3 resultados para inborn errors of metabolism

em Glasgow Theses Service


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The primary goal of systems biology is to integrate complex omics data, and data obtained from traditional experimental studies in order to provide a holistic understanding of organismal function. One way of achieving this aim is to generate genome-scale metabolic models (GEMs), which contain information on all metabolites, enzyme-coding genes, and biochemical reactions in a biological system. Drosophila melanogaster GEM has not been reconstructed to date. Constraint-free genome-wide metabolic model of the fruit fly has been reconstructed in our lab, identifying gaps, where no enzyme was identified and metabolites were either only produced or consume. The main focus of the work presented in this thesis was to develop a pipeline for efficient gap filling using metabolomics approaches combined with standard reverse genetics methods, using 5-hydroxyisourate hydrolase (5-HIUH) as an example. 5-HIUH plays a role in urate degradation pathway. Inability to degrade urate can lead to inborn errors of metabolism (IEMs) in humans, including hyperuricemia. Based on sequence analysis Drosophila CG30016 gene was hypothesised to encode 5- HIUH. CG30016 knockout flies were examined to identify Malpighian tubules phenotype, and shortened lifespan might reflect kidney disorders in hyperuricemia in humans. Moreover, LC-MS analysis of mutant tubules revealed that CG30016 is involved in purine metabolism, and specifically urate degradation pathway. However, the exact role of the gene has not been identified, and the complete method for gap filling has not been developed. Nevertheless, thanks to the work presented here, we are a step closer towards the development of a gap-filling pipeline in Drosophila melanogaster GEM. Importantly, the areas that require further optimisation were identified and are the focus of future research. Moreover, LC-MS analysis confirmed that tubules rather than the whole fly were more suitable for metabolomics analysis of purine metabolism. Previously, Dow/Davies lab has generated the most complete tissue-specific transcriptomic atlas for Drosophila – FlyAtlas.org, which provides data on gene expression across multiple tissues of adult fly and larva. FlyAtlas revealed that transcripts of many genes are enriched in specific Drosophila tissues, and that it is possible to deduce the functions of individual tissues within the fly. Based on FlyAtlas data, it has become clear that the fly (like other metazoan species) must be considered as a set of tissues, each 2 with its own distinct transcriptional and functional profile. Moreover, it revealed that for about 30% of the genome, reverse genetic methods (i.e. mutation in an unknown gene followed by observation of phenotype) are only useful if specific tissues are investigated. Based on the FlyAtlas findings, we aimed to build a primary tissue-specific metabolome of the fruit fly, in order to establish whether different Drosophila tissues have different metabolomes and if they correspond to tissue-specific transcriptome of the fruit fly (FlyAtlas.org). Different fly tissues have been dissected and their metabolome elucidated using LC-MS. The results confirmed that tissue metabolomes differ significantly from each other and from the whole fly, and that some of these differences can be correlated to the tissue function. The results illustrate the need to study individual tissues as well as the whole organism. It is clear that some metabolites that play an important role in a given tissue might not be detected in the whole fly sample because their abundance is much lower in comparison to other metabolites present in all tissues, which prevent the detection of the tissue-specific compound.

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A key aspect underpinning life-history theory is the existence of trade-offs. Trade-offs occur because resources are limited, meaning that individuals cannot invest in all traits simultaneously, leading to costs for traits such as growth and reproduction. Such costs may be the reason for the sub-maximal growth rates that are often observed in nature, though the fitness consequences of these costs would depend on the effects on lifetime reproductive success. Recently, much attention has been given to the physiological mechanism that might underlie these life-history trade-offs, with oxidative stress (OS) playing a key role. OS is characterised by a build-up of oxidative damage to tissues (e.g. protein, lipids and DNA) from attack by reactive species (RS). RS, the majority of which are by-products of metabolism, are usually neutralised by antioxidants, however OS occurs when there is an imbalance between the two. There are two main theories linking OS with growth and reproduction. The first is that traits like growth and reproduction, being metabolically demanding, lead to an increase in RS production. The second involves the diversion of resources away from self-maintenance processes (e.g. the redox system) when individuals are faced with enhanced growth or reproductive expenditure. Previous research investigating trade-offs involving growth or reproduction and self-maintenance has been equivocal. One reason for this could be that associations among redox biomarkers can vary greatly so that the biomarker selected for analysis can influence the conclusion reached about an individual’s oxidative status. Therefore the first aim of my thesis was to explore the strength and pattern of integration of five biomarkers of OS (three antioxidants, one damage and one general oxidation measure) in wild blue tit (Cyanistes caeruleus) adults and nestlings (Chapter 2). In doing so, I established that all five biomarkers should be included in future analyses, thus using this collection of biomarkers I explored my next aims; whether enhanced growth (Chapters 3 and 4) or reproductive effort (Chapter 5) can lead to increased OS levels, if these traits are traded off against self-maintenance. I accomplished these aims using both a meta-analytic and experimental approach, the latter involving manipulation of brood size in wild blue tits in order to experimentally alter growth rate of nestlings and provisioning rate (a proxy for reproductive expenditure) of adults. I also investigated the potential for redox integration to be used as an index of body condition (Chapter 2), allowing predictions about future fitness consequences of changes to oxidative state to be made. A growth – self-maintenance trade off was supported by my meta-analytic results (Chapter 4) which found OS to be a constraint on growth. However, when faced with experimentally enhanced growth, animals were typically not able to adjust this trade-off so that oxidative damage resulted. This might support the idea that energetically expensive growth causes resources to be diverted away from the redox system; however, antioxidants did not show an overall reduction in response to growth in the meta-analysis suggesting that oxidative costs of growth may result from increased RS production due to the greater metabolism needed for enhanced growth. My experimental data (Chapter 3) showed a similar pattern, with raised protein damage levels (protein carbonyls; PCs) in the fastest growing blue tit chicks in a brood, compared with their slower growing sibs. These within-brood differences in OS levels likely resulted from within-brood hierarchies and might have masked any between-brood differences, which were not observed here. Despite evidence for a growth – self-maintenance trade off, my experimental results on blue tits found no support for the hypothesis that self-maintenance is also traded off against reproduction, another energetically demanding trait. There was no link between experimentally altered reproductive expenditure and OS, nor was there a direct correlation between reproductive effort and OS (Chapter 5). However, there are various factors that likely influence whether oxidative costs are observed, including environmental conditions and whether such costs are transient. This emphasises the need for longitudinal studies following the same individuals over multiple years and across a wide range of habitats that differ in quality. This would allow investigation into how key life events interact; it might be that raised OS levels from rapid early growth have the potential to constrain reproduction or that high parental OS levels constrain offspring growth. Any oxidative costs resulting from these life-history trade-offs have the potential to impact on future fitness. Redox integration of certain biomarkers might prove to be a useful tool in making predictions about fitness, as I found in Chapter 2, as well as establishing how the redox system responds, as a whole, to changes to growth and reproduction. Finally, if the tissues measured can tolerate a given level of OS, then the level of oxidative damage might be irrelevant and not impact on future fitness at all.

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Orthopaedic infections can be polymicrobial existing as a microbiome. Infections often incorporate staphylococcal species, including Staphylococcus aureus. Such infections can lead to life threatening illness and implant failure. Furthermore, biofilm formation on the implant surface can occur, increasing pathogenicity, exacerbating antibiotic resistance and altering antimicrobial mechanism of action. Bacteria change dramatically during the transition to a biofilm growth state: phenotypically; transcriptionally; and metabolically, highlighting the need for research into molecular mechanisms involved in biofilm formation. Metabolomics can provide a tool to analyse metabolic changes which are directly related to the expressed phenotype. Here, we aimed to provide greater understanding of orthopaedic infection caused by S. aureus and biofilm formation on the implant surface. Through metagenome analysis by employing: implant material extraction; DNA extraction; microbial enrichment; and whole genome sequencing, we present a microbiome study of the infected prosthesis to resolve the causative species of orthopaedic hip infection. Results highlight the presence of S. aureus as a primary cause of orthopaedic infection along with Enterococcus faecium and the presence of secondary pathogen Clostridium difficile. Although results were hindered by the presence of host contaminating DNA even after microbial enrichment, conclusions could be made over the potential increased pathogenicity caused by the presence of a secondary pathogen and highlight method and sample preparation considerations when undertaking such a study. Following this finding, studies were focused on an orthopaedic clinical isolate of S. aureus and a metabolome extraction method for staphylococcal biofilms was developed using cell lysis through bead beating and solvent metabolome extraction. The method was found to be reproducible when coupled with liquid chromatography-mass spectrometry (LC-MS) and bioinformatics, allowing for the detection of significant changes in metabolism between planktonic and biofilm cultures to be identified and drug mechanism of actions (MOA) to be studied. Metabolomics results highlight significant changes in a number of metabolic pathways including arginine biosynthesis and purine metabolism between the two cell populations, evidence of S. aureus responding to their changing environment, including oxygen availability and a decrease in pH. Focused investigations on purine metabolism looking for biofilm modulation effects were carried out. Modulation of the S. aureus biofilm phenotype was observed through the addition of exogenous metabolites. Inosine increased biofilm biomass while formycin B, an inosine analogue, showed a dispersal effect and a potential synergistic effect in biofilm dispersal when coupled with gentamycin. Changes in metabolism between planktonic cells and biofilms highlight the requirement for antimicrobial testing to be carried out against planktonic cells and biofilms. Untargeted metabolomics was used to study the MOA of triclosan in S. aureus. The triclosan target and MOA in bacteria has already been characterised, however, questions remain over its effects in bacteria. Although the use of triclosan has come under increasing speculation, its full effects are still largely unknown. Results show that triclosan can induce a cascade of detrimental events in the cell metabolism including significant changes in amino acid metabolism, affecting planktonic cells and biofilms. Results and conclusions provide greater understanding of orthopaedic infections and specifically focus on the S. aureus biofilm, confirming S. aureus as a primary cause of orthopaedic infection and using metabolomic analysis to look at the changing state of metabolism between the different growth states. Metabolomics is a valuable tool for biofilm and drug MOA studies, helping understand orthopaedic infection and implant failure, providing crucial insight into the biochemistry of bacteria for the potential for inferences to be gained, such as the MOA of antimicrobials and the identification of novel metabolic drug targets.