Anti-Tick Microbiota Vaccine Impacts Ixodes ricinus Performance during Feeding
Bibliographic record
Abstract
The tick microbiota is a highly complex ensemble of interacting microorganisms. Keystone taxa, with a central role in the microbial networks, support the stability and fitness of the microbial communities. The keystoneness of taxa in the tick microbiota can be inferred from microbial co-occurrence networks. Microbes with high centrality indexes are highly connected with other taxa of the microbiota and are expected to provide important resources to the microbial community and/or the tick. We reasoned that disturbance of vector microbiota by removal of ubiquitous and abundant keystone bacteria may disrupt the tick-microbiota homeostasis causing harm to the tick host. These observations and reasoning prompted us to test the hypothesis that antibodies targeting keystone bacteria may harm the ticks during feeding on immunized hosts. To this aim, in silico analyses were conducted to identify keystone bacteria in the microbiota of Ixodes nymphs. The family Enterobacteriaceae was among the top keystone taxa identified in Ixodes microbiota. Immunization of α-1,3-galactosyltransferase-deficient-C57BL/6 (α1,3GT KO) mice with a live vaccine containing the Enterobacteriaceae bacterium Escherichia coli strain BL21 revealed that the production of anti-E. coli and anti-α-Gal IgM and IgG was associated with high mortality of I. ricinus nymphs during feeding. However, this effect was absent in two different strains of wild type mice, BALB/c and C57BL/6. This result concurred with a wide distribution of α-1,3-galactosyltransferase genes, and possibly α-Gal, in Enterobacteriaceae and other bacteria of tick microbiota. Interestingly, the weight of I. ricinus nymphs that fed on E. coli-immunized C57BL/6 was significantly higher than the weight of ticks that fed on C57BL/6 immunized with a mock vaccine. Our results suggest that anti-tick microbiota vaccines are a promising tool for the experimental manipulation of vector microbiota, and potentially the control of ticks and tick-borne pathogens.
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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 | 0.001 |
| 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".