BACKGROUND Several molecular imaging strategies can identify bacterial infections in humans. PET affords the potential for sensitive infection detection deep within the body. Among PET-based approaches, antibiotic-based radiotracers, which often target key bacterial-specific enzymes, have considerable promise. One question for antibiotic radiotracers is whether antimicrobial resistance (AMR) reduces specific accumulation within bacteria, diminishing the predictive value of the diagnostic test.METHODS Using a PET radiotracer based on the antibiotic trimethoprim (TMP), [11C]-TMP, we performed in vitro uptake studies in susceptible and drug-resistant bacterial strains and whole-genome sequencing (WGS) in selected strains to identify TMP resistance mechanisms. Next, we queried the NCBI database of annotated bacterial genomes for WT and resistant dihydrofolate reductase (DHFR) genes. Finally, we initiated a first-in-human protocol of [11C]-TMP in patients infected with both TMP-sensitive and TMP-resistant organisms to demonstrate the clinical feasibility of the tool.RESULTS We observed robust [11C]-TMP uptake in our panel of TMP-sensitive and -resistant bacteria, noting relatively variable and decreased uptake in a few strains of P. aeruginosa and E. coli. WGS showed that the vast majority of clinically relevant bacteria harbor a WT copy of DHFR, targetable by [11C]-TMP, and that despite the AMR, these strains should be “imageable.” Clinical imaging of patients with [11C]-TMP demonstrated focal radiotracer uptake in areas of infectious lesions.CONCLUSION This work highlights an approach to imaging bacterial infection in patients, which could affect our understanding of bacterial pathogenesis as well as our ability to better diagnose infections and monitor response to therapy.TRIAL REGISTRATION ClinicalTrials.gov NCT03424525.FUNDING Institute for Translational Medicine and Therapeutics, Burroughs Wellcome Fund, NIH Office of the Director Early Independence Award (DP5-OD26386), and University of Pennsylvania NIH T32 Radiology Research Training Grant (5T32EB004311-12).
Iris K. Lee, Daniel A. Jacome, Joshua K. Cho, Vincent Tu, Anthony J. Young, Tiffany Dominguez, Justin D. Northrup, Jean M. Etersque, Hsiaoju S. Lee, Andrew Ruff, Ouniol Aklilu, Kyle Bittinger, Laurel J. Glaser, Daniel Dorgan, Denis Hadjiliadis, Rahul M. Kohli, Robert H. Mach, David A. Mankoff, Robert K. Doot, Mark A. Sellmyer