Genotypic prediction of tuberculosis drug resistance and implementation of effective MDR-TB management

Leading partner: FZB (Germany)

An effective approach to the management of MDR-TB is to tailor drug therapy regimens on the basis of comprehensive resistance testing. CARE contributes to this effort by:

  • Helping elucidate MDR-TB epidemiology in Russia and Moldova

  • Developing a genotype-to-phenotype prediction framework based on whole genome sequencing to infer second-line TB drug resistance from genotypic data and ease the choice of personalised treatment

  • Designing and developing a software tool for phenotypic drug resistance prediction by genotype

  • Characterizing host genetic traits that predispose to extrapulmonary TB and are known to be involved in higher susceptibility to HIV

  • Defining and testing a pilot model intervention of personalised effective MDR-TB treatment in Russia and other countries of the former Soviet Union, and designing associated clinical training modules

Cohorts and DBs

Ongoing results

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We developed the first version of the software tool to predict drug-resistances from whole genome sequencing (WGS). The tool is called “Geno2Pheno[TB]”, is based on Machine Learning (ML) and we identified Random Forests (RFs) as most suitable method so far. We trained and evaluated a variety of RF-models on different genetic features for 9 important drugs (Isoniazid, Rifampicine, Streptomycin, Ethambutol Pyrazinamide, Amikacin, Capreomycin, Flouroquinolones, Thioamides) using a set of up to 2,000 Mycobacterium tuberculosis (Mtb) genome sequences. The resulting models showed overall significantly improved performance (e.g., sensitivity and specificity) compared to a state-of-the-art mutation catalogue, including both known resistance mediating and benign mutations.


In parallel, we were collecting over 400 clinical MDR-TB isolates for whole genome sequencing and extended phenotypic characterization from the Republic of Moldova and St. Petersburg, creating the MDR-TB cohort. With this newly generated dataset we will eventually describe the bacterial population structure and drug resistance development of MDR-TB isolates in Eastern Europe, and evaluate the geno2pheno[TB] tool.

A preliminary analysis of the newly established MDR-TB cohort permitted to identify genomic variants implicated in Bedaquiline (BDQ) resistance, a new hallmark drug for the treatment of MDR-TB drug therapy.

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 825673.


Francesca Incardona