ERC FUNDED PROJECTS

The sub-cellular processes that control the most critical aspects of life occur in three-dimensions (3D), and are intrinsically dynamic. While super-resolution microscopy has revolutionized cellular imaging in recent years, our current capability to observe the dynamics of life on the nanoscale is still extremely limited, due to inherent trade-offs between spatial, temporal and spectral resolution using existing approaches. We propose to develop and demonstrate an optical microscopy methodology that would enable live sub-cellular observation in unprecedented detail. Making use of multicolor 3D point-spread-function (PSF) engineering, a technique I have recently developed, we will be able to simultaneously track multiple markers inside live cells, at high speed and in five-dimensions (3D, time, and color). Multicolor 3D PSF engineering holds the potential of being a uniquely powerful method for 5D tracking. However, it is not yet applicable to live-cell imaging, due to significant bottlenecks in optical engineering and signal processing, which we plan to overcome in this project. Importantly, we will also demonstrate the efficacy of our method using a challenging biological application: real-time visualization of chromatin dynamics - the spatiotemporal organization of DNA. This is a highly suitable problem due to its fundamental importance, its role in a variety of cellular processes, and the lack of appropriate tools for studying it. The project is divided into 3 aims: 1. Technology development: diffractive-element design for multicolor 3D PSFs. 2. System design: volumetric tracking of dense emitters. 3. Live-cell measurements: chromatin dynamics. Looking ahead, here we create the imaging tools that pave the way towards the holy grail of chromatin visualization: dynamic observation of the 3D positions of the ~3 billion DNA base-pairs in a live human cell. Beyond that, our results will be applicable to numerous 3D micro/nanoscale tracking applications.

1 802 500 €

Start date: 2018-11-01, End date: 2023-10-31

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

Our affective and motivational state is important for our decisions, actions and quality of life. Many pathological conditions affect this state. For example, addictive drugs are hyperactivating the reward system and trigger a strong motivation for continued drug intake, whereas many somatic and psychiatric diseases lead to an aversive state, characterized by loss of motivation. I will study specific neural circuits and mechanisms underlying reward and aversion, and how pathological signaling in these systems can trigger relapse in drug addiction. Given the important role of the dopaminergic neurons in the midbrain for many aspects of reward signaling, I will study how synaptic plasticity in these cells, and in their target neurons in the striatum, contribute to relapse in drug seeking. I will also study the circuits underlying aversion. Little is known about these circuits, but my hypothesis is that an important component of aversion is signaled by a specific neuronal population in the brainstem parabrachial nucleus, projecting to the central amygdala. We will test this hypothesis and also determine how this aversion circuit contributes to the persistence of addiction and to relapse. To dissect this complicated system, I am developing new genetic methods for manipulating and visualizing specific functional circuits in the mouse brain. My unique combination of state-of-the-art competence in transgenics and cutting edge knowledge in the anatomy and functional organization of the circuits behind reward and aversion should allow me to decode these systems, linking discrete circuits to behavior. Collectively, the results will indicate how signals encoding aversion and reward are integrated to control addictive behavior and they may identify novel avenues for treatment of drug addiction as well as aversion-related symptoms affecting patients with chronic inflammatory conditions and cancer.

1 500 000 €

Start date: 2010-10-01, End date: 2015-09-30

Sex differences in life span and aging are ubiquitous across the animal kingdom and represent a long-standing challenge in evolutionary biology. In most species, including humans, sexes differ not only in how long they live and when they start to senesce, but also in how they react to environmental interventions aimed at prolonging their life span or decelerating the onset of aging. Therefore, sex differences in life span and aging have important implications beyond the questions posed by fundamental science. Both evolutionary reasons and medical implications of sex differences in demographic, reproductive and physiological senescence are and will be crucial targets of present and future research in the biology of aging. Here I propose a two-step approach that can provide a significant breakthrough in our understanding of the biological basis of sex differences in aging. First, I propose to resolve the age-old conundrum regarding the role of sexspecific mortality rate in sex differences in aging by developing a series of targeted experimental evolution studies in a novel model organism – the nematode, Caenorhabditis remanei. Second, I address the role of intra-locus sexual conflict in the evolution of aging by combining novel methodology from nutritional ecology – the Geometric Framework – with artificial selection approach using the cricket Teleogryllus commodus and the fruitfly Drosophila melanogaster. I will directly test the hypothesis that intra-locus sexual conflict mediates aging by restricting the adaptive evolution of diet choice. By combining techniques from evolutionary biology and nutritional ecology, this proposal will raise EU’s profile in integrative research, and contribute to the training of young scientists in this rapidly developing field.

1 391 904 €

Start date: 2010-12-01, End date: 2016-05-31

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

Main goal. We aim to understand the puzzling coexistence of antibiotic-resistant and antibiotic-sensitive species in natural soil environments, using novel quantitative experimental techniques and mathematical analysis. The ecological insights gained will be translated into novel treatment strategies for combating antibiotic resistance. Background. Microbial soil ecosystems comprise communities of species interacting through copious secretion of antibiotics and other chemicals. Defence mechanisms, i.e. resistance to antibiotics, are ubiquitous in these wild communities. However, in sharp contrast to clinical settings, resistance does not take over the population. Our hypothesis is that the ecological setting provides natural mechanisms that keep antibiotic resistance in check. We are motivated by our recent finding that specific antibiotic combinations can generate selection against resistance and that soil microbial strains produce compounds that directly target antibiotic resistant mechanisms. Approaches. We will: (1) Isolate natural bacterial species from individual grains of soil, characterize their ability to produce and resist antibiotics and identify the spatial scale for correlations between resistance and production. (2) Systematically measure interactions between species and identify interaction patterns enriched in co-existing communities derived from the same grain of soil. (3) Introducing fluorescently-labelled resistant and sensitive strains into natural soil, we will measure the fitness cost and benefit of antibiotic resistance in situ and identify natural compounds that select against resistance. (4) Test whether such “selection-inverting” compounds can slow evolution of resistance to antibiotics in continuous culture experiments. Conclusions. These findings will provide insights into the ecological processes that keep antibiotic resistance in check, and will suggest novel antimicrobial treatment strategies.

1 900 000 €

Start date: 2012-09-01, End date: 2018-08-31

When triggered by nutrient limitation, the Gram-positive bacterium Bacillus subtilis and its relatives enter a pathway of cellular differentiation culminating in the formation of a dormant cell type called a spore, the most resilient cell type known. Bacterial spores can survive for long periods of time and are able to endure extremes of heat, radiation and chemical assault. Remarkably, dormant spores can rapidly convert back to actively growing cells by a process called germination. Consequently, spore forming bacteria, including dangerous pathogens, (such as C. botulinum and B. anthracis) are highly resistant to antibacterial treatments and difficult to eradicate. Despite significant advances in our understanding of the process of spore formation, little is known about the nature of the mature spore. It is unrevealed how dormancy is maintained within the spore and how it is ceased, as the organization and the dynamics of the spore macromolecules remain obscure. The unusual biochemical and biophysical characteristics of the dormant spore make it a challenging biological system to investigate using conventional methods, and thus set the need to develop innovative approaches to study spore biology. We propose to explore the nature of spores by using B. subtilis as a primary experimental system. We intend to: (1) define the architecture of the spore chromosome, (2) track the complexity and fate of mRNA and protein molecules during sporulation, dormancy and germination, (3) revisit the basic notion of the spore dormancy (is it metabolically inert?), (4) compare the characteristics of bacilli spores from diverse ecophysiological groups, (5) investigate the features of spores belonging to distant bacterial genera, (6) generate an integrative database that categorizes the molecular features of spores. Our study will provide original insights and introduce novel concepts to the field of spore biology and may help devise innovative ways to combat spore forming pathogens.

1 630 000 €

Start date: 2008-10-01, End date: 2013-09-30

Non-Alcoholic Fatty Liver Disease (NAFLD), a disease characterized by accumulation of lipid droplets in the liver, is the major precursor for liver failure and liver cancer, and constitutes a global health challenge. An estimated 25% of the adult population suffers from NAFLD, but no FDA approved drugs are available to treat this condition. Obesity is a major NAFLD risk factor and weight-loss improves disease severity in obese patients. Bariatric surgeries are an effective treatment for obesity when lifestyle modifications fail and often lead to improvement in NAFLD and type 2 diabetes. The overreaching objective of this proposal is to combine bariatric surgery in mice and humans with advanced molecular and computational analyses to discover novel, weight-loss independent mechanisms that lead to NAFLD alleviation, and harness them to treat NAFLD. In preliminary studies, I discovered that bariatric surgery clears lipid droplets from the livers of obese db/db mice without inducing weight-loss. Using metabolic and computational analysis, I found that bariatric surgery shifts hepatic gene expression and blood metabolome of post-bariatric patients to a new trajectory, distinct from lean or sick patients. Data analysis revealed the transcription factor Egr1 and one-carbon and choline metabolism to be key drivers of weight-loss independent effects of bariatric surgery. I will use two NAFLD mouse models that do not lose weight after bariatric surgery to characterize livers of mice post-surgery. Human patients do lose weight following surgery, therefore I will use computational methods to elucidate weight-independent pathways induced by surgery, by comparing livers of lean patients to those of NAFLD patients before and shortly after bariatric surgery. Candidate pathways will be studied by metabolic flux analysis and manipulated genetically, with the ultimate goal of reaching systems-levels understanding of NAFLD and identifying surgery-mimetic therapies for this disease.

1 499 354 €

Start date: 2018-11-01, End date: 2023-10-31

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

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

Organisms evolved the ability to form a magnificent array of functional materials, which surpass any man-made product. A prominent example is diatoms, marine microalgae that form an intricate cell-wall made of meso-porous silica. Diatom silica is a tough, hierarchically built, and biocompatible material that is environmentally friendly and cheap, making it an exciting target for nanotechnology. Nevertheless, the principles of this regulated formation mechanism remain elusive. A persistent obstacle for elucidating biomineralization processes is the inaccessibility of the cellular environment for structural and chemical investigations. Recently, far-reaching developments in electron microscopy have revolutionized our abilities to investigate chemical processes inside living organisms. It is now becoming feasible to image and analyze, with nanometer-scale resolution, an intracellular mineralization process. This proposal aims to elucidate the intracellular mechanism of silica formation by diatoms. We will study cells undergoing the silicification process in situ, using a suite of state-of-the-art electron and X-ray imaging and spectroscopy tools. The combination of structural and chemical data will enable us to elucidate: 1) The concentration and stabilization mechanism of transient Si phases in the cell. 2) The nanoscale environment in which silica condensation takes place. 3) Genetic and environmental strategies to engineer the silicification process for designed outcomes. Diatom silica is a promising material for applications such as photonics, pharmaceuticals, and catalysis, which require hierarchical, high-surface area, nano-materials. The achievements of this project will inspire synthetic methodologies to produce and design nano-patterned silica, and genetically-engineer the biological silicification process to produce custom-made materials.

1 500 000 €

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

The study of synthetic molecular networks is of fundamental importance for understanding the organizational principles of biological systems and may well be the key to unraveling the origins of life. In addition, such systems may be useful for parallel synthesis of molecules, implementation of catalysis via multi-step pathways, and as media for various applications in nano-medicine and nano-electronics. We have been involved recently in developing peptide-based replicating networks and revealed their dynamic characteristics. We argue here that the structural information embedded in the polypeptide chains is sufficiently rich to allow the construction of peptide 'Systems Chemistry', namely, to facilitate the use of replicating networks as cell-mimetics, featuring complex dynamic behavior. To bring this novel idea to reality, we plan to take a unique holistic approach by studying such networks both experimentally and via simulations, for elucidating basic-principles and towards applications in adjacent fields, such as molecular electronics. Towards realizing these aims, we will study three separate but inter-related objectives: (i) design and characterization of networks that react and rewire in response to external triggers, such as light, (ii) design of networks that operate via new dynamic rules of product formation that lead to oscillations, and (iii) exploitation of the molecular information gathered from the networks as means to control switching and gating in molecular electronic devices. We believe that achieving the project's objectives will be highly significant for the development of the arising field of Systems Chemistry, and in addition will provide valuable tools for studying related scientific fields, such as systems biology and molecular electronics.

1 500 000 €

Start date: 2010-10-01, End date: 2015-09-30

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

Modern cryptography has deeply rooted connections with computational complexity theory and other areas of computer science. This proposal suggests to explore several {\em new connections} between questions in cryptography and questions from other domains, including computational complexity, coding theory, and even the natural sciences. The project is expected to broaden the impact of ideas from cryptography on other domains, and on the other hand to benefit cryptography by applying tools from other domains towards better solutions for central problems in cryptography.

1 459 703 €

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

BACKGROUND Ancient DNA research has recently entered the genomics era. Performing “ancient population genomics” is now technically possible. Utilizing the temporal aspect of this new data, we can address fundamental evolutionary questions such as the amount of selection acting on the genome or the mode and tempo of the colonization of the world. AIMS The overall goal of the proposed research is to (i) generate and analyse data to answer two long standing questions in human evolution: understanding the molecular basis of human adaptation to high altitude and investigating the timing of the Polynesian-South American contact, (ii) develop statistical approaches that combine ancient and modern genetic data to estimate the timing and the intensity of a selective sweep and an admixture event. METHODOLOGY Application: We will collect, date and DNA sequence human remains. Combining the ancient genetic data, 14C dates with existing modern genomic data will allow us to increase the resolution as to the timing of the adaptive and the admixture event, respectively, while generating unique datasets. Theory: We will build on existing methods based on one-locus classical population genetic models to develop tools to analyse whole genome time serial data. RELEVANCE Ecological: The results will address the fundamental question of how much of the human genome is undergoing selection, better characterize one of the textbook examples of adaptation in humans and contribute to our understanding of the peopling of the Americas. Medical: We will gain insights into the fundamental stress physiology experienced at high altitude and therefore into altitude-related illnesses. Methodological: The methods developed in this project will not only benefit the growing field of ancient genomics but also other fields where data is collected in a temporal manner, such as experimental evolution and epidemiology

1 498 478 €

Start date: 2016-08-01, End date: 2021-07-31

Aneuploidy, an imbalanced number of chromosomes or chromosome arms, is a distinct feature of cancer. Recent years have seen conceptual, methodological and technical advances in the field of cancer aneuploidy research, but we are just beginning to scratch the surface of the underlying biology, and the potential vulnerabilities of aneuploid cancer cells remain under-explored. Cancer aneuploidy is therefore a biological enigma and a missed opportunity for cancer therapy. Identifying the “Achilles heels” of aneuploidy remains a holy grail of cancer research. However, current models of aneuploidy fail to fully recapitulate the cellular consequences of aneuploidy in cancer, thus compromising the identification of aneuploidy-induced cellular vulnerabilities. The time is ripe to tackle cancer aneuploidy with state-of-the-art genomic and functional approaches. In this project, I propose to address the following key questions: 1) What forces shape the evolution of aneuploidy in tumors? We will integrate in silico analyses of clinical data, in vitro modeling in isogenic human cell lines, and in vivo experiments in mice, to elucidate how various cellular contexts shape the tumor aneuploidy landscape. 2) What cellular vulnerabilities are induced by aneuploidy? We will combine isogenic cell lines with large-scale genetic and chemical perturbation screens, in order to identify, validate, and mechanistically dissect vulnerabilities induced by aneuploidy in human cancer cells. These research aims fall well within my unique expertise. I mapped various aneuploidy landscapes and developed innovative experimental and computational tools for studying cancer aneuploidy. A successful completion of the project will shed light on the context-dependent cellular consequences of aneuploidy in cancer and provide proof-of-concept for its potential targeting. Ultimately, identifying aneuploidy-specific vulnerabilities will pave the way for the therapeutic exploitation of this hallmark of cancer.

1 612 500 €

Start date: 2021-10-01, End date: 2026-09-30

The metabolism of cancer cells is altered to meet cellular requirements for growth, providing novel means to selectively target tumorigenesis. While extensively studied, our current view of cancer cellular metabolism is fundamentally limited by lack of information on variability in metabolic activity between distinct subcellular compartments and cells. We propose to develop a spatio-temporal fluxomics approach for quantifying metabolic fluxes in the cytoplasm vs. mitochondria as well as their cell-cycle dynamics, combining mass-spectrometry based isotope tracing with cell synchronization, rapid cellular fractionation, and computational metabolic network modelling. Spatio-temporal fluxomics will be used to revisit and challenge our current understanding of central metabolism and its induced adaptation to oncogenic events – an important endeavour considering that mitochondrial bioenergetics and biosynthesis are required for tumorigenesis and accumulating evidences for metabolic alterations throughout the cell-cycle. Our preliminary results show intriguing oscillations between oxidative and reductive TCA cycle flux throughout the cell-cycle. We will explore the extent to which cells adapt their metabolism to fulfil the changing energetic and anabolic demands throughout the cell-cycle, how metabolic oscillations are regulated, and their benefit to cells in terms of thermodynamic efficiency. Spatial flux analysis will be instrumental for investigating glutaminolysis - a ‘hallmark’ metabolic adaptation in cancer involving shuttling of metabolic intermediates and cofactors between mitochondria and cytoplasm. On a clinical front, our spatio-temporal fluxomics analysis will enable to disentangle oncogene-induced flux alterations, having an important tumorigenic role, from artefacts originating from population averaging. A comprehensive view of how cells adapt their metabolism due to oncogenic mutations will reveal novel targets for anti-cancer drugs.

1 481 250 €

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

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

Energy and sustainability are among the biggest challenges humanity faces this century. Catalysis is an indispensable component for many potential solutions, and fundamental research in catalysis is as urgent as ever. Here, we propose to build up an interdisciplinary research program in molecular catalysis to address the challenges of energy and sustainability. There are two specific aims: (I) bio-inspired sulfur-rich metal complexes as efficient and practical electrocatalysts for hydrogen production and CO2 reduction; (II) well-defined Fe complexes of chelating pincer ligands for chemo- and stereoselective organic synthesis. An important feature of the proposed catalysts is that they are made of earth-abundant and readily available elements such as Fe, Co, Ni, S, N, etc. Design and synthesis of catalysts are the starting point and a key aspect of this project. A major inspiration comes from nature, where metallo-enzymes use readily available metals for fuel production and challenging reactions. Our accumulated knowledge and experience in spectroscopy, electrochemistry, reaction chemistry, mechanism, and catalysis will enable us to thoroughly study the synthetic catalysts and their applications towards the research targets. Furthermore, we will explore research territories such as electrode modification and fabrication, catalyst immobilization and attachment, and asymmetric catalysis. The proposed research should not only result in new insights and knowledge in catalysis that are relevant to energy and sustainability, but also produce functional, scalable, and economically feasible catalysts for fuel production and organic synthesis. The program can contribute to excellence in European research.

1 475 712 €

Start date: 2011-01-01, End date: 2015-12-31

The generation of animals by nuclear transfer demonstrated that the epigenetic state of somatic cells could be reset to an embryonic state, capable of directing the development of a new organism. The nuclear cloning technology is of interest for transplantation medicine, but any application is hampered by the inefficiency and ethical problems. A breakthrough solving these issues has been the in vitro derivation of reprogrammed Induced Pluripotent Stem “iPS” cells by the ectopic expression of defined transcription factors in somatic cells. iPS cells recapitulate all defining features of embryo-derived pluripotent stem cells, including the ability to differentiate into all somatic cell types. Further, recent publications have demonstrated the ability to directly trans-differentiate somatic cell types by ectopic expression of lineage specification factors. Thus, it is becoming increasingly clear that an ultimate goal in the stem cell field is to enable scientists to have the power to safely manipulate somatic cells by “reprogramming” their behavior at will. However, to frame this challenge, we must understand the basic mechanisms underlying the generation of reprogrammed cells in parallel to designing strategies for their medical application and their use in human disease specific research. In this ERC Starting Grant proposal, I describe comprehensive lines of experimentation that I plan to conduct in my new lab scheduled to open in April 2011 at the Weizmann Institute of Science. We will utilize exacting transgenic mammalian models and high throughput sequencing and genomic screening tools for in depth characterization of the molecular “rules” of rewiring the epigenome of somatic and pluripotent cell states. The proposed research endeavors will not only contribute to the development of safer strategies for cell reprogramming, but will also help decipher how diverse gene expression programs lead to cellular specification during normal development.

1 960 000 €

Start date: 2011-11-01, End date: 2016-10-31

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

Nonlinear optics is present in our daily life with applications, e.g. light sources for microsurgery or green laser pointer. All of them use bulk materials such as glass fibers or crystals. Generating nonlinear effects from materials at the nanoscale would expand the applications to biology as imaging markers or optoelectronic integrated devices. However, nonlinear signals scale with the volume of a material. Therefore finding materials with high nonlinearities to avoid using high power and large interaction length is challenging. Many studies focus on third order nonlinearities (described by a χ(3) tensor) present in every material (silicon, graphene…) or on metals for enhancing nonlinearities with plasmonics. My approach is to explore second-order χ(2) nanomaterials, since they show higher nonlinearities than χ(3) ones, additional properties such as birefringence, wide band gap for transparency, high refractive index (n>2), and no ohmic losses. Typical χ(2) materials are oxides (BaTiO3, LiNbO3…) with a non-centrosymmetric crystal used for wavelength conversion like in second-harmonic generation (SHG). The key idea is to demonstrate original strategies to enhance SHG of χ(2) nano-oxides with the material itself and without involving any hybrid effects from other materials such as plasmonic resonances of metals. First, I propose to use multiple Mie resonances from BaTiO3 nanoparticles to boost SHG in the UV to NIR range. Up to now, Mie effects at the nanoscale have been measured in materials with no χ(2) nonlinearities (silicon spheres). Second, since χ(2) oxides are difficult to etch, I will overcome this fabrication issue by demonstrating solution processed imprint lithography to form high-quality photonic crystal cavities from nanoparticles. Third, I will use facet processing of single LiNbO3 nanowire to obtain directionality effects for spectroscopy on-a-chip. This work fosters applications and commercial devices offering a sustainable future to this field.

1 500 000 €

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

The quest to restore damaged organs is one of the major challenges in medicine. Recent studies in both animals and in humans suggest that the heart has a limited capacity to replenish its own cardiomyocytes (CMs) throughout life, albeit inadequate to compensate for major injuries such as acute myocardial infarction (MI). Most therapeutic research in regenerative cardiogenesis is geared toward stem cell therapy as a means to replace lost CMs associated with ischemic heart disease. Clinical data evaluating the efficacy of cell-based therapy for heart disease are relatively disappointing. This proposal encompasses multidisciplinary and novel approaches to study the molecular and cellular mechanisms that govern the proliferation, differentiation and dedifferentiation of endogenous CMs, combining developmental-, systems- and cell-biology methodologies in vitro and in vivo, in chick, rodent, and human tissue samples. First, we will perform combinatorial perturbations of signaling pathways in chick embryos, focusing primarily on the FGF-ERK pathway, to investigate the molecular switch between cardiac progenitors and CMs (Aim 1). Because adult CMs have limited proliferative capacity, mainly due to mechanical constraints, in Aim 2, we will apply state-of-the-art techniques in cell biology, to determine whether specific mechno-transduction stimuli can prime the proliferation of differentiated CMs. In order to gain deeper insights into the capacity of adult CMs to renew themselves under normal and pathological conditions, in Aim 3, we will employ a novel cell lineage methodology in mouse and human tissue, based on information encoded in genome. Using this methodology, we hope to shed light on the maintenance, renewal and regenerative capacities of adult CMs in vivo. The expected outcome will be a significantly greater understanding of the bidirectional transition from proliferating cardiac progenitors into differentiated CMs, in embryonic and adult hearts.

1 500 000 €

Start date: 2012-01-01, End date: 2016-12-31

Despite massive efforts in securing software, about 60 security bugs are publicly reported each month. Systems software is prone to low level bugs caused by undefined behavior (memory corruption, type confusion, or API confusion). Exploits abuse undefined behavior to execute attacker specified code, or to leak information. We propose code sanitization (CodeSan), a comprehensive approach to improve code quality. CodeSan will sanitize software by (i) automating bug discovery during development through software testing and (ii) protecting deployed software through reflective mitigations. CodeSan trades formal completeness for practical scalability in three steps: First, policy-based sanitization makes undefined behavior (through violations of memory safety, type safety, or API flow safety) explicit and detectable given concrete test inputs. Second, automatic test case generation increases testing coverage for large programs without the need for pre-existing test cases, enabling broader and automated use of policy-based sanitization. Third, for deployed software, reflective mitigations place runtime checks precisely where they are needed based on data-flow and control-flow coverage from our testing efforts. CodeSan complements formal approaches by protecting software that is currently out of reach due to its size, complexity, or low level nature. CodeSan is a compelling, comprehensive, and adaptive approach to thoroughly address undefined behavior for complex software. The three proposed thrusts complement each other naturally and will immediately guard large software systems such as Google Chromium, Mozilla Firefox, the Android system, or the Linux kernel, making them resilient against attacks. In line with PI Payer’s track record on open sourcing his group’s research artifacts on cast sanitization, transformative fuzzing, or control-flow hijacking mitigations, all prototypes produced during CodeSan will be released as open-source.

1 499 970 €

Start date: 2020-03-01, End date: 2025-02-28

Cognition is a collective term for complex but sophisticated mental processes such as attention, learning, social interaction, language production, decision making and other executive functions. For normal brain function, these higher-order functions need to be aptly regulated and controlled, and the physiology and cellular substrates for cognitive functions are under intense investigation. The loss of cognitive control is intricately related to pathological states such as schizophrenia, depression, attention deficit hyperactive disorder and addiction. Synchronized neural activity can be observed when the brain performs several important functions, including cognitive processes. As an example, gamma activity (30-80 Hz) predicts the allocation of attention and theta activity (4-12 Hz) is tightly linked to memory processes. A large body of work indicates that the integrity of local and global neural synchrony is mediated by interneuron networks and actuated by the balance of different neuromodulators. However, much knowledge is still needed on the functional role interneurons play in cognitive processes, i.e. how the interneurons contribute to local and global network processes subserving cognition, and ultimately play a role in behavior. In addition, we need to understand how neuro-modulators, such as dopamine, regulate interneuron function. The proposed project aims to functionally determine the specific role the parvalbumin interneurons and the neuromodulator dopamine in aspects of cognition, and in behavior. In addition, we ask the question if cognition can be enhanced. We are employing a true multidisciplinary approach where brain activity is recorded in conjunctions with optogenetic manipulations of parvalbumin interneurons in animals performing cognitive tasks. In one set of experiments knock-down of dopamine receptors specifically in parvalbumin interneurons is employed to probe how this neuromodulator regulate network functions.

1 400 000 €

Start date: 2014-02-01, End date: 2019-01-31

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

The origin and evolution of sexual reproduction and sex differences represents one of the major unsolved problems in evolutionary biology, and although much progress had been made both via theory and empirical research, recent data suggest that sex chromosome evolution may be more complex than previously thought. The concept of sexual antagonism (when there is a positive intersexual genetic correlation in trait expression but opposite fitness effects of the trait(s) in males and females) has become essential to our understanding of sex chromosome evolution. The goal of this proposal is to understand how the interacting effects of sexual antagonism, sex-linked genetic variation, and sex-specific selection shape the genetic architecture of complex traits. I will test the hypotheses that: 1) individual sexually antagonistic loci are common in the genome, both in separate-sexed species and in hermaphrodites, and drive patterns of sexual antagonism often seen on the trait level. 2) That the response to sex-specific selection in sex-linked loci is usually due to standing sexually antagonistic genetic variation. 3) That sexually antagonistic variation is primarily non-additive in nature. To accomplish this, I will use a combination of approaches, including sex-limited experimental evolution of the X chromosome and reciprocal sex chromosome introgression among distantly related populations of Drosophila, quantitative genetic analysis and experimental evolution mimicking the creation of a novel sex chromosome in the hermaphroditic flatworm Macrostomum, and analytical and simulation modeling. This project will serve to confirm or refute the assumption that trait-level sexual antagonism reflects the contributions of many individual sexually antagonistic loci, increase our understanding of the contribution of coevolution of the sex chromosomes to population divergence, and help provide us with a better general understanding of how genotype maps to phenotype.

1 492 011 €

Start date: 2016-05-01, End date: 2022-04-30

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

"Nature has long inspired chemists with its abilities to stabilize ephemeral chemical species, to perform chemical reactions with unprecedented rates and selectivities, and to synthesize complex molecules and fascinating inorganic nanostructures. What natural systems consistently exploit - which is yet fundamentally different from how chemists perform reactions - is their aspect of nanoscale confinement. The goal of the proposed research program is to integrate the worlds of organic and inorganic colloidal chemistry by means of manipulating chemical reactivities and synthesizing novel molecules and nanostructures inside synthetic confined environments created using novel, unconventional approaches based on inorganic, nanostructured building blocks. The three types of confined spaces we propose are as follows: 1) nanopores within reversibly self-assembling colloidal crystals (""dynamic nanoflasks""), 2) cavities of bowl-shaped metallic nanoparticles (NPs), and 3) surfaces of spherical NPs. By taking advantage of these unique tools, we will attempt to develop, respectively, 1) a conceptually new method for catalyzing chemical reactions using light, 2) nanoscale inclusion chemistry (a field based on host-guest ""complexes"" assembled form nanosized components) and 3) to use NPs as platforms for the development of new organic reactions. While these objectives are predominantly of a fundamental nature, they can easily evolve into a variety of practical applications. Specifically, we will pursue diverse goals such as the preparation of 1) a new family of inverse opals (with potentially fascinating optical and mechanical properties), 2) artificial chaperones (NPs assisting in protein folding), and 3) size- and shape-controlled polymeric vesicles. Overall, it is believed that this marriage of organic and colloidal chemistry has the potential to change the fundamental way we perform chemical reactions, paving the way to the discovery of new phenomena and unique structures."

1 499 992 €

Start date: 2013-10-01, End date: 2018-09-30

The analysis and synthesis of complex 3D geometric data sets is of crucial importance in many scientific disciplines (e.g. bio-medicine, material science, mechanical engineering, physics) and industrial applications (e.g. drug design, entertainment, architecture). We are currently witnessing a tremendous increase in the size and complexity of geometric data, largely fueled by significant advances in 3D acquisition and digital production technology. However, existing computational tools are often not suited to handle this complexity. The goal of this project is to explore a fundamentally different way of processing 3D geometry. We will investigate a new generalized model of geometric symmetry as a unifying concept for studying spatial organization in geometric data. This model allows exposing the inherent redundancies in digital 3D data and will enable truly scalable algorithms for analysis, processing, and design of large-scale geometric data sets. The proposed research will address a number of fundamental questions: What is the information content of 3D geometric models? How can we represent, store, and transmit geometric data most efficiently? Can we we use symmetry to repair deficiencies and reduce noise in acquired data? What is the role of symmetry in the design process and how can it be used to reduce complexity? I will investigate these questions with an integrated approach that combines thorough theoretical studies with practical solutions for real-world applications. The proposed research has a strong interdisciplinary component and will consider the same fundamental questions from different perspectives, closely interacting with scientists of various disciplines, as well artists, architects, and designers.

1 160 302 €

Start date: 2011-02-01, End date: 2016-01-31

Many spectacular optical phenomena in nature are produced by the interaction of light with organic crystals. Organisms exert exquisite control over the habit and organization of these crystals to determine the type of optical effect produced by using strategies beyond the state of the art in solid state chemistry. Despite their important role in animal behavior and their huge potential to inspire new optical materials, little is known about these materials. However, recent discoveries of previously unknown organic bio-crystals indicate that many more of these materials will be found and that ‘organic bio-crystallization’ is an emergent field with important implications for materials science. My overall objective is to uncover the strategies organisms use to control the formation of organic crystals, enabling these strategies to be harnessed to develop new crystalline organic materials. A pioneering approach is proposed which entails following the crystallization pathways of organic molecules in model photonic systems undergoing development. The crystallization of guanine and isoxanthopterin will be investigated to reveal the physio-chemical and biological processes underpinning crystallization. Cryogenic electron microscopy, spectroscopy and in situ diffraction methods will determine changes in the chemical and physical properties of the crystals during crystallization. Proteomic and transcriptomic studies will identify the macromolecules responsible for controlling nucleation and growth and the genes encoding them. These bio-crystallization processes will then be artificially mimicked and manipulated to produce guanine and isoxanthopterin crystals with rationally designed crystal properties (crystal habit, composition, size), including an ambitious attempt to genetically programme guanine-producing iridophore cells as living factories to produce crystals with controlled phenotypes, laying the foundations for a new field of genetically programmed organic materials.

1 966 000 €

Start date: 2020-03-01, End date: 2025-02-28

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

Synthesizing organic molecules in high purity with designed properties is of utmost importance for pharmaceutical applications and material- and polymer sciences including the efficient production of enantiopure compounds and the compliance with ecological concerns and sustainability. The efficiency of all reaction classes has improved over the past decades. However, the basic principle and execution did not change: The target molecule is disconnected into donor and acceptor synthons and appropriate functional groups need to be introduced and adjusted to carry out the envisioned coupling. These additional steps decrease the yield and efficiency, are costly in time, resources and produce waste. The introduction of new functionalities by direct C-H or C-C bond activation is a unique and highly appealing strategy. The range of substrates is virtually unlimited, including hydrocarbons, small molecules and polymers. Such dream reactions avoid any pre-functionalization, shorten synthetic routes, make unsought disconnections possible and allow for a more efficient usage of our dwindling resources. Despite recent progress in the activations of inert bonds, narrow scopes, poor reactivities and harsh conditions hamper most general practical applications. Especially, enantioselective activations are a longstanding challenge. The outlined project seeks to address these issues by the development and exploitation of new catalytic enantioselective C-H and C-C functionalizations of broadly available organic substrates, using chiral Rh- and Pd- catalysts, additionally supported by automated screening and computational techniques. These reactions will be then applied in the streamlined synthesis of pharmaceutically relevant scaffolds and of compounds for organic electronics.

1 499 500 €

Start date: 2011-02-01, End date: 2016-01-31

The explosion of information around us has democratized knowledge and transformed its availability for people around the world. Still, since information is mediated through automated systems, access is bounded by their ability to understand language. Consider an economist asking “What fraction of the top-5 growing countries last year raised their co2 emission?”. While the required information is available, answering such complex questions automatically is not possible. Current question answering systems can answer simple questions in broad domains, or complex questions in narrow domains. However, broad and complex questions are beyond the reach of state-of-the-art. This is because systems are unable to decompose questions into their parts, and find the relevant information in multiple sources. Further, as answering such questions is hard for people, collecting large datasets to train such models is prohibitive. In this proposal I ask: Can computers answer broad and complex questions that require reasoning over multiple modalities? I argue that by synthesizing the advantages of symbolic and distributed representations the answer will be “yes”. My thesis is that symbolic representations are suitable for meaning composition, as they provide interpretability, coverage, and modularity. Complementarily, distributed representations (learned by neural nets) excel at capturing the fuzziness of language. I propose a framework where complex questions are symbolically decomposed into sub-questions, each is answered with a neural network, and the final answer is computed from all gathered information. This research tackles foundational questions in language understanding. What is the right representation for reasoning in language? Can models learn to perform complex actions in the face of paucity of data? Moreover, my research, if successful, will transform how we interact with machines, and define a role for them as research assistants in science, education, and our daily life.

1 499 375 €

Start date: 2019-04-01, End date: 2024-03-31

As evolutionary biologists we are of course motivated by the desire to gain further insight in to the evolution of natural populations. The main goals of this proposal are to (i) develop theory and methodology that will enable the identification of adaptively evolving genomic regions using polymorphism data, (ii) develop theory and methodology for the estimation of whole-genome rates of adaptive evolution, and (iii) apply the developed theory in two strategic collaborative applications. Capitalizing on recently available and soon-to-be available whole genome polymorphism data across multiple taxa, these approaches are expected to significantly improve the identification and localization of recent selective events, as well as provide long sought after information regarding the genomic distributions of selective effects. Additionally, through these on-going collaborations with empirical and experimental labs, this methodology will allow for specific hypothesis testing that will further illuminate classical examples of adaptation. Together, this proposal seeks to Describe Evolution with Theoretical, Empirical and Computational Tools (DETECT), seeking to accurately describe the very mode and tempo of Darwinian adaptation.

1 071 729 €

Start date: 2013-01-01, End date: 2017-08-31

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

The global incidence of kidney disease is on the rise, but little progress has been made to develop novel therapies or preventative measures. New methods to generated renal tissue in vitro hold great promise for regenerative medicine and the prospect of organ replacement. Most of the strategies employed differentiate induced pluripotent stem cells (iPSCs) into kidney organoids, which can be derived from patient tissue. Direct reprogramming is an alternative approach to convert one cell type into another using cell fate specifying transcription factors. We were the first to develop a method to directly reprogram mouse and human fibroblasts to kidney cells (induced renal tubular epithelial cells - iRECs) without the need for pluripotent cells. Morphological, transcriptomic and functional analyses found that directly reprogrammed iRECs are remarkably similar to native renal tubular cells. Direct reprogramming is fast, technically simple and scalable. This proposal aims to establish direct reprogramming in nephrology and develop novel in vitro models for kidney diseases that primarily affect the renal tubules. We will unravel the mechanics of how only four transcription factors can change the morphology and function of fibroblasts towards a renal tubule cell identity. These insights will be used to identify alternative routes to directly reprogram tubule cells with increased efficiency and accuracy. We will identify cell type specifying factors for reprogramming of tubular segment specific cell types. Finally, we will use of reprogrammed kidney cells to establish new in vitro models for autosomal dominant polycystic kidney disease and nephronophthisis. Direct reprogramming holds enormous potential to deliver patient specific disease models for diagnostic and therapeutic applications in the age of personalized and targeted medicine.

1 499 917 €

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

This project aims to (i) resolve challenging graph problems in distributed and dynamic settings, with a focus on connectivity problems (such as computing edge connectivity and distances), and (ii) on the way develop a systematic approach to attack problems in these settings, by thoroughly exploring relevant algorithmic and complexity-theoretic landscapes. Tasks include - building a hierarchy of intermediate computational models so that designing algorithms and proving lower bounds can be done in several intermediate steps, - explaining the limits of algorithms by proving conditional lower bounds based on old and new reasonable conjectures, and - connecting techniques in the two settings to generate new insights that are unlikely to emerge from the isolated viewpoint of a single field. The project will take advantage from and contribute to the developments in many young fields in theoretical computer science, such as fine-grained complexity and sublinear algorithms. Resolving one of the connectivity problems will already be a groundbreaking result. However, given the approach, it is likely that one breakthrough will lead to many others.

1 500 000 €

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

Modern systems are increasingly dezentralized and massively distributed computations play a vital role in the systems of the future. This project aims to advance the foundational aspects of distributed computing, particularly MessagePassing algorithms for optimization problems. The strong shift towards distributed systems also lead to a flurry of works on such algorithms -- many optimization problems now have distributed algorithms with optimal worst-case performance guarantees. Generally, these guarantees cannot be improved because they match unconditional impossibility results, which prove severe limitations on the performance of distributed algorithms in some (pathological) network topologies. Real world networks, however, are never worst-case and do not share the limiting bottleneck characteristics of these pathological topologies. In fact, there is no known barrier for ultra-fast polylogarithmic-round distributed algorithms on any network of interest. This leaves an exponential gap between current worst-case-optimal algorithms and what is likely possible in many, if not all, real-world settings. Motivated by this, this project provides a program for a general toolbox and theory for MessagePassing optimization algorithms that go beyond worst-case topologies. The main and guiding high-risk high-gain goal is the development of universally optimal distributed algorithms, which are competitive with the best algorithm on any given topology. This would constitute the strongest possible form of algorithmically adjusting to non-worst-case topologies. A detailed program with many concrete and smaller stepping stones towards this ambitious breakthrough objective is provided. Many of the novel questions stemming from this program and proposal are highly interdisciplinary, crossing boundaries between information theory, distributed computing, topological graph theory, and other parts of theoretical computer science, and are fundamental and interesting in their own right.

1 540 000 €

Start date: 2020-09-01, End date: 2025-08-31

Transcription factors (TF) regulate genome function by controlling gene expression. Comprehensive characterization of the in vivo binding of TF to the DNA in relevant primary models is a critical step towards a global understanding of the human genome. Recent advances in high-throughput genomic technologies provide an extraordinary opportunity to develop and apply systematic approaches to learn the underline principles and mechanisms of mammalian transcriptional networks. The premise of this proposal is that a tractable set of rules govern how cells commit to a specific cell type or respond to the environment, and that these rules are coded in regulatory elements in the genome. Currently our understanding of the mammalian regulatory code is hampered by the difficulty of directly measuring in vivo binding of large numbers of TFs to DNA across multiple primary cell types and their natural response to physiological stimuli. Here, we overcome this bottleneck by systematically exploring the genomic binding network of 1. All relevant TFs of key hematopoietic cells in both steady state and under relevant stimuli. 2. Follow the changes in TF networks as cells differentiate 3. Use these models to engineer cell states and responses. To achieve these goals, we developed a new method for automated high throughput ChIP coupled to sequencing (HT-ChIP-Seq). We used this method to measure binding of 40 TFs in 4 time points following stimulation of dendritic cells with pathogen components. We find that TFs vary substantially in their binding dynamics, genomic localization, number of binding events, and degree of interaction with other TFs. The analysis of this data suggests that the TF network is hierarchically organized, and composed of different types of TFs, cell differentiation factors, factors that prime for gene induction, and factors that bind more specifically and dynamically. This proposal revisits and challenges the current understanding of the mammalian regulatory code.

1 500 000 €

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

Anxiety disorders include different forms of pathological fear and anxiety and rank among the most common health concerns in human medicine. Millions of people become affected every year, and many of them do not respond to treatments. Anxiety disorders are heritable, but genetically complex. As a result, traditional gene mapping methods in the human population with prominent locus and allelic heterogeneity have not succeeded. Similarly, rodents have provided some insights into the circuitry of anxiety, but naturally occurring versions do not exist and gene deletion studies have not provided adequate models. To break through and identify new anxiety genes, I propose a novel and unique approach that resorts to man s best friend, dog. Taking advantage of the exaggerated genetic homogeneity characteristic of purebred dogs, recent genomics tools and the existence of naturally occurring heritable behaviour disorders in dogs can remedy the current lack of a suitable animal model of human psychiatric disorders. I propose to collect and perform a genome-wide association study in four breed-specific anxiety traits in dogs representing the three major forms of human anxiety: compulsive pacing and tail-chasing, noise phobia, and shyness corresponding to human OCD, panic disorder and social phobia, respectively. Canine anxiety disorders respond to human medications and other phenomenological studies suggest a share biological mechanism in both species. The proposed research has the potential to discover new genetic risk factors, which eventually will shed light on the biological basis of common neuropsychiatric disorders in both dog and human, provide insight into etiological mechanisms, enable identification of individuals at high-risk for adverse health outcomes, and facilitate development of tailored treatments.

1 381 807 €

Start date: 2010-10-01, End date: 2015-09-30

Memories can be rendered rewritable through a phenomenon called reconsolidation. The all-limiting step in this memory re-evaluation process is its initiation; the retrieval-dependent destabilization of the memory. However, the understanding of how a stable memory can be switched into a vulnerable but modifiable state is mostly in its infancy. Therefore, I aim to investigate the neural circuit mechanisms underlying retrieval-induced memory destabilization in the tractable fruit fly brain. A prerequisite to investigate the neural mechanisms involved in destabilizing a memory is to know where the learned information is stored and to have access to the associated network. Olfactory memories in flies are stored in the mushroom body as changes between odor coding principle cells and valence coding output neurons. The cell specific genetic access to the 2500 neurons of each mushroom body allows to manipulate and monitor the activity of all components of the network in behaving animals. Recently I established a paradigm that allows to study the mechanisms underlying memory reconsolidation in this numerically simple brain structure. First results indicate that I have identified specific neurons which are crucial for destabilizing reward memory. Starting from these findings I will study the neural circuit mechanisms involved in memory destabilization. I aim to generate an understanding of 1) the neural circuits underlying memory destabilization 2) how restrictive conditions gate reconsolidation 3) the role of targeted protein degradation in the destabilization of memory The work will establish the first mechanistic insight into how memories are destabilized, how a destabilized memory is represented in the brain and how boundary conditions prevent the initiation of memory reconsolidation.

1 500 000 €

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

The aim of this project is to understand the dynamics of protein-DNA interactomes underlying circadian oscillators in mammals, and how these shape circadian transcriptional output programs. Specifically our goal is to solve a fundamental issue in circadian biology: the phase specificity problem underlying circadian gene expression. We have taken a challenging and original multi-disciplinary approach in which molecular biology experiments will be tightly interlinked with computational analyses and biophysical modeling. The approach will generate time resolved protein-DNA interactomes in mouse liver for several key circadian repressors at unprecedented resolution. These experiments will be complemented with chromosome conformation capture (3C) experiments to monitor how looping interactions and 3D genome structure rearrange during the circadian cycle, which will inform on how circadian transcription networks use long-range gene regulatory mechanisms. Novel computational algorithms based on biophysical principles will be developed and implemented to optimally analyze interactome and 3C datasets. For the latter, statistical models from polymer physics will be used to reconstruct the chromatin networks and interaction maps from the 3C data. At the detailed level of individual cells, we will investigate transcription bursts, and how those are involved in the control of circadian gene expression. In particular we will exploit high temporal resolution bioluminescence reporters using a biophysical model of transcription coupled with a Hidden Markov Model (HMM). Through our innovative approach, we expect that the data generated and state-of-the-art analyses performed will lead novel insight into the role and mechanics of circadian transcription in controlling circadian outputs in mammals.

1 500 000 €

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