Evidence map›Paper›PMID 31777928›Full record

ReviewNucleic acids research2020

Strategies for in vitro engineering of the translation machinery.

Michael J Hammerling, Antje Krüger, Michael C Jewett

Abstract readReview
In one paragraph

Review in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

35 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Tuning tRNAs for improved translation.Frontiers in genetics · 2024
    Review
  10. Review
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article
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.

Michael J HammerlingDepartment of Chemical and Biological Engineering, Center for Synthetic Biology, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA.
Antje KrügerDepartment of Chemical and Biological Engineering, Center for Synthetic Biology, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA.
Michael C JewettDepartment of Chemical and Biological Engineering, Center for Synthetic Biology, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA.

Funding

Innovative technologies to transform antibiotic discovery. Project 4 Infection site-specific amplification of antimicrobial conjugatesU19AI142780 · NIAID · BROAD INSTITUTE, INC. · PI HUNG, DEBORAH T · 2019 to 2023
$33.9M
NIAID NIH HHS U19 AI142780
6 · The paper itself

Abstract

Engineering the process of molecular translation, or protein biosynthesis, has emerged as a major opportunity in synthetic and chemical biology to generate novel biological insights and enable new applications (e.g. designer protein therapeutics). Here, we review methods for engineering the process of translation in vitro. We discuss the advantages and drawbacks of the two major strategies-purified and extract-based systems-and how they may be used to manipulate and study translation. Techniques to engineer each component of the translation machinery are covered in turn, including transfer RNAs, translation factors, and the ribosome. Finally, future directions and enabling technological advances for the field are discussed.

Indexed as

BioengineeringProtein BiosynthesisAmino AcidsRibosomal ProteinsRibosomesRNA, TransferAmino AcidsRibosomal ProteinsRNA, Transfer

Identifiers

PMID31777928
PMCPMC7026604

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.