Spatial transcriptomics at the interface of implanted electrodes in the brain

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PROJECT SUMMARY Through “read-out” and “write-in” of electrical activity, implanted electrodes in the brain have enabled new discoveries in basic neuroscience research and breakthroughs in the treatment of neurological diseases and injury. However, the biological response to electrodes is widely believed to contribute to variations in recording and stimulation efficacy over time. Despite decades of research, it remains unclear which elements of the tissue response are performance-determining, as traditional metrics of the tissue response have failed to fully explain changes in signal quality, stimulation thresholds, or device longevity. It is our objective to explore new hypotheses and apply new methods to this long-standing issue. In this proposal, we will apply state-of-the-art techniques in spatial transcriptomics to the device-tissue interface. This approach will build upon our recently reported publication, which described spatiotemporal changes in gene expression surrounding devices using a combination of laser capture microscopy and RNA-sequencing. The data revealed 157 differentially expressed (DE) genes in tissue surrounding implanted electrodes in comparison to unimplanted control tissue. However, spatial transcriptomics detects the spatial distribution of transcriptional changes in tissue via barcoded RNA- capture oligonucleotides mounted to slides. The method delivers several advantages over previous approaches: (1) superior spatial resolution, (2) excellent RNA quality, and (3) the ability to assess transcriptional changes in combination with traditional immunohistochemistry labeling within the same tissue slice. Recently, we successfully applied spatial transcriptomics to rat motor cortex tissue following implantation of a single electrode array for a period of one week. The preliminary data revealed superior spatial sampling of transcriptional changes as well as newly unmasked DE genes. The purpose of this R03 application is to collect a more comprehensive pilot data set to explore these changes across multiple animals and time points (2 hours to 6 weeks), while developing analysis techniques to reveal novel gene modules expressed in tissue local to devices. The study includes two aims: Aim 1 will reveal the spatial organization of transcriptional changes surrounding implanted electrodes in the motor cortex of rats across a six-week time course and Aim 2 will develop network analysis techniques to reveal device-induced gene modules and key hub genes localized to the implant interface. We expect the project to deliver a novel data set which will be useful to the field as a stand-alone effort (all data and codes will be publicly accessible), while providing a foundation for future follow-on studies in a larger-scale proposal.