Recognition of human milk oligosaccharides by bacterial exotoxins
Bibliographic record
Abstract
The affinities of the most abundant oligosaccharides found in human milk for four bacterial exotoxins (from Vibrio cholerae and pathogenic Escherichia coli) were quantified for the first time. Association constants (Ka) for a library of 20 human milk oligosaccharides (HMOs) binding to Shiga toxin type 2 holotoxin (Stx2) and the B subunit homopentamers of cholera toxin, heat-labile toxin and Shiga toxin type 1 (CTB5, HLTB5 and Stx1B5) were measured at 25°C and pH 7 using the direct electrospray ionization mass spectrometry assay. Notably, all four bacterial toxins bind to a majority of the HMOs tested and five of the HMOs (2'-fucosyllactose, lacto-N-tetraose, lacto-N-fucopentaose I, lacto-N-fucopentaose II and lacto-N-fucopentaose III) are ligands for all four toxins. These five HMOs are also reported to bind to other bacterial toxins (e.g. toxin A and toxin B of Clostridium difficile). In all cases, the HMO affinities (apparent Ka) are relatively modest (≤15,000 M(-1)). However, at the high concentrations of HMOs typically ingested by infants, a significant fraction of these toxins, if present, is expected to be bound to HMOs. Binding measurements carried out with 2'-fucosyllactose or lacto-N-fucopentaose I, together with a high-affinity ligand based on the native carbohydrate receptor, revealed that all four toxins possess HMO-binding sites that are distinct from those of the native receptors, although evidence of competitive binding was found for lacto-N-fucopentaose I with Stx2 and 2'-fucosyllactose and lacto-N-fucopentaose I with HLTB5. Taken together, the results of this study suggest that, while HMOs are expected to bind extensively to these bacterial toxins, it is unlikely that HMO binding will effectively inhibit their interactions with their cellular receptors.
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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) | 0.000 | 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 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".