Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/15942
Title: Diagnostic expression profiles for mechanism of inhibitor action in mycobacteria
Authors: PAUL MURIMA
Keywords: Gene Expression, Drug Discovery, Antibiotic Mode of action.
Issue Date: 27-May-2009
Source: PAUL MURIMA (2009-05-27). Diagnostic expression profiles for mechanism of inhibitor action in mycobacteria. ScholarBank@NUS Repository.
Abstract: The rapid development of antibiotic resistance in Mycobacterium tuberculosis threatens the effectiveness of the current chemotherapy, thus raising the need for novel structural classes of antibiotics. A critical bottleneck for cell-based screens in the discovery of novel anti-mycobacterial agents stems from the limited understanding of the mechanism of action (MoA) of bioactive compounds. Prediction of targets and MoA for inhibitors that manifest a bactericidal or bacteriostatic activity is further limited by the incomplete understanding of the physiology of the bacilli. Genome wide expression profiling generated by microarrays has been used to observe differential expression in response to environmental stimuli. A reference compendium of transcription signatures of bacteria treated with inhibitors of known MOA can provide a valuable reference useful for both pathway characterization and prediction of MOA of uncharacterized inhibitors.We selected a subset of 90 genes from the transcription signatures of drugs and chemical genetics leads as diagnostic probes using feature reduction techniques. A quantitative polymerase chain reaction (Q-PCR) array with characteristic expression signatures for anti-mycobacterial drugs and drug candidates was defined. Independent, unbiased grouping of Q-PCR transcription profiles clustered inhibitors based on the mechanism of action. We have evidence to suggest that Q-PCR arrays can be used to characterise transcription fingerprints of early chemical genetics and whole cell screen leads. However, the data set is relatively small and a larger library of expression profiles would be needed to fully establish its predictive accuracy.
URI: http://scholarbank.nus.edu.sg/handle/10635/15942
Appears in Collections:Master's Theses (Open)

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2D heatmap.txt347 BText

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CORRELATIONMATRIX.DRUGS.txt306 BText

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CORRELATIONMATRIX.GENES.txt366 BText

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SELECTED FEATURES DENDROGRAM.txt208 BText

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2D HEATMAP.txt361 BText

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TRAINING SET DENDROGRAM.txt189 BText

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2D HEATMAP.RTPCR.txt375 BText

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