Comparative analysis and application of fluorescent protein-tagged connexins
Bibliographic record
Abstract
In order to examine connexin transport, assembly, and turnover in living cells, we tagged green fluorescent protein or its color variants to several members of the connexin family of proteins. When green fluorescent protein was tagged to the carboxyl terminal end of connexin43 (Cx43-GFP), the resulting fusion protein was transported and assembled into functional gap junctions. However, when GFP was tagged to the amino terminal end of Cx43 (GFP-Cx43), this chimera was biosynthesized, transported to the plasma membrane, but failed to form gap junction channels that could transfer Lucifer yellow. Single cells that expressed Cx43-GFP were capable of transporting this fusion protein to the cell surface in the absence of cell-cell contact. Imaging of Cx43-yellow (Y)FP (Cx43-YFP) was quite efficient; however, the low quantum yield Cx43-BFP and the requirement for ultraviolet excitation made this chimera less suitable for time-lapse imaging. Cx43-cyan C(FP) (Cx43-CFP) was more suitable for imaging than Cx43-blue (B)FP and could be effectively separated from Cx43-YFP. The versatility of tagging GFP to the carboxyl terminal end of other members of the connexin family was established when Cx32-GFP and Cx26-YFP were found to assemble into gap junctions capable of transferring Lucifer yellow. Finally, we are examining the effectiveness of using a new red fluorescent protein (DsRed) fused to connexins in combination with Cx-GFP to simultaneously examine the kinetics, transport and turnover of two connexins. Together, our studies suggest that tagging fluorescent proteins to the carboxyl terminal end of connexins is an effective and valuable approach for studying the life cycle and dynamics of connexins in living cells.
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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 | 0.001 | 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".