Back to Search
Start Over
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.
- Source :
-
ELife [Elife] 2022 May 19; Vol. 11. Date of Electronic Publication: 2022 May 19. - Publication Year :
- 2022
-
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, each being present at a pre-determined concentration, thereby determining if the sample isresistant or susceptible to each sample. The minimum inhibitory concentration (MIC) of a drug is the lowestconcentration that inhibits growth and is a more useful quantity but requires each sample to be tested at a range ofconcentrations for each drug. Using 96-well broth micro dilution plates with each well containing a lyophilised pre-determined 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.<br />Competing Interests: PF, CW, HS, TZ, EB, SH, AG, AR, SK, TW, TP, GM, CL, DC, DC, AW No competing interests declared<br /> (© 2022, Fowler et al.)
Details
- Language :
- English
- ISSN :
- 2050-084X
- Volume :
- 11
- Database :
- MEDLINE
- Journal :
- ELife
- Publication Type :
- Academic Journal
- Accession number :
- 35588296
- Full Text :
- https://doi.org/10.7554/eLife.75046