N-glycosylation is the most common protein modification in the eukaryotic secretory pathway. It involves the attachment a high mannose glycan to Asn residues in the context of Asn-X-Ser/Thr/Cys, a motif known as N-glycosylation sequon. This process is mediated by STT3A and STT3B, the catalytic subunits of the oligosaccharyltransferase complexes. STT3A forms part of complexes associated with the SEC61 translocon and functions co-translationally. Vacant sequons have another opportunity for glycosylation by complexes carrying STT3B. Local sequence information plays an important role in determining N-glycosylation efficiency, but non-local factors can also have a significant impact. For instance, certain proteins a... More
N-glycosylation is the most common protein modification in the eukaryotic secretory pathway. It involves the attachment a high mannose glycan to Asn residues in the context of Asn-X-Ser/Thr/Cys, a motif known as N-glycosylation sequon. This process is mediated by STT3A and STT3B, the catalytic subunits of the oligosaccharyltransferase complexes. STT3A forms part of complexes associated with the SEC61 translocon and functions co-translationally. Vacant sequons have another opportunity for glycosylation by complexes carrying STT3B. Local sequence information plays an important role in determining N-glycosylation efficiency, but non-local factors can also have a significant impact. For instance, certain proteins associated with human genetic diseases exhibit abnormal N-glycosylation levels despite having wild-type acceptor sites. Here, we investigated the effect of protein stability on this process. To this end, we generated a family of 40 N-glycan acceptors based on superfolder GFP, and we measured their efficiency in HEK293 cells and in two derived cell lines lacking STT3B or STT3A. Sequon occupancy was highly dependent on protein stability, improving as the thermodynamic stability of the acceptor proteins decreases. This effect is mainly due to the activity of the STT3B-based OST complex. These findings can be integrated into a simple kinetic model that distinguishes local information within sequons from global information of the acceptor proteins.