Revealing fosfomycin primary effect on Staphylococcus aureus transcriptome: modulation of cell envelope biosynthesis and phosphoenolpyruvate induced starvation
- Equal contributors
1 Department of Biotechnology and Systems Biology, National Institute of Biology, Večna pot 111, Ljubljana, SI-1000, Slovenia
2 Novartis BPO Mengeš, Lek Pharmaceuticals d.d., Kolodvorska 27, Mengeš, SI-1234, Slovenia
3 Department of Biology, Biotechnical Faculty, University of Ljubljana, Jamnikarjeva 101, Ljubljana, SI-1000, Slovenia
BMC Microbiology 2010, 10:159 doi:10.1186/1471-2180-10-159Published: 1 June 2010
Staphylococcus aureus is a highly adaptable human pathogen and there is a constant search for effective antibiotics. Fosfomycin is a potent irreversible inhibitor of MurA, an enolpyruvyl transferase that uses phosphoenolpyruvate as substrate. The goal of this study was to identify the pathways and processes primarily affected by fosfomycin at the genome-wide transcriptome level to aid development of new drugs.
S. aureus ATCC 29213 cells were treated with sub-MIC concentrations of fosfomycin and harvested at 10, 20 and 40 minutes after treatment. S. aureus GeneChip statistical data analysis was complemented by gene set enrichment analysis. A visualization tool for mapping gene expression data into biological pathways was developed in order to identify the metabolic processes affected by fosfomycin. We have shown that the number of significantly differentially expressed genes in treated cultures increased with time and with increasing fosfomycin concentration. The target pathway - peptidoglycan biosynthesis - was upregulated following fosfomycin treatment. Modulation of transport processes, cofactor biosynthesis, energy metabolism and nucleic acid biosynthesis was also observed.
Several pathways and genes downregulated by fosfomycin have been identified, in contrast to previously described cell wall active antibiotics, and was explained by starvation response induced by phosphoenolpyruvate accumulation. Transcriptomic profiling, in combination with meta-analysis, has been shown to be a valuable tool in determining bacterial response to a specific antibiotic.