In addition to being a vital component of proteins, phenylalanine is also a precursor of numerous aromatic primary and secondary metabolites with broad physiological functions. In plants phenylalanine is synthesized predominantly via the arogenate pathway in plastids. Here, we describe the structure, molecular players and subcellular localization of a microbial-like phenylpyruvate pathway for phenylalanine biosynthesis in plants. Using a reverse genetic approach and metabolic flux analysis, we provide evidence that the cytosolic chorismate mutase is responsible for directing carbon flux towards cytosolic phenylalanine production via the phenylpyruvate pathway. We also show that an alternative transcription start site of a known plastidial enzyme produces a functional cytosolic prephenate dehydratase that catalyzes the conversion of prephenate to phenylpyruvate, the intermediate step between chorismate mutase and phenylpyruvate aminotransferase. Thus, our results complete elucidation of phenylalanine biosynthesis via phenylpyruvate in plants, showing that this pathway splits from the known plastidial arogenate pathway at chorismate, instead of prephenate as previously thought, and the complete pathway is localized in the cytosol.

In addition to proteins, L-phenylalanine is a versatile precursor for thousands of plant metabolites. Production of phenylalanine-derived compounds is a complex multi-compartmental process using phenylalanine synthesized predominantly in plastids as precursor. The transporter(s) exporting phenylalanine from plastids, however, remains unknown. Here, a gene encoding a Petunia hybrida plastidial cationic amino-acid transporter (PhpCAT) functioning in plastidial phenylalanine export is identified based on homology to an Escherichia coli phenylalanine transporter and co-expression with phenylalanine metabolic genes. Radiolabel transport assays show that PhpCAT exports all three aromatic amino acids. PhpCAT downregulation and overexpression result in decreased and increased levels, respectively, of phenylalanine-derived volatiles, as well as phenylalanine, tyrosine and their biosynthetic intermediates. Metabolic flux analysis reveals that flux through the plastidial phenylalanine biosynthetic pathway is reduced in PhpCAT RNAi lines, suggesting that the rate of phenylalanine export from plastids contributes to regulating flux through the aromatic amino-acid network.

BackgroundThe C4 photosynthetic cycle supercharges photosynthesis by concentrating CO2 around ribulose-1,5-bisphosphate carboxylase and significantly reduces the oxygenation reaction. Therefore engineering C4 feature into C3 plants has been suggested as a feasible way to increase photosynthesis and yield of C3 plants, such as rice, wheat, and potato. To identify the possible transition from C3 to C4 plants, the systematic comparison of C3 and C4 metabolism is necessary.ResultsWe compared C3 and C4 metabolic networks using the improved constraint-based models for Arabidopsis and maize. By graph theory, we found the C3 network exhibit more dense topology structure than C4. The simulation of enzyme knockouts demonstrated that both C3 and C4 networks are very robust, especially when optimizing CO2 fixation. Moreover, C4 plant has better robustness no matter the objective function is biomass synthesis or CO2 fixation. In addition, all the essential reactions in C3 network are also essential for C4, while there are some other reactions specifically essential for C4, which validated that the basic metabolism of C4 plant is similar to C3, but C4 is more complex. We also identified more correlated reaction sets in C4, and demonstrated C4 plants have better modularity with complex mechanism coordinates the reactions and pathways than that of C3 plants. We also found the increase of both biomass production and CO2 fixation with light intensity and CO2 concentration in C4 is faster than that in C3, which reflected more efficient use of light and CO2 in C4 plant. Finally, we explored the contribution of different C4 subtypes to biomass production by setting specific constraints.ConclusionsAll results are consistent with the actual situation, which indicate that Flux Balance Analysis is a powerful method to study plant metabolism at systems level. We demonstrated that in contrast to C3, C4 plants have less dense topology, higher robustness, better modularity, and higher CO2 and radiation use efficiency. In addition, preliminary analysis indicated that the rate of CO2 fixation and biomass production in PCK subtype are superior to NADP-ME and NAD-ME subtypes under enough supply of water and nitrogen.

Background Metabolic fluxes represent the functional phenotypes of biochemical pathways and are essential to reveal the distribution of precursors among metabolic networks. Although analysis of metabolic fluxes, facilitated by stable isotope labeling and mass spectrometry detection, has been applied in the studies of plant metabolism, we lack experimental measurements for carbon flux towards lignin, one of the most abundant polymers in nature.ResultsWe developed a feeding strategy of excised Arabidopsis stems with 13C labeled phenylalanine (Phe) for the analysis of lignin biosynthetic flux. We optimized the feeding methods and found the stems continued to grow and lignify. Consistent with lignification profiles along the stems, higher levels of phenylpropanoids and activities of lignin biosynthetic enzymes were detected in the base of the stem. In the feeding experiments, 13C labeled Phe was quickly accumulated and used for the synthesis of phenylpropanoid intermediates and lignin. The intermediates displayed two different patterns of labeling kinetics during the feeding period. Analysis of lignin showed rapid incorporation of label into all three subunits in the polymers.ConclusionsOur feeding results demonstrate the effectiveness of the stem feeding system and suggest a potential application for the investigations of other aspects in plant metabolism. The supply of exogenous Phe leading to a higher lignin deposition rate indicates the availability of Phe is a determining factor for lignification rates.Electronic supplementary materialThe online version of this article (10.1186/s13007-018-0318-3) contains supplementary material, which is available to authorized users.

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