Increasing the brightness of red fluorescent proteins by saturation mutagenesis
Bibliographic record
Abstract
Red fluorescent proteins (RFPs) are genetically-encoded fluorophores that are widely used for in vivo imaging. For all applications of RFPs, brighter variants are desired. Previously, we improved the brightness of mRojoA, a red-shifted mutant of the widely-used RFP mCherry, by designing a triple-decker motif of aromatic rings around its chromophore. This yielded the brighter variant mRojo-VHSV, which contains a triple-decker motif consisting of His and Tyr side chains that pack against the chromophore. This improved chromophore packing resulted in an approximately 3-fold brightness increase at physiological pH. However, the His side chain in the triple-decker motif of mRojo-VHSV adopted a perpendicular arrangement to the other two, which may result in a suboptimal packing arrangement. To further improve chromophore packing in mRojo-VHSV, we performed saturation mutagenesis of residues surrounding its triple-decker motif (positions 62, 97, 165, and 199). Using a microplate fluorescence screening assay, a total of 376 colonies were screened for improved brightness. The brightest mutant found, L199M, was expressed and purified, and its spectral properties were characterized in detail. We found that the quantum yield of this variant was improved by two-fold, resulting in a two-fold brightness increase compared to mRojo-VHSV as well as a 5.3-fold increase in brightness compared to mRojoA. The L199M improved variant is the basis for continued engineering with the goal of further improving the spectral properties of this family of RFPs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".