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Computational inference of the structure and regulation of the lignin pathway in Panicum virgatum

Overview of attention for article published in Biotechnology for Biofuels and Bioproducts, September 2015
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Title
Computational inference of the structure and regulation of the lignin pathway in Panicum virgatum
Published in
Biotechnology for Biofuels and Bioproducts, September 2015
DOI 10.1186/s13068-015-0334-8
Pubmed ID
Authors

Mojdeh Faraji, Luis L. Fonseca, Luis Escamilla-Treviño, Richard A. Dixon, Eberhard O. Voit

Abstract

Switchgrass is a prime target for biofuel production from inedible plant parts and has been the subject of numerous investigations in recent years. Yet, one of the main obstacles to effective biofuel production remains to be the major problem of recalcitrance. Recalcitrance emerges in part from the 3-D structure of lignin as a polymer in the secondary cell wall. Lignin limits accessibility of the sugars in the cellulose and hemicellulose polymers to enzymes and ultimately decreases ethanol yield. Monolignols, the building blocks of lignin polymers, are synthesized in the cytosol and translocated to the plant cell wall, where they undergo polymerization. The biosynthetic pathway leading to monolignols in switchgrass is not completely known, and difficulties associated with in vivo measurements of these intermediates pose a challenge for a true understanding of the functioning of the pathway. In this study, a systems biological modeling approach is used to address this challenge and to elucidate the structure and regulation of the lignin pathway through a computational characterization of alternate candidate topologies. The analysis is based on experimental data characterizing stem and tiller tissue of four transgenic lines (knock-downs of genes coding for key enzymes in the pathway) as well as wild-type switchgrass plants. These data consist of the observed content and composition of monolignols. The possibility of a G-lignin specific metabolic channel associated with the production and degradation of coniferaldehyde is examined, and the results support previous findings from another plant species. The computational analysis suggests regulatory mechanisms of product inhibition and enzyme competition, which are well known in biochemistry, but so far had not been reported in switchgrass. By including these mechanisms, the pathway model is able to represent all observations. The results show that the presence of the coniferaldehyde channel is necessary and that product inhibition and competition over cinnamoyl-CoA-reductase (CCR1) are essential for matching the model to observed increases in H-lignin levels in 4-coumarate:CoA-ligase (4CL) knockdowns. Moreover, competition for 4-coumarate:CoA-ligase (4CL) is essential for matching the model to observed increases in the pathway metabolites in caffeic acid O-methyltransferase (COMT) knockdowns. As far as possible, the model was validated with independent data.

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Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
China 1 3%
Unknown 35 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 24%
Student > Bachelor 5 14%
Student > Ph. D. Student 5 14%
Student > Doctoral Student 3 8%
Other 3 8%
Other 6 16%
Unknown 6 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 35%
Engineering 5 14%
Chemistry 4 11%
Biochemistry, Genetics and Molecular Biology 2 5%
Chemical Engineering 1 3%
Other 5 14%
Unknown 7 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 September 2015.
All research outputs
#20,653,708
of 25,371,288 outputs
Outputs from Biotechnology for Biofuels and Bioproducts
#1,285
of 1,578 outputs
Outputs of similar age
#207,672
of 283,789 outputs
Outputs of similar age from Biotechnology for Biofuels and Bioproducts
#32
of 41 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,578 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 10th percentile – i.e., 10% 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 283,789 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.