Host variation affects the pathogenicity of, susceptibility to, and recovery from infectious diseases. Elucidating how the host environment alters antibiotic susceptibility is therefore a critical step towards the long-term goal of realizig precision medicine for the clinical management of infectious diseases. The overall objective of this project is to identify the metabolic pathways participating in antibiotic susceptibility and t determine how host metabolism may affect antibiotic treatments at the site of infection. The working hypothesis is that metabolic processes can function as bacterial control mechanisms for antibiotic susceptibility and that the host metabolome can act on these processes to affect the outcome of antibiotic treatment. This hypothesis will be tested in three specific aims: (1) identif metabolic pathways involved in antibiotic susceptibility (K99 phase); (2) characterize changes in the host metabolome elicited by antibiotic administration (K99 phase); (3) evaluate effects of the host metabolome on antibiotic killing (R00 phase). During the mentored K99 phase, bactericidal antibiotics will be counterscreened with various metabolites to identify metabolic perturbations that can affect antibiotic susceptibility. Metabolic pathways contributing to antibiotic lethality ill be identified by combining this data with metabolic modeling and machine learning. Additionally, plasma and peritoneal fluid will be sampled and metabolomically profiled from a mouse peritoneal infection model, with and without antibiotic treatment. These profiles will be used to determine if antibiotics can alter the host metabolism in ways that may affect antibiotic susceptibility at the site of infection. During the independent R00 phase, the effects of host metabolic variation on antibiotic killing will be systematically tested by quantifying antibiotic susceptibility in synthesized media defined by metabolomic profiles from published and measured human and mouse plasma samples. A better understanding of how the host metabolic environment participates in antibiotic treatment fits NIH's public health mission and has direct implications for the clinical management of infectious diseases. Work from the proposed studies will form a quantitative framework for directly evaluating how host metabolism may affect antibiotic treatment outcomes and guide improved antibiotic stewardship in clinical practice. Although the applicant has significant expertise in systems biology, this award will provide the applicant research training to gain new experimental skills and an opportunity for continued career training and mentorship from an advisory committee comprised of international leaders in systems biology, metabolomics, chemical biology and infectious diseases. The support and training provided by this award and by the advisory committee will provide the applicant tools and expertise critical to his future independent research program.

Public Health Relevance

Host variation alters the clinical response to antibiotic treatment for infectious disease, but the pathways underlying differences in patient outcome have not yet all been elucidated. The proposed research is relevant to public health because it is the first systematic investigation of how host metabolites may act on bacterial pathogen metabolism and alter antibiotic susceptibility. This work is relevant to NIH's public health mission by providing a quantitative framework for establishing precision medicine for the treatment of infectious diseases.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Career Transition Award (K99)
Project #
5K99GM118907-02
Application #
9355203
Study Section
Special Emphasis Panel (ZGM1)
Program Officer
Sesma, Michael A
Project Start
2016-09-20
Project End
2019-08-31
Budget Start
2017-09-01
Budget End
2019-08-31
Support Year
2
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
001425594
City
Cambridge
State
MA
Country
United States
Zip Code
02142
Takahashi, Noriko; Gruber, Charley C; Yang, Jason H et al. (2017) Lethality of MalE-LacZ hybrid protein shares mechanistic attributes with oxidative component of antibiotic lethality. Proc Natl Acad Sci U S A :
Meylan, Sylvain; Porter, Caroline B M; Yang, Jason H et al. (2017) Carbon Sources Tune Antibiotic Susceptibility in Pseudomonas aeruginosa via Tricarboxylic Acid Cycle Control. Cell Chem Biol 24:195-206
Yang, Jason H; Bening, Sarah C; Collins, James J (2017) Antibiotic efficacy-context matters. Curr Opin Microbiol 39:73-80
Yang, Jason H; Bhargava, Prerna; McCloskey, Douglas et al. (2017) Antibiotic-Induced Changes to the Host Metabolic Environment Inhibit Drug Efficacy and Alter Immune Function. Cell Host Microbe 22:757-765.e3