Chapter 25 : Genetic Strategies for Identifying New Drug Targets

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Bedaquiline was the first novel antitubercular to be approved by the FDA in over 4 decades ( ); delamanid is likely to follow soon ( ), and there are a number of others in the pipeline (SQ109, linezolid analogues [ ]). In fact, tuberculosis drug development is one of the few dynamic branches of an otherwise stagnating field. Although there is some basic research into antibiotics in general, little progress is being made in bringing suitable leads into the clinic ( ). Only two systemic antibiotics were approved by the FDA between 2008 and 2012, compared to six from 1998 to 2002 and 13 from 1988 to 1992, a number that must increase if we are to retain the upper hand over infectious diseases ( ). While this is, in part, due to stringent FDA regulations and the withdrawal of large pharmaceutical companies from antibiotic research ( ), it is also due to the high attrition rate in antibiotic discovery, which is further exacerbated by the so-called discovery void ( ).

Citation: Trauner A, Sassetti C, Rubin E. 2014. Genetic Strategies for Identifying New Drug Targets, p 493-509. In Hatfull G, Jacobs W (ed), Molecular Genetics of Mycobacteria, Second Edition. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MGM2-0030-2013
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Figure 1

High-frequency transposon mutagenesis. Any gene can have multiple potential transposon insertion sites (marked with dark gray bars). Transposon insertion is usually selected for by using antibiotic markers encoded within it and on a basic level results in the disruption of gene function. Identifying the site of insertion relies on the same principle as genome sequencing. Genomic DNA is sheared and an adaptor of known sequence is ligated to the fragments. In the case of transposon insertion site scoring, the resulting pool is amplified using primers specific for the transposon (in the simplest case these are the same for both flanks of the transposon; P) and a primer specific for the adapter (P). The number of reads mapping to each genomic locus is proportional to the abundance of the strain carrying this insertion. The frequency of transposon insertion reflects gene essentiality. Genes that can tolerate insertions in multiple sites throughout their coding sequence are deemed nonessential. An organism cannot tolerate the disruption of an essential gene; therefore, no insertions can be detected. Genes that are not essential in a wild-type background under “normal” conditions but become essential once the system is suitably perturbed (e.g., low pH, presence of another mutation, drug treatment) provide a special case and are considered conditionally essential. Statistical methods should be used to determine whether a gene has a significantly low number of insertions. More elaborate transposon architectures may include the presence of transcriptional terminators (Ω) or outward-facing inducible promoters (adapted from reference ). Using such systems provides greater information because transposon insertion gains additional modalities that go beyond simple gene disruption. Since the directionality of insertion carries information, it is important to be able to use different primers for each transposon flank (P, P) during insertion scoring.

Citation: Trauner A, Sassetti C, Rubin E. 2014. Genetic Strategies for Identifying New Drug Targets, p 493-509. In Hatfull G, Jacobs W (ed), Molecular Genetics of Mycobacteria, Second Edition. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MGM2-0030-2013
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Figure 2

Summary of genetic approaches to studying drug targets. Both forward- and reverse-genetic approaches can be used to provide overlapping and complementary tools for the investigation of antibiotic targets. The limitations and advantages are summarized in the boxes. The asterisk refers to a mutation within the promoter or coding region resulting in drug resistance. P, promoter; Tn, transposon; EMS, ethyl methanesulfonate; TF, transcription factor; MOA, mechanism of action.

Citation: Trauner A, Sassetti C, Rubin E. 2014. Genetic Strategies for Identifying New Drug Targets, p 493-509. In Hatfull G, Jacobs W (ed), Molecular Genetics of Mycobacteria, Second Edition. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.MGM2-0030-2013
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