Genome-wide detection of conservative site-specific recombination in bacteria
Bibliographic record
Abstract
The ability of clonal bacterial populations to generate genomic and phenotypic heterogeneity is thought to be of great importance for many commensal and pathogenic bacteria. One common mechanism contributing to diversity formation relies on the inversion of small genomic DNA segments in a process commonly referred to as conservative site-specific recombination. This phenomenon is known to occur in several bacterial lineages, however it remains notoriously difficult to identify due to the lack of conserved features. Here, we report an easy-to-implement method based on high-throughput paired-end sequencing for genome-wide detection of conservative site-specific recombination on a single-nucleotide level. We demonstrate the effectiveness of the method by successfully detecting several novel inversion sites in an epidemic isolate of the enteric pathogen Clostridium difficile. Using an experimental approach, we validate the inversion potential of all detected sites in C. difficile and quantify their prevalence during exponential and stationary growth in vitro. In addition, we demonstrate that the master recombinase RecV is responsible for the inversion of some but not all invertible sites. Using a fluorescent gene-reporter system, we show that at least one gene from a two-component system located next to an invertible site is expressed in an on-off mode reminiscent of phase variation. We further demonstrate the applicability of our method by mining 209 publicly available sequencing datasets and show that conservative site-specific recombination is common in the bacterial realm but appears to be absent in some lineages. Finally, we show that the gene content associated with the inversion sites is diverse and goes beyond traditionally described surface components. Overall, our method provides a robust platform for detection of conservative site-specific recombination in bacteria and opens a new avenue for global exploration of this important phenomenon.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".