Escherichia coli adapts metabolically to 6- and 7-fluoroindole, enabling proteome-wide fluorotryptophan substitution
Bibliographic record
Abstract
Nature has scarcely evolved a biochemistry around fluorine. However, modern science has shown that fluorinated organic molecules are suitable building blocks for biopolymers, from peptides and proteins up to entire organisms. Here, we conducted adaptive laboratory evolution (ALE) experiments to introduce organofluorine into living microorganisms. By cultivating Escherichia coli with fluorinated indole analogs, we successfully evolved microbial cells capable of utilizing either 6-fluoroindole or 7-fluoroindole for growth. Our improved ALE protocols enabled us to overcome previous challenges and adaptation was achieved, enabling a former growth inhibiting unnatural molecule to become a substrate for the cell’s protein synthesis machinery to the extent that the entire proteome underwent Trp to F-Trp substitution. In the ALE experiments, we supplied fluoroindoles to Trp-auxotrophic E. coli bacteria, exerting strong selective pressure that led to microbial adaptation. Within the cells, these indoles were converted into the corresponding amino acids (6- and 7-fluorotryptophan) and globally incorporated into the proteome at tryptophan sites. This study is a first step and establishes a strong foundation for further exploration of the mechanisms underlying fluorine-based life and how a former antimetabolite can become a vital nutrient.
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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".