ArticleScientific reports2022
Classification of antimicrobial mechanism of action using dynamic bacterial morphology imaging.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Poly(imidazolium ester) antibiotic forms intracellular polymer-nucleic acid biomolecular condensates and fight drug-resistant bacteria.Nature communications · 2025Article
- An interbacterial cysteine protease toxin inhibits cell growth by targeting type II DNA topoisomerases GyrB and ParE.PLoS biology · 2025Article
- Advancing antibiotic discovery with bacterial cytological profiling: a high-throughput solution to antimicrobial resistance.Frontiers in microbiology · 2025Review
- HoloMoA: a holography and deep learning tool for the identification of antimicrobial mechanisms of action and the detection of novel MoA.Frontiers in microbiology · 2025Article
- Harzianic acid exerts antimicrobial activity against Gram-positive bacteria and targets the cell membrane.Frontiers in microbiology · 2024Article
- Sensing of Antibiotic-Bacteria Interactions.Antibiotics (Basel, Switzerland) · 2023Review
- Mycobacteriophages in diagnosis and alternative treatment of mycobacterial infections.Frontiers in microbiology · 2023Review
- MraZ Transcriptionally Controls the Critical Level of FtsL Required for Focusing Z-Rings and Kickstarting Septation in Bacillus subtilis.Journal of bacteriology · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Antimicrobial resistance is a major threat to human health. Basic knowledge of antimicrobial mechanism of action (MoA) is imperative for patient care and for identification of novel antimicrobials. However, the process of antimicrobial MoA identification is relatively laborious. Here, we developed a simple, quantitative time-lapse fluorescence imaging method, Dynamic Bacterial Morphology Imaging (DBMI), to facilitate this process. It uses a membrane dye and a nucleoid dye to track the morphological changes of single Bacillus subtilis cells in response to antimicrobials for up to 60 min. DBMI of bacterial cells facilitated assignment of the MoAs of 14 distinct, known antimicrobial compounds to the five main classes. We conclude that DBMI is a simple method, which facilitates rapid classification of the MoA of antimicrobials in functionally distinct classes.
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