Proteomic analysis of <i>Porphyromonas gingivalis</i> exposed to nicotine and cotinine
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Smokers are more predisposed than nonsmokers to infection with Porphyromonas gingivalis, one of the most important pathogens involved in the onset and development of periodontitis. It has also been observed that tobacco, and tobacco derivatives such as nicotine and cotinine, can induce modifications to P. gingivalis virulence. However, the effect of the major compounds derived from cigarettes on expression of protein by P. gingivalis is poorly understood. Therefore, this study aimed to evaluate and compare the effects of nicotine and cotinine on the P. gingivalis proteomic profile. MATERIAL AND METHODS: Total proteins of P. gingivalis exposed to nicotine and cotinine were extracted and separated by two-dimensional electrophoresis. Proteins differentially expressed were successfully identified through liquid chromatography-mass spectrometry and primary sequence databases using MASCOT search engine, and gene ontology was carried out using DAVID tools. RESULTS: Of the approximately 410 protein spots that were reproducibly detected on each gel, 23 were differentially expressed in at least one of the treatments. A particular increase was seen in proteins involved in metabolism, virulence and acquisition of peptides, protein synthesis and folding, transcription and oxidative stress. Few proteins showed significant decreases in expression; those that did are involved in cell envelope biosynthesis and proteolysis and also in metabolism. CONCLUSION: Our results characterized the changes in the proteome of P. gingivalis following exposure to nicotine and cotinine, suggesting that these substances may modulate, with minor changes, protein expression. The present study is, in part, a step toward understanding the potential smoke-pathogen interaction that may occur in smokers with periodontitis.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".