Analysis of the Trichuris suis excretory/secretory proteins as a function of life cycle stage and their immunomodulatory properties
Bibliographic record
Abstract
Abstract Parasitic worms have a remarkable ability to modulate host immune responses through several mechanisms including excreted/secreted proteins (ESP), yet the exact nature of these proteins and their targets often remains elusive. Here, we performed mass spectrometry analyses of ESP (TsESP) from larval and adult stages of the pig whipworm Trichuris suis (Ts) and identified ~350 proteins. Transcriptomic analyses revealed large subsets of differentially expressed genes in the various life cycle stages of the parasite. Exposure of bone marrow-derived macrophages and dendritic cells to TsESP markedly diminished secretion of the pro-inflammatory cytokines TNFα and IL-12p70. Conversely, TsESP exposure strongly induced release of the anti-inflammatory cytokine IL-10, and also induced high levels of nitric oxide (NO) and upregulated arginase activity in macrophages. Interestingly, TsESP failed to directly induce CD4 + CD25 + FoxP3 + regulatory T cells (T reg cells), while OVA-pulsed TsESP-treated dendritic cells suppressed antigen-specific OT-II CD4 + T cell proliferation. Fractionation of TsESP identified a subset of proteins that promoted anti-inflammatory functions, an activity that was recapitulated using recombinant T. suis triosephosphate isomerase (TPI) and nucleoside diphosphate kinase (NDK). Our study helps illuminate the intricate balance that is characteristic of parasite-host interactions at the immunological interface, and further establishes the principle that specific parasite-derived proteins can modulate immune cell functions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".