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
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 s...
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| Vydané v: | eLife Ročník 11 |
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| Hlavní autori: | , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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England
eLife Sciences Publications Ltd
19.05.2022
eLife Sciences Publication eLife Sciences Publications, Ltd |
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| ISSN: | 2050-084X, 2050-084X |
| On-line prístup: | Získať plný text |
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| 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.
Tuberculosis is a bacterial respiratory infection that kills about 1.4 million people worldwide each year. While antibiotics can cure the condition, the bacterium responsible for this disease,
Mycobacterium tuberculosis,
is developing resistance to these treatments. Choosing which antibiotics to use to treat the infection more carefully may help to combat the growing threat of drug-resistant bacteria.
One way to find the best choice is to test how an antibiotic affects the growth of
M. tuberculosis
in the laboratory. To speed up this process, laboratories test multiple drugs simultaneously. They do this by growing bacteria on plates with 96 wells and injecting individual antibiotics in to each well at different concentrations.
The Comprehensive Resistance Prediction for Tuberculosis (CRyPTIC) consortium has used this approach to collect and analyse bacteria from over 20,000 tuberculosis patients. An image of the 96-well plate is then captured and the level of bacterial growth in each well is assessed by laboratory scientists. But this work is difficult, time-consuming, and subjective, even for tuberculosis experts. Here, Fowler et al. show that enlisting citizen scientists may help speed up this process and reduce errors that arise from analysing such a large dataset.
In April 2017, Fowler et al. launched the project ‘BashTheBug’ on the Zooniverse citizen science platform where anyone can access and analyse the images from the CRyPTIC consortium. They found that a crowd of inexperienced volunteers were able to consistently and accurately measure the concentration of antibiotics necessary to inhibit the growth of
M. tuberculosis.
If the concentration is above a pre-defined threshold, the bacteria are considered to be resistant to the treatment. A consensus result could be reached by calculating the median value of the classifications provided by as few as 17 different BashTheBug participants.
The work of BashTheBug volunteers has reduced errors in the CRyPTIC project data, which has been used for several other studies. For instance, the World Health Organization (WHO) has also used the data to create a catalogue of genetic mutations associated with antibiotics resistance in
M. tuberculosis
. Enlisting citizen scientists has accelerated research on tuberculosis and may help with other pressing public health concerns. |
|---|---|
| AbstractList | 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. Tuberculosis is a bacterial respiratory infection that kills about 1.4 million people worldwide each year. While antibiotics can cure the condition, the bacterium responsible for this disease, Mycobacterium tuberculosis, is developing resistance to these treatments. Choosing which antibiotics to use to treat the infection more carefully may help to combat the growing threat of drug-resistant bacteria. One way to find the best choice is to test how an antibiotic affects the growth of M. tuberculosis in the laboratory. To speed up this process, laboratories test multiple drugs simultaneously. They do this by growing bacteria on plates with 96 wells and injecting individual antibiotics in to each well at different concentrations. The Comprehensive Resistance Prediction for Tuberculosis (CRyPTIC) consortium has used this approach to collect and analyse bacteria from over 20,000 tuberculosis patients. An image of the 96-well plate is then captured and the level of bacterial growth in each well is assessed by laboratory scientists. But this work is difficult, time-consuming, and subjective, even for tuberculosis experts. Here, Fowler et al. show that enlisting citizen scientists may help speed up this process and reduce errors that arise from analysing such a large dataset. In April 2017, Fowler et al. launched the project ‘BashTheBug’ on the Zooniverse citizen science platform where anyone can access and analyse the images from the CRyPTIC consortium. They found that a crowd of inexperienced volunteers were able to consistently and accurately measure the concentration of antibiotics necessary to inhibit the growth of M. tuberculosis. If the concentration is above a pre-defined threshold, the bacteria are considered to be resistant to the treatment. A consensus result could be reached by calculating the median value of the classifications provided by as few as 17 different BashTheBug participants. The work of BashTheBug volunteers has reduced errors in the CRyPTIC project data, which has been used for several other studies. For instance, the World Health Organization (WHO) has also used the data to create a catalogue of genetic mutations associated with antibiotics resistance in M. tuberculosis. Enlisting citizen scientists has accelerated research on tuberculosis and may help with other pressing public health concerns. 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. Tuberculosis is a bacterial respiratory infection that kills about 1.4 million people worldwide each year. While antibiotics can cure the condition, the bacterium responsible for this disease, Mycobacterium tuberculosis, is developing resistance to these treatments. Choosing which antibiotics to use to treat the infection more carefully may help to combat the growing threat of drug-resistant bacteria. One way to find the best choice is to test how an antibiotic affects the growth of M. tuberculosis in the laboratory. To speed up this process, laboratories test multiple drugs simultaneously. They do this by growing bacteria on plates with 96 wells and injecting individual antibiotics in to each well at different concentrations. The Comprehensive Resistance Prediction for Tuberculosis (CRyPTIC) consortium has used this approach to collect and analyse bacteria from over 20,000 tuberculosis patients. An image of the 96-well plate is then captured and the level of bacterial growth in each well is assessed by laboratory scientists. But this work is difficult, time-consuming, and subjective, even for tuberculosis experts. Here, Fowler et al. show that enlisting citizen scientists may help speed up this process and reduce errors that arise from analysing such a large dataset. In April 2017, Fowler et al. launched the project ‘BashTheBug’ on the Zooniverse citizen science platform where anyone can access and analyse the images from the CRyPTIC consortium. They found that a crowd of inexperienced volunteers were able to consistently and accurately measure the concentration of antibiotics necessary to inhibit the growth of M. tuberculosis. If the concentration is above a pre-defined threshold, the bacteria are considered to be resistant to the treatment. A consensus result could be reached by calculating the median value of the classifications provided by as few as 17 different BashTheBug participants. The work of BashTheBug volunteers has reduced errors in the CRyPTIC project data, which has been used for several other studies. For instance, the World Health Organization (WHO) has also used the data to create a catalogue of genetic mutations associated with antibiotics resistance in M. tuberculosis . Enlisting citizen scientists has accelerated research on tuberculosis and may help with other pressing public health concerns. 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. 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.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. |
| Author | Zhu, Tingting Kouchaki, Samaneh Spiers, Helen Roohi, Aysha Peto, Timothy EA Walker, A Sarah Lintott, Chris Wright, Carla Fowler, Philip W Hoosdally, Sarah W Clifton, David Miller, Grant Walker, Timothy M Gibertoni Cruz, Ana L Crook, Derrick W Baeten, Elisabeth ML |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/35588296$$D View this record in MEDLINE/PubMed https://hal.science/hal-03837128$$DView record in HAL |
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| CitedBy_id | crossref_primary_10_1099_mgen_0_001429 crossref_primary_10_1016_j_csbj_2025_05_030 crossref_primary_10_1590_1806_9282_20230683 crossref_primary_10_1098_rsos_241248 crossref_primary_10_1016_j_poly_2024_117050 crossref_primary_10_1183_23120541_00952_2024 crossref_primary_10_1016_j_jece_2025_119323 crossref_primary_10_1080_1061186X_2025_2534176 crossref_primary_10_1007_s00418_023_02204_6 crossref_primary_10_1183_13993003_00239_2022 crossref_primary_10_1183_13993003_00426_2023 crossref_primary_10_1016_j_prenap_2025_100247 crossref_primary_10_1038_s41598_024_69341_3 crossref_primary_10_1080_00958972_2024_2419419 |
| Cites_doi | 10.1099/mic.0.000733 10.1016/S2213-2600(15)00466-X 10.1101/2020.07.28.223024 10.1101/20210914460353 10.1101/20210914460274 10.1183/13993003.00239-2022 10.1016/S1473-3099(17)30123-8 10.1109/MCSE.2015.65 10.1016/j.cmi.2020.10.019 10.1038/075450a0 10.22323/2.18010204 10.1073/pnas.1807190116 10.1016/S2666-5247(21)00301-3 10.1016/j.cmi.2019.01.019 10.1007/s10439-013-0964-6 10.1099/00207713-22-2-99 |
| ContentType | Journal Article |
| Contributor | Solano, Walter Grandjean, Louis Nimmo, Camus Meintjes, Graeme Knaggs, Jeff Ghodousi, Arash Hoffmann, Harald Fowler, Philip W Liu, Chunfa Plesnik, Sara Van Rie, Annelies Rodrigues, Camilla Carter, Joshua Koch, Anastasia Steyn, Adrie J C Battaglia, Simone Guthrie, Jennifer L Rathod, Priti Lachapelle, Alexander S Jarrett, Lisa Gardy, Jennifer Lalvani, Ajit Millard, James Ngcamu, Dumisani Miotto, Paolo Rakotosamimanana, Niaina Kambli, Priti Laurenson, Ian F Surve, Utkarsha Tahseen, Sabira Ismail, Nazir Ahmed Kouchaki, Samaneh Spitaleri, Andrea Ferrazoli, Lucilaine Moore, David Chetty, Darren Oliveira, Rosangela Siqueira Gao, George F Kohl, Thomas Andreas Matias, Daniela Brankin, Alice Rodger, Gillian Nilgiriwala, Kayzad Soli Watanabe Pinhata, Juliana Maira Omar, Shaheed Vally Trovato, Alberto Shah, Sanchi Claxton, Pauline Cohen, Ted Mandal, Ayan Kohlerschmidt, Donna Coronel, Jorge Earle, Sarah G Clifton, David A Vijay, Srinivasan Peto, Timothy E A Rabodoarivelo, Marie Sylvianne Joseph, Lavania Letcher, Brice Cirillo, Daniela Maria Santos-Lazaro, Da |
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| Copyright | 2022, Fowler et al. 2022, Fowler et al. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Distributed under a Creative Commons Attribution 4.0 International License 2022, Fowler et al 2022 Fowler et al |
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| Keywords | infectious disease tuberculosis microbiology citizen science clinical microbiology antibiotics M. tuberculosis |
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| References_xml | – volume: 62 year: 2018 ident: bib17 article-title: Antimicrobial Agents and Chemotherapy publication-title: ASM Journals Logo – volume-title: Github year: 2018 ident: bib5 article-title: bashthebug: a Python package to analyse the results of the Zooniverse volunteers for the BashTheBug citizen science project – volume: 164 start-page: 1522 year: 2018 ident: bib6 article-title: Automated detection of bacterial growth on 96-well plates for high-throughput drug susceptibility testing of Mycobacterium tuberculosis publication-title: Microbiology (Reading, England) doi: 10.1099/mic.0.000733 – start-page: 51 year: 2010 ident: bib13 article-title: In Proceedings of the 9th Python in Science Conference – volume: 4 start-page: 49 year: 2016 ident: bib16 article-title: Rapid, comprehensive, and affordable mycobacterial diagnosis with whole-genome sequencing: a prospective study publication-title: The Lancet. 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