Drug resistance mechanisms and drug susceptibility testing for tuberculosis : Detection of drug resistance in TB

Mathematical models predict that the future of the multidrug-resistant tuberculosis epidemic will depend on the fitness cost of drug resistance. We show that in laboratory-derived mutants of Mycobacterium tuberculosis, rifampin resistance is universally associated with a competitive fitness cost and that this cost is determined by the specific resistance mutation and strain genetic background. In contrast, we demonstrate that prolonged patient treatment can result in multidrug-resistant strains with no fitness defect and that strains with low- or no-cost resistance mutations are also the most frequent among clinical isolates.

Tuberculosis is responsible for one in four of all avoidable adult deaths in developing countries. Increased frequency and accelerated fatality of the disease among individuals infected with human immunodeficiency virus has raised worldwide concern that control programmes may be inadequate, and the emergence of multidrug-resistant strains of Mycobacterium tuberculosis has resulted in several recent fatal outbreaks in the United States. Isonicotinic acid hydrazide (isoniazid, INH) forms the core of antituberculosis regimens; however, clinical isolates that are resistant to INH show reduced catalase activity and a relative lack of virulence in guinea-pigs. Here we use mycobacterial genetics to study the molecular basis of INH resistance. A single M. tuberculosis gene, katG, encoding both catalase and peroxidase, restored sensitivity to INH in a resistant mutant of Mycobacterium smegmatis, and conferred INH susceptibility in some strains of Escherichia coli. Deletion of katG from the chromosome was associated with INH resistance in two patient isolates of M. tuberculosis.

Current molecular diagnostics of human pathogens provide limited information that is often not sufficient for outbreak and transmission investigation. Next generation sequencing (NGS) determines the DNA sequence of a complete bacterial genome in a single sequence run, and from these data, information on resistance and virulence, as well as information for typing is obtained, useful for outbreak investigation. The obtained genome data can be further used for the development of an outbreak-specific screening test. In this review, a general introduction to NGS is presented, including the library preparation and the major characteristics of the most common NGS platforms, such as the MiSeq (Illumina) and the Ion PGM™ (ThermoFisher). An overview of the software used for NGS data analyses used at the medical microbiology diagnostic laboratory in the University Medical Center Groningen in The Netherlands is given. Furthermore, applications of NGS in the clinical setting are described, such as outbreak management, molecular case finding, characterization and surveillance of pathogens, rapid identification of bacteria using the 16S-23S rRNA region, taxonomy, metagenomics approaches on clinical samples, and the determination of the transmission of zoonotic micro-organisms from animals to humans. Finally, we share our vision on the use of NGS in personalised microbiology in the near future, pointing out specific requirements.