bioRxivMicrobiology
Isolation of Genomic Deoxyxylulose Phosphate Reductoisomerase (DXR) Mutations Conferring Resistance to Fosmidomycin
G. Pines, M. C. Bassalo, E. J. Oh, A. Choudhury, A. D. Garst, R. T. Gill
Abstract
Sequence to activity mapping technologies are rapidly developing, enabling the isolation of mutations that confer novel phenotypes. Here we used the CRISPR EnAbled Trackable genome Engineering (CREATE) technology to investigate the inhibition of the essential IspC gene in Escherichia coli. IspC gene product, Deoxyxylulose Phosphate Reductoisomerase (DXR), converts 1-deoxy-D-xylulose 5-phosphate to 2-C-methyl-D-erythritol 4-phosphate in the DXP pathway. Since this pathway is shared with many pathogenic bacteria and protozoa and is missing in humans, it is an appealing target for inhibition. We created a full saturation library of 33 sites proximal to ligand binding and other sites and challenged it with the DXR-specific inhibitor, fosmidomycin. We identified several mutations that confer fosmidomycin resistance. All sites are highly conserved and also exist in pathogens including the malaria-inducing Plasmodium falciparum. These findings may have general implications on the isolation of resistance-conferring mutations and specifically, may affect the design of future generations of fosmidomycin-based drugs.\n\nSignificanceThe emergence of acquired drug resistance is a natural process that is likely to occur under most circumstances. Recently-developed technologies allow to map relative fitness contribution of multiple mutations in parallel. Such approaches may be used to predict which mutations are most likely to confer resistance, instead of waiting for them to evolve spontaneously. In this study, a rationally-designed IspC mutant library was generated genomically in E. coli. Mutants resistant to fosmidomycin, an antimalarial drug were identified, and most were in the highly conserved proline at position 274. These results may have implications on next-generation fosmidomycin drug design, and more broadly, this approach may be used for predicting mutational acquired resistance.
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