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Production of small cysteine‐rich effector proteins in Escherichia coli for structural and functional studies

Overview of attention for article published in Molecular Plant Pathology, April 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

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1 news outlet
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Title
Production of small cysteine‐rich effector proteins in Escherichia coli for structural and functional studies
Published in
Molecular Plant Pathology, April 2016
DOI 10.1111/mpp.12385
Pubmed ID
Authors

Xiaoxiao Zhang, Neal Nguyen, Susan Breen, Megan A. Outram, Peter N. Dodds, Bostjan Kobe, Peter S. Solomon, Simon J. Williams

Abstract

While the life-styles and infection strategies of plant pathogens are diverse, a prevailing feature is the use of an arsenal of secreted proteins, known as effectors that aid in microbial infection. In the case of eukaryotic filamentous pathogens such as fungi and oomycetes, effector proteins are typically dissimilar, at the protein sequence level, to known protein families and functional domains. Consequently, we currently have a limited understanding of how fungal and oomycete effectors promote disease. Protein biochemistry and structural biology are two methods that can contribute greatly to the understanding of protein function. Both techniques are dependent on obtaining proteins that are pure and functional, and generally require the use of heterologous recombinant protein expression systems. Here we present a general scheme and methodology for the production and characterisation of small cysteine-rich (SCR) effectors utilising Escherichia coli expression systems. Using this approach, we successfully produced cysteine-rich effectors derived from the biotrophic fungal pathogen Melampsora lini and the necrotrophic fungal pathogen Parastagonospora nodorum. Access to functional recombinant proteins facilitated crystallisation and functional experiments. These results will be discussed in the context of a general workflow that may serve as a template for others interested in understanding the function of SCR effector(s) from their plant pathogen(s) of interest. This article is protected by copyright. All rights reserved.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 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 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Turkey 1 1%
France 1 1%
Australia 1 1%
Unknown 69 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 19%
Researcher 13 18%
Student > Master 11 15%
Student > Bachelor 5 7%
Student > Doctoral Student 3 4%
Other 7 10%
Unknown 19 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 40%
Biochemistry, Genetics and Molecular Biology 17 24%
Computer Science 1 1%
Economics, Econometrics and Finance 1 1%
Chemistry 1 1%
Other 1 1%
Unknown 22 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 24 December 2016.
All research outputs
#2,043,945
of 25,055,009 outputs
Outputs from Molecular Plant Pathology
#124
of 1,714 outputs
Outputs of similar age
#32,889
of 307,091 outputs
Outputs of similar age from Molecular Plant Pathology
#4
of 44 outputs
Altmetric has tracked 25,055,009 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,714 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has done particularly well, scoring higher than 92% 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 307,091 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 44 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 93% of its contemporaries.