A Bivalent Securinine Compound SN3-L6 Induces Neuronal Differentiation via Translational Upregulation of Neurogenic Transcription Factors - Liao, Yumei; Zhuang, Xiaoji; Huang, Xiaojie; Peng, Yinghui; Ma, Xuanyue; Huang, Zhi-Xing; Liu, Feng; Xu, Junyu; Wang, Ying; Chen, Wei-Min; Ye, Wen-Cai; Shi, Lei (Frontiers in Pharmacology, 2018)
Developing therapeutic approaches that target neuronal differentiation will be greatly beneficial for the regeneration of neurons and synaptic networks in neurological diseases. Protein synthesis (mRNA translation) has recently been shown to regulate neurogenesis of neural stem/progenitor cells (NSPCs). However, it has remained unknown whether engineering translational machinery is a valid approach for manipulating neuronal differentiation. The present study identifies that a bivalent securinine compound SN3-L6, previously designed and synthesized by our group, induces potent neuronal differentiation through a novel translation-dependent mechanism. An iTRAQ (isobaric tag for relative and absolute quantitation)-based proteomic analysis in Neuro-2a progenitor cells revealed that SN3-L6 upregulated a group of neurogenic transcription regulators, and also upregulated proteins involved in RNA processing, translation, and protein metabolism. Notably, puromycylation and metabolic labeling of newly synthesized proteins demonstrated that SN3-L6 induced rapid and robust activation of general mRNA translation. Importantly, mRNAs of the proneural transcription factors Foxp1, Foxp4, Hsf1 and Erf were among the targets that were translationally upregulated by SN3-L6. Either inhibition of translation or knockdown of these transcription factors blocked SN3-L6 activity. We finally confirmed that protein synthesis of a same set of transcription factors was upregulated in primary cortical NPCs. These findings together identify a new compound for translational activation and neuronal differentiation, and provide compelling evidence that reprogramming transcriptional regulation network at translational levels is a promising strategy for engineering NSPCs.