Comparing Transcriptome Profiles of Neurons Interfacing Adjacent Cells and Nanopatterned Substrates Reveals Fundamental Neuronal Interactions

• Published in: Nano letters Vol. 19; no. 3; pp. 1451 - 1459
• Main Authors: Baranes, Koby, Hibsh, Dror, Cohen, Sharon, Yamin, Tony, Efroni, Sol, Sharoni, Amos, Shefi, Orit
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 13.03.2019
• Subjects: RNA-sequencing; brain machine interface; Neuronal growth; nanotopography; gene expression
• ISSN: 1530-6984; 1530-6992
• DOI: 10.1021/acs.nanolett.8b03879

Developing neuronal axons are directed by chemical and physical signals toward a myriad of target cells. According to current dogma, the resulting network architecture is critically shaped by electrical interconnections, the synapses; however, key mechanisms translating neuronal interactions into neuronal growth behavior during network formation are still unresolved. To elucidate these mechanisms, we examined neurons interfacing nanopatterned substrates and compared them to natural interneuron interactions. We grew similar neuronal populations under three connectivity conditions, (1) the neurons are isolated, (2) the neurons are interconnected, and (3) the neurons are connected only to artificial substrates, then quantitatively compared both the cell morphologies and the transcriptome-expression profiles. Our analysis shows that whereas axon-guidance signaling pathways in isolated neurons are predominant, in isolated neurons interfacing nanotopography, these pathways are downregulated, similar to the interconnected neurons. Moreover, in nanotopography, interfacing neuron genes related to synaptogenesis and synaptic regulation are highly expressed, that is, again resembling the behavior of interconnected neurons. These molecular findings demonstrate that interactions with nanotopographies, although not leading to electrical coupling, play a comparable functional role in two major routes, neuronal guidance and network formation, with high relevance to the design of regenerative interfaces.