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Validated Preclinical Murine Model for Therapeutic Testing against Multidrug Resistant Pseudomonas aeruginosa

Warawa, J.; Duan, X.; Anderson, C.; Sotsky, J. B.; Cramer, D. E.; Pfeffer, T. L.; Guo, H.; Adcock, R. S.; Lepak, A. J.; Andes, D. R.; Slone, S. A.; Stromberg, A.; Gabbard, J. D.; Severson, W.; Lawrenz, M. B.

2022-07-06 microbiology
10.1101/2022.07.05.498916 bioRxiv
Show abstract

The rise in infections caused by antibiotic resistant bacteria is outpacing the development of new antibiotics. The ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) are a group of clinically important bacteria that have developed resistance to multiple antibiotics and are commonly referred to as multidrug resistant (MDR). The medical and research communities have recognized that without new antimicrobials, infections by MDR bacteria will soon become a leading cause of morbidity and mortality. Therefore, there is an ever growing need to expedite the development of novel antimicrobials to combat these infections. Toward this end, we set out to refine an existing murine model of pulmonary Pseudomonas aeruginosa infection to generate a robust preclinical tool that can be used to rapidly and accurately predict novel antimicrobial efficacy. This refinement was achieved by characterizing the virulence of a panel of genetically diverse MDR P. aeruginosa strains in this model, both by LD50 analysis and natural history studies. Further, we defined two antibiotic regimens (aztreonam and amikacin) that can be used a comparators during the future evaluation of novel antimicrobials, and validated that the model can effectively differentiate between successful and unsuccessful treatment as predicted by in vitro inhibitory data. This validated model represents an important tool in our arsenal to develop new therapies to combat MDR P. aeruginosa, with the ability to provide rapid preclinical evaluation of novel antimicrobials that can also serve to support data from clinical studies during the investigational drug development process.

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