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QuickStep-Cloning: a sequence-independent, ligation-free method for rapid construction of recombinant plasmids

Overview of attention for article published in Journal of Biological Engineering, September 2015
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  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

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Title
QuickStep-Cloning: a sequence-independent, ligation-free method for rapid construction of recombinant plasmids
Published in
Journal of Biological Engineering, September 2015
DOI 10.1186/s13036-015-0010-3
Pubmed ID
Authors

Pawel Jajesniak, Tuck Seng Wong

Abstract

Molecular cloning is an essential step in biological engineering. Methods involving megaprimer-based PCR of a whole plasmid are promising alternatives to the traditional restriction-ligation-based molecular cloning. Their widespread use, however, is hampered by some of their inherent characteristics, e.g., linear amplification, use of self-annealing megaprimers and difficulty with performing point insertion of DNA. These limitations result in low product yield and reduced flexibility in the design of a genetic construct. Here, we present a novel technique of directional cloning, which overcomes these problems yet retaining the simplicity of whole-plasmid amplification. QuickStep-Cloning utilizes asymmetric PCRs to create a megaprimer pair with 3'-overhangs, and hence, facilitates the subsequent exponential whole-plasmid amplification. QuickStep-Cloning generates nicked-circular plasmids, thereby permitting direct bacterial transformation without DNA ligation. It allows DNA fragment integration into any plasmid at any position, in an efficient, time- and cost-effective manner, without tedious intermediate DNA gel purification, modified oligonucleotides, specialty enzymes and ultra-competent cells. The method is compatible with competent E. coli cells prepared using the conventional calcium chloride method. QuickStep-Cloning expands the versatility of megaprimer-based cloning. It is an excellent addition to the cloning toolbox, for the benefit of protein engineers, metabolic engineers and synthetic biologists.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 136 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
Uruguay 1 <1%
United Kingdom 1 <1%
China 1 <1%
Japan 1 <1%
Unknown 131 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 17%
Researcher 22 16%
Student > Master 21 15%
Student > Bachelor 14 10%
Student > Doctoral Student 9 7%
Other 19 14%
Unknown 28 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 50 37%
Biochemistry, Genetics and Molecular Biology 36 26%
Chemistry 6 4%
Medicine and Dentistry 6 4%
Pharmacology, Toxicology and Pharmaceutical Science 2 1%
Other 7 5%
Unknown 29 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 September 2015.
All research outputs
#13,033,255
of 23,316,003 outputs
Outputs from Journal of Biological Engineering
#146
of 272 outputs
Outputs of similar age
#119,745
of 274,025 outputs
Outputs of similar age from Journal of Biological Engineering
#4
of 8 outputs
Altmetric has tracked 23,316,003 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 272 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one is in the 46th percentile – i.e., 46% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 274,025 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.