Recombinase in Trio (RIT) Elements in Bacterial Genomes: Assessing the Distribution and Mobility of a Novel yet Widespread Set of Mobile Genes
Bibliographic record
Abstract
The research performed over the course of my doctorate training outlines the environmental distribution, mobility, expression and potential role of a newly described family of mobile elements as well as providing valuable information on the challenges and potential benefits of environmental metagenomics. Sequencing technologies have evolved considerably over the course of this work, and evaluating the limitations and opportunities provided by these evolving technologies has formed a significant portion of my thesis work. The remainder of the work has been dedicated to understanding the distribution and mechanisms of Recombinase in Trio (RIT) elements, a previously underappreciated mobile element found in a large diversity of strains, but predominantly in non-pathogenic bacteria. Recombinase in Trio (RIT) elements contain three tyrosine-based site-specific recombinases and display a characteristic gene order and repeat architecture that is conserved across 7 bacterial phyla (Van Houdt et al. 2006; Van Houdt et al. 2012; Ricker et al. 2013). RIT elements have been postulated to be mobile due to the occurrence of multiple identical copies within individual genomes, and are commonly found on plasmids and in genomic islands, including plant symbiosis and catabolic islands. The ability of RIT elements to excise and relocate themselves was tested using a variety of mating experiments. Although the determination of a potential target site sequence was initially elusive, this was overcome and RIT element mobility was observed during conjugation. The transformants analyzed subsequently provided some insight into the mechanism of recombination. Finally, environmental sampling was performed on Southern Ontario streams in order to develop a methodology for evaluating the mobilome community of bacterial communities.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".