Neuronal activity-dependent gene expression is stimulus-specific and changes with neuronal maturation

Neuronal activity-dependent gene expression is fundamental to a wide variety of brain functions. The field of neuronal activity-induced gene expression has advanced greatly due to studies performed in early neuronal cultures (7 to 10 DIV) and stimulated with different activation protocols. However, the effect of the developmental stage as well as the influence of specific protocol stimuli like potassium chloride (KCl)-induced depolarization, bicuculline (Bic)-mediated synaptic activation and TTX-withdrawal (TTXw) on activity-induced transcription has not been systematically studied.

To analyze the influence of neuronal maturation on activity-induced transcription, we used neuronal primary cultures to compare electrophysiological and transcriptional responses at 7 days in vitro (DIV) and 21 DIV upon KCl and Bic stimulation. Also, mature neurons in culture were subjected to treatments with KCl, Bic and TTXw and the transcriptional changes were assessed by RNA-Seq and post-hoc bioinformatic analysis.

Our results demonstrate that the developmental stage of neurons profoundly influences neuronal firing and gene expression. The response to KCl and Bicuculline was dramatically different, even though these compound-based activation protocols have been widely used and considered as methods that produce equivalent effects. Therefore, we next asked how 21DIV neurons, more advanced in their development, react to different stimuli and observed that KCl, Bic and TTXw, which trigger different firing patterns, induce specific transcriptional profiles with unique temporal dynamics and activating a variety of gene groups.

These findings hold both technical and conceptual significance. Technically, they underscore the importance of accounting for neuronal maturation and activation protocols when studying gene expression. Conceptually, they demonstrate that neuronal development and drug-induced firing patterns generate distinct expression profiles, which could be crucial for a deeper understanding of transcription-dependent plasticity mechanisms.