Time-resolved proteomic profiling reveals compositional and functional transitions across the stress granule life cycle

Abstract

Stress granules (SGs) are dynamic, membrane-less organelles. With their formation and disassembly processes characterized, it remains elusive how compositional transitions are coordinated during prolonged stress to meet changing functional needs. Here, using time-resolved proteomic profiling of the acute to prolonged heat-shock SG life cycle, we identify dynamic SG proteins, further segregated into early and late proteins. Comparison of different groups of SG proteins suggests that their biochemical properties help coordinate SG compositional and functional transitions. In particular, early proteins, with high phase-separation-propensity, drive the rapid formation of the initial SG platform, while late proteins are subsequently recruited as discrete modules to further functionalize SGs. This model, supported by immunoblotting and immunofluorescence imaging, provides a conceptual framework for the compositional transitions throughout the acute to prolonged SG life cycle. Additionally, an early SG constituent, non-muscle myosin II, is shown to promote SG formation by increasing SG fusion, underscoring the strength of this dataset in revealing the complexity of SG regulation.

Proteomic analysis of the TDP-43-associated insoluble fraction from NEFH-TDP-43 mouse brain suggests sustained stress granule formation, CLUH granule recruitment and impaired mitochondrial metabolism

“…Further comparison against a list of early and late stress granules markers (Hu et al, 2023) identified a further 16 SG markers, of which most were categorised as late SG markers. Therefore, 30% (40/134 proteins) of our SG preparation consisted of known SG markers (Hu et al, 2023; Jain et al, 2016). There were 17 proteins comparatively depleted in the SG fraction from the NEFH-TDP-43 mouse brains, when compared to the control mice (control/TDP = fold change >1.5, p<0.05) (Supplementary Table 3).…”

“…Following comparison with the mammalian SG proteome (Jain et al, 2016), 24 of our 134 enriched proteins were known SG markers (Supplementary Table 2). Further comparison against a list of early and late stress granules markers (Hu et al, 2023) identified a further 16 SG markers, of which most were categorised as late SG markers. Therefore, 30% (41/134 proteins) of our SG preparation consisted of known SG markers (Hu et al, 2023; Jain et al, 2016).…”

“…Further comparison against a list of early and late stress granules markers (Hu et al, 2023) identified a further 16 SG markers, of which most were categorised as late SG markers. Therefore, 30% (41/134 proteins) of our SG preparation consisted of known SG markers (Hu et al, 2023; Jain et al, 2016). Stress granule formation is initiated by the activation of eIF2α via its phosphorylation by either PERK, HRI, GCN2 or PKR kinases (Taniuchi et al, 2016).…”

“…From the ~5000 proteins quantified, a subset of 134 proteins were enriched and 17 proteins depleted, in the end-stage TDP-43 mouse brain tissue, compared with the control mice. Of these enriched proteins, 41 proteins were SG markers (Hu et al, 2023; Jain et al, 2016). Approximately 70% of the enriched dataset was covered by functional GO terms relating to binding of ATP and RNA, in addition to the biological processes, ribose phosphate metabolic process, and the cellular component’s, cytoskeleton and mitochondrion.…”

“…A complete list of all the TDP-43 associated proteins was generated by selection of all proteins that had quantifiable protein abundances in the TDP-43 sample group based on the unique accession numbers of the master protein. The gene symbols were used for cross species comparison against the Lunenfield RNA granule database and specific stress granule lists from (Jain et al, 2016) and (Hu et al, 2023). Protein ratios were calculated using protein abundances and Hypothesis testing was based on ANOVA (individual protein) calculations.…”