ArticleMolecular bioSystems2013
Mechanism of action-based classification of antibiotics using high-content bacterial image analysis.
Article in Molecular bioSystems, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 69 citations in OpenAlex.
- Synergistic Action of Antimicrobial Peptides and Antibiotics.International journal of molecular sciences · 2026Review
- Antibacterial Marinopyrroles and Pseudilins Act as Protonophores.ACS chemical biology · 2024Article
- Sensing of Antibiotic-Bacteria Interactions.Antibiotics (Basel, Switzerland) · 2023Review
- Classification of antimicrobial mechanism of action using dynamic bacterial morphology imaging.Scientific reports · 2022Article
- Technologies for High-Throughput Identification of Antibiotic Mechanism of Action.Antibiotics (Basel, Switzerland) · 2021Review
- Genome Characterization ofAntibiotics (Basel, Switzerland) · 2021Article
- Predicting antimicrobial mechanism-of-action from transcriptomes: A generalizable explainable artificial intelligence approach.PLoS computational biology · 2021Article
- Optical microscopy reveals the dynamic nature of B. pseudomallei morphology during β-lactam antimicrobial susceptibility testing.BMC microbiology · 2020Article
- Isolation and Characterization of Antimicrobial Peptides with Unusual Disulfide Connectivity from the Colonial AscidianMarine drugs · 2020Article
- Peptide Extracts from Native Lactic Acid Bacteria Generate Ghost Cells and Spheroplasts upon Interaction withBioMed research international · 2020Article
- Colistin causes profound morphological alteration but minimal cytoplasmic membrane perforation in populations of Escherichia coli and Pseudomonas aeruginosa.Archives of microbiology · 2018Article
- Comparative mass spectrometry-based metabolomics strategies for the investigation of microbial secondary metabolites.Natural product reports · 2017Review
- Morphological and ultrastructural changes in bacterial cells as an indicator of antibacterial mechanism of action.Cellular and molecular life sciences : CMLS · 2016Review
- Contribution of high-content imaging technologies to the development of anti-infective drugs.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2016Review
- Assay Development for Image-Based Quantification of Intracellular Bacterial Replication and Analysis of the Innate Immune Response to Infection.Assay and drug development technologies · 2015Article
- Integration of high-content screening and untargeted metabolomics for comprehensive functional annotation of natural product libraries.Proceedings of the National Academy of Sciences of the United States of America · 2015Article
- Connecting phenotype and chemotype: high-content discovery strategies for natural products research.Journal of natural products · 2015Review
- Functional chromatographic technique for natural product isolation.Organic & biomolecular chemistry · 2015Article
- Article
- Tools for characterizing bacterial protein synthesis inhibitors.Antimicrobial agents and chemotherapy · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
Image-based screening has become a mature field over the past decade, largely due to the detailed information that can be obtained about compound mode of action by considering the phenotypic effects of test compounds on cellular morphology. However, very few examples exist of extensions of this approach to bacterial targets. We now report the first high-throughput, high-content platform for the prediction of antibiotic modes of action using image-based screening. This approach employs a unique feature segmentation and extraction protocol to quantify key size and shape metrics of bacterial cells over a range of compound concentrations, and matches the trajectories of these metrics to those of training set compounds of known molecular target to predict the test compound's mode of action. This approach has been used to successfully predict the modes of action of a panel of known antibiotics, and has been extended to the evaluation of natural products libraries for the de novo prediction of compound function directly from primary screening data.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.