929 resultados para Genomic flexibility
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In the first part of this study human immunodeficiency virus type 1 (HIV-1) proviral DNA sequences derived from 201 clones of the C2-V3 env region and the first exon of the tat gene were obtained from six MV-1 infected heterosexual couples. These molecular data were used to confirm the epidemiological relationships. The ability of the molecular data to draw such conclusions was also tested with multiple phylogenetic analyses. The tat region was much more useful in establishing epidemiological relationships than the commonly used C2-V3.^ Subsequently, using nucleotide sequences from the first exon of the Tat gene, we tested the hypothesis that a Florida dentist (a common source) infected five of his patients in the course of dental procedures, against the null hypothesis that the dentist and each individual of the dental group independently acquired the virus within the local community. Multiple phylogenetic analyses demonstrated that the sequences of the five patients were significantly more related to each other than to sequences of the controls. Our results using Tat sequences, combined with envelope sequence data, strongly support a common phylogenetic epidemiological relationship among these five patients.^ A third study is presented, which deals with the effects of genomic variations in drug resistance. HIV-1 reverse transcriptase (RT) mutations were detected in DNA from peripheral blood mononuclear cells from 11 of 12 HIV-infected children after 11-20 months of zidovudine monotherapy. The codon 41/215 mutant combination was associated with general decline in health status. Patients developing the codon 70 mutation tended to have a better health status. ^
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A report from the National Institutes of Health defines a disease biomarker as a “characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention.” Early diagnosis is a crucial factor for incurable disease such as cancer and Alzheimer’s disease (AD). During the last decade researchers have discovered that biochemical changes caused by a disease can be detected considerably earlier as compared to physical manifestations/symptoms. In this dissertation electrochemical detection was utilized as the detection strategy as it offers high sensitivity/specificity, ease of operation, and capability of miniaturization and multiplexed detection. Electrochemical detection of biological analytes is an established field, and has matured at a rapid pace during the last 50 years and adapted itself to advances in micro/nanofabrication procedures. Carbon fiber microelectrodes were utilized as the platform sensor due to their high signal to noise ratio, ease and low-cost of fabrication, biocompatibility, and active carbon surface which allows conjugation with biorecognition moieties. This dissertation specifically focuses on the detection of 3 extensively validated biomarkers for cancer and AD. Firstly, vascular endothelial growth factor (VEGF) a cancer biomarker was detected using a one-step, reagentless immunosensing strategy. The immunosensing strategy allowed a rapid and sensitive means of VEGF detection with a detection limit of about 38 pg/mL with a linear dynamic range of 0–100 pg/mL. Direct detection of AD-related biomarker amyloid beta (Aβ) was achieved by exploiting its inherent electroactivity. The quantification of the ratio of Aβ1-40/42 (or Aβ ratio) has been established as a reliable test to diagnose AD through human clinical trials. Triple barrel carbon fiber microelectrodes were used to simultaneously detect Aβ1-40 and Aβ1-42 in cerebrospinal fluid from rats within a detection range of 100nM to 1.2μM and 400nM to 1μM respectively. In addition, the release of DNA damage/repair biomarker 8-hydroxydeoxyguanine (8-OHdG) under the influence of reactive oxidative stress from single lung endothelial cell was monitored using an activated carbon fiber microelectrode. The sensor was used to test the influence of nicotine, which is one of the most biologically active chemicals present in cigarette smoke and smokeless tobacco.
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The etiology of central nervous system tumors (CNSTs) is mainly unknown. Aside from extremely rare genetic conditions, such as neurofibromatosis and tuberous sclerosis, the only unequivocally identified risk factor is exposure to ionizing radiation, and this explains only a very small fraction of cases. Using meta-analysis, gene networking and bioinformatics methods, this dissertation explored the hypothesis that environmental exposures produce genetic and epigenetic alterations that may be involved in the etiology of CNSTs. A meta-analysis of epidemiological studies of pesticides and pediatric brain tumors revealed a significantly increased risk of brain tumors among children whose mothers had farm-related exposures during pregnancy. A dose response was recognized when this risk estimate was compared to those for risk of brain tumors from maternal exposure to non-agricultural pesticides during pregnancy, and risk of brain tumors among children exposed to agricultural activities. Through meta-analysis of several microarray studies which compared normal tissue to astrocytomas, we were able to identify a list of 554 genes which were differentially expressed in the majority of astrocytomas. Many of these genes have in fact been implicated in development of astrocytoma, including EGFR, HIF-1α, c-Myc, WNT5A, and IDH3A. Reverse engineering of these 554 genes using Bayesian network analysis produced a gene network for each grade of astrocytoma (Grade I-IV), and ‘key genes’ within each grade were identified. Genes found to be most influential to development of the highest grade of astrocytoma, Glioblastoma multiforme (GBM) were: COL4A1, EGFR, BTF3, MPP2, RAB31, CDK4, CD99, ANXA2, TOP2A, and SERBP1. Lastly, bioinformatics analysis of environmental databases and curated published results on GBM was able to identify numerous potential pathways and geneenvironment interactions that may play key roles in astrocytoma development. Findings from this research have strong potential to advance our understanding of the etiology and susceptibility to CNSTs. Validation of our ‘key genes’ and pathways could potentially lead to useful tools for early detection and novel therapeutic options for these tumors.
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Bio-systems are inherently complex information processing systems. Furthermore, physiological complexities of biological systems limit the formation of a hypothesis in terms of behavior and the ability to test hypothesis. More importantly the identification and classification of mutation in patients are centric topics in today's cancer research. Next generation sequencing (NGS) technologies can provide genome-wide coverage at a single nucleotide resolution and at reasonable speed and cost. The unprecedented molecular characterization provided by NGS offers the potential for an individualized approach to treatment. These advances in cancer genomics have enabled scientists to interrogate cancer-specific genomic variants and compare them with the normal variants in the same patient. Analysis of this data provides a catalog of somatic variants, present in tumor genome but not in the normal tissue DNA. In this dissertation, we present a new computational framework to the problem of predicting the number of mutations on a chromosome for a certain patient, which is a fundamental problem in clinical and research fields. We begin this dissertation with the development of a framework system that is capable of utilizing published data from a longitudinal study of patients with acute myeloid leukemia (AML), who's DNA from both normal as well as malignant tissues was subjected to NGS analysis at various points in time. By processing the sequencing data at the time of cancer diagnosis using the components of our framework, we tested it by predicting the genomic regions to be mutated at the time of relapse and, later, by comparing our results with the actual regions that showed mutations (discovered at relapse time). We demonstrate that this coupling of the algorithm pipeline can drastically improve the predictive abilities of searching a reliable molecular signature. Arguably, the most important result of our research is its superior performance to other methods like Radial Basis Function Network, Sequential Minimal Optimization, and Gaussian Process. In the final part of this dissertation, we present a detailed significance, stability and statistical analysis of our model. A performance comparison of the results are presented. This work clearly lays a good foundation for future research for other types of cancer.^
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Fluorescent proteins are valuable tools as biochemical markers for studying cellular processes. Red fluorescent proteins (RFPs) are highly desirable for in vivo applications because they absorb and emit light in the red region of the spectrum where cellular autofluorescence is low. The naturally occurring fluorescent proteins with emission peaks in this region of the spectrum occur in dimeric or tetrameric forms. The development of mutant monomeric variants of RFPs has resulted in several novel FPs known as mFruits. Though oxygen is required for maturation of the chromophore, it is known that photobleaching of FPs is oxygen sensitive, and oxygen-free conditions result in improved photostabilities. Therefore, understanding oxygen diffusion pathways in FPs is important for both photostabilites and maturation of the chromophores. We used molecular dynamics calculations to investigate the protein barrel fluctuations in mCherry, which is one of the most useful monomeric mFruit variants, and its GFP homolog citrine. We employed implicit ligand sampling and locally enhanced sampling to determine oxygen pathways from the bulk solvent into the mCherry chromophore in the interior of the protein. The pathway contains several oxygen hosting pockets, which were identified by the amino acid residues that form the pocket. We calculated the free-energy of an oxygen molecule at points along the path. We also investigated an RFP variant known to be significantly less photostable than mCherry and find much easier oxygen access in this variant. We showed that oxygen pathways can be blocked or altered, and barrel fluctuations can be reduced by strategic amino acid substitutions. The results provide a better understanding of the mechanism of molecular oxygen access into the fully folded mCherry protein barrel and provide insight into the photobleaching process in these proteins.
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The rainbow smelt (Osmerus mordax) is an anadromous teleost that produces type II antifreeze protein (AFP) and accumulates modest urea and high glycerol levels in plasma and tissues as adaptive cryoprotectant mechanisms in sub-zero temperatures. It is known that glyceroneogenesis occurs in liver via a branch in glycolysis and gluconeogenesis and is activated by low temperature; however, the precise mechanisms of glycerol synthesis and trafficking in smelt remain to be elucidated. The objective of this thesis was to provide further insight using functional genomic techniques [e.g. suppression subtractive hybridization (SSH) cDNA library construction, microarray analyses] and molecular analyses [e.g. cloning, quantitative reverse transcription - polymerase chain reaction (QPCR)]. Novel molecular mechanisms related to glyceroneogenesis were deciphered by comparing the transcript expression profiles of glycerol (cold temperature) and non-glycerol (warm temperature) accumulating hepatocytes (Chapter 2) and livers from intact smelt (Chapter 3). Briefly, glycerol synthesis can be initiated from both amino acids and carbohydrate; however carbohydrate appears to be the preferred source when it is readily available. In glycerol accumulating hepatocytes, levels of the hepatic glucose transporter (GLUT2) plummeted and transcript levels of a suite of genes (PEPCK, MDH2, AAT2, GDH and AQP9) associated with the mobilization of amino acids to fuel glycerol synthesis were all transiently higher. In contrast, in glycerol accumulating livers from intact smelt, glycerol synthesis was primarily fuelled by glycogen degradation with higher PGM and PFK (glycolysis) transcript levels. Whether initiated from amino acids or carbohydrate, there were common metabolic underpinnings. Increased PDK2 (an inhibitor of PDH) transcript levels would direct pyruvate derived from amino acids and / or DHAP derived from G6P to glycerol as opposed to oxidation via the citric acid cycle. Robust LIPL (triglyceride catabolism) transcript levels would provide free fatty acids that could be oxidized to fuel ATP synthesis. Increased cGPDH (glyceroneogenesis) transcript levels were not required for increased glycerol production, suggesting that regulation is more likely by post-translational modification. Finally, levels of a transcript potentially encoding glycerol-3-phosphatase, an enzyme not yet characterized in any vertebrate species, were transiently higher. These comparisons also led to the novel discoveries that increased G6Pase (glucose synthesis) and increased GS (glutamine synthesis) transcript levels were part of the low temperature response in smelt. Glucose may provide increased colligative protection against freezing; whereas glutamine could serve to store nitrogen released from amino acid catabolism in a non-toxic form and / or be used to synthesize urea via purine synthesis-uricolysis. Novel key aspects of cryoprotectant osmolyte (glycerol and urea) trafficking were elucidated by cloning and characterizing three aquaglyceroporin (GLP)-encoding genes from smelt at the gene and cDNA levels in Chapter 4. GLPs are integral membrane proteins that facilitate passive movement of water, glycerol and urea across cellular membranes. The highlight was the discovery that AQP10ba transcript levels always increase in posterior kidney only at low temperature. This AQP10b gene paralogue may have evolved to aid in the reabsorption of urea from the proximal tubule. This research has contributed significantly to a general understanding of the cold adaptation response in smelt, and more specifically to the development of a working scenario for the mechanisms involved in glycerol synthesis and trafficking in this species.
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Acknowledgements This study was funded by a BBSRC studentship (MA Wenzel) and NERC grants NE/H00775X/1 and NE/D000602/1 (SB Piertney). The authors are grateful to Fiona Leckie, Andrew MacColl, Jesús Martínez-Padilla, François Mougeot, Steve Redpath, Pablo Vergara† and Lucy M.I. Webster for samples; Keliya Bai, Daisy Brickhill, Edward Graham, Alyson Little, Daniel Mifsud, Lizzie Molyneux and Mario Röder for fieldwork assistance; Gillian Murray-Dickson and Laura Watt for laboratory assistance; Heather Ritchie for helpful comments on manuscript drafts; and all estate owners, factors and keepers for access to field sites, most particularly Stuart Young and Derek Calder (Edinglassie), Simon Blackett, Jim Davidson and Liam Donald (Invercauld and Glas Choille), Richard Cooke and Fred Taylor† (Invermark) and T. Helps (Catterick).
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Peer reviewed
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Peer reviewed
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This article is protected by copyright. All rights reserved. Acknowledgements This study was funded by a BBSRC studentship (MAW) and NERC grants NE/H00775X/1 and NE/D000602/1 (SBP). The authors are grateful to Mario Röder and Keliya Bai for fieldwork assistance, and all estate owners, factors and keepers for access to field sites, most particularly MJ Taylor and Mike Nisbet (Airlie), Neil Brown (Allargue), RR Gledson and David Scrimgeour (Delnadamph), Andrew Salvesen and John Hay (Dinnet), Stuart Young and Derek Calder (Edinglassie), Kirsty Donald and David Busfield (Glen Dye), Neil Hogbin and Ab Taylor (Glen Muick), Alistair Mitchell (Glenlivet), Simon Blackett, Jim Davidson and Liam Donald (Invercauld), Richard Cooke and Fred Taylor† (Invermark), Shaila Rao and Christopher Murphy (Mar Lodge), and Ralph Peters and Philip Astor (Tillypronie). Data accessibility • Genotype data (DataDryad: doi:10.5061/dryad.4t7jk) • Metadata (information on sampling sites, phenotypes and medication regimen) (DataDryad: doi:10.5061/dryad.4t7jk)
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Acknowledgements This work was supported by University of Delhi, Department of Science and Technology- Promotion of University Research and Scientific Excellence (DST-PURSE). V.G., S.H. and U.S. gratefully acknowledge the Council for Scientific and Industrial Research (CSIR), University Grant Commission (UGC) and Department of Biotechnology (DBT) for providing research fellowship.
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We were supported by the Biotechnology and Biological Sciences Research Council grant BB/H001123/1 (P.W.), the Medical Research Council grants G0601498 and G1100546/2 (P.W.), Tenovus Scotland Grant G09/17 (A.J.M.) and the University of Aberdeen (P.W.). We thank O. Tüscher for discussion, P. Teismann and the microscopy core facility at the University of Aberdeen for the use of microscopy equipment, L. Strachan, A. Plano, S. Deiana for help with behavioral testing.
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Metabolic flexibility may be generally defined as “the capacity for the organism to adapt fuel oxidation to fuel availability”. The metabolic diversification strategies used by individual bacteria vary greatly from the use of novel or acquired enzymes to the use of plasmid-localised genes and transporters. In this review, we describe the ability of lactobacilli to utilise a variety of carbon sources from their current or new environments in order to grow and survive. The genus Lactobacillus now includes more than 150 species, many with adaptive capabilities, broad metabolic capacity and species/strain variance. They are therefore, an informative example of a cell factory capable of adapting to new niches with differing nutritional landscapes. Indeed, lactobacilli naturally colonise and grow in a wide variety of environmental niches which include the roots and foliage of plants, silage, various fermented foods and beverages, the human vagina and the mammalian gastrointestinal tract (GIT; including the mouth, stomach, small intestine and large intestine). Here we primarily describe the metabolic flexibility of some lactobacilli isolated from the mammalian gastrointestinal tract, and we also describe some of the food-associated species with a proven ability to adapt to the GIT. As examples this review concentrates on the following species - Lb. plantarum, Lb. acidophilus, Lb. ruminis, Lb. salivarius, Lb. reuteri and Lb. sakei, to highlight the diversity and inter-relationships between the catabolic nature of species within the genus.
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We examined facilitators and barriers to adoption of genomic services for colorectal care, one of the first genomic medicine applications, within the Veterans Health Administration to shed light on areas for practice change. We conducted semi-structured interviews with 58 clinicians to understand use of the following genomic services for colorectal care: family health history documentation, molecular and genetic testing, and genetic counseling. Data collection and analysis were informed by two conceptual frameworks, the Greenhalgh Diffusion of Innovation and Andersen Behavioral Model, to allow for concurrent examination of both access and innovation factors. Specialists were more likely than primary care clinicians to obtain family history to investigate hereditary colorectal cancer (CRC), but with limited detail; clinicians suggested templates to facilitate retrieval and documentation of family history according to guidelines. Clinicians identified advantage of molecular tumor analysis prior to genetic testing, but tumor testing was infrequently used due to perceived low disease burden. Support from genetic counselors was regarded as facilitative for considering hereditary basis of CRC diagnosis, but there was variability in awareness of and access to this expertise. Our data suggest the need for tools and policies to establish and disseminate well-defined processes for accessing services and adhering to guidelines.