Our primary objective is to quantitatively describe how the flux and direction of the entire pathway for the biosynthesis of the lignin polymer is integrated and regulated. Our primary tool is systematic gene specific perturbation in transgenic Populus trichocarpa. We have identified, in the P. trichocarpa genome, all known pathway (21 monolignol and 4 peroxidase), and transcription factor (2 LIM, 4 MYB, 1 KNOX) genes and their corresponding proteins (using LC-tandem mass spectrometry, MS/MS), affecting lignin biosynthesis in differentiating xylem. We have perturbed all these 33 genes using artificial microRNA (amiRNA) and RNAi suppression. We have:
(1) Quantified the responses (transcripts, proteins, metabolites, lignin composition and linkages) for every relevant gene through xylem-specific and gene-specific knock-downs, plus a few constructs for over-expression.
(2) Quantified redundancy where more than one member of a gene family is expressed using gene and family specific suppression.
(3) Generated new hypotheses about mechanisms of regulation and metabolic flux from data summaries and statistical analyses.
(4) Modeled and illustrated how changes in processing components affect pathway flux and lignin structure.
Consequently, we revealed new regulatory mechanisms and answered the following questions: To what extent can the relative abundance of transcripts of specific genes predict the protein quantity? To what extent can the abundance and activity of individual enzymes predict the composition of lignin monomers? To what extent can the relative abundance of lignin monomers predict the quantity, composition, and specific linkages of lignin? To answer these questions, we developed a predictive model of lignin biosynthesis and structure.
Specific Objectives:
1. Transgene Perturbation: We generated transgenic P. trichocarpa with modified expression of all identified lignin pathway and TF genes.
2. Transcriptome Analysis: Transgenics for each gene were analyzed to test for specificity and pleiotropic effects on transcripts within and outside of the lignin pathway using microarrays, qRT-PCR, and targeted sequencing.
3. Proteomic Analysis: Changes in abundance of protein components were characterized by protein cleavage coupled with isotope dilution MS (PC-IDMS)-based LC-MS/MS for absolute protein quantity, and by LC-MS for enzyme activity. Kinetic parameters were determined for recombinant proteins from all lignin biosynthesis genes.
4. Metabolite Quantitation: GC-MS and LC-MS/MS, coupled with stable isotope-labeled metabolites as internal standards (stable isotope dilution technique), were used to quantify the effects of transgenic perturbations on type and concentration of lignin pathway metabolites to correlate metabolites and lignin structure.
5. Lignin Quantity and Structure: Wet chemistry analysis was be used to quantify lignin content of the wood for each transgenic line. Lignin monomer composition and inter-unit linkages were quantified by 1D and 2D NMR to identify correlations with pathway components and for modeling formation of lignin structures.
6. Database and Website: A public database/website was setup at the beginning of the project to integrate all project data and information, including a comprehensive NMR structure library for lignin.
7. Statistical Analysis: Univariate and multivariate statistical methods were applied to describe the degree, direction and significance of relationships among all pathway components and inter-unit linkages. Statistics is essential to establish significance of correlations and to provide quantitative information for mechanistic modeling.
8. Mechanistic and Systems Modeling: Modeling techniques integrated experimental results and statistical inference to develop mathematical representations of lignin biosynthesis and linkage structure. We integrated the information into steady-state regulatory-constrained flux balance analysis (RC-FBA).
Detailed experimental approaches to accomplish the specific objectives are described in our project website (LigninSystems.org). All information and data generated in this project, as they are collected and analyzed, is posted on this website. Click here for a list of publications generated by this project. All biological materials, including transgenic plants, are available following policies of NSF Plant Genome Program funded research and NC State University. If you have any questions about the data in this website, would like to use these data for publication, or would like to collaborate, please contact Vincent Chiang (Contacts Page).