SUMMARY Deployment of new antimicrobials is promptly circumvented by the rapid evolution of resistance, underscoring the critical need for new strategies to stay ahead in the arms-race against bacterial pathogens. Developing a detailed understanding of the circumstances as well as genetic and mechanistic basis for which antibiotic resistance develops provides opportunities for pre-emptively subverting this process. While infections caused by organisms harboring antimicrobial resistance (AMR) genes are a major cause of antibiotic treatment failure (ATF), ATF frequently occurs when the etiological agents are not AMR by traditional susceptibility testing. It is becoming increasingly recognized that transient cell-states such as tolerance, persistence and hetero-resistance are critical drivers underlying treatment failure. However, there is a paucity of data with regards to the genetic and mechanistic basis for these cell-states as well as a lack of diagnostic-detection approaches. ATF cell-states initially exist as minority variants within a population and display a transient phenotype that tends to dissipate as the stress subsides, making them challenging to detect and consequently missed in current diagnostic assays. These enabler cell-states remain mechanistically poorly understood and seem to preferentially arise during fluctuating treatment regimens, for instance caused by a drug’s PK/PD characteristics, whereby ATF cell-states can drive the re-emergence of the (susceptible) bacterial infection after antibiotic pressure wanes. Importantly, this creates opportunities where multi-step high-level resistance mutations are given an extended opportunity to emerge. Therefore, because antibiotic resistant variants often follow closely on the heels of the occurrence of ATF cell-states, these cell-states can be viewed as enablers of antibiotic treatment failure and AMR. This proposal focuses on untangling the importance of ATF cell-states in the emergence of antibiotic resistance and treatment failure, and designs new approaches and strategies to identify, track and target them. The main team consists of 4 principal investigators that have a very successful collaboration history. Together they will work on 5 challenges distributed across 3 projects and supported by an administrative and a genomics and bioinformatics core. In Challenge: 1) the full profile of possible genetic pathways that can induce ATF cell-states is determined; 2) treatment regimens that drive the emergence of ATF-cell states are determined; 3) it is determined how ATF cell-states enable the emergence of AMR; 4) drugs and compounds are screened for, that target ATF cell-state collateral sensitivities; 5) a computational deconvolution approach is developed that predicts the presence and frequency of ATF cell-states in a complex bacterial population. Overall this proposal contains a collection of conceptually and technically innovative aspects that are geared towards understating the genetic mechanisms and evolutionary forces that sit at the root of the emergence of resistance, with the ultimate goal to design new diagnostics and antimicrobial strategies that can slow or even stop the current endless arms-race “that takes all the running we can do, to keep in the same place”.

NARRATIVE The current arms-race that exists between drug discovery and the bacterial pathogens that rapidly develop resistance against these new antibiotics can be ended by interfering with the key evolutionary processes that enable resistance to emerge. Herein, we untangle the importance of the cell-states of tolerance, persistence and hetero-resistance in their roles as harbingers of antibiotic treatment failure (ATF) and enablers of resistance. We identify the treatment regimens that select for ATF cell-state induction, uncover the genetic mechanisms underlying their emergence, devise strategies to target their collateral sensitivities, and develop a proof-of- principle computational diagnostics approach that predicts the presence and frequency of ATF cell-states in complex bacterial populations.