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

Philip W. Fowler*, Ana Luíza Gibertoni Cruz, Sarah J. Hoosdally, Lisa Jarrett, Emanuele Borroni, Matteo Chiacchiaretta, Priti Rathod, Sarah Lehmann, Nikolay Molodtsov, Timothy M. Walker, Esther Robinson, Harald Hoffmann, Timothy E.A. Peto, Daniela Maria Cirillo, Grace E. Smith, Derrick W. Crook

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


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.

Original languageEnglish
Article number000733
Pages (from-to)1522-1530
Number of pages9
Issue number12
Publication statusPublished - 2018
Externally publishedYes

Bibliographical note

Funding Information:
The research was funded by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC); the CRyPTIC consortium, which is funded by a Wellcome Trust/Newton Fund-MRC Collaborative Award [200205/Z/15/Z], and the Bill and Melinda Gates Foundation Trust [OPP1133541]. T.E.A.P. and D.W.C. are NIHR Senior Investigators. T.M.W. is an NIHR Academic Clinical Lecturer. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health.

Publisher Copyright:
© 2018 The Authors.


  • Antibiotic resistance
  • Drug susceptibility testing
  • Image processing
  • Microtitre plates
  • Mycobacterium tuberculosis
  • Tuberculosis


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