High-throughput quantification

Nature Communications paper “Deep learning for high-throughput quantification of oligodendrocyte ensheathment at single-cell resolution” by a team at McGill university describes how they established a high-throughput method to assess oligodendrocyte ensheathment in-vitro, combining nanofiber culture devices and automated imaging with a heuristic approach that informed the development of a deep learning analytic algorithm.This is important because such a method could facilitate the development of therapeutics to promote myelin protection and repair, key issues in mutiple sclerosis and CNS trauma.

In one system developed by the team, oligodendrocyte cells were cultured on Mimetix electrospun polymer aligned fibers in multiwell plates. Oligodendrocytes produce myelin sheaths around axons. In this model the aligned fibers mimic axons and the extent of ensheathment can be measured in response to different treatments.  Oligodendrocyte myelination is typically quantified manually, creating a bottleneck and introducing human subjectivity. The team developed automated high-throughput methods which could accelerate the discovery of new drugs for the treatment of de-myelinating diseases.

Reference: Deep learning for high-throughput quantification of oligodendrocyte ensheathment at single-cell resolution. Yu Kang T. Xu, Daryan Chitsaz, Robert A. Brown,Qiao Ling Cui, Matthew A. Dabarno, Jack P. Antel &Timothy E. Kennedy. Communications Biology 2, Article number: 116 (2019) |