Second-generation transfer mediates efficient propagation of ICE <i>Bs1</i> in biofilms
Bibliographic record
Abstract
Abstract Horizontal gene transfer (HGT) by integrative and conjugative elements (ICEs) is an important mechanism in the spread of antibiotic resistance genes. However, little is known about the spatiotemporal dynamic of ICEs propagation in bacterial biofilms, which are multicellular structures ubiquitous in the natural and clinical environment. Using a fluorescently marked ICE Bs1 , we report here that its propagation in biofilms is favored in recipient cells expressing the biofilm matrix. Also, conjugation appears restricted to clusters of bacteria in a close neighborhood in which a high level of ICE Bs1 transfer occurs. These conjugative clusters are heterogenously distributed in the biofilm, forming close to the air-biofilm interface. Importantly, we established that transconjugant cells are the main contributors to ICE Bs1 propagation in biofilms. Our findings provide a novel spatiotemporal understanding of ICEs propagation in biofilms, which should have an important role in our understanding of horizontal gene transfer in relevant settings. Importance The transfer of mobile genetic elements between bacteria is the main cause of the spread of antibiotic resistance genes. While biofilms are the predominant bacterial lifestyle both in the environment and in clinical settings, their impact on the propagation of mobile genetic elements is still poorly understood. In this study, we examined the spatiotemporal propagation of the well-characterized integrative and conjugative element (ICE) ICE Bs1 . Using the Gram-positive B. subtilis , we observed that the main actors of ICE Bs1 propagation in biofilms are the newly formed transconjugants that allow rapid transfer of ICE Bs1 to new recipients. Our study provides a better understanding of the spatiotemporal dynamic of conjugative transfer in biofilms.
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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 | 0.000 |
| 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".