Physical and Metabolic Interactions of <i>Pseudomonas</i> sp. Strain JA5-B45 and <i>Rhodococcus</i> sp. Strain F9-D79 during Growth on Crude Oil and Effect of a Chemical Surfactant on Them
Bibliographic record
Abstract
Methods to enhance crude oil biodegradation by mixed bacterial cultures, for example, (bio)surfactant addition, are complicated by the diversity of microbial populations within a given culture. The physical and metabolic interactions between Rhodococcus sp. strain F9-D79 and Pseudomonas sp. strain JA5-B45 were examined during growth on Bow River crude oil. The effects of a nonionic chemical surfactant, Igepal CO-630 (nonylphenol ethoxylate), also were evaluated. Strain F9-D79 grew attached to the oil-water interface and produced a mycolic acid-containing capsule. Crude oil emulsification and surface activity were associated with the cellular fraction. Strain JA5-B45 grew in the aqueous phase and was unable to emulsify oil, but cell-free supernatants mediated kerosene-water emulsion formation. In coculture, stable emulsions were formed and strain JA5-B45 had an affinity for the capsule produced by strain F9-D79. Igepal CO-630 inhibited F9-D79 cells from adhering to the interface, and cells grew dispersed in the aqueous phase as 0.5-microm cocci rather than 2.5-microm rods. The surfactant increased total petroleum hydrocarbon removal by strain JA5-B45 from 4 to 22% and included both saturated compounds and aromatics. In coculture, TPH removal increased from 13 to 40% following surfactant addition. The culture pH normally increased from 7.0 to between 7.5 and 8.5, although addition of Igepal CO-630 to F9-D79 cultures resulted in a drop to pH 5.5. We suggest a dual role for the nonylphenol ethoxylate surfactant in the coculture: (i) to improve hydrocarbon uptake by strain JA5-B45 through emulsification and (ii) to prevent strain F9-D79 from adhering to the oil-water interface, indirectly increasing hydrocarbon availability. These varied effects on hydrocarbon biodegradation could explain some of the known diversity of surfactant effects.
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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 | 0.001 |
| 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".