Automated detection of bacterial growth on 96-well plates for high-throughput drug susceptibility testing of Mycobacterium tuberculosis

Microbiology (Reading). 2018 Dec;164(12):1522-1530. doi: 10.1099/mic.0.000733. Epub 2018 Oct 23.

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.

Keywords: Mycobacterium tuberculosis; antibiotic resistance; drug susceptibility testing; image processing; microtitre plates; tuberculosis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antitubercular Agents / pharmacology*
  • Automation, Laboratory
  • Diagnostic Tests, Routine
  • Drug Resistance, Bacterial
  • Image Processing, Computer-Assisted
  • Microbial Sensitivity Tests / instrumentation*
  • Microbial Sensitivity Tests / methods*
  • Mycobacterium tuberculosis / drug effects*
  • Mycobacterium tuberculosis / growth & development
  • Reproducibility of Results
  • Software

Substances

  • Antitubercular Agents