4 resultados para gene construct

em Aston University Research Archive


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Background - Our previous studies showed that the direct injection of an adenovirus construct expressing urokinase-type plasminogen activator (uPA) into experimental venous thrombi significantly reduces thrombus weight. The systemic use of adenovirus vectors is limited by inherent hepatic tropism and inflammatory response. As macrophages are recruited into venous thrombi, it is reasonable to speculate that these cells could be used to target the adenovirus uPA (ad-uPA) gene construct to the thrombus. The aims of this study were to determine whether macrophages transduced with ad-uPA have increased fibrinolytic activity and whether systemic injection of transduced cells could be used to target uPA expression to the thrombus and reduce its size. Methods - The effect of up-regulating uPA was examined in an immortalized macrophage cell line (MM6) and macrophages differentiated from human blood monocyte-derived macrophages (HBMMs). Cells were infected with ad-uPA or blank control virus (ad-blank). Fibrinolytic mediator expression, cell viability, and cytokine expression were measured by activity assays and enzyme-linked immunosorbent assays. Monocyte migration was measured using a modified Boyden chamber assay. A model of venous thrombosis was developed and characterized in mice with severe combined immunodeficiency (SCID). This model was used to study whether systemically administered macrophages over-expressing uPA reduced thrombus size. Uptake of HBMMs into the thrombus induced in these mice was confirmed by a combination of PKH2-labeled cell tracking and colocalization with human leukocyte antigen (HLA) by immunohistology. Results - Compared with ad-blank, treated HBMMs transduction with ad-uPA increased uPA production by >1000-fold (P = .003), uPA activity by 150-fold (P = .0001), and soluble uPA receptor (uPAR) by almost twofold (P = .043). Expression of plasminogen activator inhibitor (PAI-1) and PAI-2 was decreased by about twofold (P = .011) and threefold (P = .005), respectively. Up-regulation of uPA had no effect on cell viability or inflammatory cytokine production compared with ad-blank or untreated cells. Ad-uPA transduction increased the migration rate of HBMMs (about 20%, P = .03) and MM6 cells (>twofold, P = .005) compared with ad-blank treated controls. Human macrophage recruitment into the mouse thrombus was confirmed by the colocalization of HLA with the PKH2-marked cells. Systemic injection of uPA-up-regulated HBMMs reduced thrombus weight by approximately 20% compared with ad-blank (P = .038) or sham-treated controls (P = .0028). Conclusion - Transduction of HBBM with ad-uPA increases their fibrinolytic activity. Systemic administration of uPA up-regulated HBBMs reduced thrombus size in an experimental model of venous thrombosis. Alternative methods of delivering fibrinolytic agents are worth exploring.

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The aim of this work was to construct short analogues of the repetitive water-binding domain of the Pseudomonas syringae ice nucleation protein, InaZ. Structural analysis of these analogues might provide data pertaining to the protein-water contacts that underlie ice nucleation. An artificial gene coding for a 48-mer repeat sequence from InaZ was synthesized from four oligodeoxyribonucleotides and ligated into the expression vector, pGEX2T. The recombinant vector was cloned in Escherichia coli and a glutathione S-transferase fusion protein obtained. This fusion protein displayed a low level of ice-nucleating activity when tested by a droplet freezing assay. The fusion protein could be cleaved with thrombin, providing a means for future recovery of the 48-mer peptide in amounts suitable for structural analysis by nuclear magnetic resonance spectroscopy.

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Improved methods of insulin delivery are required for the treatment of insulin-dependent diabetes mellitus (IDDM) to achieve a more physiological profile of glucose homeostasis. Somatic cell gene therapy offers the prospect that insulin could be delivered by an autologous cell implant, engineered to secrete insulin in response to glucose. This study explores the feasibility of manipulating somatic cells to behave as a surrogate insulin-secreting β-cells. Initial studies were conducted using mouse pituitary AtT20 cells as a model, since these cells possess an endogenous complement of enzymes capable of processing proinsulin to mature insulin. Glucose sensitive insulin secretion was conferred to these cells by transfection with plasmids containing the human preproinsulin gene (hppI-1) and the GLUT2 gene for the glucose transporter isoform 2. Insulin secretion was responsive to changes in the glucose concentration up to about 50μM. Further studies to up-rate this glucose sensitivity into the mM range will require manipulation of the hexokinase and glucokinase enzymes. Intraperitoneal implantation of the manipulated AtT20 cells into athymic nude mice with streptozotocin-induced diabetes resulted in decreased plasma glucose concentrations. The cells formed vascularised tumours in vivo which were shown to contain insulin-secreting cells. To achieve proinsulin processing in non-endocrine cells, co-transfection with a suitable enzyme, or mutagenesis of the proinsulin itself are necessary. The mutation of the human preproinsulin gene to the consensus sequence for cleavage by the subtilisin-like serine protease, furin, was carried out. Co-transfection of human fibroblasts with wild-type proinsulin and furin resulted in 58% conversion to mature insulin by these cells. Intraperitoneal implantation of the mature-insulin secreting human fibroblasts into the diabetic nude mouse animal model gave less encouraging results than the AtT20 cells, apparently due to poor vascularisation. Cell aggregations removed from the mice at autopsy were shown to contain insulin secreting cells only at the periphery. This thesis provides evidence that it is possible to construct, by cellular engineering, a glucose-sensitive insulin-secreting surrogate β-cell. Therefore, somatic cell gene therapy offers a feasible alternative for insulin delivery in IDDM patients.

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Background: The controversy surrounding the non-uniqueness of predictive gene lists (PGL) of small selected subsets of genes from very large potential candidates as available in DNA microarray experiments is now widely acknowledged 1. Many of these studies have focused on constructing discriminative semi-parametric models and as such are also subject to the issue of random correlations of sparse model selection in high dimensional spaces. In this work we outline a different approach based around an unsupervised patient-specific nonlinear topographic projection in predictive gene lists. Methods: We construct nonlinear topographic projection maps based on inter-patient gene-list relative dissimilarities. The Neuroscale, the Stochastic Neighbor Embedding(SNE) and the Locally Linear Embedding(LLE) techniques have been used to construct two-dimensional projective visualisation plots of 70 dimensional PGLs per patient, classifiers are also constructed to identify the prognosis indicator of each patient using the resulting projections from those visualisation techniques and investigate whether a-posteriori two prognosis groups are separable on the evidence of the gene lists. A literature-proposed predictive gene list for breast cancer is benchmarked against a separate gene list using the above methods. Generalisation ability is investigated by using the mapping capability of Neuroscale to visualise the follow-up study, but based on the projections derived from the original dataset. Results: The results indicate that small subsets of patient-specific PGLs have insufficient prognostic dissimilarity to permit a distinction between two prognosis patients. Uncertainty and diversity across multiple gene expressions prevents unambiguous or even confident patient grouping. Comparative projections across different PGLs provide similar results. Conclusion: The random correlation effect to an arbitrary outcome induced by small subset selection from very high dimensional interrelated gene expression profiles leads to an outcome with associated uncertainty. This continuum and uncertainty precludes any attempts at constructing discriminative classifiers. However a patient's gene expression profile could possibly be used in treatment planning, based on knowledge of other patients' responses. We conclude that many of the patients involved in such medical studies are intrinsically unclassifiable on the basis of provided PGL evidence. This additional category of 'unclassifiable' should be accommodated within medical decision support systems if serious errors and unnecessary adjuvant therapy are to be avoided.