Characterization of the Specific Interaction between Sialoadhesin and Sialylated <i>Campylobacter jejuni</i> Lipooligosaccharides
Bibliographic record
Abstract
In Campylobacter jejuni-induced Guillain-Barré syndrome (GBS), molecular mimicry between C. jejuni lipooligosaccharide (LOS) and host gangliosides leads to the production of cross-reactive antibodies directed against the peripheral nerves of the host. Currently, the presence of surface exposed sialylated LOS in C. jejuni is the single known bacterial pathogenesis factor associated with the development of GBS. Using a unique, well-characterized strain collection, we demonstrate that GBS-associated C. jejuni strains bind preferentially to sialoadhesin (Sn, Siglec-1, or CD169), a sialic acid receptor found on a subset of macrophages. In addition, using a whole-cell enzyme-linked immunosorbent assay (ELISA), C. jejuni strains with sialylated LOS bound exclusively to soluble Sn. Mass spectrometry revealed that binding was sialic acid-linkage specific with a preference for alpha(2,3)-linked sialic acid attached to the terminal galactose of the LOS chain as seen in the gangliosides GD1a, GM1b, and GM3. This molecular interaction was also related to functional consequences as a GBS-associated C. jejuni strain that bound Sn in a whole-cell ELISA adhered to surface-expressed Sn of Sn-transfected CHO cells but was unable to adhere to wild-type CHO cells. Moreover, a sialic acid-negative mutant of the same C. jejuni strain was unable to bind Sn-transfected CHO cells. This is the first report of the preferential binding of GBS-associated C. jejuni strains to the Sn immune receptor (P = 0.014). Moreover, because this binding is dependent on sialylated LOS, the main pathogenic factor in GBS progression, the present findings bring us closer to unraveling the mechanisms that lead to formation of cross-reactive antibodies in GBS disease.
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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".