Evidence map›Paper›PMID 42297913›Full record

ArticleScientific reports2026

Leveraging rpoB amplicon signals from Xpert MTB/RIF ultra as a diagnostic opportunity for identifying Non-tuberculous mycobacteria in TB-negative specimens.

Afsana Akter Rupa, Sk Nazmul Kabir, Rumana Nasrin, Ashabul Islam, S M Mazidur Rahman, Ahammad Shafiq Sikder Adel, Andrea Maurizio Cabibbe, Arash Ghodousi, Daniela Brites, Mohammad Khaja Mafij Uddin and 1 more

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

11 authors.

Afsana Akter RupaInfectious Diseases Division, icddr,b, Dhaka, 1212, Bangladesh.
Sk Nazmul KabirInfectious Diseases Division, icddr,b, Dhaka, 1212, Bangladesh.
Rumana NasrinInfectious Diseases Division, icddr,b, Dhaka, 1212, Bangladesh.
Ashabul IslamDepartment of Mathematics and Natural Sciences, BRAC University, Dhaka, Bangladesh.
S M Mazidur RahmanInfectious Diseases Division, icddr,b, Dhaka, 1212, Bangladesh.
Ahammad Shafiq Sikder AdelInfectious Diseases Division, icddr,b, Dhaka, 1212, Bangladesh.
Andrea Maurizio CabibbeEmerging Bacterial Pathogens Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Arash GhodousiVita-Salute San Raffaele University, Milan, Italy.
Daniela BritesTuberculosis Research Unit, Swiss Tropical and Public Health Institute, Allschwil, Switzerland.
Mohammad Khaja Mafij UddinInfectious Diseases Division, icddr,b, Dhaka, 1212, Bangladesh. kmuddin@icddrb.org.
Sayera BanuInfectious Diseases Division, icddr,b, Dhaka, 1212, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-tuberculous mycobacteria (NTM) present a diagnostic challenge due to clinical overlap with tuberculosis (TB). The Xpert MTB/RIF Ultra assay occasionally detects rpoB probe amplification in specimens negative for the Mycobacterium tuberculosis complex (MTBC). We evaluated whether rpoB amplification could indicate NTM infection and support diagnostic decision-making. Specimens showing rpoB probe amplification but negative for MTBC by Xpert Ultra were selected from TB Screening and Treatment Centers (TBSTC) of icddr, b between January and August 2024. Samples underwent further testing using PCR targeting rpoB and IS6110, culture, and targeted next-generation sequencing (tNGS) to detect and identify NTM species. Among 50 specimens with rpoB amplification, rpoB PCR positivity was confirmed in all cases. Atypical mycobacterial growth was observed in 43 (86%) isolates. tNGS identified 34 isolates as NTM, with Mycobacterium gordonae (20.5%) and Mycobacterium abscessus subsp. abscessus (17.6%) being the most prevalent; 3 were MTBC, and the 6 were not detected. Receiver operating characteristic (ROC) analysis of rpoB2 threshold cycle (Ct) values demonstrated moderate diagnostic performance (AUC 0.807) with a Ct cutoff of 32.7 yielding 82.4% sensitivity, 77.8% specificity, and a positive predictive value of 93.3%. At a cutoff value of 32.7, the sensitivity and specificity for pulmonary samples were 90% and 100%, respectively, whereas for extrapulmonary samples they were 76% and 85%, respectively. These findings indicate that rpoB2 Ct values from the Xpert Ultra assay could provide additional diagnostic utility for identifying NTMs in MTBC-negative samples without additional costs.

Indexed as

Bacterial ProteinsDNA-Directed RNA PolymerasesMycobacterium Infections, NontuberculousNontuberculous MycobacteriaTuberculosisHigh-Throughput Nucleotide SequencingHumansMolecular Diagnostic TechniquesMycobacterium tuberculosisPolymerase Chain ReactionSensitivity and SpecificityBacterial ProteinsDNA-Directed RNA PolymerasesrpoB protein, Mycobacterium tuberculosisExtrapulmonaryNontuberculous mycobacteriaPulmonarytNGSXpert ultra

Identifiers

PMID42297913
PMCPMC13530228

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.