Development of SNAP-tag-mediated live cell labeling as an alternative to GFP in<i>Porphyromonas gingivalis</i>
Bibliographic record
Abstract
Porphyromonas gingivalis is an anaerobic periodontal pathogen that resides in the complex multispecies microbial biofilm known as dental plaque. Effective reporter tools are increasingly needed to facilitate physiological and pathogenetic studies of dental biofilm. Fluorescent proteins are ideal reporters for conveniently monitoring biofilm growth, but are restricted by several environmental factors, such as a requirement of oxygen to emit fluorescence. We developed a fluorescent reporter plasmid, known as the SNAP-tag, for labeling P. gingivalis cells, which encode an engineered version of the human DNA repair enzyme O(6)-alkylguanine-DNA alkyltransferase. Fluorescent substrates containing O(6)-benzylguanine covalently and specifically bind to the enzyme via stable thioether bonds. For the present study, we constructed a replicative plasmid carrying SNAP26b under the control of the P. gingivalis endogenous trxB promoter. The P. gingivalis-expressing SNAP26 protein was successfully labeled with specific fluorophores under anaerobic conditions. Porphyromonas gingivalis biofilm formation was investigated using flow cells and confocal laser scanning microscopy. A specific distribution of a strong fluorescence signal was demonstrated in P. gingivalis-SNAP26 monospecies and bispecies biofilms with Streptococcus gordonii-GFPmut3(*). These findings show that the SNAP-tag can be applied to studies of anaerobic bacteria in biofilm models and is a useful and advantageous alternative to existing labeling strategies.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".