bioRxivNeurosciencePreprint
Single cell RNA sequencing reveals limited effects of Lrrk2 genotype in a mouse model of acute CNS inflammation
Alice KaganovichiD, Liam Horan-PortelanceiD, Natalie LandeckiD, Dominic J. AcriiD, Jinhui DingiD, Rebekah G. LangstoniD, Mark CooksoniD
Abstract
BACKGROUNDPrevious data implicates neuroinflammation in the pathogenesis of Parkinsons disease (PD). Of the genes associated with PD, Leucine rich repeat kinase 2 (LRRK2) has previously been proposed to play a role in neuroinflammation. However, the extent to which LRRK2 is involved in endogenous inflammatory signaling is unclear. OBJECTIVETo examine whether endogenous mutations in LRRK2 affect responses to neuroinflammation in vivo. METHODSWe injected cohorts of mice with knock-in mutations in Lrrk2, homologous to those causing human PD, with a single intrastriatal injection of lipopolysaccharide (LPS) or control. We used single cell RNA-Sequencing to examine cell type specific responses to treatment and genotype and validated key results with orthogonal approaches. RESULTSWe found that our chosen paradigm of acute LPS exposure evokes robust transcriptional changes consistent with a multicellular neuroinflammatory response. We also found evidence of peripheral immune cell recruitment into the brain and interaction with brain-resident microglia. However, the transcriptional effects of Lrrk2 mutations were limited to small numbers of genes, including down regulation of gene ontogeny terms related to lysosomes, in microglia. CONCLUSIONSOur data clearly demonstrate that many cells in the brain respond to a single inflammatory insult with strong transcriptional responses and that, even in a model focused on CNS injection, there is interaction between peripheral and central immune cells. In contrast, the quantitative effects of Lrrk2 mutations are modest at the transcriptional level, demonstrating that additional studies are needed to clarify whether Lrrk2 mutations affect neuroinflammation in an endogenous context.
- organism: mouse
- assay: scRNA-seq
- research focus: differential expression
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 0
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