Primary data associated with doi: 10.1101/2022.04.25.489459 (A Feed-forward Pathway Drives LRRK2 kinase Membrane Recruitment and Apparent Activation)

By Ayan Adhikari, PhD and Claire Chiang
View Published Dataset

Output Details

Description

Raw immunoblotting data; tabular data for quantifications; immunofluorescence images.

Identifier (DOI)
10.5061/dryad.3tx95x6j7
Tags
  • LRRK2
  • Rab GTPases
Team
Team Alessi
Program
Collaborative Research Network
Theme
PD Functional Genomics

Meet the Authors

  • User avatar fallback logo

    Ayan Adhikari, PhD

    Key Personnel: Team Alessi, 

    Stanford University

  • User avatar fallback logo

    Claire Chiang

    Key Personnel: Team Alessi, 

    Stanford University

Related Research

Leucine Rich Repeat Kinase 2: Pathways to Parkinson’s Disease

Research on LRRK2 in Parkinson's disease has advanced, revealing how mutations activate the kinase, phosphorylate Rab proteins, disrupt cell functions like Hedgehog signaling, and contribute to the disease. LRRK2 inhibitors show promise for therapy.

View Article

Elevated brain α-synuclein, phosphorylated-tau, and oxidative stress in mice that survived influenza A pneumonitis

Influenza virus infection does not alter acute lung infection course in mice with Lrrk2 mutations. Surviving mice showed elevated neurodegeneration markers post-infection, suggesting a link between influenza and neurodegenerative diseases in humans.

View Article

Binding of Rab29 to the LRRK2 Armadillo domain by Microscale Thermophoresis

Microscale thermophoresis is a powerful tool to measure the affinities of interactions between proteins. We present here our method for determining the binding of Rab29 GTPase to the LRRK2 N-terminal Armadillo domain.

View Protocol
View More Outputs
Aligning Science Across Parkinson's
Powered by  GDPR Cookie Compliance
Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.