ArticleScientific reports2020
Efficient microbial colony growth dynamics quantification with ColTapp, an automated image analysis application.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
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- A Ratiometric pH Sensor for Gram-Positive and Gram-Negative Bacteria.Journal of the American Chemical Society · 2026Article
- A weakly supervised framework for automated biological assay assessment.Virus research · 2026Article
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- Real-time imaging of bacterial colony growth dynamics for cells with Type IV-A1 CRISPR-Cas activity.microLife · 2025Article
- Single-cell phenotypic profiling and backtracing exposes and predicts clinically relevant subpopulations in isogenic Staphylococcus aureus communities.Communications biology · 2024Article
- Investigating group AmSphere · 2024Article
- Bacterial persisters: molecular mechanisms and therapeutic development.Signal transduction and targeted therapy · 2024Review
- High-throughput characterization of the effect of sodium chloride and potassium chloride on 31 lactic acid bacteria and their co-cultures.Frontiers in microbiology · 2024Article
- First-passage-time statistics of growing microbial populations carry an imprint of initial conditions.Scientific reports · 2023Article
- Single-cell patterning and characterisation of antibiotic persistent bacteria using bio-sCAPA.Lab on a chip · 2023Article
- Bacterial colony size growth estimation by deep learning.BMC microbiology · 2023Article
- Limited Adaptation ofMicrobiology spectrum · 2023Article
- Annotated dataset for deep-learning-based bacterial colony detection.Scientific data · 2023Article
- Tools for classification of growing/non-growing bacterial colonies using laser speckle imaging.Frontiers in microbiology · 2023Article
- Article
- Methods to monitor bacterial growth and replicative rates at the single-cell level.FEMS microbiology reviews · 2022Review
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
Abstract
Populations of genetically identical bacteria are phenotypically heterogeneous, giving rise to population functionalities that would not be possible in homogeneous populations. For instance, a proportion of non-dividing bacteria could persist through antibiotic challenges and secure population survival. This heterogeneity can be studied in complex environmental or clinical samples by spreading the bacteria on agar plates and monitoring time to growth resumption in order to infer their metabolic state distribution. We present ColTapp, the Colony Time-lapse application for bacterial colony growth quantification. Its intuitive graphical user interface allows users to analyze time-lapse images of agar plates to monitor size, color and morphology of colonies. Additionally, images at isolated timepoints can be used to estimate lag time. Using ColTapp, we analyze a dataset of Staphylococcus aureus time-lapse images including populations with heterogeneous lag time. Colonies on dense plates reach saturation early, leading to overestimation of lag time from isolated images. We show that this bias can be corrected by taking into account the area available to each colony on the plate. We envision that in clinical settings, improved analysis of colony growth dynamics may help treatment decisions oriented towards personalized antibiotic therapies.
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