Recombinant Antibodies Against Subcellular Fractions Used to Track Endogenous Golgi Protein Dynamics <i>in Vivo</i>
Bibliographic record
Abstract
Generation of specific antibodies against enriched subcellular fractions is a powerful strategy to identify and characterize cellular components. We show that recombinant antibodies can be selected in vitro by phage display against complex subcellular fractions, namely microtubule-binding proteins and Golgi stacks. This technique has allowed us to overcome many limitations of the classical animal-based approach and generate cell biology-compliant antibodies. In addition, we show that intracellular expression of GFP-tagged recombinant antibodies can reveal the dynamics of endogenous proteins in vivo. Endogenous Giantin is very static and outlines the Golgi in living cells. It accumulates neither onto Golgi-derived tubules upon Brefeldin A treatment before Golgi disappearance, nor onto de novo formed Golgi mini-stacks upon microtubule depolymerization, and remains instead on the 'old' pericentriolar Golgi. This suggests that, in contrast to other Golgi matrix proteins, endogenous Giantin is very stably associated with the Golgi and does not efficiently recycle to the ER. Altogether, we show that the antibody phage display technique represents an efficient alternative to rapidly generate versatile antibodies that represent new tools to study protein function.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".