PUBLICATION
An Image Processing Tool for Automated Quantification of Bacterial Burdens in Zebrafish Larvae
- Authors
- Yamaguchi, N., Otsuna, H., Eisenberg-Bord, M., Ramakrishnan, L.
- ID
- ZDB-PUB-250109-6
- Date
- 2024
- Source
- Zebrafish : (Journal)
- Registered Authors
- Ramakrishnan, Lalita
- Keywords
- zebrafish infection model/image analysis
- MeSH Terms
-
- Animals
- Zebrafish*/microbiology
- Bacterial Load/methods
- Larva*/growth & development
- Larva*/microbiology
- Mycobacterium marinum*/growth & development
- Mycobacterium marinum*/isolation & purification
- Disease Models, Animal
- Fish Diseases/microbiology
- Mycobacterium Infections, Nontuberculous/microbiology
- Mycobacterium Infections, Nontuberculous/veterinary
- Image Processing, Computer-Assisted*/methods
- PubMed
- 39718816 Full text @ Zebrafish
Citation
Yamaguchi, N., Otsuna, H., Eisenberg-Bord, M., Ramakrishnan, L. (2024) An Image Processing Tool for Automated Quantification of Bacterial Burdens in Zebrafish Larvae. Zebrafish. :.
Abstract
Zebrafish larvae are used to model the pathogenesis of multiple bacteria. This transparent model offers the unique advantage of allowing quantification of fluorescent bacterial burdens (fluorescent pixel counts [FPC]) in vivo by facile microscopical methods, replacing enumeration of bacteria using time-intensive plating of lysates on bacteriological media. Accurate FPC measurements require laborious manual image processing to mark the outside borders of the animals so as to delineate the bacteria inside the animals from those in the culture medium that they are in. Here, we have developed an automated ImageJ/Fiji-based macro that accurately detects the outside borders of Mycobacterium marinum-infected larvae.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping