Climatic change is an increasing challenge for agriculture that is driving the development of suitable crops in order to ensure supply for both human nutrition and animal feed. In this context, it is increasingly important to understand the biochemical responses of cells to environmental cues at the whole system level, an aim that is being brought closer by advances in high throughput, cost-efficient plant metabolomics. To support molecular breeding activities, we have assessed the economic, technical and statistical feasibility of using direct mass spectrometry methods to evaluate the physiological state of maize (Zea mays L.) plants grown under different stress conditions.
Biological networks are complex (non-linear), redundant (cyclic) and compartmentalized at the subcellular level. Rational manipulation of plant metabolism may have failed due to inherent difficulties of a comprehensive understanding of regulatory loops. We first need to identify key factors controlling the regulatory loops of primary metabolism. The paradigms of plant networks are revised in order to highlight the differences between metabolic and transcriptional networks. Comparison between animal and plant transcription factors (TFs) reveal some important differences. Plant transcriptional networks function at a lower hierarchy compared to animal regulatory networks. Plant genomes contain more TFs than animal genomes, but plant proteins are smaller and have less domains as animal proteins which are often multifunctional. We briefly summarize mutant analysis and co-expression results pinpointing some TFs regulating starch enzymes in plants. Detailed information is provided about biochemical reactions, TFs and cis regulatory motifs involved in sucrose-starch metabolism, in both source and sink tissues. Examples about coordinated responses to hormones and environmental cues in different tissues and species are listed. Further advancements require combined data from single-cell transcriptomic and metabolomic approaches. Cell fractionation and subcellular inspection may provide valuable insights. We propose that shuffling of promoter elements might be a promising strategy to improve in the near future starch content, crop yield or food quality.
The recent release of the maize genome (AGPv4) contains annotation errors of invertase genes and therefore the enzymes are bestly curated manually at the protein level in a comprehensible fashion The synthesis, transport and degradation of sucrose are determining factors for biomass allocation and yield of crop plants. Invertase (INV) is a key enzyme of carbon metabolism in both source and sink tissues. Current releases of the maize genome correctly annotates only two vacuolar invertases (ivr1 and ivr2) and four cell wall invertases (incw1, incw2 (mn1), incw3, and incw4). Our comprehensive survey identified 21 INV isogenes for which we propose a standard nomenclature grouped phylogenetically by amino acid similarity: three vacuolar (INVVR), eight cell wall (INVCW), and ten alkaline/neutral (INVAN) isogenes which form separate dendogram branches due to distinct molecular features. The acidic enzymes were curated for the presence of the DPN tripeptide which is coded by one of the smallest exons reported in plants. Particular attention was placed on the molecular role of INV in vascular tissues such as the nodes, internodes, leaf sheath, husk leaves and roots. We report the expression profile of most members of the maize INV family in nine tissues in two developmental stages, R1 and R3. INVCW7, INVVR2, INVAN8, INVAN9, INVAN10, and INVAN3 displayed the highest absolute expressions in most tissues. INVVR3, INVCW5, INVCW8, and INVAN1 showed low mRNA levels. Expressions of most INVs were repressed from stage R1 to R3, except for INVCW7 which increased significantly in all tissues after flowering. The mRNA levels of INVCW7 in the vegetative stem correlated with a higher transport rate of assimilates from leaves to the cob which led to starch accumulation and growth of the female reproductive organs.
In comparison to the exponential increase of genotyping methods, phenotyping strategies are lagging behind in agricultural sciences. Genetic improvement depends upon the abundance of quantitative phenotypic data and the statistical partitioning of variance into environmental, genetic, and random effects. A metabolic phenotyping strategy was adapted to increase sample throughput while saving reagents, reducing cost, and simplifying data analysis. The chemical profiles of stem extracts from maize plants grown under low nitrogen (LN) or control trial (CT) were analyzed using optimized protocols for direct-injection electrospray ionization mass spectrometry (DIESI-MS). Specific ions significantly decreased or increased because of environmental (LN versus CT) or genotypic effects. Biochemical profiling with DIESI-MS had a superior cost-benefit compared to other standard analytical technologies (e.g., ultraviolet, near-infrared reflectance spectroscopy, high-performance liquid chromatography, and gas chromatography with flame ionization detection) routinely used for plant breeding. The method can be successfully applied in maize, strawberry, coffee, and other crop species.
Phosphoglycerate kinase (PGK, E.C. 2.7.2.3) interconverts ADP + 1,3-bisphospho-glycerate (1,3-bPGA) to ATP + 3-phosphoglycerate (3PGA). While most bacteria have a single pgk gene and mammals possess two copies, plant genomes contain three or more PGK genes. In this study, we identified five Pgk genes in the Zea mays var. B73 genome, predicted to encode proteins targeted to different subcellular compartments: ZmPgk1, ZmPgk2, and ZmPgk4 (chloroplast), ZmPgk3 (cytosol), and ZmPgk5 (nucleus). The expression of ZmPgk3 was highest in non-photosynthetic tissues (roots and cobs), where PGK activity was also greatest, consistent with a function in glycolysis. Green tissues (leaf blade and husk leaf) showed intermediate levels of PGK activity, and predominantly expressed ZmPgk1 and ZmPgk2, suggesting involvement in photosynthetic metabolism. ZmPgk5 was weakly expressed and ZmPgk4 was not detected in any tissue. Phylogenetic analysis showed that the photosynthetic and glycolytic isozymes of plants clustered together, but were distinct from PGKs of animals, fungi, protozoa, and bacteria, indicating that photosynthetic and glycolytic isozymes of plants diversified after the divergence of the plant lineage from other groups. These results show the distinct role of each PGK in maize and provide the basis for future studies into the regulation and function of this key enzyme.
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