Gab1 mediates PDGF signaling and is essential to oligodendrocyte differentiation and CNS myelination
Abstract
Oligodendrocytes (OLs) myelinate axons and provide electrical insulation and trophic support for neurons in the central nervous system (CNS). Platelet-derived growth factor (PDGF) is critical for steady-state number and differentiation of oligodendrocyte precursor cells (OPCs), but its downstream targets are unclear. Here, we show for the first time that Gab1, an adaptor protein of receptor tyrosine kinase, is specifically expressed in OL lineage cells and is an essential effector of PDGF signaling in OPCs in mice. Gab1 is down-regulated by PDGF stimulation and up-regulated during OPC differentiation. Conditional deletions of Gab1 in OLs cause CNS hypomyelination by affecting OPC differentiation. Moreover, Gab1 binds to downstream GSK3β and regulated its activity, and thereby affects the nuclear accumulation of β-catenin and the expression of a number of transcription factors critical to myelination. Our work uncovers a novel downstream target of PDGF signaling, which is essential to OPC differentiation and CNS myelination.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files.
Article and author information
Author details
Funding
Ministry of Science and Technology of the People's Republic of China (2017YFA0104200)
- Ying Shen
National Natural Science Foundation of China (31571051)
- Liang Zhou
National Natural Science Foundation of China (81625006)
- Ying Shen
National Natural Science Foundation of China (31820103005)
- Ying Shen
Natural Science Foundation of Zhejiang Province (Z15C090001)
- Ying Shen
Natural Science Foundation of Zhejiang Province (LQ17C090001)
- Na Wang
Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2017PT31038)
- Ying Shen
Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2018PT31041)
- Ying Shen
Chinese Ministry of Education Project 111 Program (B13026)
- Ying Shen
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: All of the animals were handled according to approved protocol (ZJU20160019) of the Animal Experimentation Ethics Committee of Zhejiang University.
Copyright
© 2020, Zhou et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,944
- views
-
- 326
- downloads
-
- 18
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Neuroscience
Combining electrophysiological, anatomical and functional brain maps reveals networks of beta neural activity that align with dopamine uptake.
-
- Neuroscience
During rest and sleep, memory traces replay in the brain. The dialogue between brain regions during replay is thought to stabilize labile memory traces for long-term storage. However, because replay is an internally-driven, spontaneous phenomenon, it does not have a ground truth - an external reference that can validate whether a memory has truly been replayed. Instead, replay detection is based on the similarity between the sequential neural activity comprising the replay event and the corresponding template of neural activity generated during active locomotion. If the statistical likelihood of observing such a match by chance is sufficiently low, the candidate replay event is inferred to be replaying that specific memory. However, without the ability to evaluate whether replay detection methods are successfully detecting true events and correctly rejecting non-events, the evaluation and comparison of different replay methods is challenging. To circumvent this problem, we present a new framework for evaluating replay, tested using hippocampal neural recordings from rats exploring two novel linear tracks. Using this two-track paradigm, our framework selects replay events based on their temporal fidelity (sequence-based detection), and evaluates the detection performance using each event's track discriminability, where sequenceless decoding across both tracks is used to quantify whether the track replaying is also the most likely track being reactivated.