Rapid and Convenient Oxidative Release of Thiol-Conjugated Forms of Microcystins for Chemical Analysis
Bibliographic record
Abstract
Microcystins are potent cyclic heptapeptide toxins found in some cyanobacteria, and usually contain an α,β-unsaturated carbonyl group that is readily conjugated to thiol-containing amino acids, peptides, and proteins in vivo and in vitro. Methods for deconjugating these types of adducts have recently been reported, but the reactions are slow or result in derivatized microcystins. Mercaptoethanol derivatives of a range of microcystins were therefore used as model compounds to develop deconjugation procedures in which the dialkyl sulfide linkage was oxidized to a sulfoxide or sulfone that, when treated with base, rapidly eliminated the adducted thiol as its sulfenate or sulfinate via β-elimination to afford free microcystins with the α,β-unsaturated carbonyl group intact. These free microcystins can be analyzed by LC/MS to determine the toxin profile of bound microcystins. The method was tested on Cys- and GSH-derivatives of [Dha 7 ]MC-LR. In solution, the deconjugation reactions were complete within minutes at pH 10.7 and within a few hours at pH 9.2. Oxidation of sulfides to sulfoxides is easier and more rapid than oxidation to sulfones, allowing the use of milder oxidants and shorter reaction times. Oxidation of any methionine residues present in the microcystins occurs inevitably during these procedures, and interpretation of the microcystin profile obtained by LC/MS analysis needs to take this into account. Oxidation of tryptophan residues and degradation of microcystins by excess oxidant were circumvented by the addition of Me 2 SO as a sacrificial reducing agent. These methods may be useful for other compounds that undergo conjugation via thia-Michael addition, such as acrylamide and deoxynivalenol. Oxidation of sulfides to sulfoxides can occur in vivo and could affect the bioavailability of toxins and drugs conjugated via thia-Michael addition, potentially exacerbating oxidative stress by catalytically converting GSH to its sulfenate via conjugation, oxidation, and elimination to regenerate the free toxin.
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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 | 0.001 |
| 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".