ERC FUNDED PROJECTS

Malaria parasite infection in humans has been called “the strongest known force for evolutionary selection in the recent history of the human genome”, and I hypothesize that a similar statement may apply to the mosquito vector, which is the definitive host of the malaria parasite. We previously discovered efficient malaria-resistance mechanisms in natural populations of the African malaria vector, Anopheles gambiae. Aim 1 of the proposed project will implement a novel genetic mapping design to systematically survey the mosquito population for common and rare genetic variants of strong effect against the human malaria parasite, Plasmodium falciparum. A product of the mapping design will be living mosquito families carrying the resistance loci. Aim 2 will use the segregating families to functionally dissect the underlying molecular mechanisms controlled by the loci, including determination of the pathogen specificity spectra of the host-defense traits. Aim 3 targets arbovirus transmission, where Anopheles mosquitoes transmit human malaria but not arboviruses such as Dengue and Chikungunya, even though the two mosquitoes bite the same people and are exposed to the same pathogens, often in malaria-arbovirus co-infections. We will use deep-sequencing to detect processing of the arbovirus dsRNA intermediates of replication produced by the RNAi pathway of the mosquitoes. The results will reveal important new information about differences in the efficiency and quality of the RNAi response between mosquitoes, which is likely to underlie at least part of the host specificity of arbovirus transmission. The 3 Aims will make significant contributions to understanding malaria and arbovirus transmission, major global public health problems, will aid the development of a next generation of vector surveillance and control tools, and will produce a definitive description of the major genetic factors influencing host-pathogen interactions in mosquito immunity.

2 307 800 €

Start date: 2013-03-01, End date: 2018-02-28

Tissue morphogenesis is a complex process that emerges from spatially controlled patterns of cell shape changes. Dedicated genetic programmes regulate cell behaviours, exemplified in animals by the specification of apical constriction in invaginating epithelial tissues, or the orientation of cell intercalation during tissue extension. This genetic control is constrained by physical properties of cells that dictate how they can modify their shape. A major challenge is to understand how biochemical pathways control subcellular mechanics in epithelia, such as how forces are produced by interactions between actin filaments and myosin motors, and how these forces are transmitted at cell junctions. The major objective of our project is to investigate the fundamental principles of epithelial mechanics and to understand how intercellular signals and mechanical coupling between cells coordinate individual behaviours at the tissue level. We will study early Drosophila embryogenesis and combine quantitative cell biological studies of cell dynamics, biophysical characterization of cell mechanics and genetic control of cell signalling to answer the following questions: i) how are forces generated, in particular what underlies deformation and stabilization of cell shape by actomyosin networks, and pulsatile contractility; ii) how are forces transmitted at junctions, what are the feedback interactions between tension generation and transmission; iii) how are individual cell mechanics orchestrated at the tissue level to yield collective tissue morphogenesis? We expect to encapsulate the information-based, cell biological and physical descriptions of morphogenesis in a single, coherent framework. The project should impact more broadly on morphogenesis in other organisms and shed light on the mechanisms underlying robustness and plasticity in epithelia.

2 473 313 €

Start date: 2013-05-01, End date: 2018-04-30

Separation/extraction of sources are wide concepts in information sciences, since sensors provide information mixing and an essential step consists in separating or extracting useful information from unuseful one, called noise. In this project, we consider three challenges. The first one is the multimodality. Indeed, with the multiplication of kinds of sensors, in many areas like biomedical signal processing, hyperspectral imaging, etc. there are many ways for recording the same physical phenomenon leading thus to multimodal data. Multimodality has been studied in the framework of human-computer interface or in data fusion, but never at the signal level. The objective is to provide a general framework for modeling classical multimodal properties, like complementarity, redundancy, equivalence, etc. as of function of source signals. The second challenge is nonlinearity. Indeed, there exist a few cases where the mixtures are essentially nonlinear, e.g. with chemical sensors. The main objective is to enlarge results on identifiability conditions for new classes of nonlinearities and priors on sources. The third challenge is the data size. For high-dimension data (e.g. EEG or MRI in brain imaging), separating all the sources is neither tractable nor relevant, since one would like to only extract the useful sources. Conversely, for a small number of sensors, especially smaller than the number of sources, it is again necessary to only focus on the useful signals. The main objective is to develop generic approaches able to only extract useful signals, based on simple reference signal, modeling weak properties of the useful signal. Finally, validation and relevant modeling must be based on actual signals and problems. In this project, theoretical results and algorithms will be developed in interaction with applications in biomedical engineering (brain-computer interface, EEG, fMRI), chemical engineering, audio-visual scene analysis and hyperspectral imaging.

2 499 390 €

Start date: 2013-03-01, End date: 2018-02-28

The goal of this project is to develop inexpensive, high-throughput technology to screen the thus far unexplored metabolic interactions between environmental and household chemicals and clinically relevant drugs. The main influential focus will be on human phase I metabolism (redox reactions) of common toxicants like agrochemicals and plasticizers. On the basis of their structural resemblance to pharmaceuticals and endogenous compounds, many of these chemicals are suspected to have critical effects on cytochrome P450 metabolism which is the main detoxification route of pharmaceuticals in man. However, with the current analytical instrumentation, screening of such large chemical pool would take several years, and new chemicals would be introduced faster than the old ones are screened. Thus, the main technological goal of this project is to develop novel, practically zero-cost analytical instruments that enable characterization of a compound’s metabolic profile at very high speed (<1 min/sample). This goal is achieved through miniaturization and high degree of integration of analytical instrumentation by microfabrication means, an approach often called lab(oratory)-on-a-chip. The microfabricated arrays are envisioned to incorporate all analytical key functions required (i.e., sample pretreatment, metabolic reaction, separation of the reaction products, detection) on a single chip. Thanks to the reduced dimensions, the amount of chemical waste and consumption of expensive reagents are significantly reduced. In this project, several different microfabrication techniques, from delicate cleanroom processes to extremely simple printing techniques, will be exploited to produce smart microfluidic designs and multifunctional surfaces. Towards the end of the project, more focus will be put on “printable microfluidics” which provides a truly low-cost approach for fabrication of highly customized microfluidic assays. Numerical modelling is also an integral part of the work.

1 499 668 €

Start date: 2013-05-01, End date: 2019-02-28