Deconvoluting drug interactions using physiologic processes: transcriptional disaggregation of the BPaL regimen .

Journal:
Antimicrobial agents and chemotherapy, Volume: 69, Issue: 11
Published:
November 5, 2025
PMID:
40965512
Authors:
Elizabeth A Wynn EA, Christian Dide-Agossou C, Reem Al Mubarak R, Karen Rossmassler K, Jo Hendrix J, Martin I Voskuil MI, Andrés Obregón-Henao A, Michael A Lyons MA, Gregory T Robertson GT, Camille M Moore CM, Nicholas D Walter ND
Abstract:

A key challenge in preclinical tuberculosis drug development is identifying optimal antibiotic combinations. Drug interactions are complex because one drug may affect () 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 transcriptional profiling to evaluate drug effects on 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 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 providing information distinct from CFU burden and suggesting a future where regimen selection is informed by molecular measures of physiology.


Courtesy of the U.S. National Library of Medicine