Abstract
Staphylococcus aureus is a Gram-positive pathogenic bacterium that colonizes an estimated one-third of the human population and can cause a wide spectrum of disease, ranging from superficial skin infections to life-threatening sepsis. The adaptive mechanisms that contribute to the success of this pathogen remain obscure partially due to a lack of knowledge of its metabolic requirements. Systems biology approaches can be extremely useful in predicting and interpreting metabolic phenotypes; however, such approaches rely on a chemically defined minimal medium as a basis to investigate the requirements of the cell. In this study, a chemically defined minimal medium formulation, termed synthetic minimal medium (SMM), was investigated and validated to support growth of three S. aureus strains: LAC and TCH1516 (USA300 lineage), as well as D592 (USA100 lineage). The formulated SMM was used in an adaptive laboratory evolution experiment to probe the various mutational trajectories of all three strains leading to optimized growth capabilities. The evolved strains were phenotypically characterized for their growth rate and antimicrobial susceptibility. Strains were also resequenced to examine the genetic basis for observed changes in phenotype and to design follow-up metabolite supplementation assays. Our results reveal evolutionary trajectories that arose from strain-specific metabolic requirements. SMM and the evolved strains can also serve as important tools to study antibiotic resistance phenotypes of S. aureus.
Original language | English |
---|---|
Article number | e01773-19 |
Journal | Applied and Environmental Microbiology |
Volume | 85 |
Issue number | 21 |
DOIs | |
Publication status | Published - 1 Nov 2019 |
Bibliographical note
Funding Information:H.M., L.L.W., N.D., Y.S., M.H., V.N., B.O.P., and A.M.F. were funded through an NIH NIAID grant (U01-AI124316).
Publisher Copyright:
© 2019 American Society for Microbiology.
Other keywords
- Adaptive laboratory evolution
- Staphylococcus aureus
- Systems biology