Pathway-specific dysregulation of striatal excitatory synapses by LRRK2 mutations
Abstract
LRRK2 is a kinase expressed in striatal spiny projection neurons (SPNs), cells which lose dopaminergic input in Parkinson’s disease (PD). R1441C and G2019S are the most common pathogenic mutations of LRRK2. How these mutations alter the structure and function of individual synapses on direct and indirect pathway SPNs is unknown and may reveal pre-clinical changes in dopamine-recipient neurons that predispose towards disease. Here, R1441C and G2019S knock-in mice enabled thorough evaluation of dendritic spines and synapses on pathway-identified SPNs. Biochemical synaptic preparations and super-resolution imaging revealed increased levels and altered organization of glutamatergic AMPA receptors in LRRK2 mutants. Relatedly, decreased frequency of miniature excitatory post-synaptic currents accompanied changes in dendritic spine nano-architecture, and single-synapse currents, evaluated using 2-photon glutamate uncaging. Overall, LRRK2 mutations reshaped synaptic structure and function, an effect exaggerated in R1441C dSPNs. These data open the possibility of new neuroprotective therapies aimed at SPN synapse function, prior to disease onset.
Data availability
All data generated during this study are included in the manuscript and supporting files.
Article and author information
Author details
Funding
National Institute of Neurological Disorders and Stroke (R01NS097901)
- Loukia Parisiadou
Michael J. Fox Foundation for Parkinson's Research (LRRK2 Challenge)
- Loukia Parisiadou
National Institute of Neurological Disorders and Stroke (R01NS107539)
- Yevgenia Kozorovitskiy
Rita Allen Foundation (Rita Allen Scholar Award)
- Yevgenia Kozorovitskiy
Kinship Foundation (Searle Scholar Award)
- Yevgenia Kozorovitskiy
Arnold and Mabel Beckman Foundation (Beckman Young Investigator Award)
- Yevgenia Kozorovitskiy
National Institute of Neurological Disorders and Stroke (F32NS103243)
- Nicholas Bannon
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 mouse experiments were approved by Northwestern University Animal Care and Use Committee (Approved protocol numbers IS000035451, IS00000838, and 00009022).
Copyright
© 2020, Chen 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
-
- 2,752
- views
-
- 385
- downloads
-
- 42
- 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
-
- Computational and Systems Biology
- Neuroscience
The basolateral amygdala (BLA) is a key site where fear learning takes place through synaptic plasticity. Rodent research shows prominent low theta (~3–6 Hz), high theta (~6–12 Hz), and gamma (>30 Hz) rhythms in the BLA local field potential recordings. However, it is not understood what role these rhythms play in supporting the plasticity. Here, we create a biophysically detailed model of the BLA circuit to show that several classes of interneurons (PV, SOM, and VIP) in the BLA can be critically involved in producing the rhythms; these rhythms promote the formation of a dedicated fear circuit shaped through spike-timing-dependent plasticity. Each class of interneurons is necessary for the plasticity. We find that the low theta rhythm is a biomarker of successful fear conditioning. The model makes use of interneurons commonly found in the cortex and, hence, may apply to a wide variety of associative learning situations.
-
- Neuroscience
Mice can generate a cognitive map of an environment based on self-motion signals when there is a fixed association between their starting point and the location of their goal.