Detailed ecological associations of triatomines revealed by metabarcoding and next-generation sequencing: implications for triatomine behavior and Trypanosoma cruzi transmission cycles
Bibliographic record
Abstract
Trypanosoma cruzi is the agent of Chagas disease, transmitted by hematophagous triatomine vectors. Establishing transmission cycles is key to understand the epidemiology of the disease, but integrative assessments of ecological interactions shaping parasite transmission are still limited. Current approaches also lack sensitivity to assess the full extent of this ecological diversity. Here we developed a metabarcoding approach based on next-generation sequencing to identify triatomine gut microbiome, vertebrate feeding hosts, and parasite diversity and their potential interactions. We detected a dynamic microbiome in Triatoma dimidiata, including 23 bacterial orders, which differed according to blood sources. Fourteen vertebrate species served as blood sources, corresponding to domestic, synantropic and sylvatic species, although four (human, dog, cow and mice) accounted for over 50% of blood sources. Importantly, bugs fed on multiple hosts, with up to 11 hosts identified per bug, indicating very frequent host-switching. A high clonal diversity of T. cruzi was detected, with up to 20 haplotypes per bug. This analysis provided much greater sensitivity to detect multiple blood meals and multiclonal infections with T. cruzi, which should be taken into account to develop transmission networks, and characterize the risk for human infection, eventually leading to a better control of disease transmission.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".