Evidence map›Paper›PMID 36322003›Full record

ReviewACS synthetic biology2022

A User's Guide to Golden Gate Cloning Methods and Standards.

Jasmine E Bird, Jon Marles-Wright, Andrea Giachino

Abstract readReview
In one paragraph

Review in ACS synthetic biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing papers in PubMed
–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

68 citing papers in PubMed.

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8 more citing papers are in PubMed but not listed here.

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.

Jasmine E BirdSchool of Computing, Faculty of Science Agriculture and Engineering, Newcastle University, Newcastle upon Tyne, NE1 7RU, United Kingdom.ORCID 0000-0001-6000-3228
Jon Marles-WrightBiosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom.ORCID 0000-0002-9156-3284
Andrea GiachinoBiosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom.ORCID 0000-0002-7725-1065

Funding

Biotechnology and Biological Sciences Research Council BB/N005570/1
6 · The paper itself

Abstract

The continual demand for specialized molecular cloning techniques that suit a broad range of applications has driven the development of many different cloning strategies. One method that has gained significant traction is Golden Gate assembly, which achieves hierarchical assembly of DNA parts by utilizing Type IIS restriction enzymes to produce user-specified sticky ends on cut DNA fragments. This technique has been modularized and standardized, and includes different subfamilies of methods, the most widely adopted of which are the MoClo and Golden Braid standards. Moreover, specialized toolboxes tailored to specific applications or organisms are also available. Still, the quantity and range of assembly methods can constitute a barrier to adoption for new users, and even experienced scientists might find it difficult to discern which tools are best suited toward their goals. In this review, we provide a beginner-friendly guide to Golden Gate assembly, compare the different available standards, and detail the specific features and quirks of commonly used toolboxes. We also provide an update on the state-of-the-art in Golden Gate technology, discussing recent advances and challenges to inform existing users and promote standard practices.

Indexed as

DNASynthetic BiologyCloning, MolecularDNA Restriction EnzymesGenetic VectorsDNADNA Restriction EnzymescloningGolden GateMoClorestriction enzymestandards

Identifiers

PMID36322003
PMCPMC9680027

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.