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

PW Fowler, ALG Cruz, SJ Hoosdally, L Jarrett, E Borroni, M Chiacchiaretta, P Rathod, S Lehmann, N Molodtsov, TM Walker, E Robinson, H Hoffmann, TEA Peto, DM Cirillo, GE Smith, DW Crook

Research output: Contribution to journalArticlepeer-review

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. © 2018 The Authors.
Original languageEnglish
Pages (from-to)1522-1530
Number of pages9
JournalMicrobiology
Volume164
Issue number12
DOIs
Publication statusPublished - 2018

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