ERC FUNDED PROJECTS

"This proposal develops a unified, underpinning technology to create novel, complex and biomimetic 3D environments for the control of tissue growth. As director of Cambridge Centre for Medical Materials, I have recently been approached by medical colleagues to help to solve important problems in the separate therapeutic areas of breast cancer, cardiac disease and blood disorders. In each case, the solution lies in complex 3D engineered environments for cell culture. These colleagues make it clear that existing 3D scaffolds fail to provide the required complex orientational and spatial anisotropy, and are limited in their ability to impart appropriate biochemical and mechanical cues. I have a strong track record in this area. A particular success has been the use of a freeze drying technology to make collagen based porous implants for the cartilage-bone interface in the knee, which has now been commercialised. The novelty of this proposal lies in the broadening of the established scientific base of this technology to enable biomacromolecular structures with: (A) controlled and complex pore orientation to mimic many normal multi-oriented tissue structures (B) compositional and positional control to match varying local biochemical environments, (C) the attachment of novel peptides designed to control cell behaviour, and (D) mechanical control at both a local and macroscopic level to provide mechanical cues for cells. These will be complemented by the development of (E) robust characterisation methodologies for the structures created. These advances will then be employed in each of the medical areas above. This approach is highly interdisciplinary. Existing working relationships with experts in each medical field will guarantee expertise and licensed facilities in the required biological disciplines. Funds for this proposal would therefore establish a rich hub of mutually beneficial research and opportunities for cross-disciplinary sharing of expertise."

2 486 267 €

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

"Combustion is essential to the world’s energy generation and transport needs, and will remain so for the foreseeable future. Mitigating its impact on the climate and human health, by reducing its associated emissions, is thus a priority. One significant challenge for gas-turbine combustion is combustion instability, which is currently inhibiting reductions in NOx emissions (these damage human health via a deterioration in air quality). Combustion instability is caused by a two-way coupling between unsteady combustion and acoustic waves - the large pressure oscillations that result can cause substantial mechanical damage. Currently, the lack of fast, accurate modelling tools for combustion instability, and the lack of reliable ways of suppressing it are severely hindering reductions in NOx emissions. This proposal aims to make step improvements in both fast, accurate modelling of combustion instability, and in developing reliable active control strategies for its suppression. It will achieve this by coupling low order combustor models (these are fast, simplified models for simulating combustion instability) with advances in analytical modelling, CFD simulation, reduced order modelling and control theory tools. In particular: * important advances in accurately incorporating the effect of entropy waves (temperature variations resulting from unsteady combustion) and non-linear flame models will be made; * new active control strategies for achieving reliable suppression of combustion instability, including from within limit cycle oscillations, will be developed; * an open-source low order combustor modelling tool will be developed and widely disseminated, opening access to researchers worldwide and improving communications between the fields of thermoacoustics and control theory. Thus the proposal aims to use analytical and computational methods to contribute to achieving low NOx gas-turbine combustion, without the penalty of damaging combustion instability."

1 489 309 €

Start date: 2013-01-01, End date: 2017-12-31

"I propose a systematic study of the type of genetic variation enabling adaptation and factors that limit rates of adaptation in natural populations. New methods will be developed for analysing data from experimental evolution and population genomics. The methods will be applied to state of the art data from both fields. Adaptation is generated by natural selection sieving through heritable variation. Examples of adaptation are available from the fossil record and from extant populations. Genomic studies have supplied many instances of genomic regions exhibiting footprint of natural selection favouring new variants. Despite ample proof that adaptation happens, we know little about beneficial mutations– the raw stuff enabling adaptation. Is adaptation mediated by genetic variation pre-existing in the population, or by variation supplied de novo through mutations? We know even less about what factors limit rates of adaptation. Answers to these questions are crucial for Evolutionary Biology, but also for believable quantifications of the evolutionary potential of populations. Population genetic theory makes predictions and allows inference from the patterns of polymorphism within species and divergence between species. Yet models specifying the fitness effects of mutations are often missing. Fitness landscape models will be mobilized to fill this gap and develop methods for inferring the distribution of fitness effects and factors governing rates of adaptation. Insights into the processes underlying adaptation will thus be gained from experimental evolution and population genomics data. The applicability of insights gained from experimental evolution to comprehend adaptation in nature will be scrutinized. We will unite two very different approaches for studying adaptation. The project will boost our understanding of how selection shapes genomes and open the way for further quantitative tests of theories of adaptation."

1 159 857 €

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

"Ageing is the gradual and irreversible breakdown of living systems associated with the advancement of time, which leads to an increase in vulnerability and eventual mortality. Despite recent advances in ageing research, the intrinsic complexity of the ageing process has prevented a full understanding of this process, therefore, ageing remains a grand challenge in contemporary biology. In AGELESS, we will tackle this challenge by uncovering the molecular mechanisms of halted ageing in a unique model system, the bats. Bats are the longest-lived mammals relative to their body size, and defy the ‘rate-of-living’ theories as they use twice as much the energy as other species of considerable size, but live far longer. This suggests that bats have some underlying mechanisms that may explain their exceptional longevity. In AGELESS, we will identify the molecular mechanisms that enable mammals to achieve extraordinary longevity, using state-of-the-art comparative genomic methodologies focused on bats. We will identify, using population transcriptomics and telomere/mtDNA genomics, the molecular changes that occur in an ageing wild population of bats to uncover how bats ‘age’ so slowly compared with other mammals. In silico whole genome analyses, field based ageing transcriptomic data, mtDNA and telomeric studies will be integrated and analysed using a networks approach, to ascertain how these systems interact to halt ageing. For the first time, we will be able to utilize the diversity seen within nature to identify key molecular targets and regions that regulate and control ageing in mammals. AGELESS will provide a deeper understanding of the causal mechanisms of ageing, potentially uncovering the crucial molecular pathways that can be modified to halt, alleviate and perhaps even reverse this process in man."

1 499 768 €

Start date: 2013-01-01, End date: 2017-12-31