ArticleEBioMedicine2025
Speeding up drug susceptibility testing in Mycobacterium tuberculosis using RNA biomarkers.
Article in EBioMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Heteroresistance inFrontiers in cellular and infection microbiology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEfficient management of drug-resistant tuberculosis relies on fast diagnostics. To accelerate phenotypic drug susceptibility testing [pDST] for Mycobacterium tuberculosis [TB], we introduce TRACeR-TB, a test that infers drug resistance from antibiotic-specific mRNA biomarkers.
methodsTo develop TRACeR-TB, target genes were first identified through RNA sequencing experiments conducted on two drug-exposed, susceptible strains for four antitubercular drugs. Based on these findings, we designed drug-specific multiplex Quantigene panels to quantify mRNA levels of 8-9 biomarkers per drug (class), directly from crude cell lysates. The performance of TRACeR-TB was compared to the widely used Mycobacteria Growth Indicator Tube [MGIT] pDST by subjecting 238 strains with diverse drug resistance profiles to both methods, and aligning results to genotypic data. Furthermore, we explored TRACeR-TB's potential for evaluating molecules that enhance antibiotic efficacy, and investigated its applicability in macrophage models to assess Mtb's intracellular stress responses to drugs.
findingsAntituberculosis drugs trigger distinct transcriptional stress responses in susceptible, but not resistant bacilli, enabling a differentiation of the antibiotic phenotype in only 6 h. Validation on 238 strains showed TRACeR-TB had 100% (95% CI: 93·1-100%) sensitivity and 89·5% (95% CI: 74·7-97·2%) specificity compared to, respectively, 82·3% (95% CI: 69·2%-91·5%) and 94·8% (95% CI: 81·9%-99·4%) for MGIT pDST. TRACeR-TB specificity is likely underestimated due to the inclusion of isolates harbouring uncharacterised mutations. TRACeR-TB demonstrated 100% concordance with MGIT for drugs with reliable MGIT outcomes (moxifloxacin and isoniazid). Additionally, its sensitivity outperformed current rifampicin testing, detecting resistance in all borderline-resistant strains that MGIT missed, and bedaquiline testing. Furthermore, the assay detected the predicted effect of a novel drug booster and the intracellular drug-induced stress in macrophage models, highlighting its potential for drug optimisation.
interpretationTRACeR-TB is a complementary addition to current DSTs and can have a substantial impact on the TB diagnostics field. This tool can also play a vital role in identifying resistance mutations, thereby closing gaps in genotypic knowledge, and contribute to drug discovery and development.
fundingInstitut Pasteur, Agence Nationale de la Recherche.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.