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
- University of Oxford, United Kingdom
- The Francis Crick Institute, United Kingdom
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 highly skilled 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.
Data availability
The data tables and a Jupyter notebook that allows the user to recreate the majority of figures and tables in both the manuscript and the supplemental information is freely available here: https://github.com/fowler-lab/bashthebug-consensus-datasetIt is setup so a user can either clone the repository and run the jupyter-notebook on their local computer (the installation process having installed the pre-requisites) or by clicking the "Launch Binder" button in the README, they can access and run the jupyter-notebook via their web browser, thereby avoiding any installation.I've added a short statement to the manuscript -- please advise if you think it needs changing.
Article and author information
Author details
Ana L Gibertoni Cruz
Funding
Wellcome Trust (200205/Z/15/Z)
- Philip W Fowler
- Carla Wright
- Sarah W Hoosdally
- Ana L Gibertoni Cruz
- Aysha Roohi
- Samaneh Kouchaki
- Timothy M Walker
- Timothy EA Peto
- David Clifton
- Derrick W Crook
- A Sarah Walker
Bill and Melinda Gates Foundation (OPP1133541)
- Philip W Fowler
- Carla Wright
- Sarah W Hoosdally
- Ana L Gibertoni Cruz
- Aysha Roohi
- Samaneh Kouchaki
- Timothy M Walker
- Timothy EA Peto
- David Clifton
- Derrick W Crook
- A Sarah Walker
Wellcome Trust (203141/Z/16/Z)
- Philip W Fowler
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2022, Fowler et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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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
eLife 11:e75046.
https://doi.org/10.7554/eLife.75046
Further reading
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- Computational and Systems Biology
- Microbiology and Infectious Disease
The Staphylococcus aureus clonal complex 8 (CC8) is made up of several subtypes with varying levels of clinical burden; from community-associated methicillin-resistant S. aureus USA300 strains to hospital-associated (HA-MRSA) USA500 strains and ancestral methicillin-susceptible (MSSA) strains. This phenotypic distribution within a single clonal complex makes CC8 an ideal clade to study the emergence of mutations important for antibiotic resistance and community spread. Gene-level analysis comparing USA300 against MSSA and HA-MRSA strains have revealed key horizontally acquired genes important for its rapid spread in the community. However, efforts to define the contributions of point mutations and indels have been confounded by strong linkage disequilibrium resulting from clonal propagation. To break down this confounding effect, we combined genetic association testing with a model of the transcriptional regulatory network (TRN) to find candidate mutations that may have led to changes in gene regulation. First, we used a De Bruijn graph genome-wide association study to enrich mutations unique to the USA300 lineages within CC8. Next, we reconstructed the TRN by using independent component analysis on 670 RNA-sequencing samples from USA300 and non-USA300 CC8 strains which predicted several genes with strain-specific altered expression patterns. Examination of the regulatory region of one of the genes enriched by both approaches, isdH, revealed a 38-bp deletion containing a Fur-binding site and a conserved single-nucleotide polymorphism which likely led to the altered expression levels in USA300 strains. Taken together, our results demonstrate the utility of reconstructed TRNs to address the limits of genetic approaches when studying emerging pathogenic strains.
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