Metagenomic evaluation of a Utah tar sand microbiota suggests the predominant hydrocarbonoclastic role of Actinobacteria
Bibliographic record
Abstract
<ns4:p> <ns4:bold>Background:</ns4:bold> Occurrences of tar sands have been reported in 22 states in the United States; however, the largest deposit is located in southwestern Utah. It has been suggested that tar sands were created by the microbial degradation of immobile subsurface oil over several million years; however, little is known about the indigenous microbial communities in the bituminous tar sands. <ns4:bold>Methods:</ns4:bold> This study identified Utah tar sand microbiota using next-generation sequencing technology and characterized the functional diversity using community-level physiological profile (CLPP). </ns4:p> <ns4:p> <ns4:bold>Results:</ns4:bold> Microbiota identified in these tar sands are mainly affiliated with the Gram-positive Actinobacteria and representatives of genera that have also been previously shown to degrade aromatic hydrocarbons, including <ns4:italic>Arthrobacter</ns4:italic> , <ns4:italic>Dietzia</ns4:italic> , <ns4:italic>Janibacter</ns4:italic> , <ns4:italic>Nocardioides</ns4:italic> , <ns4:italic>Microbacterium</ns4:italic> , <ns4:italic>Agrococcus</ns4:italic> and <ns4:italic>Salinibacterium</ns4:italic> , suggesting that these microbes likely play roles in the biodegradation of oil-hydrocarbons. CLPP analysis revealed less than 24 h was needed for the first color development in the microplate wells containing the polymers, whereas the duration of the lag phase of the carboxylic acids was prolonged. </ns4:p> <ns4:p> <ns4:bold>Conclusions:</ns4:bold> The quick utilization of the polymers suggests that the indigenous microbial community, especially the actinomycetes in the tar sand habitat, are poised and primed to degrade these recalcitrant compounds. </ns4:p>
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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 | 0.004 | 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 | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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 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".