2050. A Whole Genome Sequencing (WGS) Approach to Predict Daptomycin (DAP) Susceptibility of Enterococcus faecium 
Session: Poster Abstract Session: Diagnostics - Bacterial Identification & Resistance
Saturday, October 7, 2017
Room: Poster Hall CD
Background: We have previously shown that vancomycin-resistant E. faecium (VRE) with DAP MICs close to the breakpoint (4 µg/mL) harbor genetic changes associated with DAP resistance (DAP-R). Further, DAP MIC was a predictor of poor microbiological eradication in patients with VRE bacteremia treated with DAP. Furthermore, DAP-susceptible VRE isolates with DAP MIC of 3-4 µg/ml (Etest) were more likely to fail DAP therapy, independently of the DAP dose used. Here, we used WGS to determine if mutations associated with DAP-R could predict DAP MICs.

Methods: We performed WGS to identify potential determinants of DAP-R in 80 E. faecium isolates (62 DAP-S and 18 DAP-R recovered from bloodstream and other infection sites) in diverse US geographical locations. Two modeling strategies were employed with the aim of increasing the robustness of our prediction strategy, i) a logistic regression model approach to predict the probability of an isolate of exhibiting a DAP MIC of ≥ 3µg/dl based on the presence of relevant mutations, and ii) a linear regression model to predict a single doubling dilution increase on DAP MIC in the presence or absence of mutations associated with DAP-R, after transforming MICs to a log2 scale. Statistical significance (p value) was set at <0.05.

Results: Out of 62 genetic determinants examined, the presence of substitutions in LiaFSR or YycFGHI systems were independent predictors of an isolate exhibiting DAP MIC ≥ 3 µg/mL (logistic model, LiaFSR OR 8.9, p<0.0001 and YycFGHI OR 6.2; p<0.0001) or of an increase in DAP MIC (lineal model; LiaFSR β 14.6; p<0.04; YycFGHI β 1.7; p<0.0001) and were consistent in both models. When we evaluated individual genetic changes within the proteins from both systems, substitutions in YycG were associated with the greatest increase on DAP MIC (8.0 fold; β 3.0, 95% CI 2.8-4.1 p<0.0001), followed by LiaF (3.0 fold; β 1.5, 95% CI 0.17-2.9 P=0.028;), LiaS (2.0 fold; β 0.9, 95%; CI 0.2-1.6 P=0.006;) and LiaR (1.7 fold; β 0.8, 95% CI 0.1-1.5 P=0.021).

Conclusion: Our data indicate that WGS may identify organisms with elevated DAP MIC that, even if not above the clinical breakpoint, may lead to microbiological failure. WGS has the potential of providing a better guidance for DAP therapy.

German Contreras, MD MSc1, Lorena Diaz, PhD2, Rafael Rios, MSc2, Katherine C. Reyes, MD, MPH3, Mini Kamboj, MD4, Jessica Lewis, MD5, Sandra Rincon, MSc2, Jinnethe Reyes, PhD6, Lina Paola Carvajal, BSc2, Diana Panesso, PhD2, Costi D. Sifri, MD, FIDSA7, Marcus Zervos, MD8, Eric Pamer, MD9, Truc T. Tran, PharmD10, Samuel Shelburne, MD, PhD11, Jose Munita, MD12 and Cesar Arias, MD, PhD, FIDSA13, (1)Pediatric Infectious Diseases, University of Texas McGovern Medical School, Houston, TX, (2)Molecular Genetics and Antimicrobial Resistance Unit - International Center for Microbial Genomics, Universidad El Bosque, Bogota, Colombia, (3)Henry Ford Hospital, Detroit, MI, (4)Memorial Sloan Kettering Cancer Center, New York, NY, (5)Infectious Diseases, University of Virginia Medical School, Richmond, VA, (6)Universidad El Bosque, Bogota, Colombia, (7)University of Virginia Health System, Charlottesville, VA, (8)Infectious Diseases, Henry Ford Health System, Detroit, MI, (9)Infectious Diseases, Memorial Sloan Kettering Cancer Center, New York, NY, (10)Department of Internal Medicine, University of Texas McGovern Medical School at Houston, Houston, TX, (11)Infectious Diseases, MD Anderson Cancer Center, Houston, TX, (12)Genomics and Resistant Microbes (GeRM) Group, Clinica Alemana de Santiago, Universidad del Desarrollo School of Medicine, Santiago de Chile, Chile, (13)Microbiology and Molecular Genetics, University of Texas McGovern Medical School, Houston, TX

Disclosures:

G. Contreras, None

L. Diaz, None

R. Rios, None

K. C. Reyes, None

M. Kamboj, None

J. Lewis, None

S. Rincon, None

J. Reyes, None

L. P. Carvajal, None

D. Panesso, None

C. D. Sifri, None

M. Zervos, Merck: Investigator , Research grant
Genentech: Investigator , Research grant
Cempra: Investigator , Research grant
Pfizer: Investigator , Research grant

E. Pamer, None

T. T. Tran, None

S. Shelburne, None

J. Munita, None

C. Arias, None

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