Tolerance to a Diet of Toxic Microcystis aeruginosa in Caenorhabditis elegans
Bibliographic record
Abstract
Reported incidences of cyanobacterial harmful algal blooms (CHABs) are increasing across the world due to climate change and nutrient loading, dominating freshwater ecosystems and producing dangerous cyanotoxins that cause ecological damage. Microcystis aeruginosa is one of the most common species of cyanobacteria; it produces hepatotoxic and neurotoxic microcystin-LR. The ecological and human impact of algal blooms is immense, and traditional CHAB remediation methods are not always adequate in eutrophic regions such as Lake Erie in North America. As a result, a proactive, targeted approach is needed to bioremediate cyanobacteria in their pre-colonial stages. Nematodes, such as the model organism Caenorhabditis elegans, are potential candidates for bioremediating cyanobacteria such as M. aeruginosa. C. elegans have metabolic pathways that could detoxify microcystin-LR and enable tolerance to cyanobacteria in nature. We analyzed C. elegans health and fat accumulation on a diet of toxic M. aeruginosa and found that C. elegans can ingest, digest, metabolize, and survive off of this diet. The mean lifespans of the worm populations were only slightly different at 20.68 ± 0.35 (mean ± S.E.M) and 17.89 ± 0.40 when fed E. coli and toxic M. aeruginosa, respectively. In addition, a diet of toxic M. aeruginosa compared to E. coli did not have any significant impact on C. elegans pharyngeal pumping (304.2 ± 9.3 versus 330.0 ± 10.4 pumps/min), dauer response (86.3 ± 1.0 versus 83.65 ± 1.0% in dauer), mobility (209.25 ± 7.0 versus 210.15 ± 4.4 thrashes/min), or SKN-1 expression based on SKN1::GFP fluorescence measurements. Overall, a diet of toxic M. aeruginosa was able to sustain C. elegans development, and C. elegans was tolerant of it. These results suggest that C. elegans and similar nematodes could be viable candidates for cyanobacterial bioremediation.
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 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".