Analysis of Schistosoma mansoni Extracellular Vesicles Surface Glycans Reveals Potential Immune Evasion Mechanism and New Insights on Their Origins of Biogenesis
Bibliographic record
Abstract
Parasitic helminths are master manipulators of host immunity. Their strategy is complex and involves the release of excreted/secreted products, including extracellular vesicles (EVs). The protein and miRNA contents of EVs have been characterised for many parasitic helminths but, despite reports suggesting the importance of EV surface carbohydrate structures (glycans) in the interactions with target cells and thus subsequent effector functions, little is known about parasite EV glycomics. Using lectin microarrays, we identified several lectins that exhibit strong adhesion to Schistosoma mansoni EVs, suggesting the presence of multiple glycan structures on these vesicles. Interestingly, SNA-I, a lectin that recognises structures with terminal sialic acid, displayed strong affinity for S. mansoni EVs, which was completely abolished by neuraminidase treatment, suggesting sialylation in the EV sample. This finding is of interest, as sialic acids play important roles in the context of infection by aiding immune evasion, affecting target recognition, cell entry, etc., but are not thought to be synthesised by helminths. These data were validated by quantitative analysis of free sialic acid released from EVs following treatment with neuraminidase. Lectin histochemistry and fluorescence in situ hybridisation analyses on whole adult worms suggest the involvement of sub-tegumental cell bodies, as well as the digestive and excretory systems, in the release of EVs. These results support previous reports of EV biogenesis diversity in trematodes and potentially highlight new means of immune modulation and evasion employed by schistosomes.
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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".