Scalable purification of marennine and other exopolymers from diatom Haslea ostrearia's “blue water”
Bibliographic record
Abstract
Marennine is a bioactive, polydisperse and polyanionic compound produced by certain benthic diatoms of the Haslea genus. Notably, Haslea ostrearia are cultivated in photobioreactors, and their supernatant is collected to extract extracellular marennine (EMn). EMn, a promising blue pigment, has several potential applications, including serving as a pathogenicity-reducing agent in the seafood industry. Nonetheless, its extraction and characterization remain challenging. To meet the need for an efficient, standardized and scalable preparative method, we introduce an improved route to concentrate and purify marennine, prioritizing cost-efficiency and process innocuity. As an exhaustive overhaul of our preliminary study for solid-phase extraction of EMn on synthetic graphitized carbon black, we revised every step to minimize solvent and reagents inputs, while enhancing the purity of the final products. Our improved solid-phase extraction (SPE) method employs natural graphite flakes as the stationary phase, from which the crude hydroorganic extract undergoes purification through ionotropic gelation, followed by chelator-assisted dissolution and cascade diafiltration. Extraction conditions are mild and maintain the ionization state of marennine throughout the process, also allowing for the reuse of both the stationary and the mobile phases. Upon optimization, the yield of the crude extract has been shown to reach up to 87 (6) %. The versatility of the novel process is further evidenced by the isolation of four distinct marennine groups, each with a different molecular weight, as well as four additional extracellular polymeric substances from the culture supernatant. Among these, the EMn fraction with a molecular weight range of 3–1 kDa achieved a mass absorptivity of 13.4 (0.6) L·cm −1 ·g −1 , marking the highest level of purity reported thus far. • Diatom Haslea ostrearia is cultivated in photobioreactors for marennine production • Marennine and other exopolymers are harvested from culture supernatant • Solid-phase extraction uses natural graphite flakes and aqueous butanone • Purification involves ionotropic gelation, EDTA-assisted dissolution, diafiltration • Optimizations led to high crude extract yield and the highest chromophore purity
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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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".