ena-STUDY-Centre for Infectious Diseases & Microbiology-07-03-2019-00:06:30:301-243
Transcriptomic signatures uncover key metabolic determinants of the drug interaction between trimethoprim and erythromycin
Understanding interactions between antibiotics used in combination is an important research theme in microbiology , but our current knowledge of drug-drug interactions at a mechanistic level is limited. Using the interactions between an antifolate drug trimethoprim and a ribosome-targeting antibiotic erythromycin as a model, we present a transcriptomic approach for dissecting interactions between two antibiotics with different modes of action. When trimethoprim and erythromycin were combined, the transcriptional response of genes from the sulfate reduction pathway in Escherichia coli escaped the dominant effect of trimethoprim  on the transcriptome. Based on these findings, we successfully altered the drug interaction from additivity to suppression by changing the sulfate level in the growth medium and identified sulfate reduction as an important metabolic determinant that shapes the interaction between the two drugs. Our work highlights the potential of using transcriptomics as a tool for dissecting pairwise interactions between antibiotics and identifying key factors that shape drug-drug interactions.
Understanding interactions between antibiotics used in combination is an important research theme in microbiology , but our current knowledge of drug-drug interactions at a mechanistic level is limited. Using the interactions between an antifolate drug trimethoprim and a ribosome-targeting antibiotic erythromycin as a model, we present a transcriptomic approach for dissecting interactions between two antibiotics with different modes of action. When trimethoprim and erythromycin were combined, the transcriptional response of genes from the sulfate reduction pathway in Escherichia coli escaped the dominant effect of trimethoprim  on the transcriptome. Based on these findings, we successfully altered the drug interaction from additivity to suppression by changing the sulfate level in the growth medium and identified sulfate reduction as an important metabolic determinant that shapes the interaction between the two drugs. Our work highlights the potential of using transcriptomics as a tool for dissecting pairwise interactions between antibiotics and identifying key factors that shape drug-drug interactions.