NIHRDataInsights/HRCSData huggingface dataset:
Title: Developmental Epigenomics
Funder: Medical Research Council

Abstract: A fundamental current research question is to understand how cells control the access and flow of genetic information during differentiation and how these are affected in disease. This is regulated through a multi-layered epigenetic regulatory system that ensures that specific gene expression programmes are only turned on or off at the right time and location in the organism. These epigenetic programmes are crucial, since their misregulation often leads to developmental disorders and disease such as cancer. In particular, our research focuses on specific aspects of chromatin dynamics that drive this regulation, including: i) the 3D organisation of chromatin in the nucleus during gametogenesis and early embryonic development; ii) the role of chromatin organisation in human disease; and iii) epigenetic regulation mediated by genetic features such as repetitive elements or transcription factor binding. We employ a combination of bulk and single-cell genomic techniques that examine changes in these different epigenetic features (e.g., chromatin organisation, DNA methylation, chromatin modifications, gene expression) during early embryonic development in model organisms and in vitro systems. We have a strong interest in gametogenesis and early embryonic development. These are key stages in the life of an organism, when the epigenetic programmes of the fully differentiated gametes are reverted back to a totipotent state in order to give rise to a new individual. By examining changes in chromatin conformation at these key developmental points genome-wide, we can identify the molecular mechanisms that drive these changes, and as a result, decipher how these are affected in disease. In addition, we pay particular attention to the regulation of repetitive elements, since their expression is tightly regulated during gametogenesis and early embryonic development. For example, families of retrotransposons, such as the murine-specific MERVL retroelements, seem to play a key role during zygotic genome activation, a key stage when the zygotic genome takes over developmental control from the maternal contributed products present in the oocyte. Through careful computational analysis of these elements, we aim to understand how these retroviral-derived repetitive elements have evolved to acquire their own bona-fide regulatory activities in the genome. Overall, our research aims to discover key molecular mechanisms that determine the correct establishment of gene developmental programmes in the early embryo and to characterise how these are affected in human disease.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Epigenetic Memory: Understanding how epigenetic information is transmitted and changed during normal development and in disease
Funder: Medical Research Council

Abstract: Our team examines how cellular identity is established, progressively changed during differentiation and then transmitted through cell division. Understanding how epigenetic information is transmitted from mother to daughter cells during cell division is critical for understanding inherited function as well as for manipulating cell fate for therapeutic benefit. We also study how environment exposures, including those encountered in utero during pregnancy, can impact the developing epigenome and thereby influence the health of offspring throughout their lifespan and across generations. To do this we generated bespoke bioluminescent imaging models that allow the allelic expression of genes to be continuously monitored in vivo within living organisms. This provides novel preclinical models for certain diseases, as well as allowing the epigenetic consequences of environmental challenges (and drugs) encountered during pregnancy to be better understood.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING;2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;2.2 FACTORS RELATING TO PHYSICAL ENVIRONMENT
Health categories: GENERIC HEALTH RELEVANCE
Title: Functional Gene Control
Funder: Medical Research Council

Abstract: We are interested in how genomic and epigenetic information is integrated with extrinsic signals to establish functional patterns of gene expression. Our emphasis is on biological phenomena involving concerted changes in phenotype, such as cell differentiation and activation, and on the role of DNA regulatory elements such as enhancers in these processes. We combine experimental approaches (including genome-wide assays of chromatin state, enhancer-promoter contacts and gene expression) with advanced statistical and machine learning techniques to study these questions, focusing on human cells and taking advantage of genetic and epigenetic variation as ‘natural perturbations’ in this system. Our research builds on the foundations of our previous work on promoter-enhancer relationships, organisation of DNA regulatory elements and population genomics. Our goal is to delineate the ‘ground rules’ of gene regulation and, on their basis, generate functional models of gene control networks underlying transcriptional decisions. Interrogation and validation of these models will pinpoint key individual players (genes, DNA regulatory elements, extrinsic signals) and their regulatory relationships, as well as shed light on how they are affected in disease.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Host-Microbe-Diet Interactions in Ageing
Funder: Medical Research Council

Abstract: Animals rarely live in isolation, but rather exist in intimate association with other species, particularly microorganisms. The microbiota and its genes play key roles in human health and disease. Recently, several reports have linked the role of microbiota with organismal ageing. Not only the composition and function of the microbiota changes over time within an ageing organism but also the function of the microbiota can modulate organismal ageing. Yet, the causal mechanisms regulating this intertwined and complex communication remain widely unexplored and ill-defined. Despite great advances in our understanding of ageing biology from a genomic-centric approach, we do not fully comprehend why similar mutations or treatments lead to a wide-range of host phenotypes in a context-dependent manner. Nutrition and the microbiome are two key environmental factors regulating host physiology. Chemical elements originating from these exogenous sources are the cornerstone of life as they offer a source of energy, the building blocks for cellular construction and the micronutrients which are essential for the adequate functioning of cells. Importantly, the microbiome is significantly enriched for genes involved in the metabolism of dietary compounds to produce molecules of biological relevance. These metabolites may explain the present gaps in our knowledge coupling the gut microbiota to biological host mechanisms in health and disease throughout life. The overarching goal of this programme is to unravel the molecular basis of microbial and dietary-induced host metabolic-rewiring during ageing. Here, we integrate novel experimental designs to build mechanistic in silico models through systems biology approaches in order to predictively understand the contribution of diet in the regulation of host biology through or independently of the microbiome. The underlying mechanisms will be studied using the powerful genetic, microbiota and ageing model Caenorhabditis elegans, which mirrors many conserved human metabolic pathways and allows for a well-defined control of environmental cues. This interdisciplinary programme will combine state-of-the-art high-throughput screening host- microbe- diet approaches developed in the Cabreiro lab and combined omics approaches at the host and microbial level to identify and characterize: microbially-regulated host metabolic pathways regulating ageing (Aim 1); identify dietary and microbial metabolites critical for healthy ageing (Aim 2); and microbial-diet -interactions regulating metabolism and host ageing (Aim 3). Ultimately, we aim at demonstrating the power of interspecies predictive models and the possibility of creating precise genetic interventions in bacteria for discovering and harnessing new metabolites with important implications in regulating healthy ageing.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING
Health categories: GENERIC HEALTH RELEVANCE
Title: Synthetic biology approach to directed evolution of light-emitting molecules
Funder: Medical Research Council

Abstract: Directed evolution is the most commonly used and effective strategy for improving or changing activity of proteins for industrial, research and therapeutic applications. The process mimics natural selection to evolve proteins towards a researcher-defined goal. The key technical aspect of development of new proteins by directed evolution is creation of mutant libraries and their subsequent selection for highly functional variants. Fortunately, the development of DNA synthesis is causing creation of complex libraries to become routine, while screening and selection of the best-performing mutants remains in most cases an expensive and arduous task. Proteins obtained through directed evolution have variety of research and industrial applications. In particular, development of fluorescent and bioluminescent imaging, the key technology in a wide array of areas in life sciences, relies on molecular tools generated almost exclusively with directed evolution. This process of generation of a highly functional new protein is a complex laborious task. High throughput methods for bioluminescent proteins are practically non-existent, with screening of protein variants typically performed manually or in a semi-automated manner in 96-well plates. But even for fluorescent molecules where fluorescence-activated cell sorting allows for assessment of millions of variants, development of a new molecular tool for imaging is typically a project for the duration of a PhD thesis or a postdoctoral training. As a result, many of the best imaging tools being used today have been developed iteratively, with several intermediate versions published, in a process that took over a decade. This bottleneck in development of molecular tools hinders the progress in other areas of life sciences. We aim to approach directed evolution of light-emitting proteins from the perspective of synthetic biology and to delegate the process of library screening to bacterial cells allowing each cell to decide whether the gene variant it expresses is good enough. This will require engineering of cells to distinguish protein variants with different brightness and to carry out some computation that would take into account brightness values of a molecule under different conditions. To achieve this, we plan to construct photoreceptor-based genetic circuits that would allow cells to translate brightness of mutants they express into the level of expression of a selectable marker. If we are successful, both time and resources needed for development of new light-emitting proteins will be decreased, accelerating progress in other areas of science.


Research activity codes: 1.3 CHEMICAL AND PHYSICAL SCIENCES
Health categories: GENERIC HEALTH RELEVANCE
Title: Mary Lyon Centre Community Programmes - Genome Editing Mice for Medicine and the National Archive
Funder: Medical Research Council

Abstract: The objectives of the Genome Editing Mice for Medicine programme are to create novel mouse lines for preclinical studies and to refine and improve existing models. To this end, the UK academic research community is invited to nominate mouse lines for production using CRISPR/Cas9 technologies, which are reviewed by an expert panel for their value to research hypotheses or clinical diagnosis and their impact and utility for the wider research community. The Mary Lyon Centre is the UK node of the European Mouse Mutant Archive (EMMA). The National Archive at Harwell is supported by extensive IT infrastructure and strain curation services, which greatly facilitates access to mouse lines, cryopreservation, import and rederivation services for UK scientists.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS;2.6 RESOURCES AND INFRASTRUCTURE (AETIOLOGY)
Health categories: GENERIC HEALTH RELEVANCE
Title: Mary Lyon Centre - Technical Development
Funder: Medical Research Council

Abstract: The Mary Lyon Centre is an enabler of science but in order to do this effectively, at the cutting edge of technological progress, with scientific credibility we maintain an innovative technical development programme. This couples service provision with an research to develop and refine techniques in the fields of gene editing, phenotyping and cryobiology.


Research activity codes: 2.6 RESOURCES AND INFRASTRUCTURE (AETIOLOGY)
Health categories: GENERIC HEALTH RELEVANCE
Title: Visualising proteins in health and disease
Funder: Medical Research Council

Abstract: We aim to understand how molecular machines work by visualising their three-dimensional structures using electron microscopy. Molecular machines are large and flexible macromolecular assemblies that fulfil a wide range of vital processes in the cell. Just like machines from daily life, molecular machines employ movements of separate parts in their functioning. This intrinsic flexibility often makes their structural characterization a difficult task. Typically, distinct conformations are chemically similar and therefore hard to purify using biochemical techniques. Moreover, structural flexibility often interferes with crystallisation; and biophysical techniques that study the bulk are likely to provide suboptimal results in the presence of many different structures. Modern electron microscopes allow the visualization of individual assemblies. Frozen in a thin layer of ice these assemblies are free to adopt any functional conformation. Thereby electron microscopy may provide structural information about multiple conformations of an assembly, provided that images from different states may be separated. The availability of structural information about multiple functional states is likely to give much more information about the functioning of molecular machines than a single structure would. We have developed novel image processing techniques that allow separation of projection images from distinct conformational states. This task is highly complicated by the elevated levels of noise in electron microscopy images (with signal-to-noise ratios in the order of 1/10). Still, we have shown that statistical image processing algorithms based on maximum likelihood principles are capable of separating conformational states of relatively large assemblies, and reconstruction of these states to near-atomic resolution. Among other applications, we have used these algorithms to characterize structures of the human gamma-secretase complex. Recently, we have also expanded the applicability of our methods to deal with amyloid fibrils, and we have used this to study tau fibrils that were isolated from the brains of patients with Alzheimer's disease. Current efforts aim to develop new image processing techniques that will further enhance the scope of cryo-EM structure determination and apply these methods in our own lab to amyloid fibrils from ex vivo material.


Research activity codes: 1.1 NORMAL BIOLOGICAL DEVELOPMENT AND FUNCTIONING;1.4 METHODOLOGIES AND MEASUREMENTS
Health categories: GENERIC HEALTH RELEVANCE
Title: Statistical and Machine learning approaches for molecular precision medicine and beyond
Funder: Medical Research Council

Abstract: A well-established goal of precision medicine is to identify and characterise disease subtypes, since these may be associated with differential prognoses and/or treatment responses. The existence of subtypes may be suggestive of the existence of multiple aetiologies or pathobiological mechanisms, with each subtype corresponding to a distinct disease-causing process or combination of processes. For diseases in which multiple disease-causing processes are operative within or upon each patient, recent research has highlighted how the identification of signatures associated with each process can also benefit precision medicine. In this context, signatures are detectable patterns that are the imprint of each causal process; e.g. characteristic genomic changes in cancer associated with distinct mutational processes, accumulated over time. Both subtype discovery and signature identification require the deconvolution of mixed signals, whether at the patient cohort level (subtype discovery) or within each patient (signature identification). We will undertake to develop a comprehensive suite of widely applicable analysis methods, implemented in open-source software, for the deconvolution of heterogeneity, and – working with clinical and wet-lab collaborators – demonstrate their utility in application areas where they will add value, and have the greatest impact. A particular methodological challenge that will be addressed within our research programme will be how best to integrate diverse sources of molecular and other information, using both novel statistical models and probabilistic machine learning approaches. Our work may be divided into 3 subthemes: (i) probabilistic discovery of disease subtypes and signatures; (ii) the analysis of electronic health records (EHRs) to define multimorbidity clusters; and (iii) modelling heterogeneity in the analysis of ’omics datasets. We have strong collaborations with teams across the Cambridge Biomedical Campus, particularly within the Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), the Cancer Research UK Cambridge Institute (CRUK-CI), and the Cambridge Centre for Proteomics (CCP), as well as within the MRC Biostatistics Unit (BSU). Particular applications of our work include molecular characterisation of high grade serous ovarian cancer (HGSOC); pan-cancer proteomic characterisation; understanding sub-cellular protein localisation; and the development of clustering methods for genetic summary data.


Research activity codes: 2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: GENERIC HEALTH RELEVANCE
Title: Efficient designs for clinical trials
Funder: Medical Research Council

Abstract: Clinical trials are essential to establish the best regimen (dose, duration of treatment, frequency of treatment, …) of an intervention and randomized controlled trials are the gold standard to evaluate the potential efficacy and safety of a medicine or health technology. The increasing cost of clinical trials as well as the high attrition rate during the development mean, however, that new design and analysis methods to increase efficiency are greatly needed. The challenge is to seek improvements throughout the drug development process to eliminate ineffective or harmful treatments quickly and provide better estimates of the optimal dose for treatments which in turn will reduce the number of unsuccessful late stage clinical trials and allow for more efficient development of medicinal products and health technologies overall. In parallel, barriers to implementation of these novel efficient designs need to be broken down and to achieve this, close interaction with clinical experts and the pharmaceutical industry in particular is paramount. Mathematically the focus of the research is sequential and adaptive decision making based on accumulating data and the closely related topic of multiple testing. My proposed future work includes five main objectives: 1. Bayesian adaptive dose-finding trials with multiple objectives; 2. adaptive designs in small populations; 3. estimation after adaptive trials; 4. adaptive trials for infectious diseases; 5. treatment development in heterogeneous populations.


Research activity codes: 6.1 PHARMACEUTICALS
Health categories: GENERIC HEALTH RELEVANCE
Title: Innovative designs for trials: methods and implementation
Funder: Medical Research Council

Abstract: Randomised experiments are the gold standard for developing new medical interventions but they are expensive and face multiple other challenges. Novel analysis techniques can lead to efficiency gains. However, there are additional challenges which pose important barriers to the chances of success of a trial and that call for a new approach to the design of experiments. For example, developing patient-centric clinical trials for rare and fatal diseases imposes hard trade-offs between efficiency and outcome objectives My proposed research is an interdisciplinary approach motivated by improving clinical trial design through the development and application of methods that lie in the intersection between optimisation, machine learning and statistics (with links to adaptive and sequential decision making). Most of these methods have much broader applicability. My proposed future work includes four main objectives: 1. Deriving computationally tractable, optimal and nearly optimal, algorithms for designing clinical trials; 2. Improving analysis methods of optimal adaptive trials (estimation and testing); 3. Designing innovative trial designs for emerging challenges 4. Promoting update of novel designs in practice


Research activity codes: 8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE