Back

Rapid TetOn-mediated gene expression in neuronsacross the lifespan using uTTOP

Salmon, C. K.; Quesseveur, G.; Cheong, G. H. L.; Chierzi, S.; Rosen, M. P.; Green, M.; Gao, A. Y. L.; Kacerovsky, J. B.; Murai, K. K.

2023-12-07 neuroscience
10.1101/2023.12.05.570307 bioRxiv
Show abstract

Conditional expression of genes of interest is essential for interrogation of cellular development and function. Although tools exist for conditional gene expression, techniques for rapid-onset, temporally precise expression are lacking. The doxycyclineinducible TetOn expression system allows for this in numerous organ systems, however, transgenic TetOn expression cassettes become silenced in the nervous system during postnatal development. Here, we circumvent this silencing with uTTOP: in utero electroporation of Transposable TetOn Plasmids. When electroporated as transposable elements that integrate into the genome, the TetOn system allowed for robust DOX-dependent induction of expression across the postnatal lifespan of the mouse. We demonstrated induction in neurons of sensorimotor and retrospleninal cortex, hippocampus and the olfactory bulb. Latency to peak induction was [≤]12 hours, a several fold increase in induction kinetics over existing methodology for in vivo conditional expression. To demonstrate the utility of uTTOP, we induced ectopic expression of Sonic hedgehog in adult mouse layer 2/3 cortical neurons, demonstrating that its expression can diversify expression of Kir4.1 in surrounding astrocytes. The rapid induction kinetics of uTTOP allowed us to show that Kir4.1 upregulation significantly lags onset of Shh expression by [~]2 days, a difference in expression time course that is likely not resolvable with current methods. Together, these data demonstrate that uTTOP is a powerful and flexible system for conditional gene expression in multiple brain areas across the mouse lifespan.

Matching journals

The top 6 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.