1,360 research outputs found

    The Genetic and Neuronal Substrates of Melatonin Signaling in Zebrafish Sleep

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    Sleep is hypothesized to be regulated by two processes: a circadian drive, which communicates time of day to ensure that sleep is timed to the appropriate day/night phase, and a homeostatic drive, by which the propensity for sleep becomes stronger over the course of prolonged wakefulness. While studies suggest that adenosine and serotonin signaling in part mediate the homeostatic sleep drive, factors that act downstream of the circadian clock to promote sleep were unidentified until recently. Previous work in the Prober lab has shown that the nocturnal hormone melatonin acts downstream of the circadian rhythm to promote sleep in zebrafish. The downstream processes by which melatonin promotes sleep is poorly understood across all animal models. This is likely because melatonin research has been primarily conducted using nocturnal laboratory rodent models, in whom melatonin does not seem to play a role in sleep, and because of the widely held view that melatonin informs the circadian clock and does not promote sleep directly. In Chapter 1 of this thesis, I review some of the research conducted over the last 50 years that has informed our current understanding of melatonin and its role in sleep. In Chapter 2, I describe our efforts to use the zebrafish, in which melatonin is both potently sedating and essential for nightly sleep, to uncover some of the mechanisms by which melatonin might promote sleep. We found that melatonin acts through a particular melatonin receptor family called MT1, whereas melatonin receptors belonging to other families were dispensable for sleep. We show that MT1 receptors are expressed broadly throughout the zebrafish brain and are enriched in brain regions involved in sensory processing, particularly in those related to vision. We tested the hypothesis that melatonin promotes sleep, at least in part, by dampening visual responsiveness at night. We show that, separable from sleep, exogenous melatonin suppresses behavioral responses to light stimuli, and loss of endogenous melatonin results in day-like behavioral responses to light stimuli during the night. We are using whole brain imaging in live zebrafish to corroborate our behavioral results with neuronal GCaMP recordings. We hope that the findings presented here contribute to a greater understanding of melatonin’s role in sleep, which may help enhance its value as a natural therapeutic aid

    Effects of municipal smoke-free ordinances on secondhand smoke exposure in the Republic of Korea

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    ObjectiveTo reduce premature deaths due to secondhand smoke (SHS) exposure among non-smokers, the Republic of Korea (ROK) adopted changes to the National Health Promotion Act, which allowed local governments to enact municipal ordinances to strengthen their authority to designate smoke-free areas and levy penalty fines. In this study, we examined national trends in SHS exposure after the introduction of these municipal ordinances at the city level in 2010.MethodsWe used interrupted time series analysis to assess whether the trends of SHS exposure in the workplace and at home, and the primary cigarette smoking rate changed following the policy adjustment in the national legislation in ROK. Population-standardized data for selected variables were retrieved from a nationally representative survey dataset and used to study the policy action’s effectiveness.ResultsFollowing the change in the legislation, SHS exposure in the workplace reversed course from an increasing (18% per year) trend prior to the introduction of these smoke-free ordinances to a decreasing (−10% per year) trend after adoption and enforcement of these laws (β2 = 0.18, p-value = 0.07; β3 = −0.10, p-value = 0.02). SHS exposure at home (β2 = 0.10, p-value = 0.09; β3 = −0.03, p-value = 0.14) and the primary cigarette smoking rate (β2 = 0.03, p-value = 0.10; β3 = 0.008, p-value = 0.15) showed no significant changes in the sampled period. Although analyses stratified by sex showed that the allowance of municipal ordinances resulted in reduced SHS exposure in the workplace for both males and females, they did not affect the primary cigarette smoking rate as much, especially among females.ConclusionStrengthening the role of local governments by giving them the authority to enact and enforce penalties on SHS exposure violation helped ROK to reduce SHS exposure in the workplace. However, smoking behaviors and related activities seemed to shift to less restrictive areas such as on the streets and in apartment hallways, negating some of the effects due to these ordinances. Future studies should investigate how smoke-free policies beyond public places can further reduce the SHS exposure in ROK

    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

    Social interactions in bacteria mediated by bacteriocins and horizontal gene transfer

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    Bacteria are highly social organisms that frequently engage in cooperative and competitive interactions to successfully survive and reproduce. Examples include cell-to-cell communication, nutrient scavenging, and chemical warfare. However, the vast majority of our understanding of bacterial sociality has come from the laboratory strains of a small number of gram-negative social evolution model organisms, such as Pseudomonas spp. and Escherichia coli. In my thesis, I aim to expand our understanding of bacterial sociality in natural populations and further across the bacterial tree of life. I do this using two different approaches. Firstly, I use laboratory experiments and sequence analysis to study the evolution and ecology of bacteriocin-mediated competition in natural S. aureus populations, sampled as part of a carriage study on human nasal passages. Theory and laboratory experiments to date have provided extensive evidence that bacteriocin production plays a key role in determining the competitive dynamics of bacterial strains, however evidence from natural populations to support this hypothesis is lacking. I find that inhibitory strains were associated with the propensity to displace competing strains from the nasal cavity, which occurs despite inhibitory activity not being displayed by the majority of strains and targeting interspecific over intraspecific competitors. I also provide evidence for the genetic underpinnings of bacteriocin activity, by identifying five bacteriocin gene clusters associated with inhibition. Secondly, I use a comparative approach to study the role of horizontal gene transfer in stabilising cooperation across bacteria. Bacterial cooperation is typically mediated by the secretion of extracellular public goods, which are costly molecules that provide a fitness benefit to neighbouring cells. Cooperation can be destabilised by the invasion of selfish ‘cheats’ that reap the benefit of public good production without paying a cost. It is widely accepted that horizontal gene transfer, especially via plasmids, can allow cooperators to ‘re-infect’ cheats with the gene for a cooperative trait, thus stabilising cooperation. Although theoretical and experimental studies have provided evidence to support this hypothesis, a comprehensive genomic study that controls for phylogenetic non-independence across species remains to be conducted. The results from our analysis of plasmid genes from 51 diverse bacterial species do not support the cooperation hypothesis across bacteria and are instead supportive of environmental variability as a determining factor in the relationship between horizontal gene transfer and extracellular proteins. Taken together, this thesis provides a body of work that emphasises the importance of testing predictions from theoretical and laboratory experiments in natural populations, and across diverse species

    Evaluating Symbolic AI as a Tool to Understand Cell Signalling

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    The diverse and highly complex nature of modern phosphoproteomics research produces a high volume of data. Chemical phosphoproteomics especially, is amenable to a variety of analytical approaches. In this thesis we evaluate novel Symbolic AI based algorithms as potential tools in the analysis of cell signalling. Initially we developed a first order deductive, logic-based model. This allowed us to identify previously unreported inhibitor-kinase relationships which could offer novel therapeutic targets for further investigation. Following this we made use of the probabilistic reasoning of ProbLog to augment the aforementioned Prolog based model with an intuitively calculated degree of belief. This allowed us to rank previous associations while also further increasing our confidence in already established predictions. Finally we applied our methodology to a Saccharomyces cerevisiae gene perturbation, phosphoproteomics dataset. In this context we were able to confirm the majority of ground truths, i.e. gene deletions as having taken place as intended. For the remaining deletions, again using a purely symbolic based approach we were able to provide predictions on the rewiring of kinase based signalling networks following kinase encoding gene deletions. The explainable, human readable and white-box nature of this approach were highlighted, however its brittleness due to missing, inconsistent or conflicting background knowledge was also examined

    The role of RiPP proteins in plant pathogenic fungi

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    The ascomycete fungus, Zymoseptoria tritici, has risen in prevalence and significance in the past few decades, overtaking wheat pathogens such as Stagonospora nodorum for the title of most prevalent foliar wheat pathogen in the UK and Europe – as well as several other countries worldwide. Losses to the pathogen can be significant, as such, the fungus and its associated disease, Septoria tritici blotch, presents a huge threat to global wheat production and food security given the dietary importance of wheat grain. Zymoseptoria tritici infection of wheat includes a biotrophic-like latent phase and necrotrophic stage, however, the transition between the two is currently poorly understood, and assumed to involve fungal effectors which trigger the plant hypersensitive response. Equally, fungal ribosomally synthesised and post-translationally modified peptides (RiPPs) are under-researched, despite the RiPP victorin contributing to Cochliobolus victoriae virulence on Vb oat cultivars.This thesis explores a fungal RiPP from Z. tritici, the biosynthetic pathway of which has been characterised bioinformatically with knockout strains produced for future experimental confirmation of the method predicted in this work. Bioinformatic investigation also proved informative regarding RiPP repeat variation between strains of the same species and in identifying novel RiPP producers entirely. Attempts were made to understand the function of the RiPP, to determine whether it was involved in pathogenicity, as with victorin, this however remains elusive. Although the Zymoseptoria RiPP does not have a clear role in virulence given that null mutants were fully virulent, results from this work demonstrated the impact of the environment on the wheat-Zymoseptoria interaction, demonstrating the multiple routes that can be explored to control Z. tritici. Overall, this work has extended our understanding of Zymoseptoria tritici – by examining the environmental conditions conducive or inconducive to infection – and its RiPP, with this also contributing to our knowledge of fungal RiPPs more widely

    Endogenous UMIs as quantifiable reporter elements – validation studies & applications in rAAV vectorology

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    In the creation of recombinant adeno-associated viral (rAAV) vectors, terminal DNA elements known ITRs (inverted terminal repeats) of the direct the intracellular synthesis and packaging of nonviral DNA. The need to clonally amplify ITR sequences in one form or another thereby underlies the existence of all rAAV clinical products and research materials worldwide. Their tendency to form strong nonduplex structures raises problems. The genetic precursors to rAAV vectors – typically prokaryotic plasmids – are known to possess heterogenous ITR sequences as a result of replicational instability, the effects of which on vector yield and efficacy are unclear and have not been systematically explored. To shed much-needed light on this decades-old problem, I utilised unique molecular identifiers (UMIs) as reporter elements for different rAAV plasmid preparations, so that massively parallel sequencing could be used to analyse their DNA and RNA derivatives through the course of production and in vivo gene transfer. The range of vector potencies observed, while not calamitous, definitively erases the notion that this problem can be further overlooked. The success of this unconventional strategy proved to be an equally notable outcome, offering unprecedented insights into population kinetics, and achieving quantitative consistency between biological replicates comparable to q/dPCR measurement replicates of single samples. This triggered concerted efforts to formally investigate the capabilities of UMIs used in this fashion. The probabilistic principles underlying the technique were formalised and empirically validated, confirming precision capabilities akin if not superior to dPCR and qPCR at equivalent levels of stringency. Experiments also revealed a pattern of measurement bias with potentially adverse implications for other areas of count analysis including differential gene expression
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