Antibiotic resistance among bacterial pathogens remains one of the great challenges confronting public health in the world today. Despite the remarkable success of antibiotics, bacterial infections remain one of the leading causes for mortality. Increasingly, sustained and broad use of antibiotics has selected for multi-drug resistant bacteria that adapt rapidly to newer generation antibiotics and shorten their clinical efficacy. We have developed a scalable and holistic approach that we call 'Quantitative Evolutionary Dynamics'(QED) to study daptomycin and tigecycline resistance in clinical isolates of vancomycin-resistant enterococci (VRE) and to tigecycline resistance in Acinetobacter baumannii. QED can be applied across many organisms and antibiotics to provide: 1) conceptual and mechanistic insights, 2) new targets for drug design, and 3) reveal the underlying biophysical basis for changes in cellular fitness leading to greater resistance during selection. To conduct QED, we use a combination of experimental evolution in turbidostats (fermentors that maintain bacterial populations at their fastest growth rate), genomic sequencing, DNA bar-coding to measure allelic frequencies (FREQ-SEQ), RNA-Seq and physicochemical characterization, including X-ray crystallography, to provide an integrative approach to the identification and characterization of drug resistance targets and mechanisms. QED uses experimental evolution to identify the intermediates of adaptation to reconstruct the adaptive networks responsible for resistance. We use principles from evolutionary biology to rank the likely importance of such changes within the population and prioritize the most important targets for the more time consuming physical studies. QED shows excellent correspondence to in vivo clinical observations of antibiotic resistance. We produce insights not just into the clinically relevant strategies for resistance, but also the specific biochemical mechanisms of resistance, the specific candidate genes responsible for those biochemical changes, and the basis for developing a quantitative link between those changes and the fitness (e.g. resistance) of the pathogen towards a specific drug. QED is a powerful and novel approach that can complement in vivo and clinical studies as well as reveal the evolutionary dynamics of antibiotic resistance.

Public Health Relevance

In this proposal we will identify the molecular mechanisms of daptomycin and tigecycline resistance in vancomycin-resistant enterococci (VRE) and to tigecycline resistance in Acinetobacter baumannii. We use a combination of experimental evolution and biophysics to explore how changes in the genome give rise to resistance and how these changes are brought about at the molecular level. We use that information to understand how adaptation to antibiotics happens and how we might develop drugs to limit adaptation and thereby increase the effectiveness of current and future antibiotics.

National Institute of Health (NIH)
National Institute of Allergy and Infectious Diseases (NIAID)
Research Project (R01)
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Genetic Variation and Evolution Study Section (GVE)
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Huntley, Clayton C
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Rice University
Schools of Arts and Sciences
United States
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Perez, Anisha M; Gomez, Marcella M; Kalvapalle, Prashant et al. (2017) Using cellular fitness to map the structure and function of a major facilitator superfamily effluxer. Mol Syst Biol 13:964
Wang, Xu; Davlieva, Milya; Reyes, Jinnethe et al. (2017) A Novel Phosphodiesterase of the GdpP Family Modulates Cyclic di-AMP Levels in Response to Cell Membrane Stress in Daptomycin-Resistant Enterococci. Antimicrob Agents Chemother 61:
Montealegre, Maria Camila; Roh, Jung Hyeob; Rae, Meredith et al. (2017) Differential Penicillin-Binding Protein 5 (PBP5) Levels in the Enterococcus faecium Clades with Different Levels of Ampicillin Resistance. Antimicrob Agents Chemother 61:
Mehta, Heer H; Prater, Amy G; Shamoo, Yousif (2017) Using experimental evolution to identify druggable targets that could inhibit the evolution of antimicrobial resistance. J Antibiot (Tokyo) :
Tran, Truc T; Miller, William R; Shamoo, Yousif et al. (2016) Targeting cell membrane adaptation as a novel antimicrobial strategy. Curr Opin Microbiol 33:91-96
Davlieva, Milya; Tovar-Yanez, Angel; DeBruler, Kimberly et al. (2016) An Adaptive Mutation in Enterococcus faecium LiaR Associated with Antimicrobial Peptide Resistance Mimics Phosphorylation and Stabilizes LiaR in an Activated State. J Mol Biol 428:4503-4519
Davlieva, Milya; Shi, Yiwen; Leonard, Paul G et al. (2015) A variable DNA recognition site organization establishes the LiaR-mediated cell envelope stress response of enterococci to daptomycin. Nucleic Acids Res 43:4758-73
Panesso, Diana; Reyes, Jinnethe; Gaston, Elizabeth P et al. (2015) Deletion of liaR Reverses Daptomycin Resistance in Enterococcus faecium Independent of the Genetic Background. Antimicrob Agents Chemother 59:7327-34
Beabout, Kathryn; Hammerstrom, Troy G; Perez, Anisha Maria et al. (2015) The ribosomal S10 protein is a general target for decreased tigecycline susceptibility. Antimicrob Agents Chemother 59:5561-6
Beabout, Kathryn; Hammerstrom, Troy G; Wang, Tim T et al. (2015) Rampant Parasexuality Evolves in a Hospital Pathogen during Antibiotic Selection. Mol Biol Evol 32:2585-97

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