Reducing the genetic code induces massive rearrangement of the proteome
Bibliographic record
Abstract
Expanding the genetic code is an important aim of synthetic biology, but some organisms developed naturally expanded genetic codes long ago over the course of evolution. Less than 1% of all sequenced genomes encode an operon that reassigns the stop codon UAG to pyrrolysine (Pyl), a genetic code variant that results from the biosynthesis of Pyl-tRNA(Pyl). To understand the selective advantage of genetically encoding more than 20 amino acids, we constructed a markerless tRNA(Pyl) deletion strain of Methanosarcina acetivorans (ΔpylT) that cannot decode UAG as Pyl or grow on trimethylamine. Phenotypic defects in the ΔpylT strain were evident in minimal medium containing methanol. Proteomic analyses of wild type (WT) M. acetivorans and ΔpylT cells identified 841 proteins from >7,000 significant peptides detected by MS/MS. Protein production from UAG-containing mRNAs was verified for 19 proteins. Translation of UAG codons was verified by MS/MS for eight proteins, including identification of a Pyl residue in PylB, which catalyzes the first step of Pyl biosynthesis. Deletion of tRNA(Pyl) globally altered the proteome, leading to >300 differentially abundant proteins. Reduction of the genetic code from 21 to 20 amino acids led to significant down-regulation in translation initiation factors, amino acid metabolism, and methanogenesis from methanol, which was offset by a compensatory (100-fold) up-regulation in dimethyl sulfide metabolic enzymes. The data show how a natural proteome adapts to genetic code reduction and indicate that the selective value of an expanded genetic code is related to carbon source range and metabolic efficiency.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".