1,040 research outputs found

    Advanced sequencing technologies applied to human cytomegalovirus

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    The betaherpesvirus human cytomegalovirus (HCMV) is a ubiquitous viral pathogen. It is the most common cause of congenital infection in infants and of opportunistic infections in immunocompromised patients worldwide. The large double-stranded DNA genome of HCMV (236 kb) contains several genes that exhibit a high degree of variation among strains within an otherwise highly conserved sequence. These hypervariable genes encode immune escape, tropism or regulatory factors that may affect virulence. Variation arising from these genes and from an evolutionary history of recombination between strains has been hypothesised to be linked to disease severity. To investigate this, the HCMV genome has been scrutinised in detail over the years using a variety of molecular techniques, most looking only at one or a few of these genes at a time. The advent of high-throughput sequencing (HTS) technology 20 years ago then started to enable more in-depth whole-genome analyses. My study extends this field by using both HTS and the more recently developed long-read nanopore technology to determine HCMV genome sequences directly from clinical samples. Firstly, I used an Illumina HTS pipeline to sequence HCMV strains directly from formalin-fixed, paraffin-embedded (FFPE) tissues. FFPE samples are a valuable repository for the study of relatively rare diseases, such as congenital HCMV (cCMV). However, formalin fixation induces DNA fragmentation and cross-linking, making this a challenging sample type for DNA sequencing. I successfully sequenced five whole HCMV genomes from FFPE tissues. Next, I developed a pipeline utilising the single-molecule, long-read sequencer from Oxford Nanopore Technologies (ONT) to sequence HCMV initially from high-titre cellcultured laboratory strains and then from clinical samples with high HCMV loads. Finally, I utilised a direct RNA sequencing protocol with the ONT sequencer to characterise novel HCMV transcripts produced during infection in cell culture, demonstrating the existence of transcript isoforms with multiple splice sites. Overall, my findings demonstrate how advanced sequencing technologies can be used to characterise the genome and transcriptome of a large DNA virus, and will facilitate future studies on HCMV prognostic factors, novel antiviral targets and vaccine development

    Clinical, immunological and genetic features of histiocytic disorders

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    Clinical, immunological and genetic features of histiocytic disorders

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    Design of new algorithms for gene network reconstruction applied to in silico modeling of biomedical data

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    Programa de Doctorado en Biotecnología, Ingeniería y Tecnología QuímicaLínea de Investigación: Ingeniería, Ciencia de Datos y BioinformáticaClave Programa: DBICódigo Línea: 111The root causes of disease are still poorly understood. The success of current therapies is limited because persistent diseases are frequently treated based on their symptoms rather than the underlying cause of the disease. Therefore, biomedical research is experiencing a technology-driven shift to data-driven holistic approaches to better characterize the molecular mechanisms causing disease. Using omics data as an input, emerging disciplines like network biology attempt to model the relationships between biomolecules. To this effect, gene co- expression networks arise as a promising tool for deciphering the relationships between genes in large transcriptomic datasets. However, because of their low specificity and high false positive rate, they demonstrate a limited capacity to retrieve the disrupted mechanisms that lead to disease onset, progression, and maintenance. Within the context of statistical modeling, we dove deeper into the reconstruction of gene co-expression networks with the specific goal of discovering disease-specific features directly from expression data. Using ensemble techniques, which combine the results of various metrics, we were able to more precisely capture biologically significant relationships between genes. We were able to find de novo potential disease-specific features with the help of prior biological knowledge and the development of new network inference techniques. Through our different approaches, we analyzed large gene sets across multiple samples and used gene expression as a surrogate marker for the inherent biological processes, reconstructing robust gene co-expression networks that are simple to explore. By mining disease-specific gene co-expression networks we come up with a useful framework for identifying new omics-phenotype associations from conditional expression datasets.In this sense, understanding diseases from the perspective of biological network perturbations will improve personalized medicine, impacting rational biomarker discovery, patient stratification and drug design, and ultimately leading to more targeted therapies.Universidad Pablo de Olavide de Sevilla. Departamento de Deporte e Informátic

    ENGINEERING HIGH-RESOLUTION EXPERIMENTAL AND COMPUTATIONAL PIPELINES TO CHARACTERIZE HUMAN GASTROINTESTINAL TISSUES IN HEALTH AND DISEASE

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    In recent decades, new high-resolution technologies have transformed how scientists study complex cellular processes and the mechanisms responsible for maintaining homeostasis and the emergence and progression of gastrointestinal (GI) disease. These advances have paved the way for the use of primary human cells in experimental models which together can mimic specific aspects of the GI tract such as compartmentalized stem-cell zones, gradients of growth factors, and shear stress from fluid flow. The work presented in this dissertation has focused on integrating high-resolution bioinformatics with novel experimental models of the GI epithelium systems to describe the complexity of human pathophysiology of the human small intestines, colon, and stomach in homeostasis and disease. Here, I used three novel microphysiological systems and developed four computational pipelines to describe comprehensive gene expression patterns of the GI epithelium in various states of health and disease. First, I used single cell RNAseq (scRNAseq) to establish the transcriptomic landscape of the entire epithelium of the small intestine and colon from three human donors, describing cell-type specific gene expression patterns in high resolution. Second, I used single cell and bulk RNAseq to model intestinal absorption of fatty acids and show that fatty acid oxidation is a critical regulator of the flux of long- and medium-chain fatty acids across the epithelium. Third, I use bulk RNAseq and a machine learning model to describe how inflammatory cytokines can regulate proliferation of intestinal stem cells in an experimental model of inflammatory hypoxia. Finally, I developed a high throughput platform that can associate phenotype to gene expression in clonal organoids, providing unprecedented resolution into the relationship between comprehensive gene expression patterns and their accompanying phenotypic effects. Through these studies, I have demonstrated how the integration of computational and experimental approaches can measurably advance our understanding of human GI physiology.Doctor of Philosoph

    30th European Congress on Obesity (ECO 2023)

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    This is the abstract book of 30th European Congress on Obesity (ECO 2023

    Modern meat: the next generation of meat from cells

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    Modern Meat is the first textbook on cultivated meat, with contributions from over 100 experts within the cultivated meat community. The Sections of Modern Meat comprise 5 broad categories of cultivated meat: Context, Impact, Science, Society, and World. The 19 chapters of Modern Meat, spread across these 5 sections, provide detailed entries on cultivated meat. They extensively tour a range of topics including the impact of cultivated meat on humans and animals, the bioprocess of cultivated meat production, how cultivated meat may become a food option in Space and on Mars, and how cultivated meat may impact the economy, culture, and tradition of Asia

    Characterisation of M2 muscarinic acetylcholine receptor signalling in dental pulp stem cells

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    Cholinergic signalling is hypothesised to occur in stem cells, and there is evidence that mesenchymal stem cells (MSCs) express a functional cholinergic system. Expression of functional acetylcholine receptors (AChRs) have been reported in several types of MSC, which suggests that MSCs have non-neuronal cholinoceptive properties that may play a role in their regenerative potential. However, this remains relatively unexplored, particularly, in Dental pulp stem cells (DPSCs). This project commenced by reviewing AChRs in MSCs, highlighting DPSCs characteristics, and then investigated the presence of functional AChRs and their role in modulating DPSCs regenerative potential. This study commenced by identifying gene expression of both classes of AChRs, the muscarinic (mAChRs) and the nicotinic (nAChRs), in DPSCs. Protein expression of detected AChRs was assessed via western blotting and immunofluorescence. Functionality of expressed AChRs was assessed using an array of AChRs agonists and antagonists and DPSCs viable count was measured via MTT assay. Subtype selective agonist was used to study the role of the targeted AChR and its influence on DPSCs regenerative potential. Proliferation of DPSCs in response to that stimulation was assessed via measuring viable cell count using MTT assay, Cell Counting Kit-8 (CCK-8), and cell cycle analysis. Survival of DPSCs was assessed via detecting proliferation recovery, measuring Lactate dehydrogenase (LDH) levels, and detecting Annexin V/Propidium iodide staining. Stemness potential of DPSCs was assessed via detecting gene expression of MSCs stemness markers and pluripotency markers. Migration of DPSCs was investigated using a wound healing assays. Osteogenic differentiation of DPSCs was assessed via phenotypic mineralisation stains. Gene expression of cell cycle markers, stemness markers, osteogenic markers were assessed via Real-time polymerase chain reaction (q-PCR). Whole RNA sequencing (RNA-seq) was undertaking to measure transcriptome changes and enriched signalling pathways. Follow-up analysis was undertaking via measuring the phosphorylation and transcripts levels of ERK1 and ERK2 of the Mitogen-activated protein kinase (MAPK) pathway. The results showed transcripts expression for the M2, M3 and M5 mAChRs, and expression of subunits that support the formation of α7 and α4β2-nAChRs. Subtype selective agonists/antagonists results suggest DPSCs to express functional M2 mAChR, α7 nAChRs, and α4β2-nAChRs. This was based on the ability of the agonists to influence DPSCs viable count and the subtype selective antagonist to cancel that effect. The project then focussed on mAChRs and protein expression of M2, M3 and M5 mAChRs were detected. The subsequent work focused on investigating the role of the M2 mAChRs in modulating the function of DPSCs via activating this receptor through its selective agonist Arecaidine propargyl ester (APE). Activation of the M2 mAChR inhibited DPSCs proliferation, in a reversable manner, without affecting DPSCs viability or survival. Further evidence showed that the M2 mAChR inhibits DPSCs proliferation by arresting cell cycle progression. This was further corroborated via expression analysis of key genes involved in the regulating cell cycle. The results also showed that M2 mAChR activation inhibited DPSCs migration and differentiation potential but did not interfere with DPSCs stemness. This was further corroborated via expression analysis of key genes involved in stemness and osteogenesis. The data obtained suggests that M2 mAChR activation induce DPSCs to go into a quiescent state. The RNA-seq results showed that DPSCs responded differently to M2 mAChR activation 4 and 24 hours post activation, with different sets of differentially expressed genes (DEGs). The analysis of the enriched pathways suggested that M2 mAChR activation regulates cellular processes involved in metabolism, growth, adhesion, and response to stimuli. These processes function in proliferation, migration, and cell cycle through several metabolic pathways associated with response to cellular and oxidative stress. Follow up analysis showed upregulation of ERK1 and ERK2 phosphorylation and transcripts, which are downstream effectors of the MAPK pathway. The data obtained suggests that the transcriptomic data support the observed inhibitory effect of the M2 mAChR on DPSCs functions and highlights the many downstream effectors involved in the M2 mAChR downstream signalling. In conclusion, this thesis presents evidence for the expression of a functional M2 mAChR in DPSCs, indicating the involvement of ACh signalling in modulating DPSCs behaviour. It also provides a promising route ultimately to pharmacologically control the regenerative output of DPSCs

    Biomaterials for Bone Tissue Engineering 2020

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    This book presents recent advances in the field of bone tissue engineering, including molecular insights, innovative biomaterials with regenerative properties (e.g., osteoinduction and osteoconduction), and physical stimuli to enhance bone regeneration
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