Project 2 Hollow Fiber Project

Project Abstract/Summary Project #2 The CDC categorize carbapenem-resistant Acinetobacter baumannii (CRAB) and Klebsiella pneumonia (CRKP) as “urgent threats” because few antibiotics are available to combat these multidrug-resistant ‘superbugs’. Current efforts to improve outcomes are to develop new drugs active against these microbes and to

pharmacodynamically (PD) optimize the efficacies of monotherapies to maximize bacterial killing. To date, monotherapies have produced suboptimal clinical cures due to resistance emergence. Our overarching hypothesis is that highly effective therapy for CRAB and CRKP infections requires combination regimens that

maximize bacterial killing and suppress resistance emergence. We further hypothesize that understanding the target receptor binding in intact bacteria, as well as the transcriptomic, proteomic, and genomic resistance responses of CRAB and CRKP to suboptimal and therapeutic drug exposures will allow us to design and validate

dosage regimens that can successfully combat CRAB and CRKP. The mechanistic insights from Project #1 and the Mechanistic Assay Core #2 will provide an innovative, rational path for building highly effective combination dosage regimens that extensively inactivate the optimal sets of penicillin-binding proteins (PBP). These regimens

will be further enhanced by non-PBP-binding partner antibiotics, where the PBP-binders and the non-PBP- binding antibiotics each counter-select the resistance mechanisms amplified by the partner drug(s). Insights on synergistic PBP occupancy patterns and optimal target site penetration of PBP-binders will be provided by

Project #1. In SA#1, we will study the newer antimicrobials for which there is no PD information (dose range/fractionation or resistance suppression targets) in the Hollow Fiber Infection Model (HFIM). In SA#2, promising 2- and 3-drug combinations will be studied as identified by Project #1. In each SA we will use multiple

omics approaches to characterize synergistic killing and resistance suppression using samples from the HFIM. This will allow creation of optimal mono-and combination therapy regimens. A virtually unexplored area is the effect of time (4th dimension) on the expression of PBPs as well as on the associated resistance mechanisms

(e.g. β-lactamases, efflux and porins), and on non-replicative persisters (NRPs; i.e. a very hard to kill population). In SA#3, we will study these issues by using the HFIM by altering intervention time and by leveraging mechanistic insights on target site penetration, intact-cell receptor binding and the expression of resistance mechanisms. We

will assess NRPs, surviving bacteria with morphological changes, and other populations via flow cytometry of fluorescently labelled strains with sorting. The Mathematical Modeling Core #3 will characterize these synergistic antibiotic interactions to optimize the metrics of rapid/extensive killing and resistance suppression. This will serve

as a first level prospective validation of the mechanistic insights from Project #1 and will allow for an in vivo prospective validation in Project #3. Information will flow back between all 3 Projects to refinement all models.