A cell-free transcription-translation pipeline for recreating methylation patterns boosts DNA transformation in bacteria
Bibliographic record
Abstract
The bacterial world offers diverse strains for understanding medical and environmental processes and for engineering synthetic biological chassis. However, genetically manipulating these strains has faced a long-standing bottleneck: how to efficiently transform DNA. Here, we report imitating methylation patterns rapidly in TXTL (IMPRINT), a generalized, rapid, and scalable approach based on cell-free transcription-translation (TXTL) to overcome DNA restriction, a prominent barrier to transformation. IMPRINT utilizes TXTL to express DNA methyltransferases from a bacterium's restriction-modification systems. The expressed methyltransferases then methylate DNA in vitro to match the bacterium's DNA methylation pattern, circumventing restriction and enhancing transformation. With IMPRINT, we efficiently multiplex methylation by diverse DNA methyltransferases and enhance plasmid transformation in gram-negative and gram-positive bacteria. We also develop a high-throughput pipeline that identifies the most consequential methyltransferases, and we apply IMPRINT to screen a ribosome-binding site library in a hard-to-transform Bifidobacterium. Overall, IMPRINT can enhance DNA transformation, enabling the use of sophisticated genetic manipulation tools across the bacterial world.
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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".