Ubiquitous expression of the monomeric red fluorescent protein mcherry in transgenic mice
Bibliographic record
Abstract
The use of the green fluorescent protein (GFP) to label specific cell types and track gene expression in animal models, such as mice, has evolved to become an essential tool in biological research. Transgenic animals expressing genes of interest linked to GFP, either as a fusion protein or transcribed from an internal ribosomal entry site (IRES) are widely used. Enhanced GFP (eGFP) is the most common form of GFP used for such applications. However, a red fluorescent protein (RFP) would be highly desirable for use in dual-labeling applications with GFP derived fluorescent proteins, and for deep in vivo imaging of tissues. Recently, a new generation of monomeric (m)RFPs, such as monomeric (m)Cherry, has been developed that are potentially useful experimentally. mCherry exhibits brighter fluorescence, matures more rapidly, has a higher tolerance for N-terminal fusion proteins, and is more photostable compared with its predecessor mRFP1. mRFP1 itself was the first true monomer derived from its ancestor DsRed, an obligate tetramer in vivo. Here, we report the successful generation of a transgenic mouse line expressing mCherry as a fluorescent marker, driven by the ubiquitin-C promoter. mCherry is expressed in almost all tissues analyzed including pre- and post-implantation stage embryos, and white blood cells. No expression was detected in erythrocytes and thrombocytes. Importantly, we did not encounter any changes in normal development, general physiology, or reproduction. mCherry is spectrally and genetically distinct from eGFP and, therefore, serves as an excellent red fluorescent marker alone or in combination with eGFP for labelling transgenic animals.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".