NIHRDataInsights/HRCSData huggingface dataset:
Title: Mitochondrial cell biology: Understanding the molecular mechanisms and functions of mitochondrial dynamics and membrane contact sites
Funder: Medical Research Council

Abstract: Beyond their role in energy production, the concept of mitochondria as a signalling organelle has emerged, with mitochondria being implicated in processes critical for the survival and homeostatic adaptation of the cell, including cell death, calcium homeostasis, redox status, inflammation and immunity. Mitochondria have a characteristic architecture composed of a double-membrane structure, with an outer and inner mitochondrial membrane, both of which are constantly remodelled to adapt to the metabolic state of the cell. Mitochondria are dynamic organelles forming an interconnected network which is regulated by cycles of fission and fusion events, in a process known as mitochondrial dynamics. These dynamic shape transitions are not only required to ensure mitochondrial function but also to respond to cellular needs and to control cell fate decisions. Mitochondria also form an elaborate network of organelle interactions by forming mitochondria-organelle contact sites (MOCS) with the endoplasmic reticulum (ER), peroxisomes, endosomes, lysosomes, and lipid droplets. These membranes contact sites are signalling platforms enriched with specific proteins, allowing mitochondria to communicate with other organelles by exchanging signals, metabolites, calcium and lipids. They are critical in regulating mitochondrial architecture and in the execution of multiple cellular functions. However, the functional interplay between mitochondrial dynamics and membrane contact sites are not fully understood. Defects in mitochondrial morphology or MOCS have been associated to human diseases including cancer, diabetes, obesity, metabolic and neurodegenerative diseases, raising the importance of elucidating how mitochondrial dynamics and membrane contact sites control cell fate decisions and how they are involved in health and disease. Our research group aims 1) to understand the mechanisms regulating mitochondrial dynamics and how they govern cell fate decisions, 2) to identify and functionally characterise new proteins regulating mitochondria-organelle contact sites, and 3) to elucidate how mitochondrial membranes remodelling controls mtDNA dynamics and release. We investigate the relevance of these pathways in cell death and survival, cellular metabolism, inflammation as well as to human diseases including cancer. To achieve our scientific goals, we employ cutting-edge microscopy, including confocal and transmission electron microscopy as well as super-resolution live-cell microscopy, coupled to proteomics and analytical biochemical techniques.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Mitochondrial genomics in human health and diseases. (How variation in nuclear and mitochondrial DNA causes rare mitochondrial diseases and common late-onset human disorders)
Funder: Medical Research Council

Abstract: My laboratory research group is primarily interested in mixed populations of mitochondrial DNA (mtDNA heteroplasmy) – how it arises in cells, how the proportion of mutated mtDNA varies between cells in one organ, how it changes over time, and how high levels cause disease – including through interactions with the nuclear genome. This is important, because the level of heteroplasmy is the main factor determining disease severity in patients with genetic mitochondrial diseases, and in common disorders such as Parkinson’s disease where mtDNA mutations play a role. We are tackling this in three ways: (i) Defining the genetic and cell biological mechanisms underpinning transmission of mtDNA heteroplasmy down the maternal line, including the germ-line genetic bottleneck. (ii) Understanding the tissue segregation of mtDNA heteroplasmy during development and throughout life. (iii) Understanding the dynamics of somatic mtDNA mutations which arise during the life course. Our approaches use cell and animal models, human tissue, high-throughput single cell sequencing, functional genomics, super-resolution imaging, mathematical, statistical and computational techniques. I also lead a clinical translational research team based in the Department of Clinical Neurosciences which focusses on: (i) Advancing our ability to diagnose mitochondrial disorders using whole genome sequencing, systematised phenotyping and other ‘omic technologies. (ii) Experimental medicine and early phase clinical trials in mitochondrial disorders.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Mitochondria in development: Neural stem cell-niche interactions that protect the developing and aging brain against mitochondrial dysfunction
Funder: Medical Research Council

Abstract: Mitochondrial diseases are genetic disorders that impair the energy production in our cells and affect about 1 in 5,000 people in the UK. Production of energy is crucial for normal functioning of all cells and organisms. Nevertheless, symptoms of mitochondrial disease can be very diverse and tissue-specific and often only appear in adult life. This suggests that some tissues and stages of life are relatively protected from mitochondrial dysfunction, while others are more susceptible. In the lab, we study how cells and tissues respond to mitochondrial dysfunction. The brain is the main focus of our research as it is frequently affected by mitochondrial disease, with a major impact on disability and death. Our overall aim is to identify novel determinants of tissue-specific phenotypes of mitochondrial and neurodegenerative diseases, and to uncover potential therapeutic targets to treat these disorders. The main research themes are (1) how cell-type composition of a tissue and cell-to-cell communication may provide protection against mitochondrial disease, and (2) how transcription of the nuclear genome is regulated when a cell is confronted with mitochondrial dysfunction. We use a wide range of approaches, but our favourite model system is the fruit fly, Drosophila melanogaster. Up to 70% of all human disease genes also have orthologs in Drosophila, and thanks to its powerful genetics, Drosophila is widely used as a model to study development and human disease. We employ advanced genetic tools and combine these with confocal and super-resolution imaging, biosensors, and innovative DamID-based sequencing approaches to study the autonomous and non-cell-autonomous effects of tissue- and cell-type specific mitochondrial dysfunction in vivo, in the developing and aging brain. Ultimately, we hope to uncover potential therapeutic targets to treat mitochondrial and neurodegenerative disorders. This will provide novel insight for other conditions where mitochondrial dysfunction plays a role too, including diabetes and cancer.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING;2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: GENERIC HEALTH RELEVANCE
Title: Mitochondrial ATP synthase: cellular power generator, determinant of mitochondrial cristae formation, a site linked to human diseases
Funder: Medical Research Council

Abstract: The F-ATP synthases in eubacteria and mitochondria are rotary machines with many common features. We will build on past achievements to extend fundamental knowledge about them and provide a basis for putting that knowledge to practical use. The mechanism of their catalytic domains is well understood, and recently we worked out how rotation is generated by the transmembrane proton-motive force being applied directly to the enzymes rotor via a Grotthus water chain. As part of a wider collaboration we will study how the human ATP synthase is assembled. We are studying how the activity of the enzyme is regulated by the inhibitor protein IF1, how the 19 constituent subunits of the human mitochondrial enzyme are assembled in the active enzyme, and in collaboration with J. Prudent the various impacts of removing individual subunits of the enzyme on the ultrastructure of mitochondrial cristae.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Gene regulation in health and disease
Funder: Medical Research Council

Abstract: The Hughes group researches the basic mechanisms of gene regulation. We have a track record in method development to enable the mapping of gene regulatory landscapes and mechanisms in the genome. The lab combines molecular technologies with computational biology and machine learning. Previously, we developed a suite of Chromosome Conformation Capture, transcriptomics and machine leaning technologies to mechanistically understand gene regulation and the function of the non-coding genome. We leveraged these technologies to develop a platform to decode non-coding genetics such as those associated with COVID-19 severity. We aim to build on this work to develop novel approaches to measure the dynamics of chromatin proteins which drive the formation of regulatory domains. We will combine large-scale synthetic biology and machine learning approaches to build artificial regulatory domains in mammalian cells to test the rules of gene regulation and to develop a toolkit for the design and creation of bespoke regulatory circuits in the genome. We will continue to refine and employ our platform to decode non-coding human genetics, using machine learning, single cell epigenomics and super-resolution 3C technologies and deploy this via collaboration with clinical and research colleagues in the MHU, WIMM and beyond.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING;2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: GENERIC HEALTH RELEVANCE
Title: Functional genomics and development of clinical genome editing strategies
Funder: Medical Research Council

Abstract: The Davies laboratory focuses on understanding gene regulation through combining genomics, bioinformatics and genome editing approaches. We also have a major interest in translating this expertise to develop clinical genome editing strategies for treating human disease in the context of haemopoietic stem cell transplantation. Many genes are controlled by regulatory elements called promoters that lie adjacent to the transcription start site and enhancers that are located 104-106 base pairs distant from the gene. The laboratory have developed an innovative technique called Micro Capture-C (MCC), which makes it possible to define physical contacts at base pair resolution when previous methods have limited resolution below 500 base pairs. We will explore the fundamental mechanisms controlling gene regulation by improving this approach and combining it with other functional genomics approaches. This will include the use of degrons to remove key components of the transcriptional machinery. Through extensive collaboration within the MHU we wish to map the chromatin landscape to understand how variants in enhancers cause abnormal haemopoiesis. We will also engineer cellular models to test the function of perturbing regulatory elements at scale including the use of CRISPR screens. Having previously developed clinical approaches for treating haemoglobinopathies using base editing; we plan to go on to develop a method of editing haemopoietic stem cells to improve the safety of transplantation through inducing a druggable selective advantage. In addition, we are using our expertise in functional genomics to assess the safety of genome editing approaches, in which the majority of off-target mutations occur in the non-coding genome.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: HOD1: Inferring relative treatment effects from combined randomised and observational data
Funder: Medical Research Council

Abstract: Randomised controlled trial (RCT) evidence is the gold-standard to estimate relative treatment effects. Network meta-analysis (MA) is used to pool evidence from RCTs to compare multiple treatments. There is a trend towards appraising new health technologies with limited or single arm evidence, which requires adjustment methods that make strong assumptions. When RCT evidence is limited, as is increasingly the case, observational data is a potential supplementary source of evidence. We will develop methods and guidance on different ways in which observational evidence can be used in decision making in five related work packages (WP): WP1: Development of methods to adjust effect estimates for imbalances in effect modifiers in disconnected networks of RCT, including single-arm studies. Methods to estimate the degree of error in the estimates obtained will also be developed. WP2: We will investigate the properties of bias adjustment methods proposed in the literature in terms of their potential to estimate and adjust for bias and reduce decision uncertainty, to determine which method is likely to work best for different kinds of RCT and observational data structures. WP3: Real world linked patient level data offers an opportunity to explore the effect of treatments in patients who may be under-represented in RCT, but are subject to selection effects and confounding. We will explore propensity scoring, Instrumental Variable and Structural Equation Modelling for the estimation of treatment effects from such data. Simulation studies will be carried out to compare the performance of these methods. WP4: The use of registry data, adjusted for population differences and selection bias, to enhance randomised trial evidence in the context of managed entry of new pharmaceuticals will be explored. WP5: Methods will be developed to explore how biased would the evidence (including observational evidence) have to be before it changed the decision.


Research activity codes: 8.2 HEALTH AND WELFARE ECONOMICS;8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE
Title: HSM: Construction of graph-based network longitudinal algorithms to identify screening and prognostic biomarkers and therapeutic targets (GBNLA)
Funder: Medical Research Council

Abstract: The methodology developed will be based on the previously proposed idea of parenclitic network analysis. This method will enable the representation of parameters corresponding to individual patients and controls in graph form without a priori knowledge of the interactions between them. The strength of the links will be estimated based on how different they are from those in healthy control subjects. In addition to the original estimation based on linear regression, we will use estimates based on two-dimensional kernel density estimation. The generated graphs or networks will be analysed using topological indices, widely used for characterising complex networks, e.g. mean, variance, and maximal values of edge weights, vertex degree, shortest path lengths, Kleinberg,, diameter of the graph, the degree centrality, network efficiency, betweenness centrality, Google maximal page rank index, number of communities and so on. The obtained metrics corresponding to one moment in time will be obtained for all available serial measurements and then linked to the serial algorithms such as change-point detection methods, parametric empirical Bayes and methods of mean trends. All these methods have already been successfully applied by us for data analysis. In order to combine and compare our methodology with other machine learning network algorithms, we will link it to community detection analysis and various types of shallow and deep artificial neural networks. We will also compare our methods with basic algorithms and models such as Bayesian networks, decision trees and forests, and advanced SVM methods. In order to identify data-specific features of the methodology we will test all newly developed algorithms on very different datasets, testing their potential for different tasks in clinical and biotechnological practice.


Research activity codes: 4.1 DISCOVERY AND PRECLINICAL TESTING OF MARKERS AND TECHNOLOGIES;4.2 EVALUATION OF MARKERS AND TECHNOLOGIES
Health categories: GENERIC HEALTH RELEVANCE
Title: Imprinted gene expression in early life determines body composition and response to the obesogenic environment.
Funder: Medical Research Council

Abstract: Obesity, or excessive expansion of white adipose tissue, is strongly correlated with metabolic diseases such as cardiovascular disease and type II diabetes. Whereas some individuals can maintain obesity with few metabolic consequences, in others it causes disease. This difference is due to the distribution of fat storage in the body, which in turn relates to adipocyte size and proliferation. Inter-individual variation in adipose tissue depot-distribution and expandability is determined during development, and there is evidence that the majority of adipose precursor cells are already present at birth. Skeletal muscle mass across the whole range of human variation is correlated with insulin sensitivity and glucose tolerance. There is strong evidence that both fat distribution and skeletal mass are highly heritable traits. Despite this, the genetic/developmental processes underpinning human variation in body composition is poorly understood. Genetic manipulation of imprinted gene expression in mice has demonstrated that these genes functionally link body composition to energy homeostasis. Such associations between lean:adipose mass are also observed in human patients with imprinted growth disorders such as Silver Russell Syndrome and Temple Syndrome, who have have altered body compostion in early life followed by truncal obesity. However, the molecular pathways modulated by this important class of developmentally regulated genes on body composition have been relatively understudied. We will use two mouse models (deletions of the imprinted genes Dlk1 and Grb10) that shift lean:adipose mass in opposite directions, to interrogate the molecular mechanisms that underlie the early life acquisition of fat and muscle. We will combine these imprinted gene deletions with lineage tracing tools and dietary manipulation to understand the complex interplay between genetics and the environment, and to ultimately understand human variation in the susceptibility to metabolic disease.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Molecular mechanisms regulating mRNA transport and local translation in neurons.
Funder: Medical Research Council

Abstract: Dendritic arborisation and the development and differentiation of synapses are an essential part of neuronal development and require the local translation of a large ensemble of specific mRNAs. IGF2 mRNA binding protein 1 (IMP1) plays a key role in defining synaptic morphology in human neurons by regulating local mRNA translation. The goal of the proposed research is to understand, at a molecular level, how IMP1 regulates the transport and local translation of mRNAs in neurons. We propose to: - Determine how IMP1 recognize different RNA targets at the atomic level using NMR and crystallography. Then model the multi-step binding reactions using kinetic data from BLI experiments. Finally, understand how IMP1 uses different combinations of its RNA binding domains to select distinct sets of RNA targets in the cell using in parallel iCLIP assays. - Explain how Src-mediated phosphorylation of IMP1, leads to the release and translation of the bound beta-actin mRNA by determining the changes in the structure and RNA binding properties of the protein and the recruitment of protein coregulators. Assess the specificity of Src-mediated IMP1 phospho-regulation. - Directly link IMP1RNA-binding mode to IMP1-mediated mRNA localisation in neurons using smRNAFISH IF. Obtain a transcriptome-wide vision of IMP1-mediated mRNAs transport using MERFISH. - Define the structural basis of the IMP1 interaction with the molecular motor KIF11 and the relation between IMP1-RNA interaction, IMP1-motor interaction and motor processivity, as assessed by single-molecule and bulk biophysics. This work will result in novel tools and concepts useful to the study of the RNA-binding proteins regulating mRNA transport and local translation.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Imprinted genes defining a novel growth regulatory axis
Funder: Medical Research Council

Abstract: Fetal growth is highly regulated in order to achieve appropriate size and proportions at birth. Inappropriate growth can compromise survival and has been linked with increased life-long risk of adverse metabolic health, including some of the most prevalent life-threatening disorders such as obesity, diabetes and cardiovascular disease. In order to better understand these processes we are focussed on two imprinted genes with roles in fetal growth regulation, as well as lean to adipose body proportions and energy metabolism in later life. Dlk1 encodes the delta-like 1 ligand, is expressed from the paternally-inherited allele, promotes fetal growth and inhibits adipose deposition. Conversely, Grb10 encoding a signalling adaptor protein for tyrosine kinase receptors, is expressed from the maternally-inherited allele, inhibits fetal growth and is permissive for adipose deposition. Using mouse genetics we have shown that these oppositely imprinted genes, with antagonistic functions, most likely act within a common pathway. Further, while Grb10 acts to directly inhibit fetal growth, Dlk1 promotes growth by acting as an inhibitor upstream of Grb10. We propose that Dlk1 and Grb10 are defining members of a novel mammalian growth axis. Preliminary biochemical data both supports our genetic studies and has allowed us to develop a model of the Dlk1/Grb10 pathway. Here we propose testing specific aspects of this pathway by identifying additional components and key regulatory mechanisms predicted by our model. We will test candidates we have identified for the physiological 'growth' receptor targeted by Grb10 and for an inhibitor of Grb10 that must exist downstream of Dlk1. We expect to gain insights into fetal growth regulation that will impact the future development of advice and treatments to prevent growth and metabolic disorders.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE