Back

An optogenetic toolkit for robust activation of FGF, BMP, and Nodal signaling in zebrafish

Iannucci, L. E.; Velanganni, S. M. T.; Murphy, M. R.; Donahue, C. E. T.; Anderson, W. K.; Rogers, C. E.; Saul, A. J.; Rogers, K. W.

2025-04-19 developmental biology
10.1101/2025.04.17.649426 bioRxiv
Show abstract

Cell signaling regulates a wide range of biological processes including development, homeostasis, and disease. Accessible technologies to precisely manipulate signaling have important applications in basic and translational research. Here, we present an optogenetic toolkit for signaling manipulation in zebrafish embryos. We introduce a zebrafish-optimized optogenetic FGF signaling activator and a single-transcript Nodal signaling activator, and assess them together with a previously established BMP signaling activator. We thoroughly characterize this suite of tools and demonstrate light-dependent spatiotemporal control of signaling in vivo. In response to [~]455 nm (blue) light, zebrafish receptor kinase domains fused to blue light-dimerizing LOV domains enable robust signaling activation with minimal inadvertent activity in the dark or at wavelengths over 495 nm. Each optogenetic tool initiates pathway-specific signaling and activates known target genes. Signaling is activated with rapid on/off kinetics, and activation strength can be tuned by adjusting light irradiance. Finally, we demonstrate spatially localized signaling activation in vivo. Together, our results establish this optogenetic toolkit as a potent experimental platform and provide guidelines for rapid, direct, and adjustable activation of FGF, BMP, and Nodal signaling in zebrafish embryos.

Published in Developmental Biology (predicted rank #3) · training set

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.