NIHRDataInsights/HRCSData huggingface dataset:
Title: Partnership to investigate the emergence of MRSA clones in cattle and their transmission to man.
Funder: Medical Research Council

Abstract: MRSA is a major public health problem, which is exacerbated by emergence of new MRSA strains in community settings and animal populations. For example, MRSA ST398 emerged from the pig population in mainland Europe and is now widespread in man. The discovery of a novel bovine associated SCCmec, carrying a divergent mecA gene, from a phenotypically MRSA strain on a dairy farm, and its subsequent isolation from a human clinical sample, highlights the importance, to human health, of animal MRSA as a potential reservoir of emerging MRSA strains. Through a partnership grant, relevant medical and veterinary expertise will be combined to address the importance of this novel MRSA for human medicine. The proposed partnership between the Department of Veterinary Medicine and the Department of Medicine/HPA at Cambridge, the Moredun Research Institute, and the Wellcome Trust Sanger Institute will provide a unique combination of expertise in the fields of MRSA research, farm animal infectious disease research, and cutting edge bacterial genomics research to investigate emerging methicillin resistant veterinary isolates. The planned work will establish their prevalence in human and animal populations, and examine the potential for interspecies transmission. A survey of MRSA acquired from hospital screening, collecting 2100 isolates from 6 regional hospitals, will collate all MRSA that are not caused by carriage of conventional mecA. A parallel farm level prevalence survey of 600 dairy herds will be performed using bulk milk samples. Subsequently a farm level case control study will be performed to determine if there is an association between people, who work or live on farms where divergent mecA MRSA are present, and carriage of divergent mecA MRSA. Coagulase negative staphylococci, which are common bovine mastitis pathogens and a potential source of mecA, will be subjected to genome sequencing on case farms to look at mecA diversity and for evidence of possible transmission of SCCmec. Genome sequencing will also be used to perform a SNP analysis of groups of isolates, that share a sequence type and cross the host species divide, to provide a fine resolution phylogenetic analysis. The phylogenetic analysis will help us understand the micro-evolution and transmission of these novel MRSA. The research to be undertaken by the partnership will help us measure and understand the risks to human health; they will also provide a valuable insight into the origins and mechanisms of antibiotic resistance in farm animal associated MRSA.


Research activity codes: 2.2 FACTORS RELATING TO PHYSICAL ENVIRONMENT;2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: INFECTION
Title: Enhancement of the soft tissue seal around transcutaneous implants and inhibition of bacterial colonisation
Funder: Medical Research Council

Abstract: The Intraosseous Transcutaneous Amputation Prosthesis (ITAP) is an osseointegrated titanium implant which projects through the skin and provides attachment for an external prosthetic device. It results in improved quality of life for amputees by avoiding soft tissue complications associated with traditional prostheses and by allowing improved function due to increased sensory feedback (Figure 1). However, there is a significant risk of infection if a successful seal is not achieved at the skin-implant interface. The goal of ITAP is to create a tight soft tissue seal which prevents epithelial downgrowth and infection. A successful seal is dependent on a race between soft tissue attachment and bacterial colonisation. The longer the interface is kept sterile and the faster the seal is established, the lower the risk of infection. Figure 1: A-C: Near-normal motion with a transhumeral ITAP. This patient was unable to use conventional prostheses due to restricted motion. D: The skin-implant interface at 740 days. E: A radiograph of the ITAP. My research aims to decrease infection associated with ITAP by improving soft tissue ingrowth and decreasing bacterial colonisation. Porous titanium, hydroxyapatite (HA) and fibronectin (Fn) are known to individually increase cell attachment. Silver (Ag) has a broad spectrum of antimicrobial activity. I will investigate whether these surfaces can act synergistically to prevent infection of ITAP by testing the hypothesis that porous titanium will promote soft tissue ingrowth and that the seal will be further enhanced and bacterial colonisation inhibited by coating the surface with HA, Ag and Fn (HA-Ag-Fn). The study consists of two parts. Firstly, an in vitro assessment will determine concentrations of HA-Ag-Fn that inhibit bacterial colonisation without inducing cytotoxicity. A number of assays will be used to assess the antibacterial effects of HA-Ag-Fn, fibroblast attachment, fibroblast viability and the release kinetics of Ag and Fn. Secondly, an established in vivo ovine transcutaneous pin model will be used to assess soft tissue ingrowth and bacterial colonisation around porous titanium coated with HA-Ag-Fn. Surfaces will be prepared by electrodepositing HA-Ag onto titanium (Figure 2). (This method is able to produce uniform coatings inside porous titanium). Fn will be adsorbed onto the HA-Ag. This study will select surfaces that will be applied clinically to enhance the seal around ITAP. Figure 2: Scanning electron micrograph showing electrodeposited HA-Ag


Research activity codes: 3.2 INTERVENTIONS TO ALTER PHYSICAL AND BIOLOGICAL ENVIRONMENTAL RISKS;5.3 MEDICAL DEVICES
Health categories: INFECTION
Title: The role of innate and adaptive pulmonary immune responses in shaping the spectrum of Latent Tuberculosis Infection
Funder: Medical Research Council

Abstract: AIMS We will for the first time in humans comprehensively and systematically evaluate the role of both innate and adaptive host responses in different stages of the spectrum of latent tuberculosis infection (LTBI), focussing on the primary anatomical site of infection and disease control: the lung. OBJECTIVES Our objectives are to test the following three hypotheses in these subgroups: A) In patients with cleared and transient TB infection following exposure to infectious cases, up-regulated innate gene expression (including but not limited to: genes related to autophagy, key transcription factors e.g. MyD88, and cytokines e.g. IL-12) in alveolar macrophages will explain why some patients are resistant to TB infection. B) In those infected with the bacillus, successful containment of latent infection is associated with an expansion of the pulmonary population of mucosal-tropic T cells secreting IL-17, such as CD4+Th17 cells and CD161+CD8 cells. C) As antigen load increases towards active disease, there is a change in the MTB-specific CD4+T cell memory pool from an effector-memory to an effector phenotype. DESIGN A cross-sectional case-control study comparing patient groups reflecting a spectrum of TB infection and disease, as determined by detailed and advanced clinical phenotyping (including endobronchial-ultrasound guided transbronchial needle aspiration and positron emission computed tomography scanning). Each patient will have blood and bronchoalveolar fluid sampling with assays performed on these samples and their resultant cell populations to test our hypotheses. METHODOLOGY 1) For Hypothesis A, Quantitative Real-Time PCR will be used to measure gene expression of key innate effector mediators in alveolar macrophages and monocyte-derived- macrophages, with and without stimulation with M.tuberculosis. 2) For Hypothesis B, Intracellular Cytokine Staining (ICS) of peripheral blood mononuclear cells (PBMC) and BAL cells will be used to determine CD4/CD8/Th17/CD161 phenotypes. 3) For Hypothesis C, Fluorescence-linked-Immunospot assays will be used with PBMC and BAL cells to define IFN-? only, IL-2 only, and dual-secreting cells and thus enumerate functional T cell subsets for the CD4+T cell population. SCIENTIFIC AND MEDICAL OPPORTUNITIES This study will be the first to comprehensively explore the scientific basis of the spectrum of latent TB infection, using state-of-the-art phenotyping to determine TB disease stage. This will have significant bearing on the finding of local and systemic markers of clearance and containment of M.tuberculosis and thus contribute to two key translational outputs: the risk stratification of individuals following TB infection, and the correlates of protective sterilisation and non-sterilising immunity to TB infection.


Research activity codes: 2.1 BIOLOGICAL AND ENDOGENOUS FACTORS
Health categories: INFECTION
Title: A systems biology approach to understanding and combating Clostridium difficile infection.
Funder: Medical Research Council

Abstract: Aims and objectives: The bacterium Clostridium difficile causes thousands of deaths every year in the United Kingdom through healthcare-associated infections. The impact upon the healthcare system is enormous and set to worsen due to the increasing prevalence of hypervirulent and antibiotic-resistant strains: an urgent need exists to further understand C. difficile infection and to develop novel therapies with which to combat it. Computational modelling will be employed to simulate gene regulation networks involved in toxin production and sporulation (crucial processes of C. difficile infection), providing hypotheses upon the associated gene, protein and signal interactions and generating the foundation for the experimental work. Combining experimental and theoretical work will uncover fundamental mechanisms behind the infection, its complexity defying its understanding by a single discipline. Experiments will test model-driven hypotheses, providing validation and parameterisation, and yielding reliable models into which current and future therapies can be incorporated, facilitating in silico prediction of the most effective therapies and required dosages. This interdisciplinary work has the potential to improve health and longevity in the United Kingdom and worldwide, reducing the impact of C. difficile infection by accelerating the advancements of novel therapies that target toxin production directly. Design and methodology: Experimental work involving gene manipulation techniques and sequencing (ClosTron, RNA-Seq) will take place in months 12-16, 21-24 and 29-32, and will be closely integrated with the theoretical work. A modular framework is proposed for the modelling, comprising gene regulation networks involved in (i) toxin production (months 1-12) and (ii) sporulation (months 5-16), with the final module being (iii) anti-infection therapies (months 17-36); experimental work is restricted to (i) and (ii). The modules will be coupled together to form a comprehensive profile of C. difficile infection and the efficacies of a range of therapies and will involve deterministic (ordinary and partial differential equations) and stochastic (master and Langevin equations) approaches, numerical solution methods and multiscale asymptotic methods for model reduction and analysis. Collaborative visits to the Dupuy laboratory at the Institut Pasteur, Paris, are scheduled in the first and final years for model and experiment development and for discussion and dissemination of results. Scientific opportunities: Theoretical, technical and practical modules of the MSc in Molecular Medical Microbiology will be undertaken at the University of Nottingham (months 5-16) to gain expertise in microbiology laboratory work, facilitating a truly interdisciplinary approach to tackling the biomedical problem of C. difficile infection and informing the applicant‘s subsequent research career.


Research activity codes: 2.2 FACTORS RELATING TO PHYSICAL ENVIRONMENT
Health categories: INFECTION
Title: Synthesising data from multiple spatial scales and levels of detail to improve malaria transmission model predictions
Funder: Medical Research Council

Abstract: Introduction In recent years there has been a renewed effort to control malaria, with eradication as the ultimate goal. Mathematical models of malaria transmission are valuable tools to help us to understand which combinations of control measures will be most effective, and how to tailor control programmes to local conditions. However there has been limited work validating such models against data. Furthermore, malaria transmission is locally heterogeneous, but more needs to be known in order to effectively target local foci of infection (hotspots). Aims My aims are the following: 1) choose among possible models for acquisition of immunity to malaria; 2) improve these models‘ predictions of the impact of control measures; 3) estimate how fast malaria spreads through space at a local level; 4) determine which methods for detecting hotspots work best; 5) predict the impact of targeting of interventions at local hotspots of transmission. Methodology I will have access to many datasets with differing levels of detail and spatial scales. First, I will fit transmission models to the datasets that do not have control measures, to choose the best model for how various kinds of immunity develop. Then I will fit extensions of this model to datasets recording the impact of interventions. I will develop and apply methods to use data of genotyped infections and their spatial location to estimate the rate at which malaria infections spread through space and time from person to person (via mosquitoes). I will then use simulation to compare methods for detecting hotspots, and combine these results to design and assess strategies which target hotspots. Outcomes Together, these results will improve the predictions of malaria models, allowing us to use limited resources more effectively, thus having a greater chance of eliminating malaria altogether from some areas, or of controlling disease at a low level. The results will also aid the design of strategies which aim to optimise the use of resources by targeting interventions at hotspots of infection. The work will also result in methodological developments in a number of areas. It will require a comprehensive statistical framework for validating infectious disease models, combining methods that are not generally applied to complex biologically-based models. I will develop novel methods for estimating quantities relevant to infection processes from partially observed genetic data; and assess and develop methods to detect clusters of infectious disease transmission.


Research activity codes: 2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: INFECTION
Title: New methods for tracking emergent infections: integrating pathogen genomic and geographic information system data
Funder: Medical Research Council

Abstract: The rise of emerging infectious diseases constitutes a major global public health and economic problem. Understanding the reciprocal roles of transmission and environment is critical for developing effective intervention strategies. The spatial spread of pathogens can be modelled within a Bayesian framework known as phylogeography, which incorporates both genetic and geographical data, thereby allowing a priori hypothesis of spatial association to be tested. The complementary field of geographic information systems (GIS) enables testing of positional associations between ecological and landscape variables and disease incidence. Unifying these approaches would allow genomic, epidemiological and geographic data to be analysed in concert. Thus far, however, the use of GIS in molecular epidemiology is sparse, and a rigorous quantitative methodology that integrates the two fields is lacking. The goal of this project is to design innovative methods that can reveal ecological associations and predictors of infectious disease epidemics. The results can be used to inform health policy, surveillance, prevention, treatment and resource deployment. Specifically, the objective is to integrate phylogeographic and GIS approaches to model the spatio-temporal spread of pathogens by using high-resolution data on geographic and environmental variables. The resulting models will allow statistical testing of correlations between evolutionary, epidemiological, and ecological processes. To develop and validate this ecological phylogeographic framework, a diverse set of pathogens will be studied, including RNA viruses and bacteria sampled from different geographic regions worldwide. The project consists of three complementary aims: 1) GIS ecological data will be implemented within an existing Bayesian phylogeographic framework. Competing hypotheses can be evaluated by comparing the posterior distributions using model selection tools, such as Bayes factors. 2) Estimates of evolutionary processes (e.g. effective population size and gene flow) will be added to the existing ArcGIS platform, which represents each variable as a separate raster or vector layer. Spatial statistics can then be applied to the various layers to determine correlation among variables, including principal component analysis, factor analysis, and generalized linear models. 3) Ecological variables will be modelled using Bayesian inference using R codes. Evolutionary estimates are used as priors, and interactions between pathogens and a heterogeneous environment formally tested. As new sequence data becomes available over the course of the project, the models will be tested to determine whether the location/timing of the outbreak was predicted by the new methodology. Methods will be validated using intensively studied epidemics, such as the North American invasion of the West Nile Virus.


Research activity codes: 2.4 SURVEILLANCE AND DISTRIBUTION;2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: INFECTION
Title: Mathematical and Statistical Modelling of CCR5 Inhibitor Effects in Adults and Children with HIV-1 Infection
Funder: Medical Research Council

Abstract: CCR5 receptor inhibitors are a new class of antiretroviral that inhibit viral entry into host immune cells. This work aims to use mathematical/statistical modelling to understand the long-term effects of CCR5 inhibitors in adults and children. A major difference between the method proposed and a purely statistical approach is that ordinary differential equations will be applied to longitudinal data. This novel method allows fitting of mechanistic models to sparse, unbalanced observations, giving the potential to go beyond merely describing the data, to making predictions under varying hypothetical conditions. Exploration of developmental differences between adults and children, determining the place of CCR5 inhibitors in HIV-1 therapy, and mathematical investigation of non-adherence to antiretroviral medications are key objectives. Longitudinal data on viral load and CD4 counts in 1934 HIV-1-infected adults treated with antiretroviral regimens including the CCR5 inhibitor maraviroc will be used in the first part, which aims to develop a mechanistic model describing the changes in CD4 count and viral load over 48 weeks of treatment. The studies available provide data on various drug combinations, along with data in patients with non-CCR5 tropic HIV-1 infection, which will be useful in investigating immune system effects in the absence of observed antiretroviral activity. Pharmacokinetic data will also be integrated into the model.The second part adds paediatric data from around 100 subjects to be analysed using the adult mechanistic model. Developmental differences in both immunology and drug effects will be investigated through covariate model building guided by prior knowledge of ontogeny. Using the mechanistic insights gained, optimal design of treatment strategies in both clinical HIV-1 treatment and antiretroviral study design will be possible. Using the data and model, the final study is an investigation on the impact of non-adherence on drug concentrations, CD4 count and viral load. Novel methods for identifying patterns of non-adherence and for appropriate handling of data suspected to arise from non-adherence will be developed, which will be used to detect and predict its impact on clinical effect. Scientific opportunities presented in this work include access to large clinical datasets, and the chance to employ sophisticated mathematical and statistical modelling techniques that have not been widely applied to this field. The medical opportunities lie in using mathematical models to investigate antiretroviral mechanisms Simulation from model parameters will guide the design of future studies and provide treatment recommendations for clinical practice, in particular on the place of CCR5 inhibitors.


Research activity codes: 5.1 PHARMACEUTICALS
Health categories: INFECTION
Title: Bacterial vaginosis among women at high risk for HIV in East Africa: the role of behaviour, host immunity, genetics
Funder: Medical Research Council

Abstract: Aims: 1) To investigate the role of behavioural, genetic and immunological risk factors for bacterial vaginosis as well as BV-associated bacteria in a population of women at high-risk for HIV in Tanzania. 2) To develop a comprehensive framework for further research related to BV that would include each of the above factors and their interactions, and contribute to the development of interventions against BV. Objectives: 1) To investigate the prevalence of BV in two large observational cohorts, and to identify social and behavioural factors related to BV, symptomatic infection and recurrence 2) To describe the vaginal flora in women with and without BV 3) To investigate the immunological response and gene expression in women with and without BV 4) To finalise a conceptual framework to inform future epidemiological studies investigating BV Design: Secondary analyses of data from three observational cohorts and the testing and analysis of stored specimens. Methodology: This work will exploit the data previously collected from several studies in North-West Tanzania including the EDCTP-funded Women‘s Health Project (WHP), the MRC-funded Inflammation Sub-study, and MDP 301 feasibility study. With these data, we will be able to do in-depth analyses of the correlates of BV and recurrence, description and correlates of BV-specific bacteria, and description of immune responses associated with BV or BV-specific bacteria. In addition, the WHP has preserved 230 CVL cell pellets from participants attending for their 12 month (final) visit. Samples will be sequenced for selected bacteria using semi-quantitative methods, and then tested for human gene expression. With the outputs from the above analyses, I will employ advanced epidemiological methods including causal inference and infectious disease modelling to develop a conceptual framework for future research on BV. Scientific and medical opportunities: Detailed research on BV has not been carried out previously among women at high risk for HIV in sub-Saharan Africa. This research would take advantage of previously collected data to analyse correlates of BV and recurrent BV, identify BV-associated bacteria and obtain detailed data on vaginal mucosal immunity. In addition, we will be able to carry out human genome-wide expression studies that will provide a comprehensive picture of the genes and immune pathways activated during BV. With the outputs from these analyses, I will be able to develop future strategies for research projects including intervention studies on the treatment or prevention of BV with the aim of reducing reproductive health burden and HIV transmission.


Research activity codes: 2.5 RESEARCH DESIGN AND METHODOLOGIES (AETIOLOGY)
Health categories: INFECTION