| Literature DB >> 31533985 |
Yuan Cao1, Heta Parmar1, Ann Marie Simmons2, Devika Kale2, Kristy Tong2, Deanna Lieu2, David Persing2, Robert Kwiatkowski2, David Alland1, Soumitesh Chakravorty3,2.
Abstract
Molecular surveillance of rifampin-resistant Mycobacterium tuberculosis 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 rpoB gene by the use of melting temperature (Tm ) information from 4 rpoB probes which can fall in one of the 9 different assay-specified Tm windows. The large amount of Tm 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 rpoB RRDR by utilizing the pattern of the Tm of the 4 probes within the 9 windows generated by the Ultra assay. The algorithm builds a RRDR mutation-specific "Tm signature" reference library from a set of known mutations and then identifies the RRDR genotype of an unknown sample by measuring the Tm distances between the test sample and the reference Tm values. Validated using a set of clinical isolates, the algorithm correctly identified RRDR genotypes of 93% samples with a wide range of rpoB 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.Entities:
Keywords: Xpert MTB/RIF Ultra; rpoBzzm321990; tuberculosis
Year: 2019 PMID: 31533985 PMCID: PMC6935902 DOI: 10.1128/JCM.00907-19
Source DB: PubMed Journal: J Clin Microbiol ISSN: 0095-1137 Impact factor: 5.948