Bustion, A. E. | Search bioRxiv

bioRxiv2024

The kinetics of bedaquiline diffusion in tuberculous cavities opens a window for emergence of resistance.

Cavitary tuberculosis (TB) is difficult to cure and a site of relapse. Bedaquiline has been a wonder drug in the treatment of multidrug resistant TB, but emergence of resistance threatens its sustained success. To investigate the role of drug distribution in resistance development, we designed a novel laser-capture microdissection scheme to spatially resolve the penetration of bedaquiline in the necrotic center (caseum) of cavities, a recalcitrant site of disease. Working with preclinical models that form large necrotic lesions, we profiled bedaquiline and two next generation diarylquinolines TBAJ-587 and TBAJ-876. Drug concentrations were measured in laser-captured areas of cavity caseum as a function of time and distance from blood supply. To simulate drug coverage in patient cavities, the data were modeled, and drug penetration parameter estimates were linked to clinical plasma pharmacokinetics for bedaquiline and the new diarylquinolines. Pharmacokinetic-pharmacodynamic (PK-PD) simulations revealed that bedaquiline reaches efficacious concentrations in outer and deep caseum after several weeks to months and lingers at subtherapeutic concentrations up to 3 years after therapy ends. TBAJ-587 and TBAJ-876, currently in clinical development, achieve bactericidal concentrations in caseum more rapidly and shorten the window of suboptimal concentrations post treatment compared to bedaquiline. Simulations of clinically plausible dosing schemes were conducted to guide the design of clinical trials for cavitary TB and help mitigate resistance development. In summary, the slow kinetics of diffusion of bedaquiline into and out of cavity caseum creates spatio-temporal windows of subtherapeutic concentrations. Site-of-disease simulations of TBAJ-587 and TBAJ-876 predict reduced opportunities for resistance development. SIGNIFICANCEClinical resistance to bedaquiline has emerged faster than anticipated. Understanding potential contributing factors could help curb further resistance development, not only for bedaquiline but also for the next generation diarylquinolines currently in phase 2, TBAJ-587 and TBAJ-876. Here we hypothesized and confirmed that the extended time to reach steady state and slow clearance of bedaquiline leads to extremely slow diffusion into and out of cavity caseum, a recalcitrant site of TB disease and relapse. Through modeling of experimental data in a preclinical model of cavitary TB and clinical simulations, we show that the next generation diarylquinolines may reduce spatio-temporal windows of resistance development compared to bedaquiline. Our results can inform dosing schemes of diarylquinoline-based therapies that limit resistance development.

pharmacology and toxicology↗

bioRxiv2022

A novel in silico method employs chemical and protein similarity algorithms to accurately identify chemical transformations in the human gut microbiome

Bacteria within the gut microbiota possess the ability to metabolize a wide array of human drugs, foods, and toxins, but the responsible enzymes for these chemical events remain largely uncharacterized due to the time consuming nature of current experimental approaches. Attempts have been made in the past to computationally predict which bacterial species and enzymes are responsible for chemical transformations in the gut environment, but with low accuracy due to minimal chemical representation and sequence similarity search schemes. Here, we present an in silico approach that employs chemical and protein Similarity algorithms that Identify MicrobioMe Enzymatic Reactions (SIMMER). We show that SIMMER predicts the chemistry and responsible species and enzymes for a queried reaction with high accuracy, unlike previous methods. We demonstrate SIMMER use cases in the context of drug metabolism by predicting previously uncharacterized enzymes for 88 drug transformations known to occur in the human gut. Bacterial species containing these enzymes are enriched within human donor stool samples that metabolize the query compound. After demonstrating its utility and accuracy, we chose to make SIMMER available as both a command-line and web tool, with flexible input and output options for determining chemical transformations within the human gut. We present SIMMER as a computational addition to the microbiome researchers toolbox, enabling them to make informed hypotheses before embarking on the lengthy laboratory experiments required to characterize novel bacterial enzymes that can alter human ingested compounds.

bioinformatics↗