A comparison of the response of two <i>Burkholderia fungorum</i> strains grown as planktonic cells versus biofilm to dibenzothiophene and select polycyclic aromatic hydrocarbons
Bibliographic record
Abstract
In natural environments, bacteria often exist in close association with surfaces and interfaces by establishing biofilms. Here, we report on the ability of Burkholderia fungorum strains DBT1 and 95 to survive in high concentrations of hydrocarbons, and we compare their growth as a biofilm vs. planktonic cells. The 2 compounds tested were dibenzothiophene (DBT) and a mixture of naphthalene, phenanthrene, and pyrene (5:2:1) as representative compounds of thiophenes and polycyclic aromatic hydrocarbons (PAHs), respectively. The results showed that both strains were able to degrade DBT and to survive in the presence of up to a 2000 mg·L−1 concentration of this compound both as a biofilm and as free-living cells. Moreover, B. fungorum DBT1 showed reduced tolerance towards the mixed PAHs (2000 mg·L−1 naphthalene, 800 mg·L−1 phenanthrene, and 400 mg·L−1 pyrene) both as a biofilm and as free-living cells. Conversely, biofilms of B. fungorum 95 enhanced resistance against these toxic compounds compared with planktonic cells (P < 0.05). Visual observation through confocal laser scanning microscopy showed that exposure of biofilms to DBT and PAHs altered their structure: high concentrations of DBT triggered an aggregation of biofilm cells. These findings provide new perspectives on the effectiveness of using DBT-degrading bacterial strains in bioremediation of hydrocarbon-contaminated sites.
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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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".