Localization of Large ADP-Ribosylation Factor-Guanine Nucleotide Exchange Factors to Different Golgi Compartments: Evidence for Distinct Functions in Protein Traffic
Bibliographic record
Abstract
Activation of several ADP-ribosylation factors (ARFs) by guanine nucleotide exchange factors (GEFs) regulates recruitment of coat proteins (COPs) on the Golgi complex and is generally assumed to be the target of brefeldin A (BFA). The large ARF-GEFs Golgi-specific BFA resistance factor 1 (GBF1) and BFA-inhibited GEFs (BIGs) localize to this organelle but catalyze exchange preferentially on class II and class I ARFs, respectively. We now demonstrate using quantitative confocal microscopy that these GEFs show a very limited overlap with each other (15 and 23%). In contrast, GBF1 colocalizes with the cis-marker p115 (86%), whereas BIGs overlap extensively with TGN38 (83%). Consistent with these distributions, GBF1, but not BIG1, partially relocalized to peripheral sites after incubation at 15 degrees C. The new GBF1 structures represent peripheral vesicular tubular clusters (VTCs) because 88% of structures analyzed stained for both GBF1 and p115. Furthermore, as expected of VTCs, they rapidly reclustered to the Golgi complex in a microtubule-dependent manner upon warm-up. These observations suggest that GBF1 and BIGs activate distinct subclasses of ARFs in specific locations to regulate different types of reactions. In agreement with this possibility, COPI overlapped to a greater extent with GBF1 (64%) than BIG1 (31%), whereas clathrin showed limited overlap with BIG1, and virtually none with GBF1.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".