Single Isothermal Assay for Multi-Site Mutation Detection of Rifampicin Resistance in Mycobacterium tuberculosis

TL;DR

This paper introduces a simple and accurate method to detect multiple mutations in the rpoB gene of Mycobacterium tuberculosis, which is linked to rifampicin resistance.

Contribution

A novel isothermal assay design that enables multi-site mutation detection without primer competition in a single reaction.

Findings

The assay achieved 100% accuracy in detecting mutations at codon 516 of the rpoB gene.

It also identified mutations at codon 526 with 100% accuracy and achieved 97% negative percent agreement for drug-sensitive sequences.

The system showed 100% positive percent agreement for drug-resistance sequences using 42 test samples.

Abstract

Antimicrobial drug resistance is an escalating global health burden, often driven by multiple genetic changes within key resistance-associated genes. Achieving multiplex capability of mutation detection while maintaining simplicity and affordability is critical, particularly in point-of-care and resource-limited settings. Here, we introduce a strategy for multi-site mutation detection using single isothermal amplification of a nucleic acid fragment spanning multiple mutations in the rifampicin resistance-determining region (RRDR) of the rpoB gene, encompassing codons 516 and 526 in Mycobacterium tuberculosis. This unified design eliminates competition among targets amplified by multiple primer sets. Site-specific hybridization probes enable accurate discrimination between wild-type and mutant sequences, while an integrated self-calibration probe provides normalization to mitigate variability from sample concentration and sample matrix interference. To validate this approach, we applied it to detect rifampicin (RIF) resistance mutations at codons 516 and 526 of the rpoB gene in Mycobacterium tuberculosis, which are two key targets for molecular diagnostics and surveillance. Using 42 artificial DNA fragments, which included both wild-types and mutants with single- or two-site mutations, the assay achieved 100% accuracy in discriminating between wild-type and mutant sequences for codon 516. On the other hand, sequences harboring mutations at codon 526 were identified with 100% accuracy, compared to 94% accuracy for wild-type sequences. Overall, the system achieved a 100% positive percent agreement (PPA) for drug-resistance sequences and 97% negative percent agreement (NPA) for drug-sensitive sequences based on these 42 samples. These findings suggest that this method has the potential to provide a reliable framework for multi-site mutation detection.

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