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Journal article

High-content imaging to phenotype antimicrobial effects on individual bacteria at scale

Abstract:
High-content imaging (HCI) is a technique for screening multiple cells in high resolution to detect subtle morphological and phenotypic variation. The method has been commonly deployed on model eukaryotic cellular systems, often for screening new drugs and targets. HCI is not commonly utilized for studying bacterial populations but may be a powerful tool in understanding and combatting antimicrobial resistance. Consequently, we developed a high-throughput method for phenotyping bacteria under antimicrobial exposure at the scale of individual bacterial cells. Imaging conditions were optimized on an Opera Phenix confocal microscope (Perkin Elmer), and novel analysis pipelines were established for both Gram-negative bacilli and Gram-positive cocci. The potential of this approach was illustrated using isolates of Klebsiella pneumoniae, Salmonella enterica serovar Typhimurium, and Staphylococcus aureus. HCI enabled the detection and assessment of subtle morphological characteristics, undetectable through conventional phenotypical methods, that could reproducibly distinguish between bacteria exposed to different classes of antimicrobials with distinct modes of action (MOAs). In addition, distinctive responses were observed between susceptible and resistant isolates. By phenotyping single bacterial cells, we observed intrapopulation differences, which may be critical in identifying persistence or emerging resistance during antimicrobial treatment. The work presented here outlines a comprehensive method for investigating morphological changes at scale in bacterial populations under specific perturbation.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1128/msystems.00028-21

Authors


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Role:
Author
ORCID:
0000-0003-1326-0373
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Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Tropical Medicine
Role:
Author
ORCID:
0000-0003-1308-5755


Publisher:
American Society for Microbiology
Journal:
mSystems More from this journal
Volume:
6
Issue:
3
Article number:
e00028-21
Publication date:
2021-05-18
Acceptance date:
2021-04-26
DOI:
EISSN:
2379-5077
Pmid:
34006623


Language:
English
Keywords:
Pubs id:
1185087
Local pid:
pubs:1185087
Deposit date:
2021-12-22

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