7 resultados para Gene Knockdown Techniques

em Aston University Research Archive


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Introduction: Gene therapy continues to grow as an important area of research, primarily because of its potential in the treatment of disease. One significant area where there is a need for better understanding is in improving the efficiency of oligonucleotide delivery to the cell and indeed, following delivery, the characterization of the effects on the cell. Methods: In this report, we compare different transfection reagents as delivery vehicles for gold nanoparticles functionalized with DNA oligonucleotides, and quantify their relative transfection efficiencies. The inhibitory properties of small interfering RNA (siRNA), single-stranded RNA (ssRNA) and single-stranded DNA (ssDNA) sequences targeted to human metallothionein hMT-IIa are also quantified in HeLa cells. Techniques used in this study include fluorescence and confocal microscopy, qPCR and Western analysis. Findings: We show that the use of transfection reagents does significantly increase nanoparticle transfection efficiencies. Furthermore, siRNA, ssRNA and ssDNA sequences all have comparable inhibitory properties to ssDNA sequences immobilized onto gold nanoparticles. We also show that functionalized gold nanoparticles can co-localize with autophagosomes and illustrate other factors that can affect data collection and interpretation when performing studies with functionalized nanoparticles. Conclusions: The desired outcome for biological knockdown studies is the efficient reduction of a specific target; which we demonstrate by using ssDNA inhibitory sequences targeted to human metallothionein IIa gene transcripts that result in the knockdown of both the mRNA transcript and the target protein. © 2014 Jiwaji et al.

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Redox-sensitive cell signalling Thiol groups and the regulation of gene expression Redox-sensitive signal transduction pathways Protein kinases Protein phosphatases Lipids and phospholipases Antioxidant (electrophile) response element Intracellular calcium signalling Transcription factors NF-?B AP-1 p53 Cellular responses to oxidative stress Cellular responses to change in redox state Proliferation Cell death Immune cell function Reactive oxygen and nitrogen species – good or bad? Reactive oxygen species and cell death Reactive oxygen species and inflammation Are specific reactive oxygen species and antioxidants involved in modulating cellular responses? Specific effects of dietary antioxidants in cell regulation Carotenoids Vitamin E Flavonoids Inducers of phase II enzymes Disease states affected Oxidants, antioxidants and mitochondria Introduction Mitochondrial generation of reactive oxygen and nitrogen species Mitochondria and apoptosis Mitochondria and antioxidant defences Key role of mitochondrial GSH in the defence against oxidative damage Mitochondrial oxidative damage Direct oxidative damage to the mitochondrial electron transport chain Nitric oxide and damage to mitochondria Effects of nutrients on mitochondria Caloric restriction and antioxidants Lipids Antioxidants Techniques and approaches Mitochondrial techniques cDNA microarray approaches Proteomics approaches Transgenic mice as tools in antioxidant research Gene knockout and over expression Transgenic reporter mice Conclusions Future research needs

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The availability of ‘omics’ technologies is transforming scientific approaches to physiological problems from a reductionist viewpoint to that of a holistic viewpoint. This is of profound importance in nutrition, since the integration of multiple systems at the level of gene expression on the synthetic side through to metabolic enzyme activity on the degradative side combine to govern nutrient availability to tissues. Protein activity is central to the process of nutrition from the initial absorption of nutrients via uptake carriers in the gut, through to distribution and transport in the blood, metabolism by degradative enzymes in tissues and excretion through renal tubule exchange proteins. Therefore, the global profiling of the proteome, defined as the entire protein complement of the genome expressed in a particular cell or organ, or in plasma or serum at a particular time, offers the potential for identification of important biomarkers of nutritional state that respond to alterations in diet. The present review considers the published evidence of nutritional modulation of the proteome in vivo which has expanded exponentially over the last 3 years. It highlights some of the challenges faced by researchers using proteomic approaches to understand the interactions of diet with genomic and metabolic–phenotypic variables in normal populations.

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The hypoxia-inducible factor (HIF) is a key regulator of the cellular response to hypoxia which promotes oxygen delivery and metabolic adaptation to oxygen deprivation. However, the degree and duration of HIF-1α expression in hypoxia must be carefully balanced within cells in order to avoid unwanted side effects associated with excessive activity. The expression of HIF-1α mRNA is suppressed in prolonged hypoxia, suggesting that the control of HIF1A gene transcription is tightly regulated by negative feedback mechanisms. Little is known about the resolution of the HIF-1α protein response and the suppression of HIF-1α mRNA in prolonged hypoxia. Here, we demonstrate that the Repressor Element 1-Silencing Transcription factor (REST) binds to the HIF-1α promoter in a hypoxia-dependent manner. Knockdown of REST using RNAi increases the expression of HIF-1α mRNA, protein and transcriptional activity. Furthermore REST knockdown increases glucose consumption and lactate production in a HIF-1α- (but not HIF-2α-) dependent manner. Finally, REST promotes the resolution of HIF-1α protein expression in prolonged hypoxia. In conclusion, we hypothesize that REST represses transcription of HIF-1α in prolonged hypoxia, thus contributing to the resolution of the HIF-1α response.

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Although techniques such as biopanning rely heavily upon the screening of randomized gene libraries, there is surprisingly little information available on the construction of those libraries. In general, it is based on the cloning of 'randomized' synthetic oligonucleotides, in which given position(s) contain an equal mixture of all four bases. Yet, many supposedly 'randomized' libraries contain significant elements of bias and/or omission. Here, we report the development and validation of a new, PCR-based assay that enables rapid examination of library composition both prior to and after cloning. By using our assay to analyse model libraries, we demonstrate that the cloning of a given distribution of sequences does not necessarily result in a similarly composed library of clones. Thus, while bias in randomized synthetic oligonucleotide mixtures can be virtually eliminated by using unequal ratios of the four phosphoramidites, the use of such mixtures does not ensure retrieval of a truly randomized library. We propose that in the absence of a technique to control cloning frequencies, the ability to analyse the composition of libraries after cloning will enhance significantly the quality of information derived from those libraries. (C) 2000 Published by Elsevier Science B.V. All rights reserved.

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Glioblastoma multiforme (GBM) is a malignant brain tumour for which there is currently no effective treatment regime. It is thought to develop due to the overexpression of a number of genes, including the epidermal growth factor receptor (EGFR), which is found in over 40% of GBM. Novel forms of treatment such as antisense therapy may allow for the specific inhibition of aberrant genes and thus they are optimistic therapies for future treatment of GBM. Oligodeoxynucleotides (ODNs) are small pieces of DNA that are often modified to increase their stability to nucleases and can be targeted to the aberrant gene in order to inhibit it and thus prevent its transcription into protein. By specifically binding to mRNA in an antisense manner, they can bring about its degradation by a variety of mechanisms including the activation of RNase H and thus have great potential as therapeutic agents. One of the main drawbacks to the utilisation of this therapy so far is the lack of techniques that can successfully predict accessible regions on the target mRNA that the ODNs can bind to. DNA chip technology has been utilised here to predict target sequences on the EGFR mRNA and these ODNs (AS 1 and AS2) have been tested in vitro for their stability, uptake into cells and their efficacy on cellular growth, EGFR protein and mRNA. Studies showed that phosphorothioate and 2'O-methyl ODNs were significantly more stable than phosphodiester ODNs both in serum and serum-free conditions and that the mechanism of uptake into A431 cells was temperature dependent and more efficient with the use of optimised lipofectin. Efficacy results show that AS 1 and AS2 phosphorothioate antisense ODNs were capable of inhibiting cell proliferation by 69% ±4% and 65% ±4.5% respectively at 500nM in conjunction with a non-toxic dose of lipofectinTM used to enhance cellular delivery. Furthermore, control ODN sequences, 2' O-methyl derivatives and a third ODN sequence, that was found not to be capable of binding efficiently to the EGFR mRNA by DNA chip technology, showed no significant effect on cell proliferation. AS 1 almost completely inhibited EGFR protein levels within 48 hours with two doses of 500nM AS 1 with no effect on other EGFR family member proteins or by control sequences. RNA analysis showed a decrease in mRNA levels of 32.4% ±0.8% but techniques require further optimisation to confirm this. As there are variations found between human glioblastoma in situ and those developed as xenografts, analysis of effect of AS 1 and AS2 was performed on primary tumour cell lines derived from glioma patients. ODN treatment showed a specific knockdown of cell growth compared to any of the controls used. Furthermore, combination therapies were tested on A431 cell growth to determine the advantage of combining different antisense approaches and that of conventional drugs. Results varied between the combination treatments but indicated that with optimisation of treatment regimes and delivery techniques that combination therapies utilising antisense therapies would be plausible.

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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.