High-Content Imaging to Phenotype Antimicrobial Effects on Individual Bacteria at Scale.
antimicrobial resistance
bacteria
high-content imaging
image analysis
phenotyping
Journal
mSystems
ISSN: 2379-5077
Titre abrégé: mSystems
Pays: United States
ID NLM: 101680636
Informations de publication
Date de publication:
18 May 2021
18 May 2021
Historique:
entrez:
19
5
2021
pubmed:
20
5
2021
medline:
20
5
2021
Statut:
epublish
Résumé
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
Identifiants
pubmed: 34006623
pii: 6/3/e00028-21
doi: 10.1128/mSystems.00028-21
pmc: PMC8269201
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 206194
Pays : United Kingdom
Informations de copyright
Copyright © 2021 Sridhar et al.
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