Coupling azo dye degradation and biodiesel production by manganese-dependent peroxidase producing oleaginous yeasts isolated from wood-feeding termite gut symbionts
Bibliographic record
Abstract
BACKGROUND: Textile industry represents one prevalent activity worldwide, generating large amounts of highly contaminated and rich in azo dyes wastewater, with severe effects on natural ecosystems and public health. However, an effective and environmentally friendly treatment method has not yet been implemented, while concurrently, the increasing demand of modern societies for adequate and sustainable energy supply still remains a global challenge. Under this scope, the purpose of the present study was to isolate promising species of yeasts inhabiting wood-feeding termite guts, for combined azo dyes and textile wastewater bioremediation, along with biodiesel production. RESULTS: Thirty-eight yeast strains were isolated, molecularly identified and subsequently tested for desired enzymatic activity, lipid accumulation, and tolerance to lignin-derived metabolites. The most promising species were then used for construction of a novel yeast consortium, which was further evaluated for azo dyes degradation, under various culture conditions, dye levels, as well as upon the addition of heavy metals, different carbon and nitrogen sources, and lastly agro-waste as an inexpensive and environmentally friendly substrate alternative. The novel yeast consortium, NYC-1, which was constructed included the manganese-dependent peroxidase producing oleaginous strains Meyerozyma caribbica, Meyerozyma guilliermondii, Debaryomyces hansenii, and Vanrija humicola, and showed efficient azo dyes decolorization, which was further enhanced depending on the incubation conditions. Furthermore, enzymatic activity, fatty acid profile and biodiesel properties were thoroughly investigated. Lastly, a dye degradation pathway coupled to biodiesel production was proposed, including the formation of phenol-based products, instead of toxic aromatic amines. CONCLUSION: In total, this study might be the first to explore the application of MnP and lipid-accumulating yeasts for coupling dye degradation and biodiesel production.
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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 | 0.000 | 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 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".