ERC FUNDED PROJECTS

Parkinson’s disease (PD) is the second most common neurodegenerative disorder primarily caused by the progressive loss of dopaminergic (DA) neurons in the substantia nigra (SN). Despite the advances in gene discovery associated with PD, the knowledge of the PD pathogenesis is largely limited to the involvement of these genes in the generic cell death pathways, and why degeneration is specific to DA neurons and why the degeneration is progressive remain enigmatic. Broad goal of our work is therefore to elucidate the mechanisms underlying specific and progressive DA neuron degeneration in PD. Our new Drosophila model of PD ⎯Fer2 gene loss-of-function mutation⎯ is unusually well suited to address these questions. Fer2 mutants exhibit specific and progressive death of brain DA neurons as well as severe locomotor defects and short life span. Strikingly, the death of DA neuron is initiated in a small cluster of Fer2-expressing DA neurons and subsequently propagates to Fer2-negative DA neurons. We therefore propose a novel two-step model of the neurodegeneration in PD: primary cell death occurs in a specific subset of dopamindegic neurons that are genetically defined, and subsequently the failure of the neuronal connectivity triggers and propagates secondary cell death to remaining DA neurons. In this research, we will test this hypothesis and investigate the underlying molecular mechanisms. This will be the first study to examine circuit-dependency in DA neuron degeneration. Our approach will use a combination of non-biased genomic techniques and candidate-based screening, in addition to the powerful Drosophila genetic toolbox. Furthermore, to test this hypothesis beyond the Drosophila model, we will establish new mouse models of PD that exhibit progressive DA neuron degeneration. Outcome of this research will likely revolutionize the understanding of PD pathogenesis and open an avenue toward the discovery of effective therapy strategies against PD.

1 518 960 €

Start date: 2013-06-01, End date: 2018-05-31

A persistent challenge in unravelling mechanisms that regulate memory function is how to bridge the gap between inter-molecular dynamics of single proteins, activity of individual synapses and emerging properties of neuronal circuits. The prototype condition of disintegrating neuronal circuits is Alzheimer’s Disease (AD). Since the early time of Alois Alzheimer at the turn of the 20th century, scientists have been searching for a molecular entity that is in the roots of the cognitive deficits. Although diverse lines of evidence suggest that the amyloid-beta peptide (Abeta) plays a central role in synaptic dysfunctions of AD, several key questions remain unresolved. First, endogenous Abeta peptides are secreted by neurons throughout life, but their physiological functions are largely unknown. Second, experience-dependent physiological mechanisms that initiate the changes in Abeta composition in sporadic, the most frequent form of AD, are unidentified. And finally, molecular mechanisms that trigger Abeta-induced synaptic failure and memory decline remain elusive. To target these questions, I propose to develop an integrative approach to correlate structure and function at the level of single synapses in hippocampal circuits. State-of-the-art techniques will enable the simultaneous real-time visualization of inter-molecular dynamics within signalling complexes and functional synaptic modifications. Utilizing FRET spectroscopy, high-resolution optical imaging, electrophysiology, molecular biology and biochemistry we will determine the casual relationship between ongoing neuronal activity, temporo-spatial dynamics and molecular composition of Abeta, structural rearrangements within the Abeta signalling complexes and plasticity of single synapses and whole networks. The proposed research will elucidate fundamental principles of neuronal circuits function and identify critical steps that initiate primary synaptic dysfunctions at the very early stages of sporadic AD.

2 000 000 €

Start date: 2011-12-01, End date: 2017-09-30

In this project we will push the limits of microscale ultrasound-based technology to gain access to diagnostically important rare constituents of blood within minutes from blood draw. To meet the demands for shorter time from sampling to result in healthcare there is an increased interest to shift from heavy centralized lab equipment to point-of-care tests and patient self-testing. Key challenges with point-of-care equipment is to enable simultaneous measurement of many parameters at a reasonable cost and size of equipment. Therefore, microscale technologies that can take in small amounts of blood and output results within minutes are sought for. In addition, the high precision and potential for multi-stage serial processing offered by such microfluidic methods opens up for fast and automated isolation of rare cell populations, such as circulating tumor cells, and controlled high-throughput size fractionation of sub-micron biological particles, such as platelets, pathogens and extracellular vesicles. To achieve effective and fast separation of blood components we will expose blood to acoustic radiation forces in a flow-through format. By exploiting a newly discovered acoustic body force, that stems from local variations the acoustic properties of the cell suspension, we can generate self-organizing configurations of the blood cells. We will tailor and tune the acoustic cell-organization in novel ways by time modulation of the acoustic field, by altering the acoustic properties of the fluid by solute molecules, and by exploiting a novel concept of sound interaction with thermal gradients. The project will render new fundamental knowledge regarding the acoustic properties of single cells and an extensive theoretical framework for the response of cells in any aqueous medium, bounding geometry and sound field, potentially leading to new diagnostic methods.

1 999 720 €

Start date: 2019-11-01, End date: 2024-10-31

AlzheimerAlzheimer’s disease (AD) is a crucial problem in our society, raising the need for new therapeutic targets. Evidence suggests multiple non-neuronal cells are implicated in the systemic deficits of AD, but the complex cellular diversity in the brain hampers the investigation of specific cells and their interactions. Moreover, the course of the disease is highly variable, due to multiple risk factors, including aging and gender, which have overlapping molecular signatures with AD that might be further masking disease mechanisms. I propose to expand the resolution from tissues to cellular environments, and to untangle overlapping molecular signatures of gender and aging, in order to unmask molecular mechanism of AD. Technological advances in genomics and imaging, including the single nucleus RNA-sequencing methods developed by me, as well as my expertise in computational analysis and CRIPSR perturbations, provide a unique opportunity to address this challenge. I obtained preliminary results strongly suggesting that multiple cell types are indeed altered in AD brains of mice and humans, and that gender, aging, and AD have overlapping molecular features. I hypothesize that age-dependent cellular/molecular alterations are key drivers of cognitive decline, and that the dynamics of these alterations determine risk and resilience levels in individuals. We will test this hypothesis by: 1) Charting the cellular microenvironments and tissue topology of the human AD brain, to reveal cells, pathways, and cellular interactions driving AD; 2) Mapping the dynamic cellular/molecular trajectories in aging and AD in w.t. and AD mice, to untangle AD, aging, and gender dimorphism; and 3) Identifying regulators of cognitive resilience and decline in AD and aging, and connecting genes to function by detailed mechanistic investigations in vivo. Overall, our innovative proposal is expected to advance our understanding of AD mechanism, and the link to aging and gender dimorphism.

1 500 000 €

Start date: 2020-06-01, End date: 2025-05-31

Obesity associated disorders such as T2D, hypertension and CVD, commonly referred to as the “metabolic syndrome”, are prevalent diseases of industrialized societies. Deranged adipose tissue proliferation and differentiation contribute significantly to the development of these metabolic disorders. Comparatively little however is known, about how these processes influence the development of metabolic disorders. Using a multidisciplinary approach, I plan to elucidate molecular mechanisms underlying the altered adipocyte differentiation and maturation in different models of obesity associated metabolic disorders. Special emphasis will be given to the analysis of gene expression, postranslational modifications and lipid molecular species composition. To achieve this goal, I am establishing several novel methods to isolate pure primary preadipocytes including a new animal model that will allow me to monitor preadipocytes, in vivo and track their cellular fate in the context of a complete organism. These systems will allow, for the first time to study preadipocyte biology, in an in vivo setting. By monitoring preadipocyte differentiation in vivo, I will also be able to answer the key questions regarding the development of preadipocytes and examine signals that induce or inhibit their differentiation. Using transplantation techniques, I will elucidate the genetic and environmental contributions to the progression of obesity and its associated metabolic disorders. Furthermore, these studies will integrate a lipidomics approach to systematically analyze lipid molecular species composition in different models of metabolic disorders. My studies will provide new insights into the mechanisms and dynamics underlying adipocyte differentiation and maturation, and relate them to metabolic disorders. Detailed knowledge of these mechanisms will facilitate development of novel therapeutic approaches for the treatment of obesity and associated metabolic disorders.

1 607 105 €

Start date: 2008-07-01, End date: 2013-06-30

Our tissues are constantly renewed by stem cells. Over time, stem cells accumulate cellular damage that will compromise renewal and results in aging. As stem cells can divide asymmetrically, segregation of harmful factors to the differentiating daughter cell could be one possible mechanism for slowing damage accumulation in the stem cell. However, current evidence for such mechanisms comes mainly from analogous findings in yeast, and studies have concentrated only on few types of cellular damage. I hypothesize that the chronological age of a subcellular component is a proxy for all the damage it has sustained. In order to secure regeneration, mammalian stem cells may therefore specifically sort old cellular material asymmetrically. To study this, I have developed a novel strategy and tools to address the age-selective segregation of any protein in stem cell division. Using this approach, I have already discovered that stem-like cells of the human mammary epithelium indeed apportion chronologically old mitochondria asymmetrically in cell division, and enrich old mitochondria to the differentiating daughter cell. We will investigate the mechanisms underlying this novel phenomenon, and its relevance for mammalian aging. We will first identify how old and young mitochondria differ, and how stem cells recognize them to facilitate the asymmetric segregation. Next, we will analyze the extent of asymmetric age-selective segregation by targeting several other subcellular compartments in a stem cell division. Finally, we will determine whether the discovered age-selective segregation is a general property of stem cell in vivo, and it's functional relevance for maintenance of stem cells and tissue regeneration. Our discoveries may open new possibilities to target aging associated functional decline by induction of asymmetric age-selective organelle segregation.

1 500 000 €

Start date: 2016-05-01, End date: 2021-04-30

Real-world optimization problems pose major challenges to algorithmic research. For instance, (i) many important problems are believed to be intractable (i.e. NP-hard) and (ii) with the growth of data size, modern applications often require a decision making under {\em incomplete and dynamically changing input data}. After several decades of research, central problems in these domains have remained poorly understood (e.g. Is there an asymptotically most efficient binary search trees?) Existing algorithmic techniques either reach their limitation or are inherently tailored to special cases. This project attempts to untangle this gap in the state of the art and seeks new interplay across multiple areas of algorithms, such as approximation algorithms, online algorithms, fixed-parameter tractable (FPT) algorithms, exponential time algorithms, and data structures. We propose new directions from the {\em structural perspectives} that connect the aforementioned algorithmic problems to basic questions in combinatorics. Our approaches fall into one of the three broad schemes: (i) new structural theory, (ii) intermediate problems, and (iii) transfer of techniques. These directions partially build on the PI's successes in resolving more than ten classical problems in this context. Resolving the proposed problems will likely revolutionize our understanding about algorithms and data structures and potentially unify techniques in multiple algorithmic regimes. Any progress is, in fact, already a significant contribution to the algorithms community. We suggest concrete intermediate goals that are of independent interest and have lower risks, so they are suitable for Ph.D students.

1 411 258 €

Start date: 2018-02-01, End date: 2024-01-31

The hippocampus is critical for the storage of episodic memories and has been extensively studied on its role in spatial memory. The hippocampus is also a central model for in vitro studies on the molecular, cellular and microcircuit basis for learning and memory. I propose to use a new technology that I developed to record and manipulate the membrane potential of multiple neurons, simultaneously, in behaving animals to reveal the mechanisms by which hippocampal circuits process spatial information. This research will bridge the gap between the in vitro mechanistic studies and the in vivo efforts to describe the spatial representations. I first propose to employ the voltage imaging technology for detailed mechanistic studies of the function and plasticity of hippocampal microcircuits during place cell formation (Objective 1). To this end, we will combine voltage imaging with Optogenetics in head-fixed mice performing virtual navigation in familiar and novel environments. To expand to a ‘systems’ view on hippocampal plasticity, we will next establish a method for optical selection of single neurons based on their functional profile (Objective 2). We will use this technology to trace the long-range projections and the pre- and postsynaptic landscape of photo-selected CA1 neurons. In the last objective, we will combine both technologies to dissect the contribution of different entorhinal cell types (i.e. grid cells, border cells, and speed cells) to place cell formation in CA1 (objective 3). To this end, we will image the entorhinal cortex and photo-select cells based on their functional profiles. We will then image CA1 while manipulating the activity of the selected entorhinal cells. Our work will provide new discoveries on the mechanistic basis for spatial memory and will comprise a first step towards broader understanding of how the brain stores and retrieves episodic memories.

1 486 797 €

Start date: 2020-12-01, End date: 2025-11-30

Humans diverged from our closest living relatives, chimpanzees and other great apes, 6-10 million years ago. Since this divergence, our ancestors acquired genetic changes that enhanced cognition, altered metabolism, and endowed our species with an adaptive capacity to colonize the entire planet and reshape the biosphere. Through genome comparisons between modern humans, Neandertals, chimpanzees and other apes we have identified genetic changes that likely contribute to innovations in human metabolic and cognitive physiology. However, it has been difficult to assess the functional effects of these genetic changes due to the lack of cell culture systems that recapitulate great ape organ complexity. Human and chimpanzee pluripotent stem cells (PSCs) can self-organize into three-dimensional (3D) tissues that recapitulate the morphology, function, and genetic programs controlling organ development. Our vision is to use organoids to study the changes that set modern humans apart from our closest evolutionary relatives as well as all other organisms on the planet. In ANTHROPOID we will generate a great ape developmental cell atlas using cortex, liver, and small intestine organoids. We will use single-cell transcriptomics and chromatin accessibility to identify cell type-specific features of transcriptome divergence at cellular resolution. We will dissect enhancer evolution using single-cell genomic screens and ancestralize human cells to resurrect pre-human cellular phenotypes. ANTHROPOID utilizes quantitative and state-of-the-art methods to explore exciting high-risk questions at multiple branches of the modern human lineage. This project is a ground breaking starting point to replay evolution and tackle the ancient question of what makes us uniquely human?

1 500 000 €

Start date: 2019-06-01, End date: 2024-05-31

Novel sophisticated technologies that exploit the laws of quantum physics form a cornerstone for the future well-being, economic growth and security of Europe. Here photonic devices have gained a prominent position because the absorption, emission, propagation or storage of a photon is a process that can be harnessed at a fundamental level and render more practical ways to use light for such applications. However, the interaction of light with single quantum systems under ambient conditions is typically very weak and difficult to control. Furthermore, there are quantum phenomena occurring in matter at nanometer length scales that are currently not well understood. These deficiencies have a direct and severe impact on creating a bridge between quantum physics and photonic device technologies. aQUARiUM, precisely address the issue of controlling and enhancing the interaction between few photons and rolled-up nanostructures with ability to be deployed in practical applications. With aQUARiUM, we will take epsilon (permittivity)-near-zero (ENZ) metamaterials into quantum nanophotonics. To this end, we will integrate quantum emitters with rolled-up waveguides, that act as ENZ metamaterial, to expand and redefine the range of light-matter interactions. We will explore the electromagnetic design freedom enabled by the extended modes of ENZ medium, which “stretches” the effective wavelength inside the structure. Specifically, aQUARiUM is built around the following two objectives: (i) Enhancing light-matter interactions with single emitters (Enhance) independent of emitter position. (ii) Enabling collective excitations in dense emitter ensembles (Collect) coherently connect emitters on nanophotonic devices to obtain coherent emission. aQUARiUM aims to create novel light-sources and long-term entanglement generation and beyond. The envisioned outcome of aQUARiUM is a wholly new photonic platform applicable across a diverse range of areas.

1 499 431 €

Start date: 2019-01-01, End date: 2023-12-31

This proposal aims at understanding how B cell specificity and immunodominance shape primary and secondary humoral responses to influenza A virus. Influenza A virus is a relevant human pathogen causing a considerable yearly death toll and economic burden to society. Immunodominance is a major driving force of adaptive immunity and defines the hierarchical recognition of epitopes on the same antigen. Previous studies analysing B cell dynamics in primary and secondary responses have been mainly focusing on simple antigens and competition between B cell clones of the same family. Investigation using complex antigens and examining interclonal competition are surprisingly scarce. Influenza hemagglutinin (HA) is a prime candidate to study immunodominance in B cells. I have generated a set of mutant viruses that will allow for an unprecedented investigation into immunodominance and B cell interclonal competition in primary and secondary responses. These viruses can be used to isolate and enumerate antibody and B cells specific for different epitopes on the same complex antigen (HA). I will use these unique tools in combination with state-of-the-art immunological methods, multi-colour flow cytometry and single cells RNA sequencing paired with B cell receptor sequencing to gain fundamental insights into B cell regulation and anti-viral humoral responses. I will i) study the link between B cell receptor characteristics, specificity and B cell fate decisions in primary responses, ii) characterize the relative contribution of pre-existing B cells, serum antibodies and CD4 T cells for immunodominance of secondary responses, iii) define immunodominance in human individuals, repeatedly exposed to influenza virus. I expect this project to critically improve our understanding of basic B cell biology with the long-term benefit of improving current vaccination against variable viral pathogens.

1 481 697 €

Start date: 2019-12-01, End date: 2024-11-30

Distributed systems underlie many modern technologies, a prime example being the Internet. The ever-increasing abundance of distributed systems necessitates their design and usage to be backed by strong theoretical foundations. A major challenge that distributed systems face is the lack of a central authority, which brings many aspects of uncertainty into the environment, in the form of unknown network topology or unpredictable dynamic behavior. A practical restriction of distributed systems, which is at the heart of this proposal, is the limited bandwidth available for communication between the network components. A central family of distributed tasks is that of local tasks, which are informally described as tasks which are possible to solve by sending information through only a relatively small number of hops. A cornerstone example is the need to break symmetry and provide a better utilization of resources, which can be obtained by the task of producing a valid coloring of the nodes given some small number of colors. Amazingly, there are still huge gaps between the known upper and lower bounds for the complexity of many local tasks. This holds even if one allows powerful assumptions of unlimited bandwidth. While some known algorithms indeed use small messages, the complexity gaps are even larger compared to the unlimited bandwidth case. This is not a mere coincidence, and in fact the existing theoretical infrastructure is provably incapable of giving stronger lower bounds for many local tasks under limited bandwidth. This proposal zooms in on this crucial blind spot in the current literature on the theory of distributed computing, namely, the study of local tasks under limited bandwidth. The goal of this research is to produce fast algorithms for fundamental distributed local tasks under restricted bandwidth, as well as understand their limitations by providing lower bounds.

1 486 480 €

Start date: 2018-06-01, End date: 2023-11-30

Lithium ion batteries offer tremendous potential as an enabling technology for sustainable transportation and development. However, their widespread usage as the energy storage solution for electric mobility and grid-level integration of renewables is impeded by the fact that current state-of-the-art lithium ion batteries have energy densities that are too small, charge- and discharge rates that are too low, and costs that are too high. Highly publicized instances of catastrophic failure of lithium ion batteries raise questions of safety. Understanding the limitations to battery performance and origins of the degradation and failure is highly complex due to the difficulties in studying interrelated processes that take place at different length and time scales in a corrosive environment. In the project, we will (1) develop and implement quantitative methods to study the complex interrelations between structure and electrochemistry occurring at the nano-, micron-, and milli-scales in lithium ion battery active materials and electrodes, (2) conduct systematic experimental studies with our new techniques to understand the origins of performance limitations and to develop design guidelines for achieving high performance and safe batteries, and (3) investigate economically viable engineering solutions based on these guidelines to achieve high performance and safe lithium ion batteries.

1 500 000 €

Start date: 2016-05-01, End date: 2021-10-31

A fundamental challenge of pancreas biology is to understand and manipulate the determinants of beta cell mass. The homeostatic maintenance of adult beta cell mass relies largely on replication of differentiated beta cells, but the triggers and signaling pathways involved remain poorly understood. Here I propose to investigate the physiological and molecular mechanisms that control beta cell replication. First, novel transgenic mouse tools will be used to isolate live replicating beta cells and to examine the genetic program of beta cell replication in vivo. Information gained will provide insights into the molecular biology of cell division in vivo. Additionally, these experiments will address critical unresolved questions in beta cell biology, for example whether duplication involves transient dedifferentiation. Second, genetic and pharmacologic tools will be used to dissect the signaling pathways controlling the entry of beta cells to the cell division cycle, with emphasis on the roles of glucose and insulin, the key physiological input and output of beta cells. The expected outcome of these studies is a detailed molecular understanding of the homeostatic maintenance of beta cell mass, describing how beta cell function is linked to beta cell number in vivo. This may suggest new targets and concepts for pharmacologic intervention, towards the development of regenerative therapy strategies in diabetes. More generally, the experiments will shed light on one of the greatest mysteries of developmental biology, namely how organs achieve and maintain their correct size. A fundamental challenge of pancreas biology is to understand and manipulate the determinants of beta cell mass. The homeostatic maintenance of adult beta cell mass relies largely on replication of differentiated beta cells, but the triggers and signaling pathways involved remain poorly understood. Here I propose to investigate the physiological and molecular mechanisms that control beta cell replication. First, novel transgenic mouse tools will be used to isolate live replicating beta cells and to examine the genetic program of beta cell replication in vivo. Information gained will provide insights into the molecular biology of cell division in vivo. Additionally, these experiments will address critical unresolved questions in beta cell biology, for example whether duplication involves transient dedifferentiation. Second, genetic and pharmacologic tools will be used to dissect the signaling pathways controlling the entry of beta cells to the cell division cycle, with emphasis on the roles of glucose and insulin, the key physiological input and output of beta cells. The expected outcome of these studies is a detailed molecular understanding of the homeostatic maintenance of beta cell mass, describing how beta cell function is linked to beta cell number in vivo. This may suggest new targets and concepts for pharmacologic intervention, towards the development of regenerative therapy strategies in diabetes. More generally, the experiments will shed light on one of the greatest mysteries of developmental biology, namely how organs achieve and maintain their correct size.

1 445 000 €

Start date: 2010-09-01, End date: 2015-08-31

To satisfy our growing energy demand while reducing reliance on fossil fuels, a switch to renewable energy sources is vital. The intermittent nature of the latter means innovations in energy storage technology is a key grand challenge. Cost and sustainability issues currently limit the widespread use of electrochemical energy storage technologies, such as lithium ion and redox flow batteries. As the scale for energy storage is simply enormous, the only option is to look for abundant materials. However, compounds that fulfil the extensive requirements entailed at low cost has yet to be reported. While it is possible that the holy grail of energy storage will be found, for example by advanced computational tools and machine learning to design “perfect” abundant molecules, a more flexible, innovative solution to sustainable and cost-effective large-scale energy storage is required. Bi3BoostFlowBat will develop game changing strategies to widen the choice of compounds utilizable for batteries to simultaneously satisfy the requirements for low cost, optimal redox potentials, high solubility and stability in all conditions. The aim of this project is to develop cost-efficient batteries by using solid boosters and by eliminating cross over. Two approaches will be pursued for cross-over elimination 1) bio-inspired polymer batteries, where cross-over of solubilized polymers is prevented by size-exclusion membranes and 2) biphasic emulsion flow batteries, where redox species are transferred to oil phase droplets upon charge. Third research direction focuses on systems to maintain a pH gradient, to allow operation of differential pH systems to improve the cell voltages. Limits of different approaches will be explored by taking an electrochemical engineering approach to model the performance of different systems and by validating the models experimentally. This work will chart the route towards the future third generation battery technologies for the large-scale energy storage.

1 499 880 €

Start date: 2021-01-01, End date: 2025-12-31

In mammals, transcriptional control of many genes relies on cis-regulatory elements such as enhancers, which are often located tens to hundreds of kilobases away from their cognate promoters. Functional interactions between distal regulatory elements and target promoters require mutual physical proximity, which is linked to the three-dimensional structure of the chromatin fiber. Chromosome conformation capture studies revealed that chromosomes are partitioned into Topologically Associating Domains (TADs), sub-megabase domains of preferential physical interactions of the chromatin fiber. Genetic evidence showed that TAD boundaries restrict the genomic range of enhancer-promoter communication, and that interactions between regulatory sequences within TADs are further fine-tuned by smaller-scale structures. However, the mechanistic details of how physical interactions translate into transcriptional outputs are totally unknown. Here we propose to explore the biophysical mechanisms that link chromosome conformation and long-range transcriptional regulation using molecular biology, genetic engineering, single-cell experiments and physical modeling. We will measure chromosomal interactions in single cells and in time using a novel method that relies on an enzymatic process in vivo. Genetic engineering will be used to establish a cell system that allows quantitative measurement of how enhancer-promoter interactions relate to transcription at the population and single-cell levels, and to test the effects of perturbations without confounding effects. Finally, we will develop physical models of promoter operation in the presence of distal enhancers, which will be used to interpret the experimental data and formulate new testable predictions. With this integrated approach we aim at providing an entirely new layer of description of the general principles underlying transcriptional control, which could establish new paradigms for research in epigenetics and gene regulation.

1 500 000 €

Start date: 2018-01-01, End date: 2022-12-31

Immune systems are highly variable, but the sources of this variation are poorly understood. Genetic variation only explains a minor fraction of this, and we are unable to accurately predict the risk of immune mediated disease or severe infection in any given individual. I recently found that immune cells and proteins in healthy twins vary because of non-heritable influences (infections, vaccines, microbiota etc.), with only minor influences from heritable factors (Brodin, et al, Cell 2015). When and how such environmental influences shape our immune system is now important to understand. Birth represents the most transformational change in environment during the life of any individual. I propose, that environmental influences at birth, and during the first months of life could be particularly influential by imprinting on the regulatory mechanisms forming in the developing immune system. Adaptive changes in immune cell frequencies and functional states induced by early-life exposures could determine both the immune competence of the newborn, but potentially also its long-term trajectory towards immunological health or disease. Here, I propose a study of 1000 newborn children, followed longitudinally during their first 1000 days of life. By monitoring immune profiles and recording many environmental influences, we hope to understand how early life exposures can influence human immune system development. We have established a new assay based on Mass Cytometry and necessary data analysis tools (Brodin, et al, PNAS 2014), to simultaneously monitor the frequencies, phenotypes and functional states of more than 200 blood immune cell populations from only 100 microliters of blood. By monitoring environmental influences at regular follow-up visits, by questionnaires, serum measurements of infection, and gut microbiome sequencing, we aim to provide the most comprehensive analysis to date of immune system development in newborn children.

1 422 339 €

Start date: 2016-07-01, End date: 2021-06-30

In contrast to mammals, newts possess exceptional capacities among vertebrates to rebuild complex structures, such as the brain. Our goal is to bridge the gap in the regenerative outcomes between newts and mammals. My group has made significant contributions towards this goal. We created a novel experimental system, which recapitulates central features of Parkinson’s disease in newts, and provides a unique model for understanding regeneration in the adult midbrain. We showed an unexpected but key feature of the newt brain that it is akin to the mammalian brain in terms of the extent of homeostatic cell turn over, but distinct in terms of its injury response, showing the regenerative capacity of the adult vertebrate brain by activating neurogenesis in normally quiescent regions. Further we established a critical role for the neurotransmitter dopamine in controlling quiescence in the midbrain, thereby preventing neurogenesis during homeostasis and terminating neurogenesis once the correct number of neurons has been produced during regeneration. Here we aim to identify key molecular pathways that regulate adult neurogenesis, to define lineage relationships between neuronal stem and progenitor cells, and to identify essential differences between newts and mammals. We will combine pharmacological modulation of neurotransmitter signaling with extensive cellular fate mapping approaches, and molecular manipulations. Ultimately we will test hypotheses derived from newt studies with mammalian systems including newt/mouse cross species complementation approaches. We expect that our findings will provide new regenerative strategies, and reveal fundamental aspects of cell fate determination, tissue growth, and tissue maintenance in normal and pathological conditions.

1 500 000 €

Start date: 2012-02-01, End date: 2017-01-31

"The dynamic nature of the brain operates at disparate time scales ranging from milliseconds to months. How do single neurons change over such long time scales? This question remains stubborn to answer in the field of brain plasticity mainly because of limited tools to study the physiology of single neurons over time in the complex environment of the brain. The research aim of this proposal is to reveal the physiological changes of single neurons in the mammalian brain over disparate time scales using time-lapse optical imaging. Specifically, we aim to establish a new team that will develop genetic and optical tools to probe the physiological activity of single neurons, in vivo. As a model system, we will study a unique neuronal population in the mammalian brain; the adult-born local neurons in the olfactory bulb. These neurons have tremendous potential to reveal how neurons develop and maintain in the intact brain because they are accessible both genetically and optically. By following the behavior of adult-born neurons in vivo we will discover how neurons mature and maintain over days and weeks. If our objectives will be met, this study has the potential to significantly ""raise the bar"" on how neuronal plasticity is studied and reveal some basic secrets of the ever changing mammalian brain."

1 750 000 €

Start date: 2008-08-01, End date: 2013-07-31

Brown adipocytes can dissipate energy in a process called adaptive thermogenesis. Whilst the classical brown adipose tissue (BAT) depots disappear during early life in humans, cold exposure can promote the appearance of brown-like adipocytes within the white adipose tissue (WAT), termed brite (brown-in-white). Increased BAT activity results in increased energy expenditure and has been correlated with leanness in humans. Hence, recruitment of brite adipocytes may constitute a promising therapeutic strategy to treat obesity and its associated metabolic diseases. Despite the beneficial metabolic properties of brown and brite adipocytes, little is known about the molecular mechanisms underlying their specification and activation in vivo. This proposal focuses on understanding the complex biology of thermogenic adipocyte biology by studying the epigenetic and transcriptional aspects of WAT britening and BAT recruitment in vivo to identify pathways of therapeutic relevance and to better define the brite precursor cells. Specific aims are to 1) investigate epigenetic and transcriptional states and heterogeneity in human and mouse adipose tissue; 2) develop a novel time-resolved method to correlate preceding chromatin states and cell fate decisions during adipose tissue remodelling; 3) identify and validate key (drugable) epigenetic and transcriptional regulators involved in brite adipocyte specification. Experimentally, I will use adipose tissue samples from human donors and mouse models, to asses at the single-cell level cellular heterogeneity, transcriptional and epigenetic states, to identify subpopulations, and to define the adaptive responses to cold or β-adrenergic stimulation. Using computational methods and in vitro and in vivo validation experiments, I will define epigenetic and transcriptional networks that control WAT britening, and develop a model of the molecular events underlying adipocyte tissue plasticity.

1 552 620 €

Start date: 2019-03-01, End date: 2024-02-29

The Smart Building Networks (BuildNet) program will develop optimizing controllers capable of coordinating the flow of power to and from large networks of smart buildings in order to offer critical services to the power grid. The network will make use of the thermal storage of the structures and on-site micro generation capabilities of next-generation buildings, as well as the electrical capacity of attached electric vehicles in order to intelligently control the interaction between the network of buildings and the grid. The wide range of electric utility applications, such as wind capacity firming or congestion relief, that will be possible as a result of this coordinated control will in turn allow a significant increase in the percentage of European power generated from destabilizing renewable sources. Technologically, BuildNet will be built around optimization-based or model predictive control (MPC), a paradigm that is ideally suited to the task of incorporating the current network state and forward-looking information into an optimal decision-making process. The project team will develop novel distributed MPC controllers that utilize the flexibility in the consumption, storage and generation of a distributed network of buildings by exploiting the extensive experience of the PI in optimization-based control and MPC for energy efficient buildings. Because of its theoretically grounded optimization-based control approach, holistic view of building systems and connected networks, as well as a future-looking technological scope, BuildNet's outputs will deliver impact and be relevant to researchers and practitioners alike.

1 460 232 €

Start date: 2012-12-01, End date: 2017-11-30

My proposal aims to take advantage of my ground-breaking finding that it is possible to mature, or activate, the [FeFe] hydrogenase enzyme (HydA) using synthetic mimics of its catalytic [2Fe] cofactor. (Berggren et al, Nature, 2013) We will now explore the chemistry and (bio-)technological potential of the enzyme using an interdisciplinary approach ranging from in vivo biochemical studies all the way to synthetic model chemistry. Hydrogenases catalyse the interconversion between protons and H2 with remarkable efficiency. Consequently, they are intensively studied as alternatives to Pt-catalysts for these reactions, and are arguably of high (bio-) technological importance in the light of a future “hydrogen society”. The project involves the preparation of novel “artificial” hydrogenases with the primary aim of designing spectroscopic model systems via modification(s) of the organometallic [2Fe] subsite. In parallel we will prepare in vitro loaded forms of the maturase HydF and study its interaction with apo-HydA in order to further elucidate the maturation process of HydA. Moreover we will develop the techniques necessary for in vivo application of the artificial activation concept, thereby paving the way for a multitude of studies including the reactivity of artificial hydrogenases inside a living cell, but also e.g. gain-of-function studies in combination with metabolomics and proteomics. Inspired by our work on the artificial maturation system we will also draw from our knowledge of Nature’s [FeS] cluster proteins in order to prepare a novel class of “miniaturized hydrogenases” combining synthetic [4Fe4S] binding oligopeptides with [2Fe] cofactor model compounds. Our interdisciplinary approach is particularly appealing as it not only provides further insight into hydrogenase chemistry and the maturation of metalloproteins, but also involves the development of novel tools and concepts applicable to the wider field of bioinorganic chemistry.

1 494 880 €

Start date: 2017-02-01, End date: 2022-01-31

Clinical experience with globally-acting cannabinoid-1 receptor (CB1R) antagonists revealed the benefits of blocking CB1Rs for the treatment of obesity and diabetes. However, their use is hampered by increased CNS-mediated side effects. Recently, I have demonstrated that peripherally-restricted CB1R antagonists have the potential to treat the metabolic syndrome without eliciting these adverse effects. While these results are promising and are currently being developed into the clinic, our ability to rationally design CB1R blockers that would target a diseased organ is limited. The current proposal aims to develop and test cell- and organelle-specific CB1R antagonists. To establish this paradigm, I will focus our interest on the kidney, since chronic kidney disease (CKD) is the leading cause of increased morbidity and mortality of patients with diabetes. Our first goal will be to characterize the obligatory role of the renal proximal tubular CB1R in the pathogenesis of diabetic renal complications. Next, we will attempt to link renal proximal CB1R with diabetic mitochondrial dysfunction. Finally, we will develop proximal tubular (cell-specific) and mitochondrial (organelle-specific) CB1R blockers and test their effectiveness in treating CKD. To that end, we will encapsulate CB1R blockers into biocompatible polymeric nanoparticles that will serve as targeted drug delivery systems, via their conjugation to targeting ligands. The implications of this work are far reaching as they will (i) point to renal proximal tubule CB1R as a novel target for CKD; (ii) identify mitochondrial CB1R as a new player in the regulation of proximal tubular cell function, and (iii) eventually become the drug-of-choice in treating diabetic CKD and its comorbidities. Moreover, this work will lead to the development of a novel organ-specific drug delivery system for CB1R blockers, which could be then exploited in other tissues affected by obesity, diabetes and the metabolic syndrome.

1 500 000 €

Start date: 2016-04-01, End date: 2021-03-31

Recent advances have shown that therapeutic manipulations of key cell-cell interactions can have dramatic clinical outcomes. Most notable are several early successes in cancer immunotherapy that target the tumor-T cell interface. However, these successes were only partial. This is likely because the few known interactions are just a few pieces of a much larger puzzle, involving additional signaling molecules and cell types. Dendritic cells (DCs), play critical roles in the induction/suppression of T cells. At early cancer stages, DCs capture tumor antigens and present them to T cells. However, in advanced cancers, the tumor microenvironment (TME) disrupts the crosstalk between DCs and T cells. We will take a multi-step approach to explore how the TME imposes a suppressive effect on DCs and how to reverse this hazardous effect. First, we will use single cell RNA-seq to search for genes in aggressive human and mouse ovarian tumors that are highly expressed in advanced tumors compared to early tumors and that encode molecules that suppress DC activity. Second, we will design a set of CRISPR screens to find genes that are expressed in DCs and regulate the transfer of the suppressive signals. The screens will be performed in the presence of suppressive molecules to mimic the TME and are expected to uncover many key genes in DCs biology. We will develop a new strategy to find synergistic combinations of genes to target (named Perturb-comb), thereby reversing the effect of local tumor immunosuppressive signals. Lastly, we will examine the effect of modified DCs on T cell activation and proliferation in-vivo, and on tumor growth. We expect to find: (1) Signaling molecules in the TME that affect the immune system. (2) New cytokines and cell surface receptors that are expressed in DCs and signal to T cells. (3) New key regulators in DC biology and their mechanisms. (4) Combinations of genes to target in DCs that reverse the TME’s hazardous effects.

1 500 000 €

Start date: 2018-01-01, End date: 2022-12-31

Cancer genomics has revolutionized cancer research by systematic mapping of oncogenic genetic alterations of genes, yet oncogenic epigenetic alterations of regulatory elements away from genes remain elusive. I recently demonstrated that aberrant DNA methylation of CTCF binding sites perturbs chromosomal topology in IDH-mutant glioma and SDH-deficient gastrointestinal stromal tumors (GISTs). Loss of CTCF binding at the boundary between two topologically associating domains disrupts their insulation, leading to oncogene activation. This groundbreaking model links metabolic, epigenetic and topological alterations and demonstrates that they can drive oncogenesis. Aberrant DNA methylation is common in many tumors and therefore epigenetic CTCF disruption may play a role in other cancers, but this has not been studied to date. Prompted by my findings, recent advances in genome-wide characterization methods and newly available large-scale data, I now propose to systematically uncover the rules of regulation of DNA methylation at CTCF binding sites, and how its disruption in cancer leads to epigenetic heterogeneity and drives oncogenesis. To achieve that, we will develop new statistical models to systematically uncover the rules of regulation of DNA methylation at CTCF binding sites and its impact on topology (Aim 1); uncover mechanisms of epigenetic topological alterations and their role in cancer (Aim 2); and develop computational tools to study intratumor epigenetic heterogeneity to investigate the interplay between different subclones (Aim 3). Taken together, this research program will facilitate a systematic understanding of epigenetic topological alterations and their role in cancer. These are critical goals for the field in order to understand the events that drive cancer, to discover new biomarkers, dependencies and therapeutic strategies, and to inform epigenetic and other personalized therapies.

1 500 000 €

Start date: 2021-02-01, End date: 2026-01-31

The study of several genetic disorders is hampered by the lack of suitable in vitro human models. We hypothesize that the generation of patient-specific induced pluripotent stem cells (iPSCs) will allow the development of disease-specific in vitro models; yielding new pathophysiologic insights into several genetic disorders and offering a unique platform to test novel therapeutic strategies. In the current proposal we plan utilize this novel approach to establish human iPSC (hiPSC) lines for the study of a variety of inherited cardiac disorders. The specific disease states that will be studied were chosen to reflect abnormalities in a wide-array of different cardiomyocyte cellular processes. These include mutations leading to: (1) abnormal ion channel function (“channelopathies”), such as the long QT and Brugada syndromes; (2) abnormal intracellular storage of unnecessary material, such as in the glycogen storage disease type IIb (Pompe’s disease); and (3) abnormalities in cell-to-cell contacts, such as in the case of arrhythmogenic right ventricular cardiomyopathy-dysplasia (ARVC-D). The different hiPSC lines generated will be coaxed to differentiate into the cardiac lineage. Detailed molecular, structural, functional, and pharmacological studies will then be performed to characterize the phenotypic properties of the generated hiPSC-derived cardiomyocytes, with specific emphasis on their molecular, ultrastructural, electrophysiological, and Ca2+ handling properties. These studies should provide new insights into the pathophysiological mechanisms underlying the different familial arrhythmogenic and cardiomyopathy disorders studied, may allow optimization of patient-specific therapies (personalized medicine), and may facilitate the development of novel therapeutic strategies. Moreover, the concepts and methodological knowhow developed in the current project could be extended, in the future, to derive human disease-specific cell culture models for a plurality of genetic disorders; enabling translational research ranging from investigation of the most fundamental cellular mechanisms involved in human tissue formation and physiology through disease investigation and the development and testing of novel therapies that could potentially find their way to the bedside

1 500 000 €

Start date: 2011-03-01, End date: 2016-02-29

Social-science explanations for rising wage inequality have reached a dead end. Most economists argue that computerization has been primarily responsible, while on the other side of the argument are sociologists and political scientists who stress the role of political forces in the evolution process of wages. I would like to use my knowledge and experience to come up with an original theory on the complex dynamics between technology and politics in order to solve two unsettled questions regarding the role of computerization in rising wage inequality: First, how can computerization, which diffused simultaneously in rich countries, explain the divergent inequality trends in Europe and the United States? Second, what are the mechanisms behind the well-known observed positive correlation between computers and earnings? To answer the first question, I develop a new institutional agenda stating that politics, broadly defined, mitigates the effects of technological change on wages by stimulating norms of fair pay and equity. To answer the second question, I propose a truly novel perspective that conceptualizes the earnings advantage that derives from computerization around access to and control of information on the production process. Capitalizing on this new perspective, I develop a new approach to measuring computerization to capture the form of workers’ interaction with computers at work, and build a research strategy for analysing the effect of computerization on wages across countries and workplaces, and over time. This research project challenges the common understanding of technology’s role in producing economic inequality, and would thereby significantly impact all of the abovementioned disciplines, which are debating over the upswing in wage inequality, as well as public policy, which discusses what should be done to confront the resurgence of income inequality.

1 495 091 €

Start date: 2016-09-01, End date: 2021-08-31

Synapses are intercellular junctions specialized for coordinated cell-cell communication throughout the nervous system. They are organized by cell-adhesion molecules (CAMs) that bi-directionally orchestrate neuronal communication. Latrophilins (LPHNs) are a unique sub-family of CAMs that play critical roles in structuring the synaptic architecture through multifaceted interactions with a large variety of synaptic partners. Mutations in LPHN have been associated with neurodevelopmental and neuropsychiatric disorders. Despite their gravity, the mechanism governing LPHN synaptic activities remain elusive. To further our understanding of LPHN-mediated cell-cell communication, we suggest to characterize these receptors’ interactions with their intracellular and extracellular partners. For this purpose, we propose to adopt a hybrid approach driven primarily by cryo-EM, a state-of-the-art technique capable of dissecting the molecular mechanisms of super-molecular assemblies at extremely high spatial resolutions, which is our group’s main field of expertise. The cryo-EM studies will be complemented by cryo electron tomography (cryo-ET), fluorescence microscopy and biochemical approaches. Our specific aims are: Aim 1: Dissect the molecular mechanisms of LPHN activation by combining cryo-EM with biochemical methodologies. Aim 2: Characterize the LPHN interactome through cryo-EM and fluorescence microscopy. Aim 3: Resolve the architecture of the LPHN interactome at a close-to-native environment through cryo-ET. Our experimental strategy will generate a quantitative, near-atomic resolution view of LPHNs and the mechanism by which they interact with their synaptic partners and instigate trans-synaptic signal transduction. These data will be vital for understanding LPHN-mediated cell-cell communication as well as the mechanisms governing trans-synaptic interactions and could potentially highlight novel approaches to treat neurodevelopmental and neuropsychiatric disorders.

1 499 885 €

Start date: 2020-11-01, End date: 2025-10-31

The mammalian brain is assembled from thousands of neuronal cell types that are organized into distinct circuits to perform behaviourally relevant computations. To gain mechanistic insights about brain function and to treat specific diseases of the nervous system it is crucial to understand what these local circuits are computing and how they achieve these computations. By examining the structure and function of a few genetically identified and experimentally accessible neural circuits we plan to address fundamental questions about the functional architecture of neural circuits. First, are cell types assigned to a unique functional circuit with a well-defined function or do they participate in multiple circuits (“multitasking cell types”), adjusting their role depending on the state of these circuits? Second, does a neural circuit perform “a single computation” or depending on the information content of its inputs can it carry out radically different functions? Third, how, among the large number of other cell types, do the cells belonging to the same functional circuit connect together during development? We use the mouse retina as a model system to address these questions. Finally, we will study the structure and function of a specialised neural circuit in the human fovea that enables humans to read. We predict that our insights into the mechanism of multitasking, network switches and the development of selective connectivity will be instructive to study similar phenomena in other brain circuits. Knowledge of the structure and function of the human fovea will open up new opportunities to correlate human retinal function with human visual behaviour and our genetic technologies to study human foveal function will allow us and others to design better strategies for restoring vision for the blind.

1 499 000 €

Start date: 2010-11-01, End date: 2015-10-31

The cerebellum is a critical regulator of motor function, which acts to integrate ongoing body states, sensory inputs and desired outcomes to adjust motor output. This motor control is achieved by a relatively small number of neuron types receiving two main sources of inputs and forming a single output pathway, the axons of Purkinje cells. Although the cerebellum is one of the first structures of the brain to differentiate, it undergoes a prolonged differentiation period such that mature cellular and circuit configuration is achieved only late after birth. Despite the functional importance of this structure, the molecular mechanisms that control type-specific cerebellar neurons generation, differentiation, and circuit assembly are poorly understood and are the topic of the present study. In my research program, I propose to investigate the transcriptional programs that control the generation of distinct subtypes of cerebellar neurons from progenitors, including Purkinje cells, granule cells and molecular layer interneurons (Work Package 1); the diversity of Purkinje cells across cerebellar regions (Work Package 2) and the postnatal differentiation and circuit integration of granule cells and molecular layer interneurons (Work Package 3). The general bases of the approach I propose consist in: i) specifically label cerebellar neuron progenitors and their progeny at sequential developmental time points pre- and post-natally using birthdate-based tagging, ii) FAC-sort these distinct cell types, iii) isolate these cells and identify their transcriptional signatures with single-cell resolution, iv) functionally interrogate top candidate genes and associated transcriptional programs using in vivo gain- and loss-of-function approaches. Together, these experiments aim at deciphering the cell-intrinsic processes controlling cerebellar circuit formation, towards a better understanding of the molecular mechanisms underlying cerebellar function and dysfunction.

1 499 885 €

Start date: 2018-02-01, End date: 2023-01-31

The interest on autophagy, an evolutionarily conserved process in eukaryotes, has enormously increased in the last years, since autophagy is involved in many diseases such as cancer and neurodegenerative disorders. Autophagosome formation is the key process in autophagy. Despite extensive work, the model of autophagosome formation is not yet well established. Some important questions on autophagosome biogenesis remain to be elusive, such as where the bona fide marker protein of autophagosome, LC3, is lipidated, how lipidated LC3 functions in autophagosome formation, and how the proteins for LC3 lipidation and delipidation are involved in autophagosome formation. Although genetic approaches have been useful to identify genes involved in autophagy, they are chronic and thereby the dynamics of phenotypic change cannot be followed, making them not suited for study highly dynamic process such as autophagosome formation. Herein, I propose to develop and use novel chemical probes to address these issues. First, I plan to prepare semi-synthetic caged LC3 proteins and apply them to monitor dynamics of autophagosome formation in the cell in order to address those questions on autophagosome formation. The semi-synthetic LC3 proteins are expected to confer a temporal control and to realize manipulation of protein structure, which renders such studies possible. Second, I intend to develop a versatile approach targeting specific endogenous proteins using a reversible chemically induced dimerization (CID) system, termed as “knock on and off” strategy. I plan to use this approach to elucidate the function of two distinct PI3K complexes in autophagosome formation. On one hand, the establishment of novel approaches will open up a new avenue for studying biological processes. On the other hand, the use of the tool will reveal the mechanism of autophagy.

1 500 000 €

Start date: 2016-09-01, End date: 2021-08-31

The mammalian circadian clock plays a fundamental role in the liver by regulating fatty acid, glucose and xenobiotic metabolism. Impairment of this rhythm has been show to lead to diverse pathologies including metabolic syndrome. At present, it is supposed that the circadian clock regulates metabolism mostly by regulating the expression of liver enzymes at the transcriptional level. We have now collected evidence that post-transcriptional regulations play also an important role in this regulation. Particularly, recent results from our laboratory show that the circadian clock can synchronize mRNA translation in mouse liver through rhythmic activation of the Target Of Rapamycin Complex 1 (TORC1) with a 12-hours period. Based on this unexpected observation, we plan to identify the genes rhythmically translated in the mouse liver as well as the mechanisms involved in this translation. Indeed, our initial observations suggest a cap-independent translation during the day and a cap-dependent translation during the night. Identification of the different complexes involved in translation at this two different times and their correlation with the sequence, structure, and/or function of the translated genes will provide new insight into the action of the circadian clock on animal metabolism. In parallel, we will identify the signalling pathways involved in the rhythmic activation of TORC1 in mouse liver. Finally, we will study the consequences of a deregulated rhythmic translation in circadian clock-deficient mice on the metabolism and the longevity of these animals. Perturbations of the circadian clock have been linked to numerous pathologies, including obesity, type 2 diabetes and cancer. Our project on the importance of circadian clock-coordinated translation will likely reveal new findings in the field of regulation of animal metabolism by the circadian clock.

1 475 831 €

Start date: 2011-03-01, End date: 2016-02-29

The ClimaSlow project opens new interdisciplinary horizons to identify the best opportunities to enhance the global legal and regulatory framework for reducing emissions of short-lived climate pollutants (SLCFs), with particular attention to developing countries as projected key sources of future SLCF emissions. It proceeds from the assumption that strengthening the global legal and regulatory framework for SLCFs would bring important benefits in terms of slowing down climate change and reducing local air pollution. However, legal and regulatory options to step up action on SLCFs have not been studied comprehensively. Furthermore, the climate impacts of the various options are not adequately understood. In contrast to traditional legal analysis that would focus one legal system or instrument, the project will study the relevant legal and regulatory frameworks comprehensively, considering the international, regional, national and transnational levels. It will seek to identify various options, both formal legal instruments and informal regulatory initiatives, to strengthen the global legal and regulatory frameworks applicable to SLCFs. In addition to providing information on best options to regulate SLCFs, this novel, comprehensive approach will help scholars to improve their understanding of the implications of ongoing changes in global legal landscape, including its presumed fragmentation and deformalisation. Addressing an important gap in current knowledge, the project will combine analysis of the merits of the various legal and regulatory options with estimates of their climate change impacts on the basis of climate modeling. This way, it will be able to identify the alternatives that are the most promising both from the legal point of view and in terms of climate change mitigation potential. The project will generate information that is policy-relevant and context-specific but can simultaneously provide broader lessons and open new interdisciplinary horizons.

1 456 179 €

Start date: 2017-01-01, End date: 2022-06-30

Over the past decade small RNAs such as microRNAs (miRNAs) and small interfering RNAs (siRNAs) have been shown to carry pivotal roles in post-transcriptional regulation and genome protection and to play an important part in various physiological processes in animals. miRNAs can be found in a very wide range of animals yet their functions were studied almost exclusively in members of the Bilateria such as insects, nematodes and vertebrates. Hence studying their function in representatives of non-bilaterian phyla such as Cnidaria (sea anemones, corals, hydras and jellyfish) is crucial for understanding the evolution of miRNAs in animals and can provide important insights into their roles in the ancient ancestor of Cnidaria and Bilateria. The sea anemone Nematostella vectensis is an excellent model for such a study since it can be grown in large numbers throughout its life cycle in the lab and because well-established genetic manipulation techniques are available for this species. Our preliminary results indicate that miRNAs in Nematostella frequently have a nearly perfect match to their messenger RNA (mRNA) targets, resulting in cleavage of the target. This mode of action is common for plant miRNAs, but is very rare in Bilateria. This finding together with my recent discovery of a Nematostella homolog of HYL1, a protein involved in miRNA biogenesis in plants, raises the exciting possibility that the miRNA pathway existed in the common ancestor of plants and animals. Here I suggest to bring together an array of advanced biochemical and genetic methods such as gene knockdown, transgenesis, high throughput sequencing and immunoprecipitation in order to obtain - for the first time - a deep understanding of the biogenesis and mechanism of action of small RNAs in Cnidaria. This will provide a novel way to understand the evolution of this important molecular pathway and to evaluate its age and ancestral form.

1 499 587 €

Start date: 2015-05-01, End date: 2020-04-30

A key question in neuroscience is how information is processed by sensory systems to guide behavior. Most of our knowledge about sensory processing is based on presentation of simple isolated stimuli and recording corresponding neural activity in relevant brain areas. Yet sensory stimuli in real life are never isolated and typically not simple. How the brain processes complex stimuli, simultaneously arising from multiple objects is unknown. Our daily experience (as well as well-controlled experiments) shows that only parts of a complex sensory scene can be perceived - we cannot listen to more than one speaker in a party. Importantly, one can easily choose what is important and should be processed and what can be ignored as background. These observations lead to the prevalent hypothesis that feedback projections from ‘higher’ brain areas to more peripheral sensory areas are involved in processing of complex stimuli. However experimental analysis of signals conveyed by feedback projections in behaving animals is scarce. The nature of these signals and how they relate to behavior is unknown. Here I propose a cutting edge approach to directly record feedback signals in the olfactory system of behaving mice. We will use chronically implanted electrodes to record the modulation of olfactory bulb (OB) principal neurons by task related context. Additionally, we will record from piriform cortical (PC) neurons that project back to the OB. These will be tagged with channelrhodopsin-2 and identified by light sensitivity. Finally, we will express the spectrally distinct Ca++ indicators GCaMP6 and RCaMP2 in PC neurons and in olfactory sensory neurons, respectively, and use 2-photon microscopy to analyze the spatio-temporal relationship between feedforward and feedback inputs in the OB. This comprehensive approach will provide an explanation of how feedforward and feedback inputs are integrated to process complex stimuli.

1 500 000 €

Start date: 2018-04-01, End date: 2023-03-31

"Throughout evolution both intestinal helminths and commensal bacteria have inhabited our intestines. This ""ménage à trois"" situation is likely to have exerted a strong selective pressure on the development of our metabolic and immune systems. Such pressures remain in developing countries, whilst the eradication of helminths in industrialized countries has shifted this evolutionary balance—possibly underlying the increased development of chronic inflammatory diseases. We hypothesize that helminth-bacterial interactions are a key determinant of healthy homeostasis. Preliminary findings from our laboratory indicate that helminth infection of mice alters the abundance and diversity of intestinal bacteria and impacts on the availability of immuno-modulatory metabolites; this altered environment correlates with a direct health advantage, protecting against inflammatory diseases such as asthma and rheumatoid arthritis. We intend to validate and extend these data in humans by performing bacterial phlyogenetic and metabolic analysis of stool samples collected from a large cohort of children living in a helminth endemic region of Ecuador. We further propose to test our hypothesis that helminth-bacterial interactions contribute to disease modulation using experimental models of infection and disease. We plan to develop and utilize mouse models to elucidate the mechanisms through which bacterial dysbiosis and helminth infection influence the development of chronic inflammatory diseases. These models will be utilized for germ-free and recolonization experiments, investigating the relative contribution of bacteria versus helminthes to host immunity, co-metabolism and disease modulation. Taking a trans-disciplinary approach, this research will break new ground in our understanding of the crosstalk and pressures between intestinal helminth infection and commensal bacterial communities, and the implications this has for human health."

1 480 612 €

Start date: 2013-04-01, End date: 2018-03-31

The project focuses on the interface between computational and combinatorial geometry. Geometric problems emerge in a variety of computational fields that interact with the physical world. The performance of geometric algorithms is determined by the description complexity of their underlying combinatorial structures. Hence, most theoretical challenges faced by computational geometry are of a distinctly combinatorial nature. In the past two decades, computational geometry has been revolutionized by the powerful combination of random sampling techniques with the abstract machinery of geometric arrangements. These insights were used, in turn, to establish state-of-the-art results in combinatorial geometry. Nevertheless, a number of fundamental problems remained open and resisted numerous attempts to solve them. Motivated by the recent breakthrough results, in which the PI played a central role, we propose two exciting lines of study with the potential to change the landscape of this field. The first research direction concerns the complexity of Voronoi diagrams -- arguably the most common structures in computational geometry. The second direction concerns combinatorial and algorithmic aspects of geometric intersection structures, including some fundamental open problems in geometric transversal theory. Many of these questions are motivated by geometric variants of general covering and packing problems, and all efficient approximation schemes for them must rely on the intrinsic properties of geometric graphs and hypergraphs. Any progress in responding to these challenges will constitute a major breakthrough in both computational and combinatorial geometry.

1 303 750 €

Start date: 2016-09-01, End date: 2022-08-31

"Similarity is one of the most fundamental notions encountered in problems practically in every branch of science, and is especially crucial in image sciences such as computer vision and pattern recognition. The need to quantify similarity or dissimilarity of some data is central to broad categories of problems involving comparison, search, matching, alignment, or reconstruction. The most common way to model a similarity is using metrics (distances). Such constructions are well-studied in the field of metric geometry, and there exist numerous computational algorithms allowing, for example, to represent one metric using another by means of isometric embeddings. However, in many applications such a model appears to be too restrictive: many types of similarity are non-metric; it is not always possible to model the similarity precisely or completely e.g. due to missing data; some objects might be mutually incomparable e.g. if they are coming from different modalities. Such deficiencies of the metric similarity model are especially pronounced in large-scale computer vision, pattern recognition, and medical imaging applications. The ambitious goal of this project is to introduce a paradigm shift in the way we model and compute similarity. We will develop a unifying framework of computational similarity geometry that extends the theoretical metric model, and will allow developing efficient numerical and computational tools for the representation and computation of generic similarity models. The methods will be developed all the way from mathematical concepts to efficiently implemented code and will be applied to today’s most important and challenging problems in Internet-scale computer vision and pattern recognition, shape analysis, and medical imaging."

1 495 020 €

Start date: 2012-10-01, End date: 2017-09-30

Computational cameras go beyond 2D images and allow the extraction of more dimensions from the visual world such as depth, multiple viewpoints and multiple illumination conditions. They also allow us to overcome some of the traditional photography challenges such as defocus blur, motion blur, noise and resolution. The increasing variety of computational cameras is raising the need for a meaningful comparison across camera types. We would like to understand which cameras are better for specific tasks, which aspects of a camera make it better than others and what is the best performance we can hope to achieve. Our 2008 paper introduced a general framework to address the design and analysis of computational cameras. A camera is modeled as a linear projection in ray space. Decoding the camera data then deals with inverting the linear projection. Since the number of sensor measurements is usually much smaller than the number of rays, the inversion must be treated as a Bayesian inference problem accounting for prior knowledge on the world. Despite significant progress which has been made in the recent years, the space of computational cameras is still far from being understood. Computational camera analysis raises the following research challenges: 1) What is a good way to model prior knowledge on ray space? 2) Seeking efficient inference algorithms and robust ways to decode the world from the camera measurements. 3) Evaluating the expected reconstruction accuracy of a given camera. 4) Using the expected reconstruction performance for evaluating and comparing camera types. 5) What is the best camera? Can we derive upper bounds on the optimal performance? We propose research on all aspects of computational camera design and analysis. We propose new prior models which will significantly simplify the inference and evaluation tasks. We also propose new ways to bound and evaluate computational cameras with existing priors.

756 845 €

Start date: 2010-12-01, End date: 2015-11-30

PROBLEM: Despite extensive research on human-computer interaction (HCI), no method exists that guarantees the optimal or even a provably good user interface (UI) design. The prevailing approach relies on heuristics and iteration, which can be costly and even ineffective, because UI design often involves combinatorially hard problems with immense design spaces, multiple objectives and constraints, and complex user behavior. OBJECTIVES: COMPUTED establishes the foundations for optimizing UI designs. A design can be automatically optimized to given objectives and constraints by using combinatorial optimization methods that deploy predictive models of user behavior as objective functions. Although previous work has shown some improvements to usability, the scope has been restricted to keyboards and widgets. COMPUTED researches methods that can vastly expand the scope of optimizable problems. First, algorithmic support is developed for acquiring objective functions that cover the main human factors in a given HCI task. Second, formal analysis of decision problems in UI design allows combating a broader range of design tasks with efficient and appropriate optimization methods. Third, a novel interactive UI optimization paradigm for UI designers promotes fast convergence to good results even in the face of uncertainty and incomplete knowledge. IMPACT: Combinatorial UI optimization offers a strong complement to the prevailing design approaches. Because the structured search process has a high chance of finding good solutions, optimization could improve the quality of interfaces used in everyday life. Optimization can also increase cost-efficiency, because reference to optimality can eliminate fruitless iteration. Moreover, because no preknowledge of UI design is required, even novices will be able to design great UIs. Even in “messy,” less well-defined problems, it may support designers by allowing them to delegate the solving of well-known sub-problems.

1 499 790 €

Start date: 2015-04-01, End date: 2020-03-31

Devices in wireless networks are no longer used only for communicating binary information, but also for navigation and to sense their surroundings. We are currently approaching fundamental limitations in terms of communication throughput, position information availability and accuracy, and decision making based on sensory data. The goal of this proposal is to understand how the cooperative nature of future wireless networks can be leveraged to perform timekeeping, positioning, communication, and decision making, so as to obtain orders of magnitude performance improvements compared to current architectures. Our research will have implications in many fields and will comprise fundamental theoretical contributions as well as a cooperative wireless testbed. The fundamental contributions will lead to a deep understanding of cooperative wireless networks and will enable new pervasive applications which currently cannot be supported. The testbed will be used to validate the research, and will serve as a kernel for other researchers worldwide to advance knowledge on cooperative networks. Our work will build on and consolidate knowledge currently dispersed in different scientific disciplines and communities (such as communication theory, sensor networks, distributed estimation and detection, environmental monitoring, control theory, positioning and timekeeping, distributed optimization). It will give a new thrust to research within those communities and forge relations between them.

1 500 000 €

Start date: 2011-05-01, End date: 2016-04-30

The colloidal quantum dots (CQDs) are an emerging class of light-emitting compounds for solution-processed optoelectronics such as the light-emitting diodes (LEDs). Compared to the state-of-the-art compound semiconductors and organic light emitting diodes (OLED), the CQD-based LEDs possess extremely high color purity and low materials cost, representing the only feasible materials solution towards realization of the newly-defined Rec. 2020 standard for the next-generation displays. However, the theoretical upper limit of the device external quantum efficiency (EQE) is only ~20%, considerably lower than those in OLEDs and InGaN LEDs. The fundamental bottleneck is that it is not yet possible to control the emission directionality perpendicular to the substrate plane in the CQD superlattices, without compromising the photoluminescence quantum yield (PLQY). As a result, a lot of photons are wasted due to the total internal reflection (TIR) at the air/glass interface, as well as exciton quenching during interparticle energy transfer. In order to overcome the efficiency limitation, my research group pioneers synthesis, physics, and LED device of layer-controlled colloidal quantum wells (CQWs) of organic-inorganic hybrid lead halide perovskites (OIHPs), the two-dimensional nanocrystals of OIHP in colloidal solution. Our results have suggested that the materials system might be the ultimate solution for the quantum-dot based LEDs. We found that the CQWs possess: (i) the aggregation-induced emission (AIE) characteristics, boosting the film PLQY up to 97%, and (ii) the emission directionality (ED) perpendicular to the substrate plane in their self-assembled superlattices. Based on the new photophysical properties that have never been found in any other CQD systems, in this proposal, we aim to optimally utilize the characteristics of the AIE and ED, in order to realize high-efficiency and long-lifetime LED technology that can fulfill 100% Rec. 2020 color gamut.

1 498 515 €

Start date: 2020-01-01, End date: 2024-12-31

Cytotoxic T lymphocytes (CTL) and natural killer (NK) cells release granzyme and perforin from cytotoxic granules into the immune synapse to induce apoptosis of target cells that are either virus-infected or cancerous. Granzyme A activates a caspase-independent apoptotic pathway and induces mitochondrial damage characterized by superoxide anion production and loss of the mitochondrial transmembrane potential, without disrupting the integrity of the mitochondrial outer membrane; while causing single-stranded DNA damage. GzmB induces both caspase-dependent and caspase-independent cell death. In the caspase-dependent pathway, mitochondrial functions are altered as evidenced by the loss of mitochondrial transmembrane potential and the generation of reactive oxygen species (ROS). The mitochondrial outer membrane (MOM) is disrupted, resulting in the release of apoptogenic factors. To date, research on mitochondrial-dependent apoptosis has focused on mitochondrial outer membrane permeabilization (MOMP) however whether the generation of ROS is incidental or essential to the execution of apoptosis remains unclear. Like human GzmA, human GzmB promotes cell death in a ROS-dependent manner. Preliminary data suggest that human GzmB can induce ROS in a MOMP-independent manner as Bax and Bak double knockout MEF cells treated with human GzmB and perforin still display a robust ROS production and dye in an ROS-dependent manner. Since GzmA and GzmB induce cell death in a ROS-dependent manner, we hypothesize that oxygen free radicals are central to the execution of programmed cell death induced by the cytotoxic granules. Therefore, the goal of this proposal is to dissect the key molecular events triggered by ROS that lead to Citotoxic Tcell-induced target cell death. A combination of biochemical, genetic and proteomic approaches in association with Electron Spin Resonance (ESR) spectroscopy methodology will be used to unravel the essential role ROS play in CTL-mediated killing.

1 500 000 €

Start date: 2011-05-01, End date: 2016-04-30

We address a fundamental and increasingly important challenge in computer science: how to program large-scale heterogeneous parallel computers. Society relies on these computers to satisfy the growing demands of important applications such as drug design, weather prediction, and big data analytics. Architectural trends make heterogeneous parallel processors the fundamental building blocks of computing platforms ranging from quad-core laptops to million-core supercomputers; failing to exploit these architectures efficiently will severely limit the technological advance of our society. Computationally demanding problems are often inherently parallel and can readily be compiled for various target architectures. Yet, efficiently mapping data to the target memory system is notoriously hard, and the cost of fetching two operands from remote memory is already orders of magnitude more expensive than any arithmetic operation. Data access cost is growing with the amount of parallelism which makes data layout optimizations crucial. Prevalent parallel programming abstractions largely ignore data access and guide programmers to design threads of execution that are scheduled to the machine. We depart from this control-centric model to a data-centric program formulation where we express programs as collections of values, called memlets, that are mapped as first-class objects by the compiler and runtime system. Our holistic compiler and runtime system aims to substantially advance the state of the art in parallel computing by combining static and dynamic scheduling of memlets to complex heterogeneous target architectures. We will demonstrate our methods on three challenging real-world applications in scientific computing, data analytics, and graph processing. We strongly believe that, without holistic data-centric programming, the growing complexity and inefficiency of parallel programming will create a scaling wall that will limit our future computational capabilities.

1 499 672 €

Start date: 2016-06-01, End date: 2021-05-31

Life ultimately depends on the tight control of gene expression, which requires an ordered and efficient processing of various RNA molecules. Messenger RNAs (mRNAs) – bound by a constantly changing coat of passenger proteins - transit from transcription in the nucleus to translation and ultimately decay in the cytoplasm. Similarly, ribosomal rRNAs migrate through the nucleolus where they gradually en-counter ribosomal proteins to assemble functional ribosomes. Still, we know very little about the pro-cesses that orchestrate this flux of RNA in a temporal and spatial manner. Intriguingly, many RNA processing steps occur in membraneless organelles formed by liquid-liquid phase separation, e.g. nuclear speckles or the nucleolus, but the function of condensate formation in RNA processing is not known. I have discovered that the family of DEAD-box ATPases (DDXs) are master regulators of RNA-containing membraneless organelles, from bacteria to man. DDXs use their low-complexity domains and ATPase activity to regulate condensate dynamics and RNA flux through these compartments. I propose that cells use DDX-controlled condensate ‘stations’ to establish an RNA ‘transit map’ to reg-ulate the cellular flux of mRNA and rRNA molecules and to spatially and temporally control RNA pro-cessing. In three work packages, I will (1) characterize central DDXs that control mRNA flux and use DDX mutants as unique tools to map passenger protein changes along the life of an mRNA; (2) charac-terize how DDXs regulate the formation of the phase-separated nucleolar environment and facilitate the flux of rRNA during ribosome assembly; (3) dissect how DDX condensates function as biomolecular filters to selectively enrich or exclude proteins, and how selectivity contributes to the remodeling of the RNA protein coat and directional RNA flux. Our research will provide key novel insight into our understanding of RNA processing and uncover novel layers of gene expression regulation.

1 499 845 €

Start date: 2021-02-01, End date: 2026-01-31

Bacterial pathogens remain a significant threat to global health, necessitating a better understanding of host-pathogen biology. While various evidence point to early infection as a key event in the eventual progression to disease, our recent preliminary data show that during this stage, highly adaptable and dynamic host cells and bacteria engage in complex, diverse interactions that contribute to well-documented heterogeneous outcomes of infection. However, current methodologies rely on measurements of bulk populations, thereby overlooking this diversity that can trigger different outcomes. This application focuses on understanding heterogeneity during the first stages of infection in order to reduce the complexity of these interactions into informative readouts of population physiology and predictors of infection outcome. We will apply multiparametric single-cell analysis to obtain an accurate and complete description of infection with the enteric intracellular pathogen Salmonella of macrophages in vitro, and in early stages of mice colonization. We will characterize the molecular details that underlie distinct infection outcomes of individual encounters, to reconstruct the repertoire of host and pathogen strategies that prevail at critical stages of early infection. We propose the following three objectives: (1) Develop methodologies to simultaneously profile host and pathogen transcriptional changes on a single cell level; 2) Characterizing the molecular details that underlie the formation of subpopulations during macrophage infection; and (3) Determine how host and pathogen encounters in vivo result in emergence of specialized subpopulations, recruitment of immune cells and pathogen dissemination. We anticipate that this work will fundamentally shift our paradigms of infectious disease pathogenesis and lay the groundwork for the development of a new generation of therapeutic agents targeting the specific host-pathogen interactions ultimately driving disease.

1 499 999 €

Start date: 2017-10-01, End date: 2022-09-30

Crystallization fouling, a process where scale forms on surfaces, is pervasive in nature and technology, negatively impacting the energy conversion and water treatment industries. Despite significant efforts, rationally designed materials that are intrinsically resistant to crystallization fouling without the use of active methods like antiscalant additives (which can persist long after their disposal and the toxicological impact of which in effluent is questioned) remain elusive. This is because antiscalant surfaces are constructed today without sufficient reliance on an intricate but necessary science-base, of how interweaved interfacial thermofluidics, nucleation thermodynamics, and surface nanoengineering control the onset of nucleation and adhesion of frequently encountered scaling salts like calcium carbonate and calcium sulfate. Such scaling salts are common components of fouling deposits in industrial heat exchangers and membranes, which significantly inhibit heat transfer and flow performance. Therefore, guided by interfacial thermofluidic and thermodynamics theories, and employing advanced experimental methods in the areas of surface nanoengineering and diagnostics, this project will develop an integrated knowledge-base for how engineered surfaces can beneficially interact with interfacial transport phenomena in order to significantly advance antiscalant surfaces. We aim to pinpoint mechanisms for inhibiting scale nucleation and reducing adhesion in order to design and engineer antiscalant materials based on the collaborative action of their composition and topography. The effects of surface texture curvature, surface composition, and substrate compliance on scale nucleation and adhesion have intertwined and sometimes competing impacts, which we aim at elucidating to realize high performance scale-phobic surfaces. Connected to this are cutting edge materials fabrication techniques and considerations to the development of surfaces for future applications.

1 963 625 €

Start date: 2020-02-01, End date: 2025-01-31

The primary cilium is a microtubule-based organelle that organizes a variety of cellular signaling pathways. Its importance for human health is illustrated by a large collection of cilium-based diseases, the ciliopathies, caused by mutations that alter cilium formation, structure, and function. Importantly, the mammalian Hedgehog signaling pathway is critically dependent on the primary cilium, dysregulation of which contributes to severe developmental defects and a variety of cancers. The ultimate goal of this work program is to enhance our understanding of the molecular mechanisms of ciliary signaling in health and disease. This is accomplished through the development of advanced technologies that provide a currently unattainable level of spatiotemporal control over ciliary proteins in mammalian cells. Unraveling the mechanisms by which the ciliary compartment orchestrates signal transduction is challenging, because ciliary and cytoplasmic roles of proteins involved in signal transduction are tightly connected, difficult to resolve and, importantly, context-specific. Here, an innovative chemical biology program is presented that provides a powerful toolbox to overcome these challenges, allowing the intraciliary manipulation, and therefore study, of ciliary proteins. Combining chemical probes, synthetic ciliary targeting approaches, and a modular enzymatic tagging strategy, this program provides unprecedented opportunities to probe, visualize, inhibit or degrade proteins at specific times and selectively within the ciliary compartment. Specifically, these tools will be used to decipher the relationships between tubulin acetylation state, intraflagellar transport, and Hedgehog signal transduction in wild-type and ciliopathy-mutant cells. These innovative work packages synergistically provide enhanced fundamental understanding of ciliary signaling, and pave the way for novel therapeutic approaches to combat cilium-based diseases.

1 408 776 €

Start date: 2021-01-01, End date: 2025-12-31

Nowadays, extensive collection and storage of massive data sets have become a routine in multiple disciplines and in everyday life. These large amounts of intricate data often make data samples arithmetic and basic comparisons problematic, raising new challenges to traditional data analysis objectives such as filtering and prediction. Furthermore, the availability of such data constantly pushes the boundaries of data analysis to new emerging domains, ranging from neuronal and social network analysis to multimodal sensor fusion. The combination of evolved data and new domains drives a fundamental change in the field of data analysis. Indeed, many classical model-based techniques have become obsolete since their models do not embody the richness of the collected data. Today, one notable avenue of research is the development of nonlinear techniques that transition from data to creating representations, without deriving models in closed-form. The vast majority of such existing data-driven methods operate directly on the data, a hard task by itself when the data are large and elaborated. The goal of this research is to develop a fundamentally new methodology for high dimensional data analysis with diffusion operators, making use of recent transformative results in manifold and geometry learning. More concretely, shifting the focus from processing the data samples themselves and considering instead structured data through the lens of diffusion operators will introduce new powerful “handles” to data, capturing their complexity efficiently. We will study the basic theory behind this nonlinear analysis, develop new operators for this purpose, and devise efficient data-driven algorithms. In addition, we will explore how our approach can be leveraged for devising efficient solutions to a broad range of open real-world data analysis problems, involving intrinsic representations, sensor fusion, time-series analysis, network connectivity inference, and domain adaptation.

1 260 000 €

Start date: 2019-02-01, End date: 2024-01-31