Evidence map›Paper›PMID 16549877›Full record

ArticleNucleic acids research2006

In vitro selection of tRNAs for efficient four-base decoding to incorporate non-natural amino acids into proteins in an Escherichia coli cell-free translation system.

Hikaru Taira, Takahiro Hohsaka, Masahiko Sisido

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Nucleic acids research, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 22 citations in OpenAlex.

  1. Review
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  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Hikaru TairaDepartment of Bioscience and Bioengineering, Okayama University, Tsushimanaka, Okayama 700-8530, Japan.
Takahiro Hohsaka
Masahiko Sisido
Okayama University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Position-specific incorporation of non-natural amino acids into proteins is a useful technique in protein engineering. In this study, we established a novel selection system to obtain tRNAs that show high decoding activity, from a tRNA library in a cell-free translation system to improve the efficiency of incorporation of non-natural amino acids into proteins. In this system, a puromycin-tRNA conjugate, in which the 3'-terminal A unit was replaced by puromycin, was used. The puromycin-tRNA conjugate was fused to a C-terminus of streptavidin through the puromycin moiety in the ribosome. The streptavidin-puromycin-tRNA fusion molecule was collected and brought to the next round after amplification of the tRNA sequence. We applied this system to select efficient frameshift suppressor tRNAs from a tRNA library with a randomly mutated anticodon loop derived from yeast tRNA CCCG Phe. After three rounds of the selection, we obtained novel frameshift suppressor tRNAs which had high decoding activity and good orthogonality against endogenous aminoacyl-tRNA synthetases. These results demonstrate that the in vitro selection system developed here is useful to obtain highly active tRNAs for the incorporation of non-natural amino acid from a tRNA library.

Indexed as

Protein BiosynthesisAmino AcidsAmino Acyl-tRNA SynthetasesAnticodonBase SequenceCell-Free SystemCodonEscherichia coliFrameshifting, RibosomalGene LibraryMolecular Sequence DataMutationProtein EngineeringProteinsPuromycinReverse Transcriptase Polymerase Chain ReactionAmino AcidsAmino Acyl-tRNA SynthetasesAnticodonCodonProteinsPuromycinRNA, TransferRNA, Transfer, PheStreptavidin

Identifiers

PMID16549877
PMCPMC1405820
OpenAlexW2066502509

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.