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Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

The aim of this ICASE PhD project is to investigate the role of adipose tissue in hair follicle growth and cycling as a basis for novel therapeutic interventions. The research is in partnership with Unilever R&D. Adipose tissue is a key constituent of human skin whose functions extend far beyond energy storage and thermoregulation. Several mutant mouse models with defects in adipocytes have elucidated some of these previously unknown roles. For example, a genetic mouse model lacking early B-cell factor 1(Ebf1) exhibited reduced intradermal adipocytes. Hair follicles in these mice failed to re-enter the anagen phase of the hair growth cycle and remained in the resting telogen stage (Hesslein 2009). This demonstrates the importance of pre-adipocytes in the promotion of telogen to anagen transition during the hair follicle cycle in mice, and has raised increasing interest in the role of the adipocyte-hair follicle communication in the regulation of hair growth. However, the adipocyte-hair follicle communication in human skin, and how it may be manipulated in a clinically or cosmetically desirable manner, is entirely unknown. There is increasing insight into the importance of this bidirectional communication for hair follicle cycling and (murine) wave pattern formation, as well as adipocyte differentiation and function (Plikus 2008, Schmidt 2012, Donati 2014). As such, improved characterisation of this communication could provide novel targets and strategies for therapeutic intervention. The mechanism behind the potential interaction of adipocyte signals with the hair follicle is not well understood but platelet derived growth factor (PDGF) signalling may play a significant role. PDGFA mRNA is significantly elevated in adipocyte precursor cells (Festa 2011) and mice lacking PDGFA show a delay in hair follicle stem cell activation (Tomita 2006). There is strong possibility that understanding and influencing signalling of intradermal adipocytes in the hair follicle microenvironment could impact the hair follicle with potential benefits such as promoting hair growth & prolonging the follicle growing phase. This study will span the Centre for Dermatology Research and Unilever R&D facility, Colworth. Extensive training will be provided in histology, immunohistochemistry and state-of-the-art double-immunostaining and image analysis techniques. Carina will also become familiar with light, fluorescent and confocal microscopy, qRT-PCR and gene silencing in intact human skin/hair follicles.

Solar energy is a sustainable resource exceeding predicted human energy demands by >3 orders of magnitude. If this diffuse solar energy can be concentrated and stored efficiently, then it has the capacity to provide for future human energy needs. The process of oxidative photosynthesis, namely the reduction of CO2 utilizing light and water by photoautotrophs, stores solar energy in reduced carbon compounds, which are useful fuels for society. Although oxidative photosynthesis evolved some 3.5 billion years ago, it remains inefficient at converting solar energy into chemical energy and, ultimately, biomass. Commercial photovoltaics in concert with electrolyzers split water to produce hydrogen at an efficiency of approximately 10%. Photosynthetic yields for plants in optimal conditions typically do not exceed 1%, and higher-yielding microalgae species are estimated to have 3% efficiency. Under most conditions, the biological transformation of light to stored chemical energy is not limited by light but by the rate of carbon reduction. The goal of this project is to engineer pathways for diverting photosynthetic energy from linear electron flow (LEF) to alternative sinks, thereby providing alternate routes for "excess" photosynthetic capacity when carbon fixation is saturated. Our strategy is to engineer an intercellular, plug-and-play platform (PNP) that allows us to move electrons and/or reduced chemicals from modified photosynthetic source cells to independently engineered fuel-production modules that bypass the inherently inefficient carbon-fixing catalyst RuBisCO. The realization of this goal will require radical manipulation of the fundamental biology of photosynthesis and development of novel synthetic biological, chemical, and analytical techniques.

Integrating single-cell transcriptomics and single-cell open chromatin data is a promising approach for disentangling cell types in a tissue while at the same time identifying key regulators underlying the specificity of each cell type. In order to make the most of such data, computational methods need to be developed that can integrate the two data types while decomposing both into cell types. In addition to identifying cell types it is also of interest to characterise the observed transcriptomic profiles in terms of large gene expression events such as the set of signalling pathways that are "on", the cell cycle state, and so on. The main goal of this project is computational method development addressing these questions. Recent studies have focussed on the microbial surface colonisation of these floating plastics indicating a high diverse community that differs enormously from the indigenous free-living marine community. These studies have also raised concerns on the fact that polymers, mainly in the form of microplastics, accumulate persistent organic pollutants and harbour harmful microbial species that can easily enter the food chain. Biodegradation of plastics in aquatic systems has been suggested by pits visualised by scanning electron microscopy. Plastic degradation has been reported for land waste plastics and is mainly carried out by fungi and bacteria. Unfortunately, very little is known on this process in marine systems. We will take a truly interdisciplinary approach to studying this using model polymer chemistry to create synthetic probes to determine the fate of the plastics and their interactions with microbial communities.

A series of biochemical events in cells known as signalling pathways play important roles in the regulation of normal physiological functions in all organisms. Examples of processes regulated by signalling pathways include the movement of bacteria towards a food source, budding of yeast, the response of plants to pathogens, and sugar metabolism in mammals. Therefore, the ability to monitor signalling pathways is important for understanding the biochemistry of essentially all living beings. The activity of these pathways is driven by a group of enzymes known as kinases which attach a type of chemical group, known as phosphate, to other proteins. There are more than 500 different protein kinases in humans and their relationship with each other and with other proteins is very complex. The activity of protein kinases can be detected in cells by analysing phosphates attached to other proteins. Modern methods based on a technique named mass spectrometry (MS) can now detect several thousands of such phosphorylation events. This technique is known as phosphoproteomics and the information provided by this method has the potential to reveal an immense new set of knowledge on how kinases are regulated in cells and how these are altered in disease. To maximize the information that can be derived from phosphoproteomics data, we recently developed a computational approach named Kinase Substrate Enrichment Analysis (KSEA), which links the phosphorylation sites identified by MS to the kinases acting upstream. KSEA algorithms then calculate the enrichment of substrates belonging to given kinases in the dataset. We found that values given by KSEA can be used to measure the activities of all kinases for which substrates are known. However, only about 10% of phosphorylation sites detectable by MS are annotated with the kinases acting upstream. Therefore, only a small fraction of the data obtained in a phosphoproteomic experiment are actually informative for understanding cell biochemistry. To address this issue, in this application we aim to assemble a database of phosphorylation sites annotated with the signalling pathway they belong to. Our hypothesis is that, when used together with KSEA, this database of phosphorylation sites will have the ability to measure signalling with unprecedented depth, thus significantly advancing our understanding of the fundamental properties of biological systems. We will initially focus on signalling pathways operating in human cells but the same approaches could be used to advance the understanding of signalling in other organisms. The database of signalling pathways will be built by classifying phosphorylation events on proteins based on whether these are increased or decreased by drugs that target kinases and by their patterns of modulation by agents known to activate protein kinases. These experiments are now possible because a large array of kinase inhibitors have recently been developed, to be used as drugs to treat diseases such as cancer and inflammation, and because of the recent development of techniques for quantitative phosophoproteomics. We expect to treat cells with at least 100 kinase inhibitors, targeting a minimum of 50 different kinases. By performing this classification systematically and in different cells lines, we will identify relationships between different kinases and will discriminate signalling events that are core for several cell types from those that are cell type specific. Systematic classification of phosphorylation sites will also identify markers of signalling that can be used to measure how these events are remodelled in cells that have changed their characteristics due to disease or because they have become insensitive to therapy. We also hypothesise that a classification of phosphorylation sites based on their patterns of modulation by kinase inhibitors will be useful in constructing models to predict the best kinase inhibitors that can modify a given phenotype.

Nervous system development is one of the most complex biological processes in nature. Understanding the molecular mechanism and the genes involved in the differentiation of stem cells into neurons is crucial in deciphering the development of the nervous system. A model widely used to study neuronal stem cell biology is Drosophila melanogaster, which will be adopted in this project, as it resembles aspects of the mammalian system (1). Thanks to the easy culturing techniques and vast genetic toolkit it offers fertile grounds to gain deeper understanding of the genetic regulators and molecular mechanisms behind neuronal development. The transcription factor Lola is one of several proteins that maintain the differentiated state of neurons. In a study by Southall et al., lola mutants lead to the regression of neurons into a stem-cell like state and the development of tumours (2). These tumours develop due to the tightly regulated programming of the cells being perturbed. Therefore, it is crucial to identify the mechanism maintaining the cell fate and what other proteins are involved in this process. To investigate this, a yeast-two-hybrid screen was carried out to detect protein-protein interactions with Lola. Two of the high confidence hits from this screen were proteins CG7518 and Cap-G which will be the focus of this project (personal communication, Southall). In this study we will exploit the genetic toolkit available in Drosophila to induce overexpression and RNAi knockdown of said proteins and investigate phenotypes in neurons at larval and adult stages. Immunostaining techniques are used on larval and adult brains to image the proteins of interest using confocal microscopy. CRISPR/Cas9 system will be used to create a cell-type specific loss-of-function mutants for both our candidate interactors and observe potential phenotypes. The aim is to characterise CG7518 and its potential interactions with Lola, as its molecular function is still unknown. We hypothesise CG7518 to be a Lola regulator by inhibiting its function, either by retaining it in the cytoplasm, modifying its structure or targeting it for degradation. Preliminary data shows that CG7518 is a cytoplasmic protein ubiquitously expressed in the nervous system throughout all stages of development. This implies that it may have a broader biological role and experiments will focus on whether specific neuronal phenotypes can be observed. Any effects to Lola localisation will be investigated as it is a nuclear protein whilst our candidate is cytoplasmic. Cap-G is a subunit of the condensin I protein complex and is necessary for condensation, assembly and segregation of chromosomes (3). Its interaction with Lola sparks an interest, as Lola is activated post-mitotically, whilst Cap-G is mainly expressed in dividing cells. This implies that Cap-G may have a temporal-regulated role in the early stages of differentiation, interacting with Lola. To investigate whether Cap-G has a post-mitotic function and a potential role in cell differentiation, several methods are used. Quantitative PCR can be carried out on adult brains to quantify the Cap-G expression in post-mitotic neurons, as no cell division is present in adult brains. Moreover, DamID will reveal the DNA and chromatin binding-sites of Cap-G, offering an insight on its function. The understanding of these Lola interactors will be an addition to the molecular puzzle regulating the maintenance of neuronal differentiation. The implications of this study are relevant not only for our understanding of developmental biology but also to decifer factors involved in tumour initiation and regenerative medicine. Neurological diseases such as Parkinson's and multiple sclerosis would highly benefit from the advancement of knowledge in this field to lead therapeutic progress (4)

This project uses a new way of working, by combining modelling and experimental approaches together in a way that both informs each arm of the project, but more importantly brings them together allowing us to better understand the complex interactions of the mucosal immune response to the bacterial pathogen Campylobacter jejuni. C. jejuni is the most common cause of foodborne bacterial gastroenteritis worldwide, with the overwhelming majority of cases associated with chicken. Despite the fact that around 70% of UK retail chicken is contaminated with Campylobacter our understanding of its infection biology in the broiler chicken in surprisingly limited. Our recent work has begun to elucidate the innate immune response to infection of the chicken and combining data from these studies with a modelling approach through Bayesian structural equation modelling has allowed us to identify immunological differences between chicken breeds that underlie differences in infection phenotype. This project will build upon previous work to model innate, adaptive and regulatory responses during C. jejuni infection to determine which are involved in long-term colonization of the chicken, those associated with clearance of infection and those with poor gut health. Using this combined approach gives us a unique insight as to what is important and how this could be utilized in controls such as vaccines or make improvements to chicken gut health thereby improving animal health and welfare and ultimately reduce the burden of Campylobacter associated with chicken production.

Phoma stem canker, caused by the fungal pathogen Leptosphaeria maculans, is a damaging disease on oilseed rape in the UK, causing annual yield losses > £100M despite use of fungicides costing £20M. With recent loss of the most effective fungicides (e.g. Punch C) through EU legislation and predicted global warming, potential yield losses will increase. Use of host resistance to control this disease is becoming ever more important. However, new sources of resistance are often rendered ineffective due to pathogen population changes. The aims of this project are to monitor the emergence of new virulent races of L. maculans and to develop new control strategies to increase durability of host resistance. To maintain effectiveness of cultivar resistance against L. maculans, this project will use molecular technology to investigate the differences between different regions in distribution of virulent races of L. maculans in populations assessed from spore samples and from crop plant samples. Results will be used to guide deployment of cultivars with suitable resistance for the region where the corresponding avirulent pathogen races are predominant. Resistance against L. maculans relies on major resistance (R) gene-mediated qualitative resistance and minor gene-mediated quantitative resistance. The fungus L. maculans has high evolutionary potential to overcome host resistance. Resistance can be rendered ineffective in 2-3 years due to L. maculans population changes from avirulent to virulent. This project will investigate the molecular events leading to virulent mutations in L. maculans by exploiting new genomic information about L. maculans. Modelling work shows that the range and severity of phoma stem canker will increase under predicted global warming. To investigate the effects of environmental factors (e.g. temperature) on operation of different R genes for resistance against L. maculans, severity of phoma stem canker on cultivars with different R genes will be assessed in field experiments in different regions (i.e. different environments) and in controlled environment experiments at different temperatures. Recent work showed that R gene-mediated resistance against L. maculans (an apoplastic pathogen) operates by recognition of pathogen effectors through receptor-like proteins (RLPs). The sequences of R genes stable at increased temperatures and the genome sequences of host Brassica napus and its related species B. rapa and B. oleracea will be used to identify candidate R genes coding for RLPs. New knowledge obtained from this project will be used to develop strategies to improve control of phoma stem canker by using effective cultivar resistance. Improved control of this disease will benefit growers by reducing yield losses. It will also address the challenge of food security. The environment will also benefit from reduced use of fungicides.

This project addresses the key challenges facing dairy goat milk production by using new genetic and genomic technologies to improve the quality of milk production and disease management. The main challenge is to breed healthy goats with resistance to bacterial infections leading to mastitis, and to identify sires with daughters that have lower susceptibility to mastitis and generate genomic predictions of merit for this trait. The wider goat industry in the UK and abroad will access genomic predictions of enhanced mastitis resistance via new molecular technology from the creatipon of a low density (LD), lower cost customised single nucleotide polymorphism (SNP) array for UK goats. This allows for the use of more cost-effective molecular technology to predict ('impute') the information that was previously generated by the more expensive, more comprehensive SNP array and enabling more animals to be genotyped. The project will ensure sustainable breeding objectives for dairy goats in the long-term, by including routine collection of mastitis records as indicators of health and longevity, thereby helping to translate previous TSB-funded research into practice. It is estimated that mastitis affects up to a third of all UK dairy goats during their reproductive life. Even thoughthis hasn't been formally quantified in the UK, we anticipate that YDG loses around £286K p.a. in lost productivity and additional replacement costs. Mastitis is termed a 'complex trait' in animal breeding terms, i.e. whereby many genes are involved in determining whether or not animals succumb to clinical (or subclinical) disease. For this reason, using well recorded goats, the overall aim of the project is to generate genetic (EBV) and genomic (GEBV) breeding values that will identify genetically more resistant animals to mastitis, irrespective of the causative organisms. Such approach is in line with the EU regulations, which are aiming to restrict the use of active compounds to control agricultural diseases, which increases the risk of pathogens developing resistance to current biological and chemical control measures. Breeding of animals with increased disease resistance and thus improved health will allow the animals to better realise their genetic potential for milk production. The use of EBVs and GEBVs will allow for accurate elimination of animals with high susceptibility to mastitis, thus acting as a measure of early identification of potential disease. This proposal is a collaborative project that will stimulate the production of high quality goat milk in the UK. This will be done through the exploitation of new genomic technology (a low-density (LD), single nucleotide polymorphism, (SNP) array that is tailored to UK goat breeds), to identify high genetic and genomic merit dairy goats for mastitis resistance, functional fitness, health, and longevity, whilst attaining high levels of milk production. This will result in a balanced breeding programme, which is necessary for sustainable intensification of goat milk production. The challenge is for the UK goat milk industry to become a leading international player in the supply of high genetic merit livestock for milk production, whilst building a reputation for the supply of animals of high disease resistance. The identification of sires with daughters with high mastitis resistance will greatly reduce losses due to veterinary costs and decreased milk supply. Breeding of goats with increased resistance for mastitis will become a unique selling point for the industrial partner. The routine inclusion of mastitis phenotyping for the goat selection index is likely to improve mastitis resistance, in a similar way to that which has recently occurred for fertility in the dairy cattle, initiated by the uptake of the new dairy fertility index.

Cell migration is important for normal development of animal embryos and tissue repair and regeneration in adults. It is controlled by environmental cues provided by diffusible factors and interactions of cells with the structural components of the three-dimensional extracellular matrix (ECM) through which they move. Two important and interacting classes of adhesion receptors in animal cells are the integrins and the syndecans. Integrins are a large family of heterodimeric molecules, the nature of the aB dimers determining their specificity for ECM ligands. Syndecans are a family of four heparan sulphate proteoglycans which bind growth factors and also act themselves as ECM-binding receptors. These two classes of molecules work together to control cell adhesion and its signalling consequences, and in particular integrins a5B1 and aVB3 and syndecan-4 are required for cell adhesion and migration on fibronectin-rich matrices via the formation and turnover of focal adhesions. Another recently discovered class of molecules known as the ADAMTS metalloproteinases (a disintegrin and metalloproteinase with thrombospondin-like motifs) also influence cell migration. The project will address the hypothesis that ADAMTS metalloproteinases regulate cell movement by affecting cell surface syndecan-4 presentation or function, leading to changes in integrin a5B1 and aVB3 trafficking and focal adhesion dynamics. This project will provide training in advanced cell and molecular techniques including immunolocalization, fluorescence activated cell sorting (FACS) and timelapse videomicroscopy to study the adhesion and migration of mouse embryo fibroblasts (MEFs) that are deficient in either integrins a5, B3, syndecan-4 or ADAMTS-1 or -15.