Zebrafish Bacterial Load Analyzer

These pages are in support of:
Zebrafish embryo screen for mycobacterial genes involved in initiation of granuloma formation reveals a novel ESX-1 component.
Esther J.M. Stoop, Tim Schipper, Sietske K. Rosendahl Huber, Alexander E. Nezhinsky,
Fons J. Verbeek, Sudagar S. Gurcha, Gurdyal S. Besra, Christina M.J.E. Vandenbroucke-Grauls,
Wilbert Bitter and Astrid M. van der Sar
Disease Models and Mechanisms, Submitted (2010)

The research/experimental procedures on bacterial load was performed at the VUMC, Amsterdam, the Netherlands. We collaborated in this project in designing and implementing software for the quantification of bacterial load.

In order to quantify bacterial load in zebrafish, fluorescent images of infected zebrafish embryos were analyzed with specially designed, dedicated software. For the analysis, 3 types of images are distinguished.

Images are acquired of one and the same zebrafish embryo using bright-light (left) and a fluorescent (right) microscope setup.

First, blanco images are obtained. Blanco images are acquired with the fluorescent microscope and contain embryos that are not infected. Consequently, from these images, the average fluorescence background can be established per experimental set.

Second, the reference images are obtained. These reference images are acquired with the fluorescent microscope and contain embryos infected with wildtype bacteria. Each reference image is thresholded by the background value obtained from the blanco images.

Per image the sum of the pixels from the red fluorescent channel above the threshold is divided by the number of embryos. This is done so for the whole set of images in an experiment. This measurement provides us a reference value of the amount of (red) fluorescent pixels per embryo at 100% infection.

The procedure for the reference images is repeated for each experimental image in the set and subsequently, the amount of (red) fluorescent pixels is provided as a percentage with respect to the level of the infection in the wildtype.

Results are written to a comma separated file so that further statistical analysis and classification can be applied to the data. The processing does not require any operator interaction as all threshold values are derived from the images.

The following screenshots illustrate the mode of operation the zebrafish bacterial load analyser. Version 2.0 of the interface.

Choosing directories containing images

Presentation of the images to the user

View/edit image

Select image type

Running the algorithm

  • Output is printed to the interface output window and to the output.csv file.
  • The template matching algorithm, if used, automatically approximates the space where the zebrafish are located
  • Contact Alexander Nezhinsky or Fons Verbeek for information.

    For more information, see also:
    Nezhinsky A., Verbeek F.J. (2010)
    Pattern recognition for high throughput zebrafish imaging using genetic algorithm optimization.
    5th IAPR Conference on Pattern Recognition in BioInformatics (PRIB 2010).
    Lecture Notes in BioInformatics 6282, Springer, (Berlin - Heidelberg) 301-312