Spatio-temporal Proteomic Analysis of Stress Granule Disassembly Using APEX Reveals Regulation by SUMOylation and Links to ALS Pathogenesis

Abstract

Highlights• Multi bait APEX proximity labelling reveals 109 novel SG proteins and two distinct SG substructures.• Proteomic dissection of SG temporal disassembly under basal conditions and with a model of neurodegeneration. SummaryCytoplasmic stress granules (SG) form in response to a variety of cellular stresses by phase-separation of proteins associated with non-translating mRNAs. SG provide insight into the biology of neurodegeneration, including amyotrophic lateral sclerosis (ALS) because they approximate some of the molecular conditions for nucleation of insoluble aggregates in neuropathological inclusions.Whereas much has been learned about SG formation, a major gap remains in understanding the compositional changes SG undergo during normal disassembly and under disease conditions. Here, we address this gap by proteomic dissection of SG temporal disassembly sequence, using multi-bait APEX proximity-proteomics. We discover 109 novel SG-proteins and characterize at proteomic resolution two biophysically distinct SG substructures. We further demonstrate that dozens of additional proteins are recruited to SG specifically during disassembly, indicating that it is a highly regulated process. The involved proteins link SG disassembly, to mitochondrial biology and the cytoskeleton. Parallel analysis with C9ORF72-associated dipeptides, which are found in patients with ALS and frontotemporal dementia, demonstrated compositional changes in SG during the course of disassembly and focused our attention on the roles SUMOylation in SG disassembly. We demonstrate that broad SUMOylation of SG-proteins is required for SG disassembly and is impaired by C9ORF72-associated dipeptides, representing an unexplored potential molecular mechanism of neurodegeneration. Altogether, out study fundamentally increases the knowledge about SG composition in human cells by dissecting the SG spatio-temporal proteomic landscape, provides an in-depth resource for future work on SG function and reveals basic and disease-relevant mechanisms of SG disassembly.