bioRxivNeurosciencePreprint
Spreading alpha-Synuclein Oligomers Trigger Astrocyte Changes and Astrocyte-Glutamatergic Neuron system dysfunction in an Age-related Manner
Jaehyun LeeBaeiD, Verena BoppiD, Alicia GorethiD, Veselin GrozdanoviD, Julia K. Kühlwein, Ermanno Gazzola, Daniel Rombach, Laura Meier, Leda DimouiD, Karin M. DanzeriD
Abstract
BackgroundParkinsons disease (PD) is characterized by the progressive accumulation and spatio-temporal spread of -synuclein (-syn) oligomers and a progressive loss of dopaminergic neurons. Many studies showed a direct cytotoxic effect of -syn oligomers on neurons. Other cell types including astrocytes were also reported to show specific responses to -syn and are believed to play a role in the spreading of PD pathology. MethodsTo investigate the transcriptional and cellular consequences of -syn oligomer spreading, we employed spatial transcriptomics and single-nucleus RNA sequencing (snRNA-seq) in a transgenic PD mouse model expressing human -syn in neurons. We further compared our findings to published public snRNA-seq datasets from human PD patients ResultsOur analysis identified -syn spreading mostly to the substantia nigra and defined a transcriptional "Spreading Signature" associated with -syn pathology. We found an age correlated increase in astrocytes, close interactions between astrocytes and -syn, and transcriptional dysregulation of the astrocyte-glutamatergic neuron axis. We further identified two subtypes of glutamatergic neurons that are vulnerable to astrocytic changes. Comparative analysis with human PD snRNA-seq data showed concordant transcriptional changes related to astrocytic dysfunctions and diminished neuronal signaling. ConclusionBased on our results, we propose a model of -syn oligomer spreading involving astrocytes, glutamatergic synapses, and a disturbance in the astrocyte-glutamatergic neuron axis.
- organism: mouse
- assay: spatial transcriptomics
- assay: snRNA-seq
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 0
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