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Sequence-based prediction of permissive stretches for internal protein tagging and knockdown

Overview of attention for article published in BMC Biology, October 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Average Attention Score compared to outputs of the same age and source

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13 tweeters

Citations

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7 Dimensions

Readers on

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46 Mendeley
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Title
Sequence-based prediction of permissive stretches for internal protein tagging and knockdown
Published in
BMC Biology, October 2017
DOI 10.1186/s12915-017-0440-0
Pubmed ID
Authors

Sabine Oesterle, Tania Michelle Roberts, Lukas Andreas Widmer, Harun Mustafa, Sven Panke, Sonja Billerbeck

Abstract

Internal tagging of proteins by inserting small functional peptides into surface accessible permissive sites has proven to be an indispensable tool for basic and applied science. Permissive sites are typically identified by transposon mutagenesis on a case-by-case basis, limiting scalability and their exploitation as a system-wide protein engineering tool. We developed an apporach for predicting permissive stretches (PSs) in proteins based on the identification of length-variable regions (regions containing indels) in homologous proteins. We verify that a protein's primary structure information alone is sufficient to identify PSs. Identified PSs are predicted to be predominantly surface accessible; hence, the position of inserted peptides is likely suitable for diverse applications. We demonstrate the viability of this approach by inserting a Tobacco etch virus protease recognition site (TEV-tag) into several PSs in a wide range of proteins, from small monomeric enzymes (adenylate kinase) to large multi-subunit molecular machines (ATP synthase) and verify their functionality after insertion. We apply this method to engineer conditional protein knockdowns directly in the Escherichia coli chromosome and generate a cell-free platform with enhanced nucleotide stability. Functional internally tagged proteins can be rationally designed and directly chromosomally implemented. Critical for the successful design of protein knockdowns was the incorporation of surface accessibility and secondary structure predictions, as well as the design of an improved TEV-tag that enables efficient hydrolysis when inserted into the middle of a protein. This versatile and portable approach can likely be adapted for other applications, and broadly adopted. We provide guidelines for the design of internally tagged proteins in order to empower scientists with little or no protein engineering expertise to internally tag their target proteins.

Twitter Demographics

The data shown below were collected from the profiles of 13 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 20%
Student > Master 9 20%
Researcher 8 17%
Student > Bachelor 7 15%
Student > Postgraduate 3 7%
Other 4 9%
Unknown 6 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 33%
Agricultural and Biological Sciences 10 22%
Computer Science 4 9%
Chemical Engineering 3 7%
Engineering 2 4%
Other 6 13%
Unknown 6 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 03 July 2019.
All research outputs
#2,962,304
of 15,371,078 outputs
Outputs from BMC Biology
#739
of 1,311 outputs
Outputs of similar age
#82,477
of 321,718 outputs
Outputs of similar age from BMC Biology
#87
of 127 outputs
Altmetric has tracked 15,371,078 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,311 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.1. This one is in the 43rd percentile – i.e., 43% 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 321,718 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 74% of its contemporaries.
We're also able to compare this research output to 127 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.