Kelly Hines (Presenter)
University of Washington
Authorship: Kelly M. Hines(1), Adam Waalkes(2), Kelsi Penewit(2), Elizabeth A. Holmes(2), Stephen J. Salipante(2), Brian J. Werth(3), and Libin Xu(1)
(1)Department of Medicinal Chemistry, University of Washington School of Pharmacy, Seattle, WA; (2)Department of Laboratory Medicine, University of Washington, Seattle, WA; (3)Department of Pharmacy, University of Washington School of Pharmacy, Seattle, WA
| Short Abstract Lipopeptide and lipoglycopeptide antimicrobials daptomycin and dalbavancin, respectively, were developed as last-resort therapies for the management of MRSA, but emerging cross-resistance among these therapies and the glycopeptide vancomycin is a threat to patient outcomes. β-Lactam antimicrobials are known to exhibit a “seesaw effect” with vancomycin and daptomycin, whereby β-lactam minimum inhibitory concentrations (MICs) decrease as daptomycin and vancomycin MICs increase. We have evaluated membrane lipid content, β-lactam susceptibilities and genetic mutations of in vitro derived mutants of MRSA strain N315 with resistance to vancomycin, daptomycin and dalbavancin to develop predictive signatures of cross-resistance and the β-lactam “seesaw effect". |
Long Abstract
Introduction
Methicillin-resistant Staphylococcus aureus (MRSA) is among one of the most serious antimicrobial resistance concerns and accounts for nearly 11,000 deaths per year.[1] The glycopeptide (GP) vancomycin is the first-line antimicrobial therapy for the treatment of MRSA. However, approximately 40% of patients with MRSA will fail therapy, and 20% will die despite vancomycin treatment.[2-4] Lipopeptide (LP) and lipoglycopeptide (LGP) antimicrobials daptomycin and dalbavancin, respectively, were developed as last-resort therapies for the management of MRSA, but emerging cross-resistance among these therapies is a threat to patient outcomes. Genetic studies of GP, LP and LGP resistance have found mutations in cell envelope stress response genes, including members of the vraTSR and yycFG multi-component regulatory systems.[5, 6] β-lactam antimicrobials are known to exhibit a “seesaw effect” with vancomycin and daptomycin in GP/LP/LGP-resistant bacteria, whereby β-lactam minimum inhibitory concentrations (MICs) decrease as daptomycin and vancomycin MICs increase.[7-10] One possible explanation is the interaction of β-lactams with the same cell envelope stress response systems that are mutated in GP/LP/LGP resistance.[11,12] To develop predictive signatures of the β-lactam “seesaw effect,” we have evaluated membrane lipid content, β-lactam susceptibilities and genetic mutations of in vitro derived mutants of MRSA strain N315 with resistance to vancomycin, daptomycin, and/or dalbavancin.
Methods
Isogenic in vitro derived mutants of MRSA strain N315 with reduced susceptibility to vancomycin (VAN-8, MIC 8 µg/mL), daptomycin (DAP-1, MIC 1 µg/mL), dalbavancin (DAL-0.5, MIC 0.5 µg/mL), moxifloxacin (MOX, MIC 32 µg/mL) and doxycycline (DOX, MIC 2 µg/mL) were selected using a serial passage method. All mutants were evaluated for susceptibility to vancomycin, daptomycin, dalbavancin and the β-lactams nafcillin and cephalexin. Whole genome sequencing was performed for the vancomycin, daptomycin and dalbavancin mutants to characterize genetic mutations. For lipidomics analysis, each mutant was grown overnight in BHI broth. The pellets (n = 3 per mutant) were dried under vacuum, weighed, and lipids were extracted using the Folch method.[13] Lipid extracts were analyzed by hydrophilic interaction liquid chromatography (HILIC) coupled to ion mobility-mass spectrometry (HILIC-IM-MS) modes to achieve separation of glycerolipid and glycerophospholipid species.[14] Collision cross section (CCS) calibration was performed using a set of phosphatidylcholine (PC) and phosphatidylethanolamine (PE) standards in positive and negative modes, respectively.[15] The resulting data were submitted to Progenesis QI (Waters) for alignment, peak picking, and multivariate statistical analysis. The resulting features were filtered by ANOVA p ≤ 0.001 and fold-change ≥ 2.
Results
Whole genome sequencing of the in vitro derived N315 mutants identified mutations in yycG in the DAP-1 and DAL-0.5 strains. A mutation in vraS was also identified in DAP-1. In VAN-8, no mutations in the yycFG or vraTSR systems were detected. However, a mutation in the quinolone resistance gene norA was identified. Susceptibility profiling of the N315-mutants confirmed that susceptibility to GP, LP and LGP antimicrobials was reduced in VAN-8, DAP-1, and DAL-0.5, with the exception of susceptibility of DAP-1 to dalbavancin, where no change in MIC was observed. Susceptibility profiling of the N315-mutants against the β-lactams nafcillin and cephalexin revealed the “seesaw effect” in VAN-8 and DAP-1, with 32- and 64-fold reductions in nafcillin MICs and 32- and 256-fold reduction in cephalexin MICs, respectively. The DAL-0.5 mutant displayed no or small seesaw effect with β-lactams. The cephalexin MIC was reduced only 4-fold in DAL-0.5, whereas the nafcillin MIC was actually increased by more than 2-fold. Untargeted lipidomics analysis by HILIC-IM-MS revealed clear differences in the lipid profiles of the N315-derived mutants. While MOX and DOX mutants showed no significant changes relative to the N315 parent strain, the VAN-8, DAL-0.5, and DAP-1 mutants all separated from the parent strain along principal component 1 due to changes in phosphatidylglycerol (PGs) and diglycosyldiacylglycerol (DGDGs) levels. DAP-1 was further separated from VAN-8 and DAL-0.5 along PC2 due to elevated abundance of lysyl-PGs. Among the lipid species altered in the N315-mutants, several individual species of PGs correlated with the observed “seesaw effect” in VAN-8 and DAP-1 whereas their abundance in DAL-0.5, where no or small seesaw effect was observed, was not significantly different from that of parent N315.
Conclusions & Discussion
Our analysis of in vitro derived mutants of MRSA strain N315 with reduced susceptibility to vancomycin, daptomycin, and dalbavancin have revealed trends towards GP/LP/LGP cross-resistance and synergistic changes in β-lactam susceptibility commonly known as the “seesaw effect.” Lipidomics analysis of these mutants indicate that resistance to different cell envelope-active antimicrobials result in characteristic changes to the bacterial lipidome, including lipid species that distinguish β-lactams with or without “seesaw effect” in GP/LP/LGP resistance. Our results suggest that lipid signatures may have value as predictive markers for the seesaw effect and synergistic effects between β-lactam and GP/LP/LGP in GP or LP-resistant MRSA.
References & Acknowledgements:
This study was supported by a grant from the University of Washington School of Pharmacy Faculty Innovation Fund (to LX and BJW) and the startup fund to LX from the Department of Medicinal Chemistry in the School of Pharmacy at the University of Washington. B.J.W. has received research support from Allergan and Merck.
References
1. CDC. Antibiotic Resistance Threats in the United States, 2013. [cited 2016 October 3]; Available from: https://www.cdc.gov/drugresistance/threat-report-2013/pdf/ar-threats-2013-508.pdf#page=13.
2. Britt, N.S., et al., Vancomycin 24-Hour Area under the Curve/Minimum Bactericidal Concentration Ratio as a Novel Predictor of Mortality in Methicillin-Resistant Staphylococcus aureus Bacteremia. Antimicrobial Agents and Chemotherapy, 2016. 60(5): p. 3070-3075.
3. Claeys, K.C., et al., Daptomycin Improves Outcomes Regardless of Vancomycin MIC in a Propensity-Matched Analysis of Methicillin-Resistant Staphylococcus aureus Bloodstream Infections. Antimicrobial Agents and Chemotherapy, 2016. 60(10): p. 5841-5848.
4. Yilmaz, M., et al., Mortality predictors of Staphylococcus aureus bacteremia: a prospective multicenter study. Annals of Clinical Microbiology and Antimicrobials, 2016. 15.
5. Howden, B.P., et al., Reduced vancomycin susceptibility in Staphylococcus aureus, including vancomycin-intermediate and heterogeneous vancomycin-intermediate strains: resistance mechanisms, laboratory detection, and clinical implications. Clin Microbiol Rev, 2010. 23(1): p. 99-139.
6. Jones, T., et al., Failures in clinical treatment of Staphylococcus aureus Infection with daptomycin are associated with alterations in surface charge, membrane phospholipid asymmetry, and drug binding. Antimicrob Agents Chemother, 2008. 52(1): p. 269-78.
7. Ortwine, J.K., et al., Reduced glycopeptide and lipopeptide susceptibility in Staphylococcus aureus and the "seesaw effect": Taking advantage of the back door left open? Drug Resistance Updates, 2013. 16(3-5): p. 73-79.
8. Werth, B.J., et al., Ceftaroline Increases Membrane Binding and Enhances the Activity of Daptomycin against Daptomycin-Nonsusceptible Vancomycin-Intermediate Staphylococcus aureus in a Pharmacokinetic/Pharmacodynamic Model (vol 57, pg 66, 2013). Antimicrobial Agents and Chemotherapy, 2013. 57(3): p. 1565-1565.
9. Werth, B.J., et al., Novel Combinations of Vancomycin plus Ceftaroline or Oxacillin against Methicillin-Resistant Vancomycin-Intermediate Staphylococcus aureus (VISA) and Heterogeneous VISA. Antimicrobial Agents and Chemotherapy, 2013. 57(5): p. 2376-2379.
10. Barber, K.E., et al., Potent synergy of ceftobiprole plus daptomycin against multiple strains of Staphylococcus aureus with various resistance phenotypes. Journal of Antimicrobial Chemotherapy, 2014. 69(11): p. 3006-3010.
11. Boyle-Vavra, S., et al., VraT/YvqF Is Required for Methicillin Resistance and Activation of the VraSR Regulon in Staphylococcus aureus. Antimicrobial Agents and Chemotherapy, 2013. 57(1): p. 83-95.
12. Qureshi, N.K., S.H. Yin, and S. Boyle-Vavra, The Role of the Staphylococcal VraTSR Regulatory System on Vancomycin Resistance and vanA Operon Expression in Vancomycin-Resistant Staphylococcus aureus. Plos One, 2014. 9(1).
13. Folch, J., M. Lees, and G.H.S. Stanley, A SIMPLE METHOD FOR THE ISOLATION AND PURIFICATION OF TOTAL LIPIDES FROM ANIMAL TISSUES. Journal of Biological Chemistry, 1957. 226(1): p. 497-509.
14. Hines, K.M., J. Herron, and L.B. Xu, Assessment of altered lipid homeostasis by HILIC-ion mobility-mass spectrometry-based lipidomics. Journal of Lipid Research, 2017. 58(4): p. 809-819.
15. Hines, K.M., et al., Evaluation of Collision Cross Section Calibrants for Structural Analysis of Lipids by Traveling Wave Ion Mobility-Mass Spectrometry. Analytical Chemistry, 2016. 88(14): p. 7329-7336.
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