Multi-probe single melt profiling enables mutation screening of long genomic regions for RRDR rifampicin susceptibility

Abstract Tuberculosis drug resistance can arise from single-base mutations that often cluster within genomic hotspots. For example, mutations within the 81-base rifampicin resistance-determining region (RRDR) of Mycobacterium tuberculosis rpoB account for over 96% of rifampicin-resistant cases globally. Mutation screening by post-PCR melt analysis uses sequence-specific derivative melt temperatures (T m s) to identify single-base changes. These single-base changes are more difficult to identify in longer regions like the RRDR because the mutation-induced T m shift decreases as target length increases. In this report, we preserve single-nucleotide sensitivity by dividing the long region into smaller non-overlapping segments and using multiple unlabeled melt probes to screen for non-mutated PCR products. This approach, Multi-probe Single Melt Profiling (MSMP), was applied to the RRDR to generate one intercalated melt profile with two distinct, sequence-sensitive T m s. A Receiver Operating Characteristic (ROC)-defined cutoff for susceptibility was identified. 100% classification accuracy was achieved, with all clinically significant RRDR variant samples falling below at least one segment-specific cutoff and all wild-type samples satisfying both cutoffs. By enabling multi-probe, temperature-based multiplexing in a single intercalated melt profile, MSMP achieves high-resolution screening of long-span hotspots. As longer hotspots emerge, this cost-effective, accessible framework provides a practical approach for susceptibility screening, particularly in resource-limited settings.

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Publication Details

Journal
Scientific Reports
Published
2026-08-18
DOI
https://doi.org/10.1038/s41598-026-63840-1
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
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article

Multi-probe single melt profiling enables mutation screening of long genomic regions for RRDR rifampicin susceptibility

Nicholas Spurlock, Megan E. Pask, Frederick R. Haselton, Nicole A. Malofsky et al.
Scientific Reports
Tuberculosis Research and Epidemiology
article

Multi-probe single melt profiling enables mutation screening of long genomic regions for RRDR rifampicin susceptibility

Nicholas Spurlock, Megan E. Pask, Frederick R. Haselton, Nicole A. Malofsky, Swayashreyee B. Dhungel, Alexandrea A. Howard
article en

Abstract

Abstract Tuberculosis drug resistance can arise from single-base mutations that often cluster within genomic hotspots. For example, mutations within the 81-base rifampicin resistance-determining region (RRDR) of Mycobacterium tuberculosis rpoB account for over 96% of rifampicin-resistant cases globally. Mutation screening by post-PCR melt analysis uses sequence-specific derivative melt temperatures (T m s) to identify single-base changes. These single-base changes are more difficult to identify in longer regions like the RRDR because the mutation-induced T m shift decreases as target length increases. In this report, we preserve single-nucleotide sensitivity by dividing the long region into smaller non-overlapping segments and using multiple unlabeled melt probes to screen for non-mutated PCR products. This approach, Multi-probe Single Melt Profiling (MSMP), was applied to the RRDR to generate one intercalated melt profile with two distinct, sequence-sensitive T m s. A Receiver Operating Characteristic (ROC)-defined cutoff for susceptibility was identified. 100% classification accuracy was achieved, with all clinically significant RRDR variant samples falling below at least one segment-specific cutoff and all wild-type samples satisfying both cutoffs. By enabling multi-probe, temperature-based multiplexing in a single intercalated melt profile, MSMP achieves high-resolution screening of long-span hotspots. As longer hotspots emerge, this cost-effective, accessible framework provides a practical approach for susceptibility screening, particularly in resource-limited settings.

Scientific Reports
Openalex Percentile: Top 9%
Tuberculosis Research and Epidemiology
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