Which Neurons Respond to Epidural Electrical Stimulation (EES)?
One of the most severe types of injury is a spinal cord injury that disrupts the delicate neural circuitry between the brain and the spinal cord. This can often result in partial or complete paralysis. One of the few successful treatment avenues for spinal cord injuries is epidural electrical stimulation (EES), where implanted electrodes deliver electrical signals to surviving neurons in the spinal cord.
Since its development 50 years ago, EES has been known to help restore some motor function, especially related to walking. The technique and electrodes have also been refined over time to maximize their effectiveness. However, it has remained unclear exactly how EES remodels neural circuits in the spinal cord, or which subpopulations of neurons are the most essential to the healing process.
Using Single Cell and Spatial Transcriptomics to Identify Neuronal Subpopulations
In a recent Nature paper, Kathe et. al. harnessed single cell transcriptomics to examine the gene expression changes that occur in neurons during recovery from a spinal cord injury in a mouse model treated with EES. The authors had previously developed a machine-learning model that identifies cell types that respond to certain biological stimuli. Using this tool, they identified a specific type of neuron that produces a robust response to EES.
In their mouse model, simply increasing function of these neurons mimicked the same improvements in walking and motor function as EES and rehabilitation. Conversely, ablating those neurons prevented the normal recovery of walking seen in a mouse model of a more mild spinal cord injury. Taken together, these results demonstrate the value of (1) using bioinformatics to (2) determine a molecular map of recovery and (3) improve the ability to target and protect beneficial cell types.
Outsourcing Bioinformatics Analysis: How We Can Help
The applications of single cell approaches are innumerable, and our clients are at the forefront of tackling research questions using these kinds of sophisticated bioinformatics approaches. However, transforming raw sequence data of any kind into actionable biological insights is no small feat.
As experts across data types from cutting-edge sequencing platforms, we can help you tackle the challenging computational tasks of storing, analyzing and interpreting genomic data. Bridge Informatics’ bioinformaticians are trained bench biologists, so they understand the biological questions driving your computational analysis. Click here to schedule a free introductory call with a member of our team.
Jane Cook, Biochemist & Content Writer, Bridge Informatics
Jane Cook, leading Content Writer for Bridge Informatics, has written over 100 articles on the latest topics and trends for the bioinformatics community. Jane’s broad and deep interdisciplinary molecular biology experience spans developing biochemistry assays to genomics. Prior to joining Bridge, Jane held research assistant roles in biochemistry research labs across a variety of therapeutic areas. While obtaining her B.A. in Biochemistry from Trinity College in Dublin, Ireland, Jane also studied journalism at New York University’s Arthur L. Carter Journalism Institute. As a native Texan, she embraces any challenge that comes her way. Jane hails from Dallas but returns to Ireland any and every chance she gets. If you’re interested in reaching out, please email daniel.dacey@old.bridgeinformatics.com or dan.ryder@old.bridgeinformatics.com.
