Back

Interactors of sacsin DNAJ domain identify function in organellar transport and membrane composition relevant to ARSACS pathogenesis

Pare, A. M.; Cheng-Boivin, Z.; Dabbaghizadeh, A.; Minotti, S.; Durham, H. D.; Gentil, B. J.

2024-01-09 cell biology
10.1101/2024.01.08.574743 bioRxiv
Show abstract

Autosomal Recessive Spastic Ataxia of the Charlevoix Saguenay (ARSACS) is caused by loss of function mutations in the SACS gene encoding sacsin, a 520kDa protein with multiple functional domains. The goal of this study was to identify client proteins interacting with the J domain, a cochaperone domain interacting with Hsp70 chaperones, to gain insights into sacsins function and its disruption in experimental models of ARSACS. Pull downs from mouse brain identified Rabs and Rab-associated proteins including Rab1b, ARF5 and endophilin B2, involved in organelle trafficking. In cell and mouse models of ARSACS, higher molecular weight species of Rab1b were identified on SDS-PAGE in addition to the normal 25kDa band and Rab1was retained in the soma along with membranous organelles (i.e., ER, Golgi and ATG9 autophagic vesicles). These changes were reversed by expression of the DNAJ domain or the Ubl domain of sacsin and occurred independent of the formation of abnormal bundles of intermediate filaments, a key feature of ARSACS. Although Rab1b was associated with both Golgi and ER in both Sacs+/+ and Sacs-/- cells, expression of the DNAJ domain or the Ubl domain of sacsin increased Rab1b association with ER and restored normal electrophoretic mobility. Finally, subcellular distribution of another membrane protein, neuroplastin, a key receptor for synapse formation and plasticity, also was impaired, pointing to a general problem in Rab-dependent membrane trafficking in the absence of sacsin.

Matching journals

The top 15 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.