Polysorbate 80 Differentially Impacts Erinacine Production Profiles in Submerged Cultures of Hericium
Bibliographic record
Abstract
The mycelia of Hericium erinaceus contain neuroprotective cyathane diterpenoids (e.g., erinacine A). There is evidence that cultivation of submerged mycelia with surfactants increases glucose uptake and biomass, but the impact on erinacine production is unknown. Here, we tested the impact of glucose and polysorbate 80 on the mycelial erinacine profiles of five Hericium strains cultivated under submergence, including those of Hericium erinaceus, Hericium americanum, and Hericium coralloides. Metabolite profiling confirmed that mycelial extracts contained 13% to 91% of the erinacines A, C and P in additive-free cultures of all strains, with the remainder secreted to the culture medium. Overall, erinacine P production was several orders of magnitude greater than that of the other erinacines, except for H. erinaceus (DAOMC 251029), where erinacine C was most evident. H. coralloides (DAOMC 251017) produced the greatest concentrations of erinacines A and P. For the most part mycelial erinacine concentrations were reduced in cultures co-supplemented with glucose and polysorbate 80. This treatment caused an 83–100% reduction in the concentrations of erinacines A, C, and P in the mycelial extracts of most strains. By contrast, there was evidence that glucose and polysorbate 80 had no effect on erinacine A production within mycelia of H. americanum, and erinacine P concentrations in H. erinaceus (DAOMC 251029) and H. americanum (DAOMC 251011). In most strains, the secretion of erinacines to the culture medium declined with glucose and polysorbate 80. Conversely, these additives increased the concentrations of erinacines C and P in the culture medium filtrate of H. americanum (DAOMC 21467) and yielded more secreted erinacine P in H. erinaceus (DAOMC 251029). The information provides feasible strategies to produce mycelia with unique erinacine profiles including those rich in erinacine P.
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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) | 0.001 | 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".