# Comprehensive characterization of Rv0678 bedaquiline resistance-conferring polymorphisms

> **NIH NIH R21** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2024 · $204,479

## Abstract

ABSTRACT
Bedaquiline is central to nearly all shorter, modernized all-oral regimens being evaluated and is revolutionizing
rifampin-resistant tuberculosis treatment. Yet, despite extensive research activity in this space, a poor
understanding of the genotype-phenotype correlation (i.e., the association between specific mutations
(genotype) and the resulting spectrum of resistance) is the primary barrier to developing an accurate molecular
diagnostic for bedaquiline. We propose accelerating discovery in this area using an unbiased, comprehensive
mutational and screening strategy to determine the range and scope of all rv0678 mutations conferring
bedaquiline resistance. We will construct a library of M. tuberculosis clones carrying single-nucleotide
polymorphisms and specific indels, and we will screen this library in vitro and in a murine model. The success
of our proposed work will provide a template to accelerate the discovery of resistance-conferring variants for all
new and repurposed agents and help close the diagnostic gap, allowing for the development of tests to rapidly
inform treatment decisions, regardless of resource setting.

## Key facts

- **NIH application ID:** 10989064
- **Project number:** 1R21AI180963-01A1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** John Zapata Metcalfe
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $204,479
- **Award type:** 1
- **Project period:** 2024-05-14 → 2026-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10989064

## Citation

> US National Institutes of Health, RePORTER application 10989064, Comprehensive characterization of Rv0678 bedaquiline resistance-conferring polymorphisms (1R21AI180963-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10989064. Licensed CC0.

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