This study presents a method for visualizing infection dynamics in anesthetized zebrafish embryos using fluorescently labeled pathogenic bacteria. The protocol allows for a direct comparison of infection progression in live embryos with and without biomaterial exposure.
Begin with anesthetized zebrafish embryos injected with fluorescently labeled pathogenic bacteria, either alone or mixed with biomaterial microspheres, to model biomaterial-associated infection in vivo.
Place a Petri dish containing basal media with anesthetic on the stage of a stereo fluorescence microscope equipped with appropriate filters.
Add methylcellulose solution to the dish to create a viscous medium that immobilizes embryos for imaging.
Transfer individual embryos into the methylcellulose and align them horizontally, ensuring the injection site is visible.
Using the bright-field filter, focus on the injection site to target the infected region.
Set the Z-stack imaging parameters and acquire fluorescence images at different depths to capture infection dynamics in three dimensions.
Using software, analyze the images captured over time to quantify fluorescence intensity and monitor bacterial distribution.
This protocol enables a direct comparison of infection progression in live embryos with and without biomaterial exposure.
Place a 100-millimeter Petri dish containing E3 medium supplemented with 0.02% tricaine on a stereo fluorescence microscope stage, and add 500 microliters of 2% methylcellulose into the Petri dish. To monitor the infection progress by fluorescence microscopy, equip the appropriate bright-field and fluorescent filters, align the anesthetized infected embryos horizontally in a spot of methylcellulose in a Petri dish.
Use the bright-field filter to bring the damaged injected tissue into focus at a 160x magnification. Set the Z-stack depth at 10 micrometers and the step size at five micrometers to allow the recording of three consecutive images. Then image the individual embryos under identical optimized settings at a 160x magnification.
Use the ObjectJ plugin in ImageJ to analyze the images.