitro assays and to achieve a comprehensive molecular and structural view of the human centriole. All together, we expect that these advances will help understand basic principles underlying centriole and cilia formation as well as might have further relevance for human health.
Max ERC Funding
1 498 965 €
Duration
Start date: 2017-01-01, End date: 2021-12-31
Project acronym ALMP_ECON
Project Effective evaluation of active labour market policies in social insurance programs - improving the interaction between econometric evaluation estimators and economic theory
Researcher (PI) Bas Van Der Klaauw
Host Institution (HI) STICHTING VU
Call Details Starting Grant (StG), SH1, ERC-2007-StG
Summary In most European countries social insurance programs, like welfare, unemployment insurance and disability insurance are characterized by low reemployment rates. Therefore, governments spend huge amounts of money on active labour market programs, which should help individuals in finding work. Recent surveys indicate that programs which aim at intensifying job search behaviour are much more effective than schooling programs for improving human capital. A second conclusion from these surveys is that despite the size of the spendings on these programs, evidence on its effectiveness is limited. This research proposal aims at developing an economic framework that will be used to evaluate the effectiveness of popular programs like offering reemployment bonuses, fraud detection, workfare and job search monitoring. The main innovation is that I will combine economic theory with recently developed econometric techniques and detailed administrative data sets, which have not been explored before. While most of the literature only focuses on short-term outcomes, the available data allow me to also consider the long-term effectiveness of programs. The key advantage of an economic model is that I can compare the effectiveness of the different programs, consider modifications of programs and combinations of programs. Furthermore, using an economic model I can construct profiling measures to improve the targeting of programs to subsamples of the population. This is particularly relevant if the effectiveness of programs differs between individuals or depends on the moment in time the program is offered. Therefore, the results from this research will not only be of scientific interest, but will also be of great value to policymakers.
Summary
In most European countries social insurance programs, like welfare, unemployment insurance and disability insurance are characterized by low reemployment rates. Therefore, governments spend huge amounts of money on active labour market programs, which should help individuals in finding work. Recent surveys indicate that programs which aim at intensifying job search behaviour are much more effective than schooling programs for improving human capital. A second conclusion from these surveys is that despite the size of the spendings on these programs, evidence on its effectiveness is limited. This research proposal aims at developing an economic framework that will be used to evaluate the effectiveness of popular programs like offering reemployment bonuses, fraud detection, workfare and job search monitoring. The main innovation is that I will combine economic theory with recently developed econometric techniques and detailed administrative data sets, which have not been explored before. While most of the literature only focuses on short-term outcomes, the available data allow me to also consider the long-term effectiveness of programs. The key advantage of an economic model is that I can compare the effectiveness of the different programs, consider modifications of programs and combinations of programs. Furthermore, using an economic model I can construct profiling measures to improve the targeting of programs to subsamples of the population. This is particularly relevant if the effectiveness of programs differs between individuals or depends on the moment in time the program is offered. Therefore, the results from this research will not only be of scientific interest, but will also be of great value to policymakers.
Max ERC Funding
550 000 €
Duration
Start date: 2008-07-01, End date: 2013-06-30
Project acronym ANTIVIRNA
Project Structural and mechanistic studies of RNA-guided and RNA-targeting antiviral defense pathways
Researcher (PI) Martin Jinek
Host Institution (HI) UNIVERSITAT ZURICH
Call Details Starting Grant (StG), LS1, ERC-2013-StG
Summary The evolutionary pressures exerted by viruses on their host cells constitute a major force that drives the evolution of cellular antiviral mechanisms. The proposed research is motivated by our interest in the roles of protein-RNA interactions in both prokaryotic and eukaryotic antiviral pathways and will proceed in two directions. The first project stems from our current work on the CRISPR pathway, a recently discovered RNA-guided adaptive defense mechanism in bacteria and archaea that silences mobile genetic elements such as viruses (bacteriophages) and plasmids. CRISPR systems rely on short RNAs (crRNAs) that associate with CRISPR-associated (Cas) proteins and function as sequence-specific guides in the detection and destruction of invading nucleic acids. To obtain molecular insights into the mechanisms of crRNA-guided interference, we will pursue structural and functional studies of DNA-targeting ribonuceoprotein complexes from type II and III CRISPR systems. Our work will shed light on the function of these systems in microbial pathogenesis and provide a framework for the informed engineering of RNA-guided gene targeting technologies. The second proposed research direction centres on RNA-targeting antiviral strategies employed by the human innate immune system. Here, our work will focus on structural studies of major interferon-induced effector proteins, initially examining the allosteric activation mechanism of RNase L and subsequently focusing on other antiviral nucleases and RNA helicases, as well as mechanisms by which RNA viruses evade the innate immune response of the host. In our investigations, we plan to approach these questions using an integrated strategy combining structural biology, biochemistry and biophysics with cell-based functional studies. Together, our studies will provide fundamental molecular insights into RNA-centred antiviral mechanisms and their impact on human health and disease.
Summary
The evolutionary pressures exerted by viruses on their host cells constitute a major force that drives the evolution of cellular antiviral mechanisms. The proposed research is motivated by our interest in the roles of protein-RNA interactions in both prokaryotic and eukaryotic antiviral pathways and will proceed in two directions. The first project stems from our current work on the CRISPR pathway, a recently discovered RNA-guided adaptive defense mechanism in bacteria and archaea that silences mobile genetic elements such as viruses (bacteriophages) and plasmids. CRISPR systems rely on short RNAs (crRNAs) that associate with CRISPR-associated (Cas) proteins and function as sequence-specific guides in the detection and destruction of invading nucleic acids. To obtain molecular insights into the mechanisms of crRNA-guided interference, we will pursue structural and functional studies of DNA-targeting ribonuceoprotein complexes from type II and III CRISPR systems. Our work will shed light on the function of these systems in microbial pathogenesis and provide a framework for the informed engineering of RNA-guided gene targeting technologies. The second proposed research direction centres on RNA-targeting antiviral strategies employed by the human innate immune system. Here, our work will focus on structural studies of major interferon-induced effector proteins, initially examining the allosteric activation mechanism of RNase L and subsequently focusing on other antiviral nucleases and RNA helicases, as well as mechanisms by which RNA viruses evade the innate immune response of the host. In our investigations, we plan to approach these questions using an integrated strategy combining structural biology, biochemistry and biophysics with cell-based functional studies. Together, our studies will provide fundamental molecular insights into RNA-centred antiviral mechanisms and their impact on human health and disease.
Max ERC Funding
1 467 180 €
Duration
Start date: 2013-11-01, End date: 2018-10-31
Project acronym ASAP
Project Thylakoid membrane in action: acclimation strategies in algae and plants
Researcher (PI) Roberta Croce
Host Institution (HI) STICHTING VU
Call Details Starting Grant (StG), LS1, ERC-2011-StG_20101109
Summary Life on earth is sustained by the process that converts sunlight energy into chemical energy: photosynthesis. This process is operating near the boundary between life and death: if the absorbed energy exceeds the capacity of the metabolic reactions, it can result in photo-oxidation events that can cause the death of the organism. Over-excitation is happening quite often: oxygenic organisms are exposed to (drastic) changes in environmental conditions (light intensity, light quality and temperature), which influence the physical (light-harvesting) and chemical (enzymatic reactions) parts of the photosynthetic process to a different extent, leading to severe imbalances. However, daily experience tells us that plants are able to deal with most of these situations, surviving and happily growing. How do they manage? The photosynthetic membrane is highly flexible and it is able to change its supramolecular organization and composition and even the function of some of its components on a time scale as fast as a few seconds, thereby regulating the light-harvesting capacity. However, the structural/functional changes in the membrane are far from being fully characterized and the molecular mechanisms of their regulation are far from being understood. This is due to the fact that all these mechanisms require the simultaneous presence of various factors and thus the system should be analyzed at a high level of complexity; however, to obtain molecular details of a very complex system as the thylakoid membrane in action has not been possible so far. Over the last years we have developed and optimized a range of methods that now allow us to take up this challenge. This involves a high level of integration of biological and physical approaches, ranging from plant transformation and in vivo knock out of individual pigments to ultrafast-spectroscopy in a mix that is rather unique for my laboratory and will allow us to unravel the photoprotective mechanisms in algae and plants.
Summary
Life on earth is sustained by the process that converts sunlight energy into chemical energy: photosynthesis. This process is operating near the boundary between life and death: if the absorbed energy exceeds the capacity of the metabolic reactions, it can result in photo-oxidation events that can cause the death of the organism. Over-excitation is happening quite often: oxygenic organisms are exposed to (drastic) changes in environmental conditions (light intensity, light quality and temperature), which influence the physical (light-harvesting) and chemical (enzymatic reactions) parts of the photosynthetic process to a different extent, leading to severe imbalances. However, daily experience tells us that plants are able to deal with most of these situations, surviving and happily growing. How do they manage? The photosynthetic membrane is highly flexible and it is able to change its supramolecular organization and composition and even the function of some of its components on a time scale as fast as a few seconds, thereby regulating the light-harvesting capacity. However, the structural/functional changes in the membrane are far from being fully characterized and the molecular mechanisms of their regulation are far from being understood. This is due to the fact that all these mechanisms require the simultaneous presence of various factors and thus the system should be analyzed at a high level of complexity; however, to obtain molecular details of a very complex system as the thylakoid membrane in action has not been possible so far. Over the last years we have developed and optimized a range of methods that now allow us to take up this challenge. This involves a high level of integration of biological and physical approaches, ranging from plant transformation and in vivo knock out of individual pigments to ultrafast-spectroscopy in a mix that is rather unique for my laboratory and will allow us to unravel the photoprotective mechanisms in algae and plants.
Max ERC Funding
1 696 961 €
Duration
Start date: 2011-12-01, End date: 2017-11-30
Project acronym assemblyNMR
Project 3D structures of bacterial supramolecular assemblies by solid-state NMR
Researcher (PI) Adam Lange
Host Institution (HI) FORSCHUNGSVERBUND BERLIN EV
Call Details Starting Grant (StG), LS1, ERC-2013-StG
Summary Supramolecular assemblies – formed by the self-assembly of hundreds of protein subunits – are part of bacterial nanomachines involved in key cellular processes. Important examples in pathogenic bacteria are pili and type 3 secretion systems (T3SS) that mediate adhesion to host cells and injection of virulence proteins. Structure determination at atomic resolution of such assemblies by standard techniques such as X-ray crystallography or solution NMR is severely limited: Intact T3SSs or pili cannot be crystallized and are also inherently insoluble. Cryo-electron microscopy techniques have recently made it possible to obtain low- and medium-resolution models, but atomic details have not been accessible at the resolution obtained in these studies, leading sometimes to inaccurate models.
I propose to use solid-state NMR (ssNMR) to fill this knowledge-gap. I could recently show that ssNMR on in vitro preparations of Salmonella T3SS needles constitutes a powerful approach to study the structure of this virulence factor. Our integrated approach also included results from electron microscopy and modeling as well as in vivo assays (Loquet et al., Nature 2012). This is the foundation of this application. I propose to extend ssNMR methodology to tackle the structures of even larger or more complex homo-oligomeric assemblies with up to 200 residues per monomeric subunit. We will apply such techniques to address the currently unknown 3D structures of type I pili and cytoskeletal bactofilin filaments. Furthermore, I want to develop strategies to directly study assemblies in a native-like setting. As a first application, I will study the 3D structure of T3SS needles when they are complemented with intact T3SSs purified from Salmonella or Shigella. The ultimate goal of this proposal is to establish ssNMR as a generally applicable method that allows solving the currently unknown structures of bacterial supramolecular assemblies at atomic resolution.
Summary
Supramolecular assemblies – formed by the self-assembly of hundreds of protein subunits – are part of bacterial nanomachines involved in key cellular processes. Important examples in pathogenic bacteria are pili and type 3 secretion systems (T3SS) that mediate adhesion to host cells and injection of virulence proteins. Structure determination at atomic resolution of such assemblies by standard techniques such as X-ray crystallography or solution NMR is severely limited: Intact T3SSs or pili cannot be crystallized and are also inherently insoluble. Cryo-electron microscopy techniques have recently made it possible to obtain low- and medium-resolution models, but atomic details have not been accessible at the resolution obtained in these studies, leading sometimes to inaccurate models.
I propose to use solid-state NMR (ssNMR) to fill this knowledge-gap. I could recently show that ssNMR on in vitro preparations of Salmonella T3SS needles constitutes a powerful approach to study the structure of this virulence factor. Our integrated approach also included results from electron microscopy and modeling as well as in vivo assays (Loquet et al., Nature 2012). This is the foundation of this application. I propose to extend ssNMR methodology to tackle the structures of even larger or more complex homo-oligomeric assemblies with up to 200 residues per monomeric subunit. We will apply such techniques to address the currently unknown 3D structures of type I pili and cytoskeletal bactofilin filaments. Furthermore, I want to develop strategies to directly study assemblies in a native-like setting. As a first application, I will study the 3D structure of T3SS needles when they are complemented with intact T3SSs purified from Salmonella or Shigella. The ultimate goal of this proposal is to establish ssNMR as a generally applicable method that allows solving the currently unknown structures of bacterial supramolecular assemblies at atomic resolution.
Max ERC Funding
1 456 000 €
Duration
Start date: 2014-05-01, End date: 2019-04-30
Project acronym AUTOMATION
Project AUTOMATION AND INCOME DISTRIBUTION: A QUANTITATIVE ASSESSMENT
Researcher (PI) David Hémous
Host Institution (HI) UNIVERSITAT ZURICH
Call Details Starting Grant (StG), SH1, ERC-2018-STG
Summary Since the invention of the spinning frame, automation has been one of the drivers of economic growth. Yet, workers, economist or the general public have been concerned that automation may destroy jobs or create inequality. This concern is particularly prevalent today with the sustained rise in economic inequality and fast technological progress in IT, robotics or self-driving cars. The empirical literature has showed the impact of automation on income distribution. Yet, the level of wages itself should also affect the incentives to undertake automation innovations. Understanding this feedback is key to assess the long-term effect of policies. My project aims to provide the first quantitative account of the two-way relationship between automation and the income distribution.
It is articulated around three parts. First, I will use patent data to study empirically the causal effect of wages on automation innovations. To do so, I will build firm-level variation in the wages of the customers of innovating firms by exploiting variations in firms’ exposure to international markets. Second, I will study empirically the causal effect of automation innovations on wages. There, I will focus on local labour market and use the patent data to build exogenous variations in local knowledge. Third, I will calibrate an endogenous growth model with firm dynamics and automation using Danish firm-level data. The model will replicate stylized facts on the labour share distribution across firms. It will be used to compute the contribution of automation to economic growth or the decline of the labour share. Moreover, as a whole, the project will use two different methods (regression analysis and calibrated model) and two different types of data, to answer questions of crucial policy importance such as: Taking into account the response of automation, what are the long-term effects on wages of an increase in the minimum wage, a reduction in labour costs, or a robot tax?
Summary
Since the invention of the spinning frame, automation has been one of the drivers of economic growth. Yet, workers, economist or the general public have been concerned that automation may destroy jobs or create inequality. This concern is particularly prevalent today with the sustained rise in economic inequality and fast technological progress in IT, robotics or self-driving cars. The empirical literature has showed the impact of automation on income distribution. Yet, the level of wages itself should also affect the incentives to undertake automation innovations. Understanding this feedback is key to assess the long-term effect of policies. My project aims to provide the first quantitative account of the two-way relationship between automation and the income distribution.
It is articulated around three parts. First, I will use patent data to study empirically the causal effect of wages on automation innovations. To do so, I will build firm-level variation in the wages of the customers of innovating firms by exploiting variations in firms’ exposure to international markets. Second, I will study empirically the causal effect of automation innovations on wages. There, I will focus on local labour market and use the patent data to build exogenous variations in local knowledge. Third, I will calibrate an endogenous growth model with firm dynamics and automation using Danish firm-level data. The model will replicate stylized facts on the labour share distribution across firms. It will be used to compute the contribution of automation to economic growth or the decline of the labour share. Moreover, as a whole, the project will use two different methods (regression analysis and calibrated model) and two different types of data, to answer questions of crucial policy importance such as: Taking into account the response of automation, what are the long-term effects on wages of an increase in the minimum wage, a reduction in labour costs, or a robot tax?
Max ERC Funding
1 295 890 €
Duration
Start date: 2018-11-01, End date: 2023-10-31
Project acronym BayesianMarkets
Project Bayesian markets for unverifiable truths
Researcher (PI) Aurelien Baillon
Host Institution (HI) ERASMUS UNIVERSITEIT ROTTERDAM
Call Details Starting Grant (StG), SH1, ERC-2014-STG
Summary Subjective data play an increasing role in modern economics. For instance, new welfare measurements are based on people’s subjective assessments of their happiness or their life satisfaction. A problem of such measurements is that people have no incentives to tell the truth. To solve this problem and make those measurements incentive compatible, I will introduce a new market institution, called Bayesian markets.
Imagine we ask people whether they are happy with their life. On Bayesian markets, they will trade an asset whose value is the proportion of people answering Yes. Only those answering Yes will have the right to buy the asset and those answering No the right to sell it. Bayesian updating implies that “Yes” agents predict a higher value of the asset than “No” agents do and, consequently, “Yes” agents want to buy it while “No” agents want to sell it. I will show that truth-telling is then the optimal strategy.
Bayesian markets reward truth-telling the same way as prediction markets (betting markets) reward people for reporting their true subjective probabilities about observable events. Yet, unlike prediction markets, they do not require events to be objectively observable. Bayesian markets apply to any type of unverifiable truths, from one’s own happiness to beliefs about events that will never be observed.
The present research program will first establish the theoretical foundations of Bayesian markets. It will then develop the proper methodology to implement them. Finally, it will disseminate the use of Bayesian markets via applications.
The first application will demonstrate how degrees of expertise can be measured and will apply it to risks related to climate change and nuclear power plants. It will contribute to the political debate by shedding new light on what true experts think about these risks. The second application will provide the first incentivized measures of life satisfaction and happiness.
Summary
Subjective data play an increasing role in modern economics. For instance, new welfare measurements are based on people’s subjective assessments of their happiness or their life satisfaction. A problem of such measurements is that people have no incentives to tell the truth. To solve this problem and make those measurements incentive compatible, I will introduce a new market institution, called Bayesian markets.
Imagine we ask people whether they are happy with their life. On Bayesian markets, they will trade an asset whose value is the proportion of people answering Yes. Only those answering Yes will have the right to buy the asset and those answering No the right to sell it. Bayesian updating implies that “Yes” agents predict a higher value of the asset than “No” agents do and, consequently, “Yes” agents want to buy it while “No” agents want to sell it. I will show that truth-telling is then the optimal strategy.
Bayesian markets reward truth-telling the same way as prediction markets (betting markets) reward people for reporting their true subjective probabilities about observable events. Yet, unlike prediction markets, they do not require events to be objectively observable. Bayesian markets apply to any type of unverifiable truths, from one’s own happiness to beliefs about events that will never be observed.
The present research program will first establish the theoretical foundations of Bayesian markets. It will then develop the proper methodology to implement them. Finally, it will disseminate the use of Bayesian markets via applications.
The first application will demonstrate how degrees of expertise can be measured and will apply it to risks related to climate change and nuclear power plants. It will contribute to the political debate by shedding new light on what true experts think about these risks. The second application will provide the first incentivized measures of life satisfaction and happiness.
Max ERC Funding
1 500 000 €
Duration
Start date: 2016-01-01, End date: 2020-12-31
