Evolving Bacterial Fitness with an Expanded Genetic Code is a research paper published in Scientific Reports (2018). On theSindex it has a DataRank of 0.672. It has been cited 13 times, with 13 citing works in its 1-hop citation network.
Abstract Since the fixation of the genetic code, evolution has largely been confined to 20 proteinogenic amino acids. The development of orthogonal translation systems that allow for the codon-specific incorporation of noncanonical amino acids may provide a means to expand the code, but these translation systems cannot be simply superimposed on cells that have spent billions of years optimizing their genomes with the canonical code. We have therefore carried out directed evolution experiments with an orthogonal translation system that inserts 3-nitro- L -tyrosine across from amber codons, creating a 21 amino acid genetic code in which the amber stop codon ambiguously encodes either 3-nitro- L -tyrosine or stop. The 21 amino acid code is enforced through the inclusion of an addicted, essential gene, a beta-lactamase dependent upon 3-nitro- L -tyrosine incorporation. After 2000 generations of directed evolution, the fitness deficit of the original strain was largely repaired through mutations that limited the toxicity of the noncanonical. While the evolved lineages had not resolved the ambiguous coding of the amber codon, the improvements in fitness allowed new amber codons to populate protein coding sequences.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.396
From this paper's citation signal
Citation Network Contribution
0.277
From 12 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 59% comes from its base citations and 41% from the citation network (12 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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