Oral Presentation 27th Annual Lorne Proteomics Symposium 2022

Shifting picture of astrocyte responses through targeted spatial organelle proteomics-based interactions (#55)

Ben B Wang 1 , Sandra Isenmann 1 , Cheng Huang 2 , Ralf B Schittenhelm 2 , Pirjo M Apaja 1 3
  1. South Australian Health and Medical Research Institute and EMBL Australia, Adelaide, SA, Australia
  2. Monash Proteomics and Metabolomics Facility, Monash University, Clayton, Victoria, Australia
  3. Organelle Proteostasis Diseases, Flinders University, Bedford Park, SA, Australia

Astrocytes are brain cells that have a significant role in supporting brain metabolism, ionic and protein homeostasis (proteostasis). Because of these many roles, their dysregulation is associated with complex brain processes and diseases such as neurodegeneration.

We used spatial membrane organelle proteomics to find interactome networks for the astrocyte regulatory membrane protein signalling cluster, which dysregulation has been associated with complex brain diseases and phenotypes from autism to neuroinflammation. We used label-free affinity-purification mass spectrometry (AP-MS) and proximity-dependent biotin identification (BioID-MS) at a whole cell and organelle level1 to gain information of the native (health) and disrupted (disease) cluster identity in moving subcellular membranes. A computational approach was used to assign confidence scores2 to protein-protein interactions and to build the protein-protein interaction networks.

To gain further insight into the observed phenomena between the healthy and diseases associated cluster, we compared their spatial protein networks. This pin-pointed shifting interactions inside protein families such as solute carriers and gave focused targets with a subcellular location. Specifically, comparing some of the networks and targets with a genetic loss-of-function and biochemical experimentations revealed hidden proteostasis stress response pathways.

This study gives merits of combining targeted and spatial proteomics with other experimental approaches to gain knowledge of hidden and deep mechanistic insights. It highlights the benefits of profiling changing interactomes in health and diseases.

  1. 1. Go CD et al., A proximity-dependent biotinylation map of a human cell. 2021, Nature 595(7865):120-124
  2. 2. Choi H et al., Probabilistic scoring of affinity purification-mass spectrometry data, Nat Methods, 2011, (1):70-3