Dynamic nesting of <i>Anaplasma marginale</i> in the microbial communities of <i>Rhipicephalus microplus</i>
Bibliographic record
Abstract
Abstract Interactions within the tick microbiome involving symbionts, commensals, and tick‐borne pathogens (TBPs) play a pivotal role in disease ecology. This study explored temporal changes in the microbiome of Rhipicephalus microplus , an important cattle tick vector, focusing on its interaction with Anaplasma marginale . To overcome limitations inherent in sampling methods relying on questing ticks, which may not consistently reflect pathogen presence due to variations in exposure to infected hosts in nature, our study focused on ticks fed on chronically infected cattle. This approach ensures continuous pathogen exposure, providing a more comprehensive understanding of the nesting patterns of A. marginale in the R. microplus microbiome. Using next‐generation sequencing, microbiome dynamics were characterized over 2 years, revealing significant shifts in diversity, composition, and abundance. Anaplasma marginale exhibited varying associations, with its increased abundance correlating with reduced microbial diversity. Co‐occurrence networks demonstrated Anaplasma 's evolving role, transitioning from diverse connections to keystone taxa status. An integrative approach involving in silico node removal unveils the impact of Anaplasma on network stability, highlighting its role in conferring robustness to the microbial community. This study provides insights into the intricate interplay between the tick microbiome and A. marginale , shedding light on potential avenues for controlling bovine anaplasmosis through microbiome manipulation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".