Back

Demyelination induces transcriptional reprogramming in proprioceptive and Aβ rapidly adapting low-threshold-mechanoreceptor neurons.

Elbaz, B.; Yang, L.; Rader, B. L.; Kawaguchi, R.; Traka, M.; Woolf, C. J.; Renthal, W.; Popko, B.

2021-11-23 neuroscience
10.1101/2021.11.23.469748 bioRxiv
Show abstract

Schwann cells, the main glial cell in the peripheral nervous system (PNS), ensheath bundles of small unmyelinated axons or form myelin on larger axons. PNS injuries initiate transcriptional reprograming in both Schwann cells and sensory neurons that promotes regeneration. While the factors that initiate the transcriptional reprograming in Schwann cells are well characterized, the full range of stimuli that initiate this reprograming in sensory neurons remain elusive. Here, using a genetic model of Schwann cell ablation, we find that Schwann cell loss results in transient PNS demyelination without overt axonal loss. By profiling sensory ganglia at single-cell resolution we show that this demyelination induces transcriptional reprogramming preferably in proprioceptive and A{beta} RA-LTMR neurons. Transcriptional reprograming is assumed to be a cell autonomous response of sensory neurons to mechanical axonal injury. By identifying similar reprograming in non-injured, demyelinated neurons, our study suggests that this reprograming represents a non-cell autonomous transcriptional response of sensory neurons to the loss of axon-Schwann cell interactions. HighlightsO_LIAblation of Schwann cells results in transient PNS demyelination, without overt axonal loss. C_LIO_LISchwann cell loss results in transcriptional reprograming in specific sensory neurons. C_LIO_LISpinal nerve transection (mechanical injury of axons) and demyelination (intact axons) induces similar transcriptional responses in DRG neurons. C_LIO_LIThe transcriptional response to demyelination among DRG neurons is specific to the large myelinated proprioceptive and A{beta} RA-LTMR neurons. C_LI

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.