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The alignment of enzymatic steps reveals similar metabolic pathways and probable recruitment events in Gammaproteobacteria

Overview of attention for article published in BMC Genomics, November 2015
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  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

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Title
The alignment of enzymatic steps reveals similar metabolic pathways and probable recruitment events in Gammaproteobacteria
Published in
BMC Genomics, November 2015
DOI 10.1186/s12864-015-2113-0
Pubmed ID
Authors

Augusto Cesar Poot-Hernandez, Katya Rodriguez-Vazquez, Ernesto Perez-Rueda

Abstract

It is generally accepted that gene duplication followed by functional divergence is one of the main sources of metabolic diversity. In this regard, there is an increasing interest in the development of methods that allow the systematic identification of these evolutionary events in metabolism. Here, we used a method not based on biomolecular sequence analysis to compare and identify common and variable routes in the metabolism of 40 Gammaproteobacteria species. The metabolic maps deposited in the KEGG database were transformed into linear Enzymatic Step Sequences (ESS) by using the breadth-first search algorithm. These ESS represent subsequent enzymes linked to each other, where their catalytic activities are encoded in the Enzyme Commission numbers. The ESS were compared in an all-against-all (pairwise comparisons) approach by using a dynamic programming algorithm, leaving only a set of significant pairs. From these comparisons, we identified a set of functionally conserved enzymatic steps in different metabolic maps, in which cell wall components and fatty acid and lysine biosynthesis were included. In addition, we found that pathways associated with biosynthesis share a higher proportion of similar ESS than degradation pathways and secondary metabolism pathways. Also, maps associated with the metabolism of similar compounds contain a high proportion of similar ESS, such as those maps from nucleotide metabolism pathways, in particular the inosine monophosphate pathway. Furthermore, diverse ESS associated with the low part of the glycolysis pathway were identified as functionally similar to multiple metabolic pathways. In summary, our comparisons may help to identify similar reactions in different metabolic pathways and could reinforce the patchwork model in the evolution of metabolism in Gammaproteobacteria.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 4%
Brazil 1 4%
Unknown 21 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 17%
Researcher 4 17%
Professor > Associate Professor 4 17%
Student > Bachelor 3 13%
Other 2 9%
Other 5 22%
Unknown 1 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 30%
Biochemistry, Genetics and Molecular Biology 6 26%
Computer Science 4 17%
Engineering 2 9%
Social Sciences 1 4%
Other 1 4%
Unknown 2 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 30 August 2016.
All research outputs
#7,668,611
of 23,344,526 outputs
Outputs from BMC Genomics
#3,677
of 10,745 outputs
Outputs of similar age
#120,931
of 389,159 outputs
Outputs of similar age from BMC Genomics
#142
of 389 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,745 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 58% 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 389,159 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 55% of its contemporaries.
We're also able to compare this research output to 389 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 62% of its contemporaries.