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Essential validation methods for E. coli strains created by chromosome engineering

Overview of attention for article published in Journal of Biological Engineering, July 2015
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Title
Essential validation methods for E. coli strains created by chromosome engineering
Published in
Journal of Biological Engineering, July 2015
DOI 10.1186/s13036-015-0008-x
Pubmed ID
Authors

Sriram Tiruvadi Krishnan, M. Charl Moolman, Theo van Laar, Anne S. Meyer, Nynke H. Dekker

Abstract

Chromosome engineering encompasses a collection of homologous recombination-based techniques that are employed to modify the genome of a model organism in a controlled fashion. Such techniques are widely used in both fundamental and industrial research to introduce multiple insertions in the same Escherichia coli strain. To date, λ-Red recombination (also known as recombineering) and P1 phage transduction are the most successfully implemented chromosome engineering techniques in E. coli. However, due to errors that can occur during the strain creation process, reliable validation methods are essential upon alteration of a strain's chromosome. Polymerase chain reaction (PCR)-based methods and DNA sequence analysis are rapid and powerful methods to verify successful integration of DNA sequences into a chromosome. Even though these verification methods are necessary, they may not be sufficient in detecting all errors, imposing the requirement of additional validation methods. For example, as extraneous insertions may occur during recombineering, we highlight the use of Southern blotting to detect their presence. These unwanted mutations can be removed via transducing the region of interest into the wild type chromosome using P1 phages. However, in doing so one must verify that both the P1 lysate and the strains utilized are free from contamination with temperate phages, as these can lysogenize inside a cell as a large plasmid. Thus, we illustrate various methods to probe for temperate phage contamination, including cross-streak agar and Evans Blue-Uranine (EBU) plate assays, whereby the latter is a newly reported technique for this purpose in E. coli. Lastly, we discuss methodologies for detecting defects in cell growth and shape characteristics, which should be employed as an additional check. The simple, yet crucial validation techniques discussed here can be used to reliably verify any chromosomally engineered E. coli strains for errors such as non-specific insertions in the chromosome, temperate phage contamination, and defects in growth and cell shape. While techniques such as PCR and DNA sequence verification should standardly be performed, we illustrate the necessity of performing these additional assays. The discussed techniques are highly generic and can be easily applied to any type of chromosome engineering.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
China 1 2%
Unknown 57 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 19%
Student > Bachelor 10 17%
Student > Master 9 15%
Researcher 8 14%
Student > Doctoral Student 3 5%
Other 10 17%
Unknown 8 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 29%
Biochemistry, Genetics and Molecular Biology 15 25%
Engineering 5 8%
Immunology and Microbiology 4 7%
Chemistry 3 5%
Other 5 8%
Unknown 10 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 01 July 2015.
All research outputs
#15,687,628
of 23,312,088 outputs
Outputs from Journal of Biological Engineering
#190
of 272 outputs
Outputs of similar age
#155,428
of 264,502 outputs
Outputs of similar age from Journal of Biological Engineering
#4
of 5 outputs
Altmetric has tracked 23,312,088 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% 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 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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