A crowd of BashTheBug volunteers reproducibly and accurately measure the minimum inhibitory concentrations of 13 antitubercular drugs from photographs of 96-well broth microdilution plates

The Zooniverse Volunteer Community, The CRyPTIC Consortium

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10 Citations (Scopus)

Abstract

Tuberculosis is a respiratory disease that is treatable with antibiotics. An increasing prevalence of resistance means that to ensure a good treatment outcome it is desirable to test the susceptibility of each infection to different antibiotics. Conventionally this is done by culturing a clinical sample and then exposing aliquots to a panel of antibiotics, Using 96-well broth micro dilution plates with each well containing a lyophilised predetermined amount of an antibiotic is a convenient and cost-effective way to measure the MICs of several drugs at once for a clinical sample. Although accurate, this is still an expensive and slow process that requires highlyskilled and experienced laboratory scientists. Here we show that, through the BashTheBug project hosted on the Zooniverse citizen science platform, a crowd of volunteers can reproducibly and accurately determine the MICs for 13 drugs and that simply taking the median or mode of 11-17 independent classifications is sufficient. There is therefore a potential role for crowds to support (but not supplant) the role of experts in antibiotic susceptibility testing.

Original languageEnglish
Article numbere75046
JournaleLife
Volume11
DOIs
Publication statusPublished - May 2022

Bibliographical note

Funding Information:
BashTheBug was supported by Welcome through the Enriching Engagement Grants scheme at the University of Oxford. This work was also supported by Wellcome Trust/Newton Fund-MRC Collaborative Award [200205/Z/15/Z]; and Bill & Melinda Gates Foundation Trust [OPP1133541]. This study is funded by the National Institute for Health Research (NIHR) Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, a partnership between Public Health England and the University of Oxford. The research was also funded/supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC). The computational aspects of this research were supported by the Wellcome Trust Core Award Grant Number 203141/Z/16/Z and the NIHR Oxford BRC. This publication uses data generated via the Zooniverse.org platform, development of which is funded by generous support, including from the National Science Foundation, NASA, the Institute of Museum and Library Services, UKRI, a Global Impact Award from Google, and the Alfred P. Sloan Foundation.

Publisher Copyright:
© 2022, eLife Sciences Publications Ltd. All rights reserved.

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