Automatic Identification of Individual rpoB Gene Mutations Responsible for Rifampin Resistance in Mycobacterium tuberculosis by Use of Melting Temperature Signatures Generated by the Xpert MTB/RIF Ultra Assay

Molecular surveillance of rifampin-resistant can help to monitor the transmission of the disease. The Xpert MTB/RIF Ultra assay detects mutations in the rifampin resistance-determining region (RRDR) of the gene by the use of melting temperature ( ) information from 4 probes which can fall in one of...

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Bibliographic Details
Published in:Journal of clinical microbiology 2019-12, Vol.58 (1)
Main Authors: Cao, Yuan, Parmar, Heta, Simmons, Ann Marie, Kale, Devika, Tong, Kristy, Lieu, Deanna, Persing, David, Kwiatkowski, Robert, Alland, David, Chakravorty, Soumitesh
Format: Article
Language:English
Subjects:
Mycobacteriology and Aerobic Actinomycetes
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Summary:Molecular surveillance of rifampin-resistant can help to monitor the transmission of the disease. The Xpert MTB/RIF Ultra assay detects mutations in the rifampin resistance-determining region (RRDR) of the gene by the use of melting temperature ( ) information from 4 probes which can fall in one of the 9 different assay-specified windows. The large amount of data generated by the assay offers the possibility of an RRDR genotyping approach more accessible than whole-genome sequencing. In this study, we developed an automated algorithm to specifically identify a wide range of mutations in the RRDR by utilizing the pattern of the of the 4 probes within the 9 windows generated by the Ultra assay. The algorithm builds a RRDR mutation-specific " signature" reference library from a set of known mutations and then identifies the RRDR genotype of an unknown sample by measuring the distances between the test sample and the reference values. Validated using a set of clinical isolates, the algorithm correctly identified RRDR genotypes of 93% samples with a wide range of single and double mutations. Our analytical approach showed a great potential for fast RRDR mutation identification and may also be used as a stand-alone method for ruling out relapse or transmission between patients. The algorithm can be further modified and optimized for higher accuracy as more Ultra data become available.
ISSN:0095-1137
1098-660X
DOI:10.1128/JCM.00907-19