University of Oxford

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6,133 Projects, page 1 of 1,227
  • Funder: UKRI Project Code: 2604825
    Partners: University of Oxford

    NMR spectroscopy is one of the only techniques that can determine the structure and dynamics of a protein in the solution state. However, when NMR is applied to large proteins, the resulting spectra suffer from a lack of signal intensity and resolution. This resolution problem has reduced the number of proteins that can be studied effectively by NMR, meaning that important information on their dynamics is being missed. Techniques such as protein deuteration as well as TROSY and methyl-TROSY NMR pulse sequences have been developed to increase the resolution in the NMR spectra of large proteins. While these developments have proved successful, they have not been able to solve the problem. The purpose of this research project is to develop these techniques further to study even larger proteins. The current best technique, methyl-TROSY, works by labelling proteins with 13CH3 groups. Relaxation interference between different dipolar and chemical shift anisotropy (CSA) relaxation mechanisms within the 13CH3 group. This leads to each peak of the quartet in the NMR spectrum having a different linewidth and intensity, known as the TROSY effect. Phase cycling can then be used to plot only the sharpest, most intense peak in the spectrum, enhancing the resolution of the spectrum. Fluorine nuclei have a large asymmetric electron distribution around them, leading to a large CSA. Therefore, it is thought that 13CF3 nuclei will lead to greater relaxation interference enabling enhanced NMR signal intensity and resolution. James' research will focus on the modelling of NMR relaxation rates followed by expression 13CF3 labelled proteins to see if this labelling can improve the NMR spectrum resolution. Whilst previous attempts to measure the TROSY effect in 13CF3 labelled proteins have been unsuccessful, these have been in shorter peptide chains. In mathematical models, it has been predicted that the TROSY effect will exist for larger proteins, but this needs to be proved experimentally. If the TROSY effect is observed for 13CF3 labelled proteins and the effect is stronger than for 13CH3 labelled proteins, a new protocol to study large proteins via NMR will have been developed, significantly increasing signal intensity and resolution. Another benefit of using a 13CF3 probe is that 19F nuclei are rarely found in biology, meaning that the protein of interest could be studied in-vivo without the spectrum suffering from background noise. This protocol could then be applied to a range of large biologically relevant proteins whose NMR spectra currently suffer from poor signal intensity and resolution. Thereby, important structures and dynamics of such proteins can be determined.

  • Funder: UKRI Project Code: 1813152
    Partners: University of Oxford

    Oncolytic viruses can replicate selectively within the tumour microenvironment and kill tumour cells, before spreading to infect adjacent cells. They can kill cells directly and can also encode potent biologicals for selective expression within tumours. However, viruses must be able to produce multiple copies of themselves under the challenging nutrient-restricted and acidic environment of solid tumours. This project will explore the interface between adenovirus activity and the limitation of amino acid supply within tumours, for example mediated by over-expression of the enzyme IDO which breaks down local tryptophan. It will also cover adenovirus activity under acidic conditions found to be in solid tumours. The work should go on to then monitor the resulting environment following virus infection and how this may affect long term changes in the tumour, for example the activity of immune cells, specifically T cells following oncolytic viral infection. The project will be at the interface of basic biology and therapeutic development and will make use of many techniques including molecular cloning as well as virology and cell culture techniques.

  • Funder: UKRI Project Code: EP/F059361/1
    Funder Contribution: 175,282 GBP
    Partners: University of Oxford

    Heart disease is the most common cause of illness and death in the western world. Each year it causes over 208,000 deaths in the UK including nearly half of all non-accidental deaths. Improving the treatment of heart disease is one of the main priorities of the NHS. The aim of this project is to work out the best way we can improve the diagnosis and treatment of heart disease by using state of the art computer models that have been built and personalised for each patient using information such as scans of their heart. These computer models can predict what goes on in the heart by using detailed mathematical formulae which copy they way the heart behaves all the way down to the millions of cells that make up the heart. This works is now possible because of the rapid increases in computer power which means they can quickly do the large number of calculations needed to make the models work. Also because we can do very detailed three-dimensional scans of the heart in patients at the same time as measure the electrical patterns and blood pressure inside the heart we are putting in very accurate information into the models and so can get accurate answers out. These answers have the potential of telling us which patients are going to be at risk of a heart attack or what's the best ways to treat patients whose hearts are not working well. By getting this research to work and implemented in hospital we should be able to substantially improve the treatment of patients with heart disease and even reduce the costs to the NHS.

  • Funder: UKRI Project Code: BB/H016813/1
    Funder Contribution: 384,541 GBP
    Partners: University of Oxford

    We are able to recognize and understand speech across many different speakers, voice pitches and listening conditions. However, the acoustic waveform of a sound (e.g. the vowel 'ae') will vary considerably depending on the individual speaker, and the 'ae' may be embedded in a cacophony of other, background sounds in our often noisy environments. Despite this, we have no difficulty recognizing an 'ae' as an 'ae', suggesting that the brain is capable of forming a representation of the vowel sound which is invariant to these 'nuisance' variables. For vowel sounds, the timbre, or vowel identity, is determined by the spectral envelope. Filtering by the mouth, lips and tongue results in energy peaks, or 'formants' in the spectrum, and it is the location of these formants which differentiates vowel sounds from one another. Thus, the fact that we are able to discriminate 'ae' from 'ih' irrespective of the gender, age or accent of a speaker suggests that we are able to form an invariant representation of the formant relations independently of the fundamental frequency, room reverberations, or spatial location in both quiet and noisy conditions. The aim of this research program is to discover where and how such invariant representations arise in the central auditory system and how these representations are maintained in noisy environments. Forming invariant representations is one of the greatest challenges for sensory systems, and understanding where and how such representations are read out is crucial for the design of any neuroprosthetic device. Our research uses ferrets as their hearing range spans a very similar range of frequencies to ours. Moreover, ferret vocalizations share many similarities with human vowel sounds. Ferrets rapidly learn to discriminate vowel sounds and we are able to record the activity of their nerve cells whilst they perform such listening tasks. By probing the circumstances under which the ferret is able to discriminate vowel sounds, and measuring the neural activity, we can look for where in the auditory brain invariant vowel representation might occur. The second part of this project involves reversibly silencing individual brain areas by cooling them. The principle of this technique is much the same was as using an ice pack to cool pain neurons in a bruised piece of skin. Small 'cryoloops' are implanted above auditory cortex in trained animals.This technique allows us to test whether particular brain areas are causally involved in vowel discrimination. The final part of this project investigates the role of visual information in auditory perception. It is well known that seeing a persons mouth movements while they talk to you enhances your ability to understand them - especially if you are listening in a very noisy room. When trying to pick out a quiet sound in a noisy background knowing when the sound is likely to occur also enhances your ability to correctly identify it. It has recently been shown that visual information is integrated into the very earliest auditory cortical areas. However, quite how this visual information shapes our auditory perception is unknown. The work in this proposal seeks to examine how visual information helps a trained animal to identify vowel sounds more accurately, whilst simultaneously examining how the visual stimulus influences the behaviour of neurons in auditory cortex. Inappropriate integration of auditory and visual information is postulated to underlie schizophrenic symptoms and understanding how informative visual stimuli influence auditory cortical activity will provide valuable insight into how sensory integration occurs in the healthy brain.Hearing impaired individuals most frequently suffer from an inability to effectively identify speech in noisy environments. Understanding how neurons are able to represent vowel identity robustly across a variety of listening conditions and noise environments will enhance hearing aid and cochlear implant design.

  • Funder: UKRI Project Code: MR/T002107/1
    Funder Contribution: 771,800 GBP
    Partners: University of Oxford

    Diabetes affects >425 million people worldwide and accounts for one death every 6 seconds. In the UK, ~3.7 million people currently have the disease (90% have type 2 diabetes) and a further 1 million are undiagnosed. Diabetes increases the risk of heart disease, stroke, kidney disease and blindness, and reduces life expectancy by up to 10 years. It also consumes about 10% of the UK's direct healthcare costs. If we are to ameliorate the severe socio-economic impact of diabetes, and to develop new and better therapies, it is essential to have a clearer understanding of the underlying molecular mechanisms involved. The overall aim of this proposal is to generate this knowledge and to identify new pathways and targets for therapeutic drug development. Type 2 diabetes is characterised by a chronically elevated level of blood sugar (chronic hyperglycaemia), which results from insufficient secretion of the hormone insulin from the beta-cells of the pancreas. The hyperglycaemia fuels diabetes progression by further reducing beta-cell function and mass. We aim to understand how chronic hyperglycaemia impairs beta-cell function and mass, so speeding beta-cell decline. Such fundamental knowledge is currently lacking but has the potential to transform therapy, facilitating the development of novel drugs targeted at improving insulin secretion and preserving beta-cell function. It is well established that glucose (sugar) must be metabolised in order to stimulate insulin secretion. Work from several laboratories, including our own, has previously shown that this is because a glucose metabolite known as ATP, regulates the activity of a tiny pore in the beta-cell membrane known as the KATP channel. When this pore is open, insulin is not released. An acute rise in blood glucose leads to ATP generation, KATP channel closure and insulin release. However, studies suggest that chronic elevation of blood glucose adversely affects beta-cell metabolism, leading to a failure of ATP generation and KATP channel closure. Consequently, insulin secretion is prevented. Our recent studies indicate this is because hyperglycaemia causes marked changes in the expression of metabolic genes. Why this happens is unknown. We now aim to understand precisely how chronic hyperglycaemia, like that which occurs in diabetes, leads to changes in beta-cell metabolism, gene and protein expression, and ATP production. Understanding how hyperglycaemia impairs beta-cell function and mass in diabetes will provide novel insights into how its deleterious effects can be prevented and/or reversed, and identification of the pathways involved should help pinpoint specific targets for therapeutic drug development.