↓ Skip to main content

Engineering an allosteric transcription factor to respond to new ligands

Overview of attention for article published in Nature Methods, December 2015
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
6 news outlets
blogs
4 blogs
twitter
36 X users
patent
10 patents
facebook
1 Facebook page
googleplus
4 Google+ users

Citations

dimensions_citation
278 Dimensions

Readers on

mendeley
607 Mendeley
citeulike
4 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Engineering an allosteric transcription factor to respond to new ligands
Published in
Nature Methods, December 2015
DOI 10.1038/nmeth.3696
Pubmed ID
Authors

Noah D Taylor, Alexander S Garruss, Rocco Moretti, Sum Chan, Mark A Arbing, Duilio Cascio, Jameson K Rogers, Farren J Isaacs, Sriram Kosuri, David Baker, Stanley Fields, George M Church, Srivatsan Raman

Abstract

Genetic regulatory proteins inducible by small molecules are useful synthetic biology tools as sensors and switches. Bacterial allosteric transcription factors (aTFs) are a major class of regulatory proteins, but few aTFs have been redesigned to respond to new effectors beyond natural aTF-inducer pairs. Altering inducer specificity in these proteins is difficult because substitutions that affect inducer binding may also disrupt allostery. We engineered an aTF, the Escherichia coli lac repressor, LacI, to respond to one of four new inducer molecules: fucose, gentiobiose, lactitol and sucralose. Using computational protein design, single-residue saturation mutagenesis or random mutagenesis, along with multiplex assembly, we identified new variants comparable in specificity and induction to wild-type LacI with its inducer, isopropyl β-D-1-thiogalactopyranoside (IPTG). The ability to create designer aTFs will enable applications including dynamic control of cell metabolism, cell biology and synthetic gene circuits.

X Demographics

X Demographics

The data shown below were collected from the profiles of 36 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 607 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 <1%
Belgium 2 <1%
Denmark 2 <1%
United Kingdom 2 <1%
Lithuania 1 <1%
Singapore 1 <1%
Switzerland 1 <1%
Korea, Republic of 1 <1%
Brazil 1 <1%
Other 2 <1%
Unknown 589 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 172 28%
Researcher 111 18%
Student > Bachelor 75 12%
Student > Master 66 11%
Student > Doctoral Student 27 4%
Other 81 13%
Unknown 75 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 209 34%
Agricultural and Biological Sciences 149 25%
Chemistry 50 8%
Engineering 32 5%
Chemical Engineering 18 3%
Other 48 8%
Unknown 101 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 97. 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 14 January 2024.
All research outputs
#427,666
of 25,164,268 outputs
Outputs from Nature Methods
#517
of 5,337 outputs
Outputs of similar age
#7,203
of 401,977 outputs
Outputs of similar age from Nature Methods
#6
of 108 outputs
Altmetric has tracked 25,164,268 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,337 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 36.0. This one has done particularly well, scoring higher than 90% 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 401,977 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 98% of its contemporaries.
We're also able to compare this research output to 108 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.