United States

DNA, the blueprint of life, is found within 46 chromosomes in every human cell; if stretched out end to end, it would measure two metres in length. In order for these 46 chromosomes to fit into the "control-room" of every cell, known as the nucleus, the DNA must be very tightly packaged. This is achieved by wrapping the DNA around the surface of special proteins, called histones, that are spaced regularly along the DNA like beads on a string. Each DNA-histone bead is known as a nucleosome and each nucleosome is able to pack very closely against its neighbours to form highly compact fibres called chromatin. Although chromatin fibers are very good at compacting DNA into small spaces, they are poor at allowing other proteins access to the DNA. Many normal processes in the cell involve proteins binding to DNA, such as when genes are decoded to make protein, when chromosomes are replicated prior to cell division, and when special repair proteins are called upon to fix sites of DNA damage. Consequently, complicated organisms like humans, with highly packaged DNA, have had to develop specialized machinery for opening chromatin at very specific regions of the chromosome. This machinery includes a large number of specialized proteins. One group of proteins, known as chromatin remodelling complexes (CRCs), help to expose DNA by using energy to slide or remove nucleosomes within chromatin. CRCs are protein machines, much larger than a single nucleosome, and made up of proteins responsible for recruitment to the correct chromosome region, binding to nucleosomes, or helping to generate the force required for nucleosome sliding or removal. Multiple different CRCs exist in human cells, each made up of similar proteins that can interact with chromatin in subtly different ways or target the complex to different regions of the chromosome. The recruitment of a CRC to the start of a gene is an important early step in the process of turning on, or activating, that gene. If the cell makes a mistake, failing to recruit CRCs to their correct sites or instead recruiting those complexes to the wrong set of genes, then a dangerous cascade can result in the loss of control of normal cell events such as cell division and death. This type of gene dysregulation takes place at an early stage in the development of every human cancer. Over the past decade, advances in DNA sequencing technology have allowed scientists to identify mistakes in the DNA code, known as DNA mutations, that are found in many types of human cancer. A surprising finding from these studies was that DNA mutations leading to the loss of protein components from one single CRC, known as the BAF complex, are present in as many as 20% of all human cancers. Further investigations showed that DNA mutations altering the BAF complex cause many normal target genes to be switched off whereas new and inappropriate genes often become active. Although the BAF complex is very often the target of mutations in cancer, surprisingly little is currently known about this important machine, with many questions still unaddressed. For example, how are the different proteins organized in the BAF complex? What roles do the different proteins play in the recruitment of the complex to the correct target genes? How does the BAF complex interact with nucleosomes? How does BAF use energy to bring about nucleosome sliding or eviction? The overarching goal of my future research will be to address these questions using a repertoire of cutting-edge structural biology techniques such as cryo-electron microscopy, protein cross-linking, X-ray crystallography and computational modelling, in order to provide a detailed description of the organization, recruitment and remodelling activity of this important human complex. Such findings will provide a framework for understanding the molecular basis of BAF complex dysregulation, with broad implications for the future treatment of many human cancers.

The recent recognition of the central role played by the microbiome in human health has lead to a paradigm shift in medicine, with ever-increasing awareness of how these host-specific communities of microorganisms can affect patient health. In the past decade, the gut microbiome has emerged as a contributor to disease processes throughout the body, but only recently has been shown to influence orthopaedic biomechanics. Early findings suggest that the microbiome may help answer questions in orthopaedic biomechanics that are not well addressed by current interventions and highlight the promise of the emerging field of "Musculoskeletal Microbiology". To date, analysis of gut-microbiome crosstalk has almost exclusively relied on the genomic or metagenomic analysis of samples collected from humans or animals. This is because no method exists to establish stable complex communities of gut commensal microorganisms in direct contact with intestinal epithelium and its overlying mucus layer in vitro. Although animal models have been used to analyse host-microbiome interactions and their contributions to pathophysiology, there are no in vitro systems available to verify these interactions in human cells cultured with a complex human microbiome. Thus, there is a great unmet need for experimental models that can sustain complex populations of human aerobic and anaerobic microbiota in contact with living human tissues to analyse dynamic and physiologically relevant human host-microbiome interactions. This project will bring together the Organ-on-a-Chip technology applied by Dr Verbruggen to develop a bone-chip model, with microbiome cultures and metabolomic data from an animal model developed by a founder of this new field of Musculoskeletal Microbiology, Prof Hernandez. With industrial support from the leading manufacturer of organ-chip technology, Emulate, and on-site expertise in 3D models of the microbiome, from Co-Investigator Dr Krishna Kumar, this project will build a proof-of-concept multi-organ chip system that links the gut microbiome with a bone-chip model. This chip model will provide a leap forward in drug discovery by providing a precision model to pick apart the important biological mechanisms, as well as providing a new technology to speed up drug testing while using less animals.

Schizophrenia is a mental disorder that involves symptoms such as hallucinations, delusions, and cognitive and motivational impairments. It affects a large number of people - more than 500,000 in the UK alone - and can cause lifelong disability. We currently only have one family of drugs that can treat psychotic symptoms (delusions and hallucinations). These were discovered in the 1950s, and they block a receptor found in nerve cells in the brain: the dopamine 2 receptor. They help two thirds of people suffering from psychosis, but the remainder have ongoing symptoms. Despite intensive research, we have not found any alternative treatments for psychosis, and no treatment at all for cognitive impairment. Lots of evidence indicates that dysfunction in another receptor also makes a major contribution to psychosis: the NMDA receptor. The NMDA receptor exists all over the brain, on various kinds of cells - some excitatory (E cells), some inhibitory (I cells). Slightly different subtypes of the NMDA receptor exist on these different cells, and in different parts of the brain. Different strands of evidence from psychosis research indicate that the primary problem in schizophrenia might be NMDA receptor dysfunction on either E or I cells specifically. There might be different groups of patients with E or I cell dysfunction, for example. Or I cells might try to compensate for NMDA receptor dysfunction on E cells, by reducing their activity. Pharmaceutical companies have produced many drugs that can act at NMDA receptors, and despite some promising early results, all these drugs have failed large scale clinical trials. One likely reason is that not all patients with the same diagnosis have the same underlying causes of those symptoms. For example, there are many causes of breathlessness (asthma, pneumonia, heart failure, lung fibrosis, etc), and all require different treatments. There may well be numerous underlying causes of psychosis symptoms: for example, E cell problems in some, I cell problems in others. These groups would need treatments specifically targeted to E or I cells respectively. The aim of this project is to find ways of identifying these subgroups with 'low E' or 'low I' function, and at what stage they might best be targeted. I will do this using a variety of methods, but all are based around the use of simple tasks (e.g. listening to tones) whilst electrical signals in the brain are recorded using electroencephalography (EEG). I will use computational models to estimate E and I cell function from these recorded EEG signals. I will study datasets of participants with schizophrenia or psychosis at different stages of their illness and also a very large dataset of young people at risk of developing psychosis. I will also study mice who will undergo the same simple tasks, and who will be given low doses of drugs that cause either 'low E' or 'low I' states. The purpose of all these experiments is to establish i) which cells (E or I) would be the best to target with an existing NMDA receptor-based drug, and ii) when (at what illness stage) that drug should be given. In Part 2 of the project, I will test these predictions in a sample of 100 people with early schizophrenia. I will use computational models of their brain signals to estimate whether they have 'low E' and/or 'low I' pathology. I will then give them a drug boosting E cell function (for example) for 3 months, and measure its effects on symptoms and cognition. The key question is: can my model estimate of E or I function predict the effects of the drug? If so, this could mean we could use these models to assign treatments for psychosis, and test this approach in a large scale clinical trial.

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