ArticleScience advances2025
Sustainable regeneration of 20 aminoacyl-tRNA synthetases in a reconstituted system toward self-synthesizing artificial systems.
Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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.
Who cites it
11 citing papers in PubMed.
- Optimized SPE-HPLC-FLD Method for the Simultaneous Determination of Olaparib, Propranolol, and Furosemide in Human Urine.Biomedical chromatography : BMC · 2026Article
- A self-replicating artificial module-genome that generates bacterial chromosome replication system in vitro.Nucleic acids research · 2026Article
- PURE makes PURE: reconstitution of the PURE cell-free system from self-synthesized proteins.Nature communications · 2026Article
- Experimental evolution toward extinction in a molecular host-parasite system.Molecular biology and evolution · 2026Article
- Impact of Reducing Agents on Protein Synthesis in a Reconstituted Cell-Free Protein Synthesis System.ACS synthetic biology · 2026Article
- Engineering genetic elements for microbial protein expression systems: Advances, challenges, applications, and prospects.Synthetic and systems biotechnology · 2026Review
- Autonomous biogenesis of all thirty proteins of the Escherichia coli translation machinery.Nature communications · 2025Article
- Genetically Encoded Control ofACS synthetic biology · 2025Article
- Simultaneous in vitro expression of minimal 21 transfer RNAs by tRNA array method.Nature communications · 2025Article
- Building a Synthetic Cell Together.Nature communications · 2025Review
- The Japan-UK Synthetic Biology Conference, Spring 2025: Strengthening Global Links to Engineer Biology.ACS synthetic biology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In vitro construction of self-reproducible artificial systems is a major challenge in bottom-up synthetic biology. Here, we developed a reconstituted system capable of sustainably regenerating all 20 aminoacyl-transfer RNA synthetases (AARS), which are major components of the translation system. To achieve this, we needed five types of improvements: (i) optimization of AARS sequences for efficient translation, (ii) optimization of the composition of the translation system to enhance translation, (iii) employment of another bacterial AlaRS and SerRS to improve each aminoacylation activity, (iv) diminishing the translational inhibition caused by certain AARS sequences by codon optimization and EF-P addition, and (v) balancing the DNA concentrations of 20 AARS to match each requirement. After these improvements, we succeeded in the sustainable regeneration of all 20 AARS for up to 20 cycles of 2.5-fold serial dilutions. These methodologies and results provide a substantial advancement toward the realization of self-reproducible artificial systems.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.