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. 2003 Sep;47(9):2903-13.
doi: 10.1128/AAC.47.9.2903-2913.2003.

Signature gene expression profiles discriminate between isoniazid-, thiolactomycin-, and triclosan-treated Mycobacterium tuberculosis

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Signature gene expression profiles discriminate between isoniazid-, thiolactomycin-, and triclosan-treated Mycobacterium tuberculosis

Joanna C Betts et al. Antimicrob Agents Chemother. 2003 Sep.

Abstract

Genomic technologies have the potential to greatly increase the efficiency of the drug development process. As part of our tuberculosis drug discovery program, we used DNA microarray technology to profile drug-induced effects in Mycobacterium tuberculosis. Expression profiles of M. tuberculosis treated with compounds that inhibit key metabolic pathways are required as references for the assessment of novel antimycobacterial agents. We have studied the response of M. tuberculosis to treatment with the mycolic acid biosynthesis inhibitors isoniazid, thiolactomycin, and triclosan. Thiolactomycin targets the beta-ketoacyl-acyl carrier protein (ACP) synthases KasA and KasB, while triclosan inhibits the enoyl-ACP reductase InhA. However, controversy surrounds the precise mode of action of isoniazid, with both InhA and KasA having been proposed as the primary target. We have shown that although the global response profiles of isoniazid and thiolactomycin are more closely related to each other than to that of triclosan, there are differences that distinguish the mode of action of these two drugs. In addition, we have identified two groups of genes, possibly forming efflux and detoxification systems, through which M. tuberculosis may limit the effects of triclosan. We have developed a mathematical model, based on the expression of 21 genes, which is able to perfectly discriminate between isoniazid-, thiolactomycin-, or triclosan-treated M. tuberculosis. This model is likely to prove invaluable as a tool to improve the efficiency of our drug development programs by providing a means to rapidly confirm the mode of action of thiolactomycin analogues or novel InhA inhibitors as well as helping to translate enzyme activity into whole-cell activity.

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Figures

FIG. 1.
FIG. 1.
Overlap of genes regulated by isoniazid, thiolactomycin, or triclosan treatment of M. tuberculosis. Numbers within the sectors indicate the total numbers of genes regulated uniquely or in common by either 1× or 5× MIC treatment of each drug at either 2 or 6 h (P < 0.001). INH, isoniazid; TLM, thiolactomycin; TRC, triclosan.
FIG. 2.
FIG. 2.
Two-dimensional cluster analysis of the drug-treated expression profiles. Two-dimensional agglomerative clustering was performed on the 877 genes significantly regulated in response to any of the drug treatments (P < 0.001). The individual genes are represented on the x axis and the different samples are indicated on the y axis. Red, upregulation; green, downregulation; black, no change relative to the time zero control. INH, isoniazid; TLM, thiolactomycin; TRC, triclosan.
FIG. 3.
FIG. 3.
Response of the kas operon to isoniazid, thiolactomycin, or triclosan treatment as measured by QRT-PCR. (A) Schematic representation of the kas operon in the M. tuberculosis H37Rv genome. Ratio between the number of cDNA copies detected in each sample relative to the time zero control by QRT-PCR at 2 h (B) and 6 h (C) is represented. Each value is the average of two biological replicates, each analyzed in duplicate. INH, isoniazid; TLM, thiolactomycin; TRC, triclosan.
FIG. 4.
FIG. 4.
Genes induced by triclosan treatment of M. tuberculosis as measured by QRT-PCR. Organization of Rv1685c to Rv1687c (A) and Rv3160c to Rv3161c (C) in the M. tuberculosis H37Rv genome. Ratio between the number of cDNA copies detected in each sample relative to the time zero control by QRT-PCR for Rv1685c to Rv1687c (B) and Rv3160c to Rv3161c (D). Each value is the average of two biological replicates, each analyzed in duplicate. TRC, triclosan.
FIG. 5.
FIG. 5.
PCA of isoniazid, thiolactomycin, triclosan, and control expression profiles. The largest source of variance is explained on the x axis and the second largest on the y axis. Each hybridization is represented by a single point. Isoniazid treatments, circles; thiolactomycin treatments, triangles; triclosan treatments, squares; vehicle control treatments, diamonds. Two-hour treatments, open shapes; 6-h treatments, closed shapes. 1× MIC, black; 5× MIC, red; vehicle control, blue.

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References

    1. Alland, D., I. Kramnik, T. R. Weisbrod, L. Otsubo, R. Cerny, L. P. J. W. Miller, and B. R. Bloom. 1998. Identification of differentially expressed mRNA in prokaryotic organisms by customized amplification libraries (DECAL)—the effect of isoniazid on gene expression in Mycobacterium tuberculosis. Proc. Natl. Acad. Sci. USA 95:13227-13232. - PMC - PubMed
    1. Bammert, G., and J. Fostel. 2000. Genome-wide expression patterns in Saccharomyces cerevisiae: comparison of drug treatments and genetic alterations affecting biosynthesis of ergosterol. Antimicrob. Agents Chemother. 44:1255-1265. - PMC - PubMed
    1. Banerjee, A., E. Dubnau, A. Quemard, A. S. Balasubramanian, K. S. Um, T. Wilson, D. Collins, G. W. de Lisle, and W. R. Jacobs. 1994. inhA, a gene encoding a target for isoniazid and ethionamide in Mycobacterium tuberculosis. Science 263:227-230. - PubMed
    1. Barry, C. E., M. Wilson, R. Lee, and G. K. Schoolnik. 2000. DNA microarrays and combinatorial chemical libraries: tools for the drug discovery pipeline. Int. J. Tuberc. Lung Dis. 4:S189-S193. - PubMed
    1. Betts, J. C. 2002. Transcriptomics and proteomics: tools for the identification of novel drug targets and vaccine candidates for tuberculosis. IUBMB Life 53:239-242. - PubMed

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