Dye Lipophilicity and Retention in Lipid Membranes: Implications for Single-Molecule Spectroscopy
Bibliographic record
Abstract
Fluorescence studies of individual lipid vesicles rely on the proper positioning of probes in the lipid milieu. This is true for both positional tags and chemoselective fluorogenic probes that undergo chemical modification following reaction with an analyte of interest within the lipid environment. The present report describes lipophilicity and localization estimations for a series of BODIPY dyes bearing substituents of varying hydrophobicity. We also studied fluorogenic trap-reporter probes that undergo fluorescence emission enhancement upon trapping of reactive oxygen species (ROS), including lipid peroxyl radicals. We show that caution has to be taken to extrapolate ensemble partition measurements of dyes to the single-molecule regime as a result of the dramatically different lipid concentration prevailing in ensemble versus single-molecule experiments. We show that the mole fraction of dyes that remains embedded in liposomes during a typical single-molecule experiment may be accurately determined from a ratiometric single-particle imaging analysis. We further demonstrate that fluorescence correlation spectroscopy (FCS) provides a very rapid and reliable estimate of the lipophilic nature of a given dye under highly dilute single-molecule-like conditions. Our combined single-particle spectroscopy and FCS experiments suggest that the minimal mole fraction of membrane-associated dyes (x(m)) as determined from FCS experiments is about 0.5 for adequate dye retention during single-molecule imaging in lipid membranes. Our work further highlights the dramatic effect that chemical modifications can have on chemoselective fluorogenic probe localization.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".