Integrase-directed recovery of functional genes from genomic libraries
Bibliographic record
Abstract
Large population sizes, rapid growth and 3.8 billion years of evolution firmly establish microorganisms as a major source of the planet's biological and genetic diversity. However, up to 99% of the microorganisms in a given environment cannot be cultured. Culture-independent methods that directly access the genetic potential of an environmental sample can unveil new proteins with diverse functions, but the sequencing of random DNA can generate enormous amounts of extraneous data. Integrons are recombination systems that accumulate open reading frames (gene cassettes), many of which code for functional proteins with enormous adaptive potential. Some integrons harbor hundreds of gene cassettes and evidence suggests that the gene cassette pool may be limitless in size. Accessing this genetic pool has been hampered since sequence-based techniques, such as hybridization or PCR, often recover only partial genes or a small subset of those present in the sample. Here, a three-plasmid genetic strategy for the sequence-independent recovery of gene cassettes from genomic libraries is described and its use by retrieving functional gene cassettes from the chromosomal integron of Vibrio vulnificus ATCC 27562 is demonstrated. By manipulating the natural activity of integrons, we can gain access to the caches of functional genes amassed by these structures.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".