Harnessing the Potential of Native Microbial Communities for Bioremediation of Oil Spills in the Iberian Peninsula NW Coast
Bibliographic record
Abstract
Oil spills are among the most catastrophic events to marine ecosystems and current remediation techniques are not suitable for ecological restoration. Bioremediation approaches can take advantage of the activity of microorganisms with biodegradation capacity thus helping to accelerate the recovery of contaminated environments. The use of native microorganisms can increase the bioremediation efficiency since they have higher potential to survive in the natural environment while preventing unpredictable ecological impacts associated with the introduction of non-native organisms. In order to know the geographical scale to which a native bioremediation consortium can be applied, we need to understand the spatial heterogeneity of the natural microbial communities with potential for hydrocarbon degradation. In the present study, we aim to describe the genetic diversity and the potential of native microbial communities to degrade petroleum hydrocarbons, at an early stage of bioremediation, along the NW Iberian Peninsula coast, an area particularly susceptible to oil spills. Seawater samples collected in 47 sites were exposed to crude oil for 2 weeks, in enrichment experiments. Seawater samples collected in situ , and samples collected after the enrichment with crude oil, were characterized for prokaryotic communities by using 16S rRNA gene amplicon sequencing and predictive functional profiling. Results showed a drastic decrease in richness and diversity of microbial communities after the enrichment with crude oil. Enriched microbial communities were mainly dominated by genera known to degrade hydrocarbons, namely Alcanivorax , Pseudomonas , Acinetobacter , Rhodococcus , Flavobacterium , Oleibacter , Marinobacter , and Thalassospira , without significant differences between geographic areas and locations. Predictive functional profiling of the enriched microbial consortia showed a high potential to degrade the aromatic compounds aminobenzoate, benzoate, chlorocyclohexane, chlorobenzene, ethylbenzene, naphthalene, polycyclic aromatic compounds, styrene, toluene, and xylene. Only a few genera contributed for more than 50% of this genetic potential for aromatic compounds degradation in the enriched communities, namely Alcanivorax , Thalassospira , and Pseudomonas spp. This work is a starting point for the future development of prototype consortia of hydrocarbon-degrading bacteria to mitigate oil spills in the Iberian NW coast.
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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 | 0.001 | 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".