A cleavable signal peptide controls the topology and Golgi targeting of the membrane protein TMEM165
Velings, M.-O.; Simar, R.; Bleret, A.; Tevel, V.; Boonen, M.; Morsomme, P.
Show abstract
TMEM165 is a Golgi-resident multi-pass membrane protein involved in divalent cation homeostasis and associated with congenital disorders of glycosylation, yet its N-terminal biogenesis has remained unresolved. Here, we demonstrate that TMEM165 contains a functional cleavable signal peptide required for correct Golgi targeting and membrane topology. Loss of this signal peptide causes protein mislocalization, and altered topology with N-terminal cytosolic exposure, whereas extended N-terminal deletion restores both Golgi localization and overall membrane topology, consistent with insertion mediated by the first transmembrane domain as commonly described for multi-pass membrane proteins. Importantly, this N-terminally truncated form remains responsive to manganese-induced degradation and partially restores glycosylation defects associated with TMEM165 deficiency, indicating that the extended N-terminal region is dispensable for core TMEM165 function. Together, these findings identify the signal peptide as a key determinant of TMEM165 biogenesis and suggest that its conservation may contribute not only to membrane targeting, but also to maintaining the proper luminal environment of the N-terminus during early biogenesis.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- The C. elegans Tubby homolog dynamically modulates olfactory cilia membrane morphogenesis and phospholipid composition 94%
- Partitioning to ordered membrane domains regulates the kinetics of secretory traffic 94%
- Interaction of NPC2 protein with Lysobisphosphatidic Acid is required for normal endolysosomal cholesterol trafficking 94%
Similar papers in this journal
Similar papers in this journal
"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.