ERC FUNDED PROJECTS

I propose to pursue two emerging Force Microscopy techniques that allow measuring structural properties below the surface of the specimen. Whereas Force Microscopy (most commonly known under the name AFM) is usually limited to measuring the surface topography and surface properties of a specimen, I will demonstrate that Force Microscopy can achieve true 3D images of the structure of the cell nucleus. In Ultrasound Force Microscopy, an ultrasound wave is launched from below towards the surface of the specimen. After the sound waves interact with structures beneath the surface of the specimen, the local variations in the amplitude and phase shift of the ultrasonic surface motion is collected by the Force Microscopy tip. Previously, measured 2D maps of the surface response have shown that the surface response is sensitive to structures below the surface. In this project I will employ miniature AFM cantilevers and nanotube tips that I have already developed in my lab. This will allow me to quickly acquire many such 2D maps at a much wider range of ultrasound frequencies and from these 2D maps calculate the full 3D structure below the surface. I expect this technique to have a resolving power better than 10 nm in three dimensions as far as 2 microns below the surface. In parallel I will introduce a major improvement to a technique based on Nuclear Magnetic Resonance (NMR). Magnetic Resonance Force Microscopy measures the interaction of a rotating nuclear spin in the field gradient of a magnetic Force Microscopy tip. However, these forces are so small that they pose an enormous challenge. Miniature cantilevers and nanotube tips, in combination with additional innovations in the detection of the cantilever motion, can overcome this problem. I expect to be able to measure the combined signal of 100 proton spins or fewer, which will allow me to measure proton densities with a resolution of 5 nm, but possibly even with atomic resolution.

1 794 960 €

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

Chromosomal DNA is continuously subjected to exogenous and endogenous damaging insults. In the presence of DNA damage cells activate a multi-faceted checkpoint response that delays cell cycle progression and promotes DNA repair. Failures in this response lead to genomic instability, the main feature of cancer cells. Several cancer-prone human syndromes including the Ataxia teleangiectasia (A-T), the A-T Like Disorder (ATLD) and the Seckel Syndrome reflect defects in the specific genes of the DNA damage response such as ATM, MRE11 and ATR. DNA damage response pathways are poorly understood at biochemical level in vertebrate organisms. We have established a cell-free system based on Xenopus laevis egg extract to study molecular events underlying DNA damage response. This is the first in vitro system that recapitulates different aspects of the DNA damage response in vertebrates. Using this system we propose to study the biochemistry of the ATM, ATR and the Mre11 complex dependent DNA damage response. In particular we will: 1) Dissect the signal transduction pathway that senses DNA damage and promotes cell cycle arrest and DNA damage repair; 2) Analyze at molecular level the role of ATM, ATR, Mre11 in chromosomal DNA replication and mitosis during normal and stressful conditions; 3) Identify substrates of the ATM and ATR dependent DNA damage response using an innovative screening procedure.

1 000 000 €

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

In a changing world, one hallmark feature of human behaviour is the ability to learn about the statistics of the environment and use this prior information for action selection. Knowing about a forthcoming event allows for adjusting our actions pre-emptively, which can optimize survival. This proposal studies how the human brain learns about the uncertainty in the environment, and how this leads to flexible and efficient action selection. I hypothesise that the accumulation of evidence for future movements through learning reflects a fundamental organisational principle for action control. This explains widely distributed perceptual-, learning-, decision-, and movement-related signals in the human brain. However, little is known about the concerted interplay between brain regions in terms of effective connectivity which is required for flexible behaviour. My proposal seeks to shed light on this unresolved issue. To this end, I will use i) a multi-disciplinary neuroimaging approach, together with model-based analyses and Bayesian model comparison, adapted to human reaching behaviour as occurring in daily life; and ii) two novel approaches for testing effective connectivity: dynamic causal modelling (DCM) and concurrent transcranial magnetic stimulation-functional magnetic resonance imaging. My prediction is that action selection relies on effective connectivity changes, which are a function of the prior information that the brain has to learn about. If true, this will provide novel insight into the human ability to select actions, based on learning about the uncertainty which is inherent in contextual information. This is relevant for understanding action selection during development and ageing, and for pathologies of action such as Parkinson s disease or stroke.

1 341 805 €

Start date: 2011-06-01, End date: 2016-05-31

In the last ten years there has been a surge of interest in non-modal analysis applied to canonical problems in fundamental fluid mechanics. Even in simple flows, the stability behaviour predicted by non-modal analysis can be completely different from and far more accurate than that predicted by conventional eigenvalue analysis. As well as being more accurate, the tools of non-modal analysis, such as Lagrangian optimization, are very versatile. Furthermore, the outputs, such as receptivity and sensitivity maps of a flow, provide powerful insight for engineers. They describe where a flow is most receptive to forcing or where the flow is most sensitive to modification. The application of non-modal analysis to canonical problems has set the scene for step changes in engineering practice in fluid mechanics and thermoacoustics. The technical objectives of this proposal are to apply non-modal analysis to high Reynolds number flows, reacting flows and thermoacoustic systems, to compare theoretical predictions with experimental measurements and to embed these techniques within an industrial design tool that has already been developed by the group. This research group s vision is that future generations of engineering CFD tools will contain modules that can perform non-modal analysis. The generalized approach proposed here, combined with challenging scientific and engineering examples that are backed up by experimental evidence, will make this possible and demonstrate it to a wider engineering community.

1 301 196 €

Start date: 2010-12-01, End date: 2016-06-30

Within a 12 month period, 20% of adults will meet criteria for one or more clinical anxiety disorders (ADs). These disorders are hugely disruptive, placing an emotional burden on individuals and their families. While both cognitive behavioural therapy and pharmacological treatment are widely viewed as effective strategies for managing ADs, systematic review of the literature reveals that only 30–45% of patients demonstrate a marked response to treatment (anxiety levels being reduced into the nonaffected range). In addition, a significant proportion of initial responders relapse after treatment is discontinued. There is hence a real and marked need to improve upon current approaches to AD treatment. One possible avenue for improving response rates is through optimizing initial treatment selection. Specifically, it is possible that certain individuals might respond better to cognitive interventions while others might respond better to pharmacological treatment. Recently it has been suggested that there may be two or more distinct biological pathways disrupted in anxiety. If this is the case, then specification of these pathways may be an important step in predicting which individuals are likely to respond to which treatment. Few studies have focused upon this issue and, in particular, upon identifying neural markers that might predict response to cognitive (as opposed to pharmacological) intervention. The proposed research aims to address this. Specifically, it tests the hypothesis that there are at least two mechanisms disrupted in ADs, one entailing amygdala hyper-responsivity to cues that signal threat, the other impoverished recruitment of frontal regions that support cognitive and emotional regulation. Two series of functional magnetic resonance imaging experiments will be conducted. These will investigate differences in amygdala and frontal function during (a) attentional processing and (b) fear conditioning. Initial clinical experiments will investigate whether Generalised Anxiety Disorder and Specific Phobia involve differing degrees of disruption to frontal versus amygdala function during these tasks. This work will feed into training studies, the goal being to characterize AD patient subgroups that benefit from cognitive training.

1 708 407 €

Start date: 2011-04-01, End date: 2016-08-31

It has long been understood that genes contribute to phenotypes that are then the basis of selection. However, the nature and process of this relationship remains largely theoretical, and the relative contribution of change in gene expression and coding sequence to phenotypic diversification is unclear. The aim of this proposal is to fuse information about sexually dimorphic phenotypes, the mating systems and sexually antagonistic selective agents that shape sexual dimorphism, and the sex-biased gene expression patterns that encode sexual dimorphisms, in order to create a cohesive integrated understanding of the relationship between evolution, the genome, and the animal form. The primary approach of this project is to harnesses emergent DNA sequencing technologies in order to measure evolutionary change in gene expression and coding sequence in response to different sex-specific selection regimes in a clade of birds with divergent mating systems. Sex-specific selection pressures arise in large part as a consequence of mating system, however males and females share nearly identical genomes, especially in the vertebrates where the sex chromosomes house very small proportions of the overall transcriptome. This single shared genome creates sex-specific phenotypes via different gene expression levels in females and males, and these sex-biased genes connect sexual dimorphisms, and the sexually antagonistic selection pressures that shape them, with the regions of the genome that encode them. The Galloanserae (fowl and waterfowl) will be used to in the proposed project, as this clade combines the necessary requirements of both variation in mating systems and a well-conserved reference genome (chicken). The study species selected from within the Galloanserae for the proposal exhibit a range of sexual dimorphism and sperm competition, and this will be exploited with next generation (454 and Illumina) genomic and transcriptomic data to study the gene expression patterns that underlie sexual dimorphisms, and the evolutionary pressures acting on them. This work will be complemented by the development of mathematical models of sex-specific evolution that will be tested against the gene expression and gene sequence data in order to understand the mechanisms by which sex-specific selection regimes, arising largely from mating systems, shape the phenotype via the genome.

1 350 804 €

Start date: 2011-01-01, End date: 2016-07-31

Epidemiology and public health planning will increasingly rely on the analysis of genetic sequence data. The recent swine-derived influenza A/H1N1 pandemic may represent a tipping point in this trend, as it is arguably the first time when multiple strains of a human pathogen have been sequenced essentially in real time from the very beginning of its spread. However, the full potential of genetic information cannot be fully exploited to infer the spread of epidemics due to the lack of statistical methodologies capable of reconstructing transmission routes from genetic data structured both in time and space. To address this urgent need, we propose to develop a methodological framework for the reconstruction of the spatiotemporal dynamics of disease outbreaks and epidemics based on genetic sequence data. Rather than reconstructing most recent common ancestors as in phylogenetics, we will directly infer the most likely ancestries among the sampled isolates. This represents an entirely novel paradigm and allows for the development of statistically coherent and powerful inference software within a Bayesian framework. The methodological framework will be developed in parallel with the analysis of real genetic/genomic data from important human pathogens. We will in particular focus on the 2009 A/H1N1 pandemic influenza, methicilin-resistant Staphylococcus aureus clones (MRSAs), Batrachochytrium dendrobatidis, a fungus currently devastating amphibian populations worldwide. The tools we are proposing to develop are likely to impact radically on the field of infectious disease epidemiology and affect the way infectious emerging pathogens are monitored by biologists and public health professionals.

1 483 080 €

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

This ERC-StG proposal, BIOMOF, outlines a dual strategy for the growth and processing of porous metal-organic framework (MOF) materials, inspired by the interfacial interactions that characterise highly controlled biomineralisation processes. The aim is to prepare MOF (bio)-composite materials of hierarchical structure and multi-modal functionality to address key societal challenges in healthcare, catalysis and energy. In order for MOFs to reach their full potential, a transformative approach to their growth, and in particular their processability, is required since the insoluble macroscopic micron-sized crystals resulting from conventional syntheses are unsuitable for many applications. The BIOMOF project defines chemically flexible routes to MOFs under mild conditions, where the added value with respect to wide-ranging experimental procedures for the growth and processing of crystalline controllably nanoscale MOF materials with tunable structure and functionality that display significant porosity for wide-ranging applications is extremely high. Theme 1 exploits protein vesicles and abundant biopolymer matrices for the confined growth of soluble nanoscale MOFs for high-end biomedical applications such as cell imaging and targeted drug delivery, whereas theme 2 focuses on the cost-effective preparation of hierarchically porous MOF composites over several length scales, of relevance to bulk industrial applications such as sustainable catalysis, separations and gas-storage. This diverse yet complementary range of applications arising simply from the way the MOF is processed, coupled with the versatile structural and physical properties of MOFs themselves indicates strongly that the BIOMOF concept is a powerful convergent new approach to applied materials chemistry.

1 492 970 €

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

A fundamental feature of language is that it allows us to reproduce what others have said. It is traditionally assumed that there are two ways of doing this: direct discourse, where you preserve the original speech act verbatim, and indirect discourse, where you paraphrase it in your own words. In accordance with this dichotomy, linguists have posited a number of universal characteristics to distinguish the two modes. At the same time, we are seeing more and more examples that seem to fall somewhere in between. I reject the direct indirect distinction and replace it with a new paradigm of blended discourse. Combining insights from philosophy and linguistics, my framework has only one kind of speech reporting, in which a speaker always attempts to convey the content of the reported words from her own perspective, but can quote certain parts verbatim, thereby effectively switching to the reported perspective. To explain why some languages are shiftier than others, I hypothesize that a greater distance from face-to-face communication, with the possibility of extra- and paralinguistic perspective marking, necessitated the introduction of an artificial direct indirect separation. I test this hypothesis by investigating languages that are closely tied to direct communication: Dutch child language, as recent studies hint at a very late acquisition of the direct indirect distinction; Dutch Sign Language, which has a special role shift marker that bears a striking resemblance to the quotational shift of blended discourse; and Ancient Greek, where philologists have long been observing perspective shifts. In sum, my research combines a new philosophical insight on the nature of reported speech with formal semantic rigor and linguistic data from child language experiments, native signers, and Greek philology.

677 254 €

Start date: 2011-03-01, End date: 2016-08-31