Abstract

BackgroundLignin is a natural polymer that is interwoven with cellulose and hemicellulose within plant cell walls. Due to this molecular arrangement, lignin is a major contributor to the recalcitrance of plant materials with respect to the extraction of sugars and their fermentation into ethanol, butanol, and other potential bioenergy crops. The lignin biosynthetic pathway is similar, but not identical in different plant species. It is in each case comprised of a moderate number of enzymatic steps, but its responses to manipulations, such as gene knock-downs, are complicated by the fact that several of the key enzymes are involved in several reaction steps. This feature poses a challenge to bioenergy production, as it renders it difficult to select the most promising combinations of genetic manipulations for the optimization of lignin composition and amount.ResultsHere, we present several computational models than can aid in the analysis of data characterizing lignin biosynthesis. While minimizing technical details, we focus on the questions of what types of data are particularly useful for modeling and what genuine benefits the biofuel researcher may gain from the resulting models. We demonstrate our analysis with mathematical models for black cottonwood (Populus trichocarpa), alfalfa (Medicago truncatula), switchgrass (Panicum virgatum) and the grass Brachypodium distachyon.ConclusionsDespite commonality in pathway structure, different plant species show different regulatory features and distinct spatial and topological characteristics. The putative lignin biosynthes pathway is not able to explain the plant specific laboratory data, and the necessity of plant specific modeling should be heeded.

Highlights

  • Lignin is a natural polymer that is interwoven with cellulose and hemicellulose within plant cell walls

  • It is important to the production and manipulation of bioenergy crops to understand the details of lignin synthesis and the deposition and polymerization of monolignols in the plant cell wall

  • Faraji et al Biotechnol Biofuels (2018) 11:34 it is possible and feasible to intervene in the phenylpropanoid pathway of lignin biosynthesis in a targeted and effective manner, for instance through gene knockdowns

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Summary

Results

We present several computational models than can aid in the analysis of data characterizing lignin biosynthesis. We focus on the questions of what types of data are use‐ ful for modeling and what genuine benefits the biofuel researcher may gain from the resulting models. We demon‐ strate our analysis with mathematical models for black cottonwood (Populus trichocarpa), alfalfa (Medicago truncatula), switchgrass (Panicum virgatum) and the grass Brachypodium distachyon

Conclusions
Background
Discussion
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