ERC FUNDED PROJECTS

The world has a significant medical challenge in repairing injured or diseased joints. Joint degeneration and its related pain is a major socio-economic burden that will increase over the next decade and is currently addressed by implanting a metal prosthesis. For the long term, the ideal solution to joint injury is to successfully regenerate rather than replace the damaged cartilage with synthetic implants. Recent advances in key technologies are now bringing this “holy grail” within reach; regenerative approaches, based on cell therapy, are already clinically available albeit only for smaller focal cartilage defects. One of these key technologies is three-dimensional (3D) bio-printing, which provides a greatly controlled placement and organization of living constructs through the layer-by-layer deposition of materials and cells. These tissue constructs can be applied as tissue models for research and screening. However, the lack of biomechanical properties of these tissue constructs has hampered their application to the regeneration of damaged, degenerated or diseased tissue. Having established a cartilage-focussed research laboratory in the University Medical Center Utrecht, I have addressed this biomechanical limitation of hydrogels through the use of hydrogel composites. Specifically, I have pioneered a 3D bio-printing technology that combines accurately printed small diameter thermoplast filaments with cell invasive hydrogels to form strong fibre-reinforced constructs. This, in combination with bioreactor technology, is the key to the generation of larger, complex tissue constructs with cartilage-like biomechanical resilience. With 3D-JOINT I will use my in-depth bio-printing and bioreactor knowledge and experience to develop a multi-phasic 3D-printed biological replacement of the joint.

1 998 871 €

Start date: 2015-07-01, End date: 2020-06-30

Currently fuels, plastics, and drugs are predominantly manufactured from oil. A transition towards renewable resources critically depends on new catalysts, for instance to convert small molecules (such as solar or biomass derived hydrogen, carbon monoxide, water and carbon dioxide) into more complex ones (such as oxygenates, containing oxygen atoms in their structure). Catalyst development now often depends on trial and error rather than rational design, as the heterogeneity of these composite systems hampers detailed understanding of the role of each of the components. I propose 3D model catalysts as a novel enabling tool to overcome this problem. Their well-defined nature allows unprecedented precision in the variation of structural parameters (morphology, spatial distribution) of the individual components, while at the same time they mimic real catalysts closely enough to allow testing under industrially relevant conditions. Using this approach I will address fundamental questions, such as: * What are the mechanisms (structural, electronic, chemical) by which non-metal promoters influence the functionality of copper-based catalysts? * Which nanoalloys can be formed, how does their composition influence the surface active sites and catalytic functionality under reaction conditions? * Which size and interface effects occur, and how can we use them to tune the actitivity and selectivity towards desired products? Our 3D model catalysts will be assembled from ordered mesoporous silica and carbon support materials and Cu-based promoted and bimetallic nanoparticles. The combination with high resolution characterization and testing under realistic conditions allows detailed insight into the role of the different components; critical for the rational design of novel catalysts for a future more sustainable production of chemicals and fuels from renewable resources.

1 999 625 €

Start date: 2015-09-01, End date: 2020-08-31

Serotonin (5-HT) is a central neuromodulator and a major target of therapeutic psychoactive drugs, but relatively little is known about how it modulates information processing in neural circuits. The theory of predictive coding postulates that the brain combines raw bottom-up sensory information with top-down information from internal models to make perceptual inferences about the world. We hypothesize, based on preliminary data and prior literature, that a role of 5-HT in this process is to report prediction errors and promote the suppression and weakening of erroneous internal models. We propose that it does this by inhibiting top-down relative to bottom-up cortical information flow. To test this hypothesis, we propose a set of experiments in mice performing olfactory perceptual tasks. Our specific aims are: (1) We will test whether 5-HT neurons encode sensory prediction errors. (2) We will test their causal role in using predictive cues to guide perceptual decisions. (3) We will characterize how 5-HT influences the encoding of sensory information by neuronal populations in the olfactory cortex and identify the underlying circuitry. (4) Finally, we will map the effects of 5-HT across the whole brain and use this information to target further causal manipulations to specific 5-HT projections. We accomplish these aims using state-of-the-art optogenetic, electrophysiological and imaging techniques (including 9.4T small-animal functional magnetic resonance imaging) as well as psychophysical tasks amenable to quantitative analysis and computational theory. Together, these experiments will tackle multiple facets of an important general computational question, bringing to bear an array of cutting-edge technologies to address with unprecedented mechanistic detail how 5-HT impacts neural coding and perceptual decision-making.

2 486 074 €

Start date: 2016-01-01, End date: 2020-12-31

Cell volume regulation is crucial for any living cell because changes in volume determine the metabolic activity through e.g. changes in ionic strength, pH, macromolecular crowding and membrane tension. These physical chemical parameters influence interaction rates and affinities of biomolecules, folding rates, and fold stabilities in vivo. Understanding of the underlying volume regulatory mechanisms has immediate application in biotechnology and health, yet these factors are generally ignored in systems analyses of cellular functions. My team has uncovered a number of mechanisms and insights of cell volume regulation. The next step forward is to elucidate how the components of a cell volume regulatory circuit work together and control the physicochemical conditions of the cell. I propose construction of a synthetic cell in which an osmoregulatory transporter and mechanosensitive channel form a minimal volume regulatory network. My group has developed the technology to reconstitute membrane proteins into lipid vesicles (synthetic cells). One of the challenges is to incorporate into the vesicles an efficient pathway for ATP production and maintain energy homeostasis while the load on the system varies. We aim to control the transmembrane flux of osmolytes, which requires elucidation of the molecular mechanism of gating of the osmoregulatory transporter. We will focus on the glycine betaine ABC importer, which is one of the most complex transporters known to date with ten distinct protein domains, transiently interacting with each other. The proposed synthetic metabolic circuit constitutes a fascinating out-of-equilibrium system, allowing us to understand cell volume regulatory mechanisms in a context and at a level of complexity minimally needed for life. Analysis of this circuit will address many outstanding questions and eventually allow us to design more sophisticated vesicular systems with applications, for example as compartmentalized reaction networks.

2 247 231 €

Start date: 2015-07-01, End date: 2020-06-30