Deconvoluting drug interactions using M. tuberculosis physiologic processes: transcriptional disaggregation of the BPaL regimen in vivo

Abstract

A key challenge in preclinical tuberculosis drug development is identifying optimal antibiotic combinations. Drug interactions are complex because one drug may affect Mycobacterium tuberculosis (Mtb) physiology in a way that alters the activity of another drug. Conventional pharmacodynamic evaluation based on colony-forming units (CFU) does not provide information about this physiologic interaction because CFU enumerates bacteria but does not give information about the drug's effect on bacterial cellular processes. SEARCH-TB is a novel pharmacodynamic (PD) approach that uses targeted in vivo transcriptional profiling to evaluate drug effects on Mtb physiology. To evaluate SEARCH-TB's capacity to elucidate drug interactions, we deconstructed the BPaL (bedaquiline, pretomanid, and linezolid) regimen in the BALB/c high-dose aerosol mouse infection model, measuring the effect of 2-, 7-, and 14-day treatment with drugs in monotherapy, pairwise combinations, and as a three-drug combination. Monotherapy induced drug-specific Mtb transcriptional responses by day 2 with continued evolution over 14 days. Bedaquiline dominated pairwise combinations with pretomanid and linezolid, whereas the pretomanid-linezolid combination induced a transcriptional profile intermediate between either drug. In the three-drug BPaL regimen, adding both pretomanid and linezolid to bedaquiline yielded a greater transcriptional response than expected, based on pairwise results. This work demonstrates that physiologic perturbations induced by a single drug may be modified in complex ways when drugs are combined. This establishes proof of concept that SEARCH-TB provides a highly granular readout of drug interactions in vivo, providing information distinct from CFU burden and suggesting a future where regimen selection is informed by in vivo molecular measures of Mtb physiology.

Keywords: M. tuberculosis; RNA sequencing; antibiotic exposure; antibiotic interaction.