Abstract
As a follow-up of the "spoligoriftyping" development, we present here an extension of this technique which includes the detection of isoniazid resistance-associated mutations in a new 59-plex assay, i.e., tuberculosis-spoligo-rifampin-isoniazid typing (TB-SPRINT), running on microbead-based multiplexed systems. This assay improves the synergy between clinical microbiology and epidemiology by providing (i) mutation-based prediction of drug resistance profiles for patient treatment and (ii) genotyping data for tuberculosis (TB) surveillance. This third-generation microbead-based high-throughput assay for TB runs on the Luminex 200 system and on the recently launched MagPix system (Luminex, Austin, TX). Spoligotyping patterns obtained by the TB-SPRINT method were 100% (n = 85 isolates; 3,655/3,655 spoligotype data points) concordant with those obtained by microbead-based and membrane-based spoligotyping. Genetic drug susceptibility typing provided by the TB-SPRINT method was 100% concordant with resistance locus sequencing (n = 162 for rpoB gene sequencing and n = 76 for katG and inhA sequencing). Considering phenotypic drug susceptibility testing (DST) as the reference method, the sensitivity and specificity of TB-SPRINT regarding Mycobacterium tuberculosis complex (n = 162 isolates) rifampin resistance were both 100%, and those for isoniazid resistance were 90.4% (95% confidence interval, 85 to 95%) and 100%, respectively. Used routinely in national TB reference and specialized laboratories, the TB-SPRINT assay should simultaneously improve personalized medicine and epidemiological surveillance of multidrug-resistant (MDR) TB. This assay is expected to play an emerging role in public health in countries with heavy burdens of MDR TB and/or HIV/TB coinfection. Application of this assay directly to biological samples, as well as development for extensively drug-resistant (XDR) TB detection by inclusion of second-line antituberculosis drug-associated mutations, is under development. With bioinformatical methods and data mining to reduce the number of targets to the most informative ones, locally adapted formats of this technique can easily be developed everywhere.