A multi-omics quantitative integrative analysis of lignin biosynthesis can advance the strategic engineering of wood for timber, pulp, and biofuels. Lignin is polymerized from three monomers (monolignols) produced by a grid-like pathway. The pathway in wood formation of Populus trichocarpa has at least 21 genes, encoding enzymes that mediate 37 reactions on 24 metabolites, leading to lignin and affecting wood properties. We perturb these 21 pathway genes and integrate transcriptomic, proteomic, fluxomic and phenomic data from 221 lines selected from ~2000 transgenics (6-month-old). The integrative analysis estimates how changing expression of pathway gene or gene combination affects protein abundance, metabolic-flux, metabolite concentrations, and 25 wood traits, including lignin, tree-growth, density, strength, and saccharification. The analysis then predicts improvements in any of these 25 traits individually or in combinations, through engineering expression of specific monolignol genes. The analysis may lead to greater understanding of other pathways for improved growth and adaptation.

We established a predictive kinetic metabolic-flux model for the 21 enzymes and 24 metabolites of the monolignol biosynthetic pathway using Populus trichocarpa secondary differentiating xylem. To establish this model, a comprehensive study was performed to obtain the reaction and inhibition kinetic parameters of all 21 enzymes based on functional recombinant proteins. A total of 104 Michaelis-Menten kinetic parameters and 85 inhibition kinetic parameters were derived from these enzymes. Through mass spectrometry, we obtained the absolute quantities of all 21 pathway enzymes in the secondary differentiating xylem. This extensive experimental data set, generated from a single tissue specialized in wood formation, was used to construct the predictive kinetic metabolic-flux model to provide a comprehensive mathematical description of the monolignol biosynthetic pathway. The model was validated using experimental data from transgenic P. trichocarpa plants. The model predicts how pathway enzymes affect lignin content and composition, explains a longstanding paradox regarding the regulation of monolignol subunit ratios in lignin, and reveals novel mechanisms involved in the regulation of lignin biosynthesis. This model provides an explanation of the effects of genetic and transgenic perturbations of the monolignol biosynthetic pathway in flowering plants.

The hydroxylation of 4-and 3-ring carbons of cinnamic acid derivatives during monolignol biosynthesis are key steps that determine the structure and properties of lignin. Individual enzymes have been thought to catalyze these reactions. In stem differentiating xylem (SDX) of Populus trichocarpa, two cinnamic acid 4-hydroxylases (PtrC4H1 and PtrC4H2) and a p-coumaroyl ester 3-hydroxylase (PtrC3H3) are the enzymes involved in these reactions. Here we present evidence that these hydroxylases interact, forming heterodimeric (PtrC4H1/C4H2, PtrC4H1/C3H3, and PtrC4H2/C3H3) and heterotrimeric (PtrC4H1/C4H2/C3H3) membrane protein complexes. Enzyme kinetics using yeast recombinant proteins demonstrated that the enzymatic efficiency (V max /k m ) for any of the complexes is 70-6,500 times greater than that of the individual proteins. The highest increase in efficiency was found for the PtrC4H1/ C4H2/C3H3-mediated p-coumaroyl ester 3-hydroxylation. Affinity purification-quantitative mass spectrometry, bimolecular fluorescence complementation, chemical cross-linking, and reciprocal coimmunoprecipitation provide further evidence for these multiprotein complexes. The activities of the recombinant and SDX plant proteins demonstrate two protein-complex-mediated 3-hydroxylation paths in monolignol biosynthesis in P. trichocarpa SDX; one converts pcoumaric acid to caffeic acid and the other converts p-coumaroyl shikimic acid to caffeoyl shikimic acid. Cinnamic acid 4-hydroxylation is also mediated by the same protein complexes. These results provide direct evidence for functional involvement of membrane protein complexes in monolignol biosynthesis.

Normalization of spectral counts (SpCs) in label-free shotgun proteomic approaches is important to achieve reliable relative quantification. Three different SpC normalization methods, total spectral count (TSpC) normalization, normalized spectral abundance factor (NSAF) normalization, and normalization to selected proteins (NSP) were evaluated based on their ability to correct for day-to-day variation between gel-based sample preparation and chromatographic performance. Three spectral counting data sets obtained from the same biological conidia sample of the rice blast fungus Magnaporthe oryzae were analyzed by 1D gel and liquid chromatography-tandem mass spectrometry (GeLC-MS/MS). Equine myoglobin and chicken ovalbumin were spiked into the protein extracts prior to 1D-SDS- PAGE as internal protein standards for NSP. The correlation between SpCs of the same proteins across the different data sets was investigated. We report that TSpC normalization and NSAF normalization yielded almost ideal slopes of unity for normalized SpC versus average normalized SpC plots, while NSP did not afford effective corrections of the unnormalized data. Furthermore, when utilizing TSpC normalization prior to relative protein quantification, t-testing and fold-change revealed the cutoff limits for determining real biological change to be a function of the absolute number of SpCs. For instance, we observed the variance decreased as the number of SpCs increased, which resulted in a higher propensity for detecting statistically significant, yet artificial, change for highly abundant proteins. Thus, we suggest applying higher confidence level and lower fold-change cutoffs for proteins with higher SpCs, rather than using a single criterion for the entire data set. By choosing appropriate cutoff values to maintain a constant false positive rate across different protein levels (i.e., SpC levels), it is expected this will reduce the overall false negative rate, particularly for proteins with higher SpCs.

The economic value of wood/pulp from many tree species is largely dictated by the quantity and chemical properties of lignin, which is directly related to the composition and linkages of monolignols comprising the polymer. Although much is known regarding the monolignol biosynthetic pathway, our understanding is still deficient due to the lack of quantitative information at the proteomic level. We developed an assay based on protein cleavage isotope dilution mass spectrometry (PC-IDMS) for the determination of all potential, primary enzymes involved in the biosynthesis of monolignols and the peroxidases responsible for their polymerization to form lignin in the model tree species, Populus trichocarpa. Described is the identification of quantitative surrogate peptides through shotgun analysis of native and recombinant proteins, optimization of trypsin proteolysis using fractional factorial design of experiments, and development of a liquid chromatography-selected reaction monitoring method for specific detection of all targeted peptides. Of the 25 targeted enzymes, three were undetected in the normal xylem tissues, and all but two of the detectable species showed good day-to-day precision (CV < 10%). This represents the most comprehensive assay for quantification of proteins regulating monolignol biosynthesis and will lead to a better understanding of lignin formation at a systems level.