Application of a pH-Sensitive Fluoroprobe (C-SNARF-4) for pH Microenvironment Analysis in <i>Pseudomonas aeruginosa</i> Biofilms
Bibliographic record
Abstract
An important feature of microbial biofilms is the development of four-dimensional physical and chemical gradients in space and time. There is need for novel approaches to probe these so-called microenvironments to determine their effect on biofilm-specific processes. In this study, we describe the use of seminaphthorhodafluor-4F 5-(and-6) carboxylic acid (C-SNARF-4) for pH microenvironment analysis in Pseudomonas aeruginosa biofilms. C-SNARF-4 is a fluorescent ratiometric probe that allows pH quantification independent of probe concentration and/or laser intensity. By confocal scanning laser microscopy, C-SNARF-4 revealed pH heterogeneity throughout the biofilm in both the x,y and x,z planes, with values ranging from pH 5.6 (within the biofilm) to pH 7.0 (bulk fluid). pH values were typically remarkably different than those just a few micrometers away. Although this probe has been successfully used in a number of eukaryotic systems, problems have been reported which describe spectral emission changes as a result of macromolecular interactions with the fluorophore. To assess how the biofilm environment may influence fluorescent properties of the dye, fluorescence of C-SNARF-4 was quantified via spectrofluorometry while the probe was suspended in various concentrations of representative biofilm matrix components (i.e., proteins, polysaccharides, and bacterial cells) and growth medium. Surprisingly, our data demonstrate that few changes in emission spectra occur as a result of matrix interactions below pH 7. These studies suggest that C-SNARF-4 can be used as a reliable indicator of pH microenvironments, which may help elucidate their influence on the medical and geobiological roles of natural biofilms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".