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An integrated workflow for phenazine-modifying enzyme characterization

Overview of attention for article published in Journal of Industrial Microbiology & Biotechnology, March 2018
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  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

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3 tweeters

Citations

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1 Dimensions

Readers on

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5 Mendeley
Title
An integrated workflow for phenazine-modifying enzyme characterization
Published in
Journal of Industrial Microbiology & Biotechnology, March 2018
DOI 10.1007/s10295-018-2025-5
Pubmed ID
Authors

R. Cameron Coates, Benjamin P. Bowen, Ernst Oberortner, Linda Thomashow, Michalis Hadjithomas, Zhiying Zhao, Jing Ke, Leslie Silva, Katherine Louie, Gaoyan Wang, David Robinson, Angela Tarver, Matthew Hamilton, Andrea Lubbe, Meghan Feltcher, Jeffery L. Dangl, Amrita Pati, David Weller, Trent R. Northen, Jan-Fang Cheng, Nigel J. Mouncey, Samuel Deutsch, Yasuo Yoshikuni

Abstract

Increasing availability of new genomes and putative biosynthetic gene clusters (BGCs) has extended the opportunity to access novel chemical diversity for agriculture, medicine, environmental and industrial purposes. However, functional characterization of BGCs through heterologous expression is limited because expression may require complex regulatory mechanisms, specific folding or activation. We developed an integrated workflow for BGC characterization that integrates pathway identification, modular design, DNA synthesis, assembly and characterization. This workflow was applied to characterize multiple phenazine-modifying enzymes. Phenazine pathways are useful for this workflow because all phenazines are derived from a core scaffold for modification by diverse modifying enzymes (PhzM, PhzS, PhzH, and PhzO) that produce characterized compounds. We expressed refactored synthetic modules of previously uncharacterized phenazine BGCs heterologously in Escherichia coli and were able to identify metabolic intermediates they produced, including a previously unidentified metabolite. These results demonstrate how this approach can accelerate functional characterization of BGCs.

Twitter Demographics

The data shown below were collected from the profiles of 3 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 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 80%
Unknown 1 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 80%
Unknown 1 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 12 September 2019.
All research outputs
#8,073,531
of 14,015,503 outputs
Outputs from Journal of Industrial Microbiology & Biotechnology
#675
of 1,032 outputs
Outputs of similar age
#141,965
of 276,576 outputs
Outputs of similar age from Journal of Industrial Microbiology & Biotechnology
#2
of 11 outputs
Altmetric has tracked 14,015,503 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,032 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 33rd percentile – i.e., 33% 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 276,576 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.