Mutually beneficial FAB consortia fortify stress resistance of Euglena mutabilis: evidence from sequencing, antibiotics, and Cd challenges
Bibliographic record
Abstract
Abstract Background Synthetic algal-fungal and algal-bacterial cultures have been investigated for technological applications because the microbe interactions enhance growth and improve stress tolerance of the co-cultures. Yet these studies often disregarded natural consortia due to the complexity of environmental samples. The protist Euglena mutabilis is found in association with other microbes in acidic environments with high heavy metal (HM) concentrations. This may suggest that microbial interactions are essential for the alga’s ability to tolerate these extreme environments. Our study assessed the Cd tolerance of a natural fungal-algal-bacterial (FAB) association where the algae is replaced by the photosynthetic protist E. mutabilis. Results This study provides the first assessment of antimycotic and antibiotic agents on E. mutabilis. Our results indicate that suppression of associated fungal and bacterial partners significantly decreases the number of viable E. mutabilis cells upon Cd exposure. However, axenic Euglena gracilis recovered and grew well following antibiotic treatments. Interestingly, both Euglena species displayed increased chlorophyll production upon Cd exposure. Finally, the constituent organisms in the E. mutabilis FAB consortia were identified using PacBio sequencing to be a Talaromyces sp and Acidiphilium acidophilum. Conclusion This study uncovers a possible tripartite symbiotic relationship, a FAB consortia, that withstands exposure to high concentrations of HM. This unique fungus, bacterium, and E. mutabilis interaction strengthens the photobiont’s resistance to Cd and provides a model for the types of FAB interactions that could be used to create a self-sustaining bioremediation technology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".