Trypanosomes Modify the Behavior of Their Insect Hosts: Effects on Locomotion and on the Expression of a Related Gene
Bibliographic record
Abstract
BACKGROUND: As a result of evolution, the biology of triatomines must have been significantly adapted to accommodate trypanosome infection in a complex network of vector-vertebrate-parasite interactions. Arthropod-borne parasites have probably developed mechanisms, largely still unknown, to exploit the vector-vertebrate host interactions to ensure their transmission to suitable hosts. Triatomines exhibit a strong negative phototaxis and nocturnal activity, believed to be important for insect survival against its predators. METHODOLOGY/PRINCIPAL FINDINGS: In this study we quantified phototaxis and locomotion in starved fifth instar nymphs of Rhodnius prolixus infected with Trypanosoma cruzi or Trypanosoma rangeli. T. cruzi infection did not alter insect phototaxis, but induced an overall 20% decrease in the number of bug locomotory events. Furthermore, the significant differences induced by this parasite were concentrated at the beginning of the scotophase. Conversely, T. rangeli modified both behaviors, as it significantly decreased bug negative phototaxis, while it induced a 23% increase in the number of locomotory events in infected bugs. In this case, the significant effects were observed during the photophase. We also investigated the expression of Rpfor, the triatomine ortholog of the foraging gene known to modulate locomotion in other insects, and found a 4.8 fold increase for T. rangeli infected insects. CONCLUSIONS/SIGNIFICANCE: We demonstrated for the first time that trypanosome infection modulates the locomotory activity of the invertebrate host. T. rangeli infection seems to be more broadly effective, as besides affecting the intensity of locomotion this parasite also diminished negative phototaxis and the expression of a behavior-associated gene in the triatomine vector.
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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".