A giant leap in sequence space reveals the intracellular complexities of evolving a new function
Bibliographic record
Abstract
Abstract Selection for a promiscuous enzyme activity provides substantial opportunity for competition between endogenous and new substrates to influence the evolutionary trajectory, an aspect that has generally been overlooked in laboratory directed evolution studies. We evolved the Escherichia coli nitro/quinone reductase NfsA to detoxify chloramphenicol by randomising eight active site residues simultaneously and interrogating ∼250,000,000 reconfigured NfsA variants. Analysis of every possible evolutionary intermediate of the two best chloramphenicol reductases revealed complex epistatic interactions that restrict each hypothetical trajectory. In both cases, improved chloramphenicol detoxification was only possible after one essential substitution had eliminated activity with endogenous quinone substrates. Unlike the predominantly weak trade-offs seen in previous experimental studies, this substrate incompatibility suggests endogenous metabolites have considerable potential to shape evolutionary outcomes. Unselected prodrug-converting activities were mostly unaffected, which emphasises the importance of negative selection to effect enzyme specialisation, and offers an application for the evolved genes as dual-purpose selectable/counter-selectable markers.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".