Project Home

Welcome to the homepage of the NSF-funded Regulation and Modeling of Lignin Biosynthesis Project (DBI-0922391). The purpose of this site is to provide background and updated progress on the development of predictive models of lignin biosynthesis in wood formation in the model woody plant, Populus trichocarpa (black cottonwood), and to provide centralized access to our expanding database (LigninSystemsDB) on systems modeling of lignin biosynthesis and to our transgenic collection.


Lignin is a phenolic polymer in cell walls of all vascular plants. Lignin polymerization is irreversible, providing an absolute end point in the metabolic pathway. Its accumulation creates a hydrophobic surface for water transport and its specific chemical structures form a pre-existing barrier limiting herbivory and restricting pathogens. The ability of woody plants to establish forest ecosystems depends on lignin. Lignin quantity and structures are also main barriers to the utilization of biomass for energy, materials and food. This NSF-funded project seeks to build models to quantitatively illustrate how the entire pathway is organized and regulated and to reveal new regulatory and metabolic flux control mechanisms, leading to lignin quantity and structures.

Research Approach and Goal

The project used P. trichocarpa (genotype Nisqually-1) and a systems approach including advanced quantitative methods of genomics, proteomics, biochemistry and structural chemistry, to provide the most comprehensive analysis of the regulation of lignin biosynthesis in wood formation ever undertaken. We took a transgenic perturbation strategy to systematically knock down all known pathway and regulatory genes involved in lignin biosynthesis during wood formation. We analyzed all knock-downs with transcriptomics, mass spectrometry proteomics, enzymology, metabolite profiling, and 1D & 2D NMR for lignin structure quantification. We integrated this information using correlation matrices and path analysis to formulate mechanisms of regulatory and metabolic pathway interactions. Such mechanisms were iteratively refined and validated by a signaling graph approach, providing specific regulatory constraints to flux distribution analysis and lignin structural predictions for a quantitative model of the biosynthesis of the lignin polymer. Our goal is a predictive model of lignin biosynthesis for greater understanding of the plant response to environmental stress and for more precise strategies to improve plant productivity and the production of energy, materials and food.