ABSTRACT
M. tuberculosis grows slowly and is challenging to work with experimentally compared with many other bacteria. Although microtitre plates have the potential to enable high-throughput phenotypic testing of M. tuberculosis, they can be difficult to read and interpret. Here we present a software package, the Automated Mycobacterial Growth Detection Algorithm (AMyGDA), that measures how much M. tuberculosis is growing in each well of a 96-well microtitre plate. The plate used here has serial dilutions of 14 anti-tuberculosis drugs, thereby permitting the MICs to be elucidated. The three participating laboratories each inoculated 38 96-well plates with 15 known M. tuberculosis strains (including the standard H37Rv reference strain) and, after 2 weeks' incubation, measured the MICs for all 14 drugs on each plate and took a photograph. By analysing the images, we demonstrate that AMyGDA is reproducible, and that the MICs measured are comparable to those measured by a laboratory scientist. The AMyGDA software will be used by the Comprehensive Resistance Prediction for Tuberculosis: an International Consortium (CRyPTIC) to measure the drug susceptibility profile of a large number (>30000) of samples of M. tuberculosis from patients over the next few years.
Subject(s)
Antitubercular Agents/pharmacology , Microbial Sensitivity Tests/instrumentation , Microbial Sensitivity Tests/methods , Mycobacterium tuberculosis/drug effects , Automation, Laboratory , Diagnostic Tests, Routine , Drug Resistance, Bacterial , Image Processing, Computer-Assisted , Mycobacterium tuberculosis/growth & development , Reproducibility of Results , SoftwareABSTRACT
Infections with >1 Mycobacterium tuberculosis strain(s) are underrecognized. We show, in vitro and in vivo, how first-line treatment conferred a competitive growth advantage to amplify a multidrug-resistant M. tuberculosis strain in a patient with mixed infection. Diagnostic techniques that identify mixed tubercle bacilli populations are needed to curb the spread of multidrug resistance.
Subject(s)
Antitubercular Agents/pharmacology , Coinfection/diagnosis , Isoniazid/pharmacology , Mycobacterium tuberculosis/genetics , Tuberculosis, Multidrug-Resistant/diagnosis , Tuberculosis, Pulmonary/diagnosis , Aged , Antitubercular Agents/therapeutic use , Coinfection/drug therapy , Coinfection/microbiology , Culture Techniques , Delayed Diagnosis , Drug Resistance, Multiple, Bacterial , Drug Therapy, Combination , Ethambutol/pharmacology , Ethambutol/therapeutic use , Humans , Isoniazid/therapeutic use , Male , Minisatellite Repeats , Molecular Diagnostic Techniques , Multilocus Sequence Typing , Mycobacterium tuberculosis/growth & development , Mycobacterium tuberculosis/isolation & purification , Treatment Outcome , Tuberculosis, Multidrug-Resistant/drug therapy , Tuberculosis, Multidrug-Resistant/microbiology , Tuberculosis, Pulmonary/drug therapy , Tuberculosis, Pulmonary/microbiologyABSTRACT
OBJECTIVES: Since the emergence of multidrug-resistant and extensively drug-resistant tuberculosis, there has been a call for a rapid assay to detect rifampicin-resistant strains that can be implemented into a routine service to analyse all strains in a specific geographical location. Denaturing HPLC (dHPLC) is a rapid screening test that can detect mutations in PCR amplicons. The aim of this study was to evaluate the dHPLC analysis of rifampicin-resistant Mycobacterium tuberculosis isolates using an extensive strain collection from Hong Kong and the UK and a collection of 84 consecutive clinical isolates. METHODS: DNA from 51 rifampicin-resistant M. tuberculosis strains from the UK and Hong Kong identified from 1996 to 2005 was extracted and each mutation was defined by capillary electrophoresis. A 400 bp PCR product was amplified from each strain, heteroduplexed with a known susceptible control (H37Rv) and analysed by dHPLC at 67.0 degrees C. RESULTS: Forty-five out of 51 (88.2%) rifampicin-resistant strains with known DNA mutations were detected by dHPLC. Two out of 84 clinical isolates were phenotypically rifampicin-resistant and dHPLC detected a mutation in the rpoB amplicon for both these isolates. dHPLC detected a mutation in 1 out of 82 phenotypically rifampicin-susceptible isolates (M482T, a non-cluster I/II mutation). In a combined analysis of all strains and isolates, mutation detection by dHPLC analysis exhibited 88.2% sensitivity and 98.8% specificity. CONCLUSIONS: This study shows that dHPLC analysis is sensitive and specific and could be implemented in a routine clinical service.