Profiling the effect of nafcillin on HA-MRSA D712 using bacteriological and physiological media

Akanksha Rajput, Saugat Poudel, Hannah Tsunemoto, Michael Meehan, Richard Szubin, Connor A. Olson, Anne Lamsa, Yara Seif, Nicholas Dillon, Alison Vrbanac, Joseph Sugie, Samira Dahesh, Jonathan M. Monk, Pieter C. Dorrestein, Rob Knight, Victor Nizet, Bernhard O. Palsson, Adam M. Feist

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Abstract

Staphylococcus aureus strains have been continuously evolving resistance to numerous classes of antibiotics including methicillin, vancomycin, daptomycin and linezolid, compounding the enormous healthcare and economic burden of the pathogen. Cation-adjusted Mueller-Hinton broth (CA-MHB) is the standard bacteriological media for measuring antibiotic susceptibility in the clinical lab, but the use of media that more closely mimic the physiological state of the patient, e.g. mammalian tissue culture media, can in certain circumstances reveal antibiotic activities that may be more predictive of effectiveness in vivo. In the current study, we use both types of media to explore antibiotic resistance phenomena in hospital-acquired USA100 lineage methicillin-resistant, vancomycin-intermediate Staphylococcus aureus (MRSA/VISA) strain D712 via multidimensional high throughput analysis of growth rates, bacterial cytological profiling, RNA sequencing, and exo-metabolomics (HPLC and LC-MS). Here, we share data generated from these assays to shed light on the antibiotic resistance behavior of MRSA/VISA D712 in both bacteriological and physiological media.
Original languageEnglish
Article number322
JournalScientific Data
Volume6
Issue number1
ISSN2052-4463
DOIs
Publication statusPublished - 2019

Cite this

Rajput, A., Poudel, S., Tsunemoto, H., Meehan, M., Szubin, R., Olson, C. A., Lamsa, A., Seif, Y., Dillon, N., Vrbanac, A., Sugie, J., Dahesh, S., Monk, J. M., Dorrestein, P. C., Knight, R., Nizet, V., Palsson, B. O., & Feist, A. M. (2019). Profiling the effect of nafcillin on HA-MRSA D712 using bacteriological and physiological media. Scientific Data, 6(1), [322]. https://doi.org/10.1038/s41597-019-0331-z