Molecular Regulation of Trypanosoma congolense-Induced Nitric Oxide Production in Macrophages
Bibliographic record
Abstract
BALB/c mice are highly susceptible while C57BL/6 mice are relatively resistant to experimental Trypanosoma congolense infection. Several reports show that an early interferon-gamma (IFN-γ) response in infected mice is critically important for resistance via the activation of macrophages and production of nitric oxide (NO). NO is a pivotal effector molecule and possesses both cytostatic and cytolytic properties for the parasite. However, the molecular mechanisms leading to T. congolense (TC)-induced NO release from macrophages are not known. In this study, we investigated the signaling pathways induced by trypanosomes in immortalized macrophage cell lines from the highly susceptible BALB/c (BALB.BM) and relatively resistant C57Bl/6 (ANA-1) mice. We found that T. congolense whole cell extract (TC-WCE) induces significantly higher levels of NO production in IFN-γ-primed ANA-1 than BALB.BM cells, which was further confirmed in primary bone marrow-derived macrophage (BMDM) cultures. NO production was dependent on mitogen-activated protein kinase (MAPK, including p38, Erk1/2, and JNK) phosphorylation and was significantly inhibited by specific MAPK inhibitors in BALB.BM, but not in ANA-1 cells. In addition, T. congolense- and IFN-γ-induced NO production in ANA-1 and BALB.BM cells was dependent on STAT1 phosphorylation and was totally suppressed by the use of fludarabine (a specific STAT1 inhibitor). We further show that T. congolense induces differential iNOS transcriptional promoter activation in IFN-γ-primed cells, which is dependent on the activation of both GAS1 and GAS2 transcription factors in BALB.BM but only on GAS1 in ANA-1 cells. Taken together, our findings show the existence of differential signalling events that lead to NO production in macrophages from the highly susceptible and relatively resistant mice following treatment with IFN-γ and T. congolense. Understanding these pathways may help identify immunomodulatory mechanisms that regulate the outcome of infection during Trypanosome infections.
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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".