Modernized Tools for Streamlined Genetic Manipulation of Wild and Diverse Symbiotic Bacteria
Bibliographic record
Abstract
ABSTRACT The capacity to associate symbiotic bacteria with vital aspects of plant and animal biology is outpacing our understanding of the mechanisms shaping these interactions. A major barrier to mechanistic studies is the paucity of tools for genetically manipulating wild and diverse bacterial isolates. Solving this problem is crucial to elucidating the cellular and molecular rules that govern symbiotic relationships and ultimately harnessing them for agricultural and biomedical applications. Therefore, we constructed a series of vectors that expedite genetic knock-in and knock-out procedures across a range of bacterial lineages. This was accomplished by developing strategies for domestication-free bacterial conjugation, designing plasmids with customizable features, and streamlining allelic exchange using visual markers of homologous recombination. These tools enabled a comparative study based on live imaging of diverse bacterial symbionts native to the zebrafish intestine, with which we discovered heterogeneous colonization patterns and a striking correlation between bacterial population biogeography and cellular behavior.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".