Fluorescent dyes alter intracellular targeting and function of cell‐penetrating tetrapeptides
Bibliographic record
Abstract
Fluorescent labels are commonly used to investigate the mechanisms of cellular uptake and intracellular distribution of cell-penetrating peptides. However, labels such as fluorescein and rhodamine are relatively large and very lipophilic and may significantly alter physicochemical properties of small peptides. To minimize the impact of the fluorescent probe on a tetrapeptide, we substituted one of the amino acids (Lys4) in a tetrapeptide ([Dmt1]DALDA, Dmt-D-Arg-Phe-Lys-NH2 where Dmt = 2',6'-dimethyltyrosine) with two different fluorescent amino acids (beta-dansyl-L-alpha,beta-diaminopropionic acid (dnsDap4) or beta-anthraniloyl-L-alpha,beta-diaminopropionic acid (atnDap4)). Initial studies with confocal laser scanning microscopy (CLSM) showed very different localization patterns for the two fluorescent analogs, with [Dmt1,atnDap4]DALDA showing mitochondrial localization and [Dmt1,dnsDap4]DALDA showing diffuse cytoplasmic localization. Studies with isolated mouse liver mitochondria suggested that [Dmt1,dnsDap4]DALDA targeted the mitochondrial matrix resulting in mitochondrial depolarization, opening of the permeability transition pore, mitochondrial swelling, and rapid release of the peptide into the cytoplasm. In contrast, [Dmt1,atnDap4]DALDA was retained in the inner mitochondrial membrane and did not induce mitochondrial swelling. Furthermore, [Dmt1,atnDap4]DALDA protected mitochondria against Ca2+-induced swelling. Importantly, the unlabeled parent peptide [Dmt1]DALDA behaved like [Dmt1,atnDap4]DALDA and was mitoprotective. These findings suggest that experimental results obtained with fluorescent labels must be interpreted with caution, and the use of multiple fluorophores, together with confirmation using the original or radiolabeled molecule, is recommended.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".