Exomer complex regulates protein traffic at the TGN through differential interactions with cargos and clathrin adaptor complexes is a research paper published in The FASEB Journal (2021). On theSindex it has a DataRank of 0.584. It has been cited 16 times, with 11 citing works in its 1-hop citation network.
Abstract Protein sorting at the trans ‐Golgi network (TGN) usually requires the assistance of cargo adaptors. However, it remains to be examined how the same complex can mediate both the export and retention of different proteins or how sorting complexes interact among themselves. In Saccharomyces cerevisiae , the exomer complex is involved in the polarized transport of some proteins from the TGN to the plasma membrane (PM). Intriguingly, exomer and its cargos also show a sort of functional relationship with TGN clathrin adaptors that is still unsolved. Here, using a wide range of techniques, including time‐lapse and BIFC microscopy, we describe new molecular implications of the exomer complex in protein sorting and address its different layers of functional interaction with clathrin adaptor complexes. Exomer mutants show impaired amino acid uptake because it facilitates not only the polarized delivery of amino acid permeases to the PM but also participates in their endosomal traffic. We propose a model for exomer where it modulates the recruitment of TGN clathrin adaptors directly or indirectly through the Arf1 function. Moreover, we describe an in vivo competitive relationship between the exomer and AP‐1 complexes for the model cargo Chs3. These results highlight a broad role for exomer in regulating protein sorting at the TGN that is complementary to its role as cargo adaptor and present a model to understand the complexity of TGN protein sorting.
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Base Score Contribution
0.425
From this paper's citation signal
Citation Network Contribution
0.159
From 9 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 73% comes from its base citations and 27% from the citation network (9 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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