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Auxotrophy to Xeno-DNA: an exploration of combinatorial mechanisms for a high-fidelity biosafety system for synthetic biology applications

Overview of attention for article published in Journal of Biological Engineering, August 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#9 of 222)
  • High Attention Score compared to outputs of the same age (92nd percentile)

Mentioned by

twitter
55 tweeters
googleplus
1 Google+ user
reddit
1 Redditor

Citations

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7 Dimensions

Readers on

mendeley
51 Mendeley
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1 CiteULike
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Title
Auxotrophy to Xeno-DNA: an exploration of combinatorial mechanisms for a high-fidelity biosafety system for synthetic biology applications
Published in
Journal of Biological Engineering, August 2018
DOI 10.1186/s13036-018-0105-8
Pubmed ID
Authors

Christopher M. Whitford, Saskia Dymek, Denise Kerkhoff, Camilla März, Olga Schmidt, Maximilian Edich, Julian Droste, Boas Pucker, Christian Rückert, Jörn Kalinowski

Abstract

Biosafety is a key aspect in the international Genetically Engineered Machine (iGEM) competition, which offers student teams an amazing opportunity to pursue their own research projects in the field of Synthetic Biology. iGEM projects often involve the creation of genetically engineered bacterial strains. To minimize the risks associated with bacterial release, a variety of biosafety systems were constructed, either to prevent survival of bacteria outside the lab or to hinder horizontal or vertical gene transfer. Physical containment methods such as bioreactors or microencapsulation are considered the first safety level. Additionally, various systems involving auxotrophies for both natural and synthetic compounds have been utilized by iGEM teams in recent years. Combinatorial systems comprising multiple auxotrophies have been shown to reduced escape frequencies below the detection limit. Furthermore, a number of natural toxin-antitoxin systems can be deployed to kill cells under certain conditions. Additionally, parts of naturally occurring toxin-antitoxin systems can be used for the construction of 'kill switches' controlled by synthetic regulatory modules, allowing control of cell survival. Kill switches prevent cell survival but do not completely degrade nucleic acids. To avoid horizontal gene transfer, multiple mechanisms to cleave nucleic acids can be employed, resulting in 'self-destruction' of cells. Changes in light or temperature conditions are powerful regulators of gene expression and could serve as triggers for kill switches or self-destruction systems. Xenobiology-based containment uses applications of Xeno-DNA, recoded codons and non-canonical amino acids to nullify the genetic information of constructed cells for wild type organisms. A 'minimal genome' approach brings the opportunity to reduce the genome of a cell to only genes necessary for survival under lab conditions. Such cells are unlikely to survive in the natural environment and are thus considered safe hosts. If suitable for the desired application, a shift to cell-free systems based on Xeno-DNA may represent the ultimate biosafety system. Here we describe different containment approaches in synthetic biology, ranging from auxotrophies to minimal genomes, which can be combined to significantly improve reliability. Since the iGEM competition greatly increases the number of people involved in synthetic biology, we will focus especially on biosafety systems developed and applied in the context of the iGEM competition.

Twitter Demographics

The data shown below were collected from the profiles of 55 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 25%
Student > Ph. D. Student 9 18%
Student > Bachelor 8 16%
Researcher 6 12%
Other 2 4%
Other 4 8%
Unknown 9 18%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 26 51%
Agricultural and Biological Sciences 7 14%
Computer Science 2 4%
Immunology and Microbiology 1 2%
Veterinary Science and Veterinary Medicine 1 2%
Other 4 8%
Unknown 10 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 32. 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 02 November 2020.
All research outputs
#712,261
of 16,389,200 outputs
Outputs from Journal of Biological Engineering
#9
of 222 outputs
Outputs of similar age
#21,322
of 280,204 outputs
Outputs of similar age from Journal of Biological Engineering
#1
of 1 outputs
Altmetric has tracked 16,389,200 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 222 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one has done particularly well, scoring higher than 95% of its peers.
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 280,204 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them