A fat body transcriptome analysis of the immune responses of Rhodnius prolixus to artificial infections with bacteria
Bibliographic record
Abstract
BACKGROUND: Rhodnius prolixus is an important vector of Trypanosoma cruzi, the causal agent of Chagas disease in humans. Despite the medical importance of this and other triatomine vectors, the study of their immune responses has been limited to a few molecular pathways and processes. Insect immunity studies were first described for holometabolous insects such as Drosophila melanogaster, and it was assumed that their immune responses were conserved in all insects. However, study of the immune responses of triatomines and other hemimetabolous insects has revealed discrepancies between these and the Drosophila model. METHODS: To expand our understanding of innate immune responses of triatomines to pathogens, we injected fifth instar nymphs of R. prolixus with the Gram-negative (Gr-) bacterium Enterobacter cloacae, the Gram-positive (Gr+) bacterium Staphylococcus aureus, or phosphate-buffered saline (PBS), and evaluated transcript expression in the fat body 8 and 24 h post-injection (hpi). We analyzed the differential expression of transcripts at each time point, and across time, for each treatment. RESULTS: At 8 hpi, the Gr- bacteria-injected group had a large number of differentially expressed (DE) transcripts, and most of the changes in transcript expression were maintained at 24 hpi. In the Gr+ bacteria treatment, few DE transcripts were detected at 8 hpi, but a large number of transcripts were DE at 24 hpi. Unexpectedly, the PBS control also had a large number of DE transcripts at 24 hpi. Very few DE transcripts were common to the different treatments and time points, indicating a high specificity of the immune responses of R. prolixus to different pathogens. Antimicrobial peptides known to be induced by the immune deficiency pathway were induced upon Gr- bacterial infection. Many transcripts of genes from the Toll pathway that are thought to participate in responses to Gr+ bacteria and fungi were induced by both bacteria and PBS treatment. Pathogen recognition receptors and serine protease cascade transcripts were also overexpressed after Gr- bacteria and PBS injections. Gr- injection also upregulated transcripts involved in the metabolism of tyrosine, a major substrate involved in the melanotic encapsulation response to pathogens. CONCLUSIONS: These results reveal time-dependent pathogen-specific regulation of immune responses in triatomines, and hint at strong interactions between the immune deficiency and Toll pathways.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.002 | 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 teacher head, 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".