Exploiting the Genetic Diversity of Maize Using a Combined Metabolomic, Enzyme Activity Profiling, and Metabolic Modeling Approach to Link Leaf Physiology to Kernel Yield

Metabolite-based genome-wide association studies enable the dissection of the genetic bases of flavonoids, betaine and spermidine in wolfberry (Lycium)

Wolfberry is a plant with medicinal and food values. However, its bioactive ingredients and the corresponding genetic bases have not been determined. Here, we de novo generated a chromosome-level genome assembly for wolfberry, yielding a genome sequence of ~1.77 Gb with contig N50 of 50.55 Mb and 39 224 predicted gene models. A variation map, using 307 re-sequenced accessions, was called based on this genome assembly. Furthermore, the fruit metabolome of these accessions was profiled using 563 annotated metabolites, which separated Lycium barbarum L. and non-L. barbarum L. The flavonoids, coumarins, alkaloids and nicotinic acid contents were higher in the former than in the latter. A metabolite-based genome-wide association study mapped 156 164 significant single nucleotide polymorphisms corresponding to 340 metabolites. This included 19 219 unique lead single nucleotide polymorphisms in 1517 significant association loci, of which three metabolites, flavonoids, betaine and spermidine, were highlighted. Two candidate genes, LbUGT (evm.TU.chr07.2692) and LbCHS (evm.TU.chr07.2738), with non-synonymous mutations, were associated with the flavonoids content. LbCHS is a structural gene that interacts with a nearby MYB transcription factor (evm.TU.chr07.2726) both in L. barbarum and L. ruthenicum. Thus, these three genes might be involved in the biosynthesis/metabolism of flavonoids. LbSSADH (evm.TU.chr09.627) was identified as possibly participating in betaine biosynthesis/metabolism. Four lycibarbarspermidines (E-G and O) were identified, and only the lycibarbarspermidines O content was higher in L. barbarum varieties than in non-L. barbarum varieties. The evm.TU.chr07.2680 gene associated with lycibarbarspermidines O was annotated as an acetyl-CoA-benzylalcohol acetyltransferase, suggesting that it is a candidate gene for spermidine biosynthesis. These results provide novel insights into the specific metabolite profile of non-L. barbarum L. and the genetic bases of flavonoids, betaine and spermidine biosynthesis/metabolism.

Mining genic resources regulating nitrogen-use efficiency based on integrative biological analyses and their breeding applications in maize and other crops

Nitrogen (N) is an essential factor for limiting crop yields, and cultivation of crops with low nitrogen-use efficiency (NUE) exhibits increasing environmental and ecological risks. Hence, it is crucial to mine valuable NUE improvement genes, which is very important to develop and breed new crop varieties with high NUE in sustainable agriculture system. Quantitative trait locus (QTL) and genome-wide association study (GWAS) analysis are the most common methods for dissecting genetic variations underlying complex traits. In addition, with the advancement of biotechnology, multi-omics technologies can be used to accelerate the process of exploring genetic variations. In this study, we integrate the substantial data of QTLs, quantitative trait nucleotides (QTNs) from GWAS, and multi-omics data including transcriptome, proteome, and metabolome and further analyze their interactions to predict some NUE-related candidate genes. We also provide the genic resources for NUE improvement among maize, rice, wheat, and sorghum by homologous alignment and collinearity analysis. Furthermore, we propose to utilize the knowledge gained from classical cases to provide the frameworks for improving NUE and breeding N-efficient varieties through integrated genomics, systems biology, and modern breeding technologies.

Proteomic Analysis Revealed the Antagonistic Effect of Decapitation and Strigolactones on the Tillering Control in Rice

Removing the panicle encourages the growth of buds on the elongated node by getting rid of apical dominance. Strigolactones (SLs) are plant hormones that suppress tillering in rice. The present study employed panicle removal (RP) and external application of synthesized strigolactones (GR) to modulate rice bud growth at node 2. We focused on the full-heading stage to investigate proteomic changes related to bud germination (RP-Co) and suppression (GR-RP). A total of 434 represented differentially abundant proteins (DAPs) were detected, with 272 DAPs explicitly specified in the bud germination process, 106 in the bud suppression process, and 28 in both. DAPs in the germination process were most associated with protein processing in the endoplasmic reticulum and ribosome biogenesis. DAPs were most associated with metabolic pathways and glycolysis/gluconeogenesis in the bud suppression process. Sucrose content and two enzymes of sucrose degradation in buds were also determined. Comparisons of DAPs between the two reversed processes revealed that sucrose metabolism might be a key to modulating rice bud growth. Moreover, sucrose or its metabolites should be a signal downstream of the SLs signal transduction that modulates rice bud outgrowth. Contemplating the result so far, it is possible to open new vistas of research to reveal the interaction between SLs and sucrose signaling in the control of tillering in rice.

Benzotriazole Ultraviolet Stabilizers (BUVSs) as Potential Protein Kinase Antagonists in Rice

The ubiquitous occurrence of benzotriazole ultraviolet stabilizers (BUVSs) in the environment and organisms has warned of their potential ecological and health risks. Studies showed that some BUVSs exerted immune and chronic toxicities to animals by disturbing signaling transduction, yet limited research has investigated the toxic effects on crop plants and the underlying mechanisms of signaling regulation. Herein, a laboratory-controlled hydroponic experiment was conducted on rice to explore the phytotoxicity of BUVSs by integrating conventional biochemical experiments, transcriptomic analysis, competitive sorption assays, and computational studies. The results showed that BUVSs inhibited the growth of rice by 6.30-20.4% by excessively opening the leaf stomas, resulting in increased transpiration. BUVSs interrupted the transduction of abscisic acid (ABA) signal through competitively binding to Ca2+-dependent protein kinase (CDPK), weakening the CDPK phosphorylation and further inhibiting the downstream signaling. As structural analogues of ATP, BUVSs acted as potential ABA signaling antagonists, leading to physiological dysfunction in mediating stomatal closure under stresses. This is the first comprehensive study elucidating the effects of BUVSs on the function of key proteins and the associated signaling transduction in plants and providing insightful information for the risk evaluation and control of BUVSs.

The Key Role of Glutamate Dehydrogenase 2 (GDH2) in the Control of Kernel Production in Maize (Zea mays L.)

The agronomic potential of glutamate dehydrogenase 2 (GDH2) in maize kernel production was investigated by examining the impact of a mutation on the corresponding gene. Mu-insertion homozygous and heterozygous mutant lines lacking GDH2 activity were isolated and characterized at the biochemical, physiological and agronomic levels. In comparison to the wild type and to the homozygous ghd2 mutants, the heterozygous gdh2 mutant plants were characterized by a decrease in the root amino acid content, whereas in the leaves an increase of a number of phenolic compounds was observed. On average, a 30 to 40% increase in kernel yield was obtained only in the heterozygous gdh2 mutant lines when plants were grown in the field over two years. The importance of GDH2 in the control of plant productivity is discussed in relation to the physiological impact of the mutation on amino acid content, with primary carbon metabolism mostly occurring in the roots and secondary metabolism occurring in the leaves.

Carbohydrate metabolism enzymes and phenotypic characterization of diverse lines of the climate-resilient food, feed, and bioenergy crop Camelina sativa

Climate change poses tremendous pressure on agriculture. Camelina sativa is an ancient, low-input, high-quality oilseed crop for food, feed and industrial applications that has retained its natural stress tolerance. Its climate resilience, adaptability to different growth conditions, and the qualities of its seed oil and cake have spurred the interest in camelina. However, due to a period of neglect it has not yet undergone intensive breeding and knowledge about this multi-purpose crop is still limited. Metabolism is strongly associated with plant growth and development and little information is available on camelina primary carbohydrate metabolism. Here, eight camelina lines from different geographic and climatic regions were characterized for important growth parameters and agricultural traits. Furthermore, the activities of key enzymes of the carbohydrate metabolism were analysed in leaves, seedpods, capsules, and developing seeds. The lines differed in shoot and leaf morphology, plant height, biomass formation as well as in seed yield and seed oil and protein content. Key carbohydrate metabolism enzymes showed specific activity signatures in leaves and reproductive organs during seed development, and different lines exhibited distinct enzyme activity patterns, providing a valuable basis for developing new physiological markers for camelina breeding programs.

Genome-Wide Identification and Analysis of the Maize Serine Peptidase S8 Family Genes in Response to Drought at Seedling Stage

Subtilisin-like proteases (subtilases) are found in almost all plant species and are involved in regulating various biotic and abiotic stresses. Although the literature on subtilases in different plant species is vast, the gene function of the serine peptidase S8 family and its maize subfamily is still unknown. Here, a bioinformatics analysis of this gene family was conducted by describing gene structure, conserved motifs, phylogenetic relationships, chromosomal distributions, gene duplications, and promoter cis-elements. In total, we identified 18 ZmSPS8 genes in maize, distributed on 7 chromosomes, and half of them were hydrophilic. Most of these proteins were located at the cell wall and had similar secondary and tertiary structures. Prediction of cis-regulatory elements in promoters illustrated that they were mainly associated with hormones and abiotic stress. Maize inbred lines B73, Zheng58, and Qi319 were used to analyze the spatial-temporal expression patterns of ZmSPS8 genes under drought treatment. Seedling drought results showed that Qi319 had the highest percent survival after 14 d of withholding irrigation, while B73 was the lowest. Leaf relative water content (LRWC) declined more rapidly in B73 and to lower values, and the nitrotetrazolium blue chloride (NBT) contents of leaves were higher in Qi319 than in the other inbreds. The qPCR results indicated that 6 serine peptidase S8 family genes were positively or negatively correlated with plant tolerance to drought stress. Our study provides a detailed analysis of the ZmSPS8s in the maize genome and finds a link between drought tolerance and the family gene expression, which was established by using different maize inbred lines.

15N-labelling of Leaves Combined with GC-MS Analysis as a Tool for Monitoring the Dynamics of Nitrogen Incorporation into Amino Acids

Labeling plant material such as detached leaves with ¹⁵NH₄⁺ is a very instrumental method for the characterization of metabolic pathways of mineral nitrogen assimilation and incorporation into amino acids. A procedure of labeling, followed by amino acid extraction, purification, and derivatization for gas chromatography coupled to mass spectrometry (GC/MS) analysis, is presented. The rationale of heavy isotope abundance calculations and amino acid quantification is detailed. This method is adaptable to various plant species and various kinds of investigations, such as elucidating physiological changes occurring as a result of gene mutations (overexpression or inhibition) in natural variants or genetically modified crops, or characterization of metabolic fluxes in genotypes exhibiting contrasted physiological or developmental adaptive responses to biotic and/or abiotic environmental stresses. Furthermore, the benefit of working on detached organs or pieces of organs is to investigate finely the metabolism of species that are not amenable to laboratory work, such as plants growing in natural environments or under agricultural conditions in the field.

Analysis of metabolic differences in maize in different growth stages under nitrogen stress based on UPLC-QTOF-MS

Introduction

Maize has a high demand for nitrogen during the growth period. The study of metabolic changes in maize can provide a theoretical basis for rational nitrogen nutrition regulation.

Methods

In order to investigate the changes of different metabolites and their metabolic pathways in maize leaves under nitrogen stress, we used ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) for metabolomic analysis of maize leaves under different nitrogen treatments at three critical growth stages (V4, V12 and R1) in a pot experiment under natural conditions.

Results and discussion

The results showed that nitrogen stress significantly affected sugar metabolism and nitrogen metabolism, and affected carbon and nitrogen balance, and the effects of stress on maize leaves metabolism increased with the growth process. Metabolic pathways such as the TCA cycle and starch and sucrose metabolism were mainly affected at the seeding stage (V4). The stress response to nitrogen deficiency also showed significant upregulation of flavonoids such as luteolin and astragalin during the booting stage (V12) and anthesis-silking stage (R1). During R1 stage, the synthesis of tryptophan and phenylalanine and the degradation of lysine were significantly affected. Compared with nitrogen stress, the metabolic synthesis of key amino acids and jasmonic acid were intensified and the TCA cycle was promoted under nitrogen sufficiency conditions. This study initially revealed that the response mechanism of maize to nitrogen stress at the metabolic level.

Variation of vitamin B contents in maize inbred lines: Potential genetic resources for biofortification

Vitamin B and its derivatives possess diverse physiological functions and are essential micronutrients for humans. Their variation in crops is important for the identification of genetic resources used to develop new varieties with enhanced vitamin B. In this research, remarkable variations were observed in kernels of 156 maize inbred lines, ranging from 107.61 to 2654.54 μg per 100 g for vitamin B1, 1.19–37.37 μg per 100 g for B2, 19.60–213.75 μg per 100 g for B3, 43.47–590.86 μg per 100 g for B5, and 138.59–1065.11 μg per 100 g for B6. Growing inbreeds in Hainan and Hebei provinces of China revealed environmental and genotype interactions among these vitamins and the correlations between them in maize grain. Several inbred lines were identified as good sources of vitamin B and promising germplasms for maize breeding, namely By855 and Si273 are overall rich in all the studied vitamins, and GY386B and CML118 are specially enriched with derivatives of vitamin B6. The present study can assist maize breeders with germplasm resources of vitamin B for biofortification to offer people nutritious foods.

Enzyme activity profiling for physiological phenotyping within functional phenomics: plant growth and stress responses

High-throughput profiling of key enzyme activities of carbon, nitrogen, and antioxidant metabolism is emerging as a valuable approach to integrate cell physiological phenotyping into a holistic functional phenomics approach. However, the analyses of the large datasets generated by this method represent a bottleneck, often keeping researchers from exploiting the full potential of their studies. We address these limitations through the exemplary application of a set of data evaluation and visualization tools within a case study. This includes the introduction of multivariate statistical analyses that can easily be implemented in similar studies, allowing researchers to extract more valuable information to identify enzymatic biosignatures. Through a literature meta-analysis, we demonstrate how enzyme activity profiling has already provided functional information on the mechanisms regulating plant development and response mechanisms to abiotic stress and pathogen attack. The high robustness of the distinct enzymatic biosignatures observed during developmental processes and under stress conditions underpins the enormous potential of enzyme activity profiling for future applications in both basic and applied research. Enzyme activity profiling will complement molecular -omics approaches to contribute to the mechanistic understanding required to narrow the genotype-to-phenotype knowledge gap and to identify predictive biomarkers for plant breeding to develop climate-resilient crops.

Estimation of amino acid contents in maize leaves based on hyperspectral imaging

Estimation of the amino acid content in maize leaves is helpful for improving maize yield estimation and nitrogen use efficiency. Hyperspectral imaging can be used to obtain the physiological and biochemical parameters of maize leaves with the advantages of being rapid, non-destructive, and high throughput. This study aims to estimate the multiple amino acid contents in maize leaves using hyperspectral imaging data. Two nitrogen (N) fertilizer experiments were carried out to obtain the hyperspectral images of fresh maize leaves. The partial least squares regression (PLSR) method was used to build the estimation models of various amino acid contents by using the reflectance of all bands, sensitive band range, and sensitive bands. The models were then validated with the independent dataset. The results showed that (1) the spectral reflectance of most amino acids was more sensitive in the range of 400-717.08 nm than other bands. The estimation accuracy was better by using the reflectance of the sensitive band range than that of all bands; (2) the sensitive bands of most amino acids were in the ranges of 505.39-605 nm and 651-714 nm; and (3) among the 24 amino acids, the estimation models of the β-aminobutyric acid, ornithine, citrulline, methionine, and histidine achieved higher accuracy than those of other amino acids, with the R ², relative root mean square error (RE), and relative percent deviation (RPD) of the measured and estimated value of testing samples in the range of 0.84-0.96, 8.79%-19.77%, and 2.58-5.18, respectively. This study can provide a non-destructive and rapid diagnostic method for genetic sensitive analysis and variety improvement of maize.

Crop genetic diversity uncovers metabolites, elements, and gene networks predicted to be associated with high plant biomass yields in maize

Rapid population growth and increasing demand for food, feed, and bioenergy in these times of unprecedented climate change require breeding for increased biomass production on the world's croplands. To accelerate breeding programs, knowledge of the relationship between biomass features and underlying gene networks is needed to guide future breeding efforts. To this end, large-scale multiomics datasets were created with genetically diverse maize lines, all grown in long-term organic and conventional cropping systems. Analysis of the datasets, integrated using regression modeling and network analysis revealed key metabolites, elements, gene transcripts, and gene networks, whose contents during vegetative growth substantially influence the build-up of plant biomass in the reproductive phase. We found that S and P content in the source leaf and P content in the root during the vegetative stage contributed the most to predicting plant performance at the reproductive stage. In agreement with the Gene Ontology enrichment analysis, the cis-motifs and identified transcription factors associated with upregulated genes under phosphate deficiency showed great diversity in the molecular response to phosphate deficiency in selected lines. Furthermore, our data demonstrate that genotype-dependent uptake, assimilation, and allocation of essential nutrient elements (especially C and N) during vegetative growth under phosphate starvation plays an important role in determining plant biomass by controlling root traits related to nutrient uptake. These integrative multiomics results revealed key factors underlying maize productivity and open new opportunities for efficient, rapid, and cost-effective plant breeding to increase biomass yield of the cereal crop maize under adverse environmental factors.

Antagonistic Effect of Sucrose Availability and Auxin on Rosa Axillary Bud Metabolism and Signaling, Based on the Transcriptomics and Metabolomics Analysis

Shoot branching is crucial for successful plant development and plant response to environmental factors. Extensive investigations have revealed the involvement of an intricate regulatory network including hormones and sugars. Recent studies have demonstrated that two major systemic regulators-auxin and sugar-antagonistically regulate plant branching. However, little is known regarding the molecular mechanisms involved in this crosstalk. We carried out two complementary untargeted approaches-RNA-seq and metabolomics-on explant stem buds fed with different concentrations of auxin and sucrose resulting in dormant and non-dormant buds. Buds responded to the combined effect of auxin and sugar by massive reprogramming of the transcriptome and metabolome. The antagonistic effect of sucrose and auxin targeted several important physiological processes, including sink strength, the amino acid metabolism, the sulfate metabolism, ribosome biogenesis, the nucleic acid metabolism, and phytohormone signaling. Further experiments revealed a role of the TOR-kinase signaling pathway in bud outgrowth through at least downregulation of Rosa hybrida BRANCHED1 (RhBRC1). These new findings represent a cornerstone to further investigate the diverse molecular mechanisms that drive the integration of endogenous factors during shoot branching.

Impacts of environmental conditions, and allelic variation of cytosolic glutamine synthetase on maize hybrid kernel production

Cytosolic glutamine synthetase (GS1) is the enzyme mainly responsible of ammonium assimilation and reassimilation in maize leaves. The agronomic potential of GS1 in maize kernel production was investigated by examining the impact of an overexpression of the enzyme in the leaf cells. Transgenic hybrids exhibiting a three-fold increase in leaf GS activity were produced and characterized using plants grown in the field. Several independent hybrids overexpressing Gln1-3, a gene encoding cytosolic (GS1), in the leaf and bundle sheath mesophyll cells were grown over five years in different locations. On average, a 3.8% increase in kernel yield was obtained in the transgenic hybrids compared to controls. However, we observed that such an increase was simultaneously dependent upon both the environmental conditions and the transgenic event for a given field trial. Although variable from one environment to another, significant associations were also found between two GS1 genes (Gln1-3 and Gln1-4) polymorphic regions and kernel yield in different locations. We propose that the GS1 enzyme is a potential lead for producing high yielding maize hybrids using either genetic engineering or marker-assisted selection. However, for these hybrids, yield increases will be largely dependent upon the environmental conditions used to grow the plants.

Amiour et al. use a multi-year field trial evaluation and association mapping to determine if increased enzyme activity and native allelic variations at the GS1 loci in maize contribute to differences in grain yield. Overexpression of GS1 and polymorphisms in the corresponding loci were associated with kernel yield, indicating that GS1 expression can directly control kernel production and that GS1 has a potential lead in the production of high yielding maize hybrids depending on environmental conditions.

Mining plant metabolomes: Methods, applications, and perspectives

Plants produce a variety of metabolites that are essential for plant growth and human health. To fully understand the diversity of metabolites in certain plants, lots of methods have been developed for metabolites detection and data processing. In the data-processing procedure, how to effectively reduce false-positive peaks, analyze large-scale metabolic data, and annotate plant metabolites remains challenging. In this review, we introduce and discuss some prominent methods that could be exploited to solve these problems, including a five-step filtering method for reducing false-positive signals in LC-MS analysis, QPMASS for analyzing ultra-large GC-MS data, and MetDNA for annotating metabolites. The main applications of plant metabolomics in species discrimination, metabolic pathway dissection, population genetic studies, and some other aspects are also highlighted. To further promote the development of plant metabolomics, more effective and integrated methods/platforms for metabolite detection and comprehensive databases for metabolite identification are highly needed. With the improvement of these technologies and the development of genomics and transcriptomics, plant metabolomics will be widely used in many fields.

The utility of metabolomics as a tool to inform maize biology

With the rise of high-throughput omics tools and the importance of maize and its products as food and bioethanol, maize metabolism has been extensively explored. Modern maize is still rich in genetic and phenotypic variation, yielding a wide range of structurally and functionally diverse metabolites. The maize metabolome is also incredibly dynamic in terms of topology and subcellular compartmentalization. In this review, we examine a broad range of studies that cover recent developments in maize metabolism. Particular attention is given to current methodologies and to the use of metabolomics as a tool to define biosynthetic pathways and address biological questions. We also touch upon the use of metabolomics to understand maize natural variation and evolution, with a special focus on research that has used metabolite-based genome-wide association studies (mGWASs).

Characterization of effects of genetic variants via genome-scale metabolic modelling

Genome-scale metabolic networks for model plants and crops in combination with approaches from the constraint-based modelling framework have been used to predict metabolic traits and design metabolic engineering strategies for their manipulation. With the advances in technologies to generate large-scale genotyping data from natural diversity panels and other populations, genome-wide association and genomic selection have emerged as statistical approaches to determine genetic variants associated with and predictive of traits. Here, we review recent advances in constraint-based approaches that integrate genetic variants in genome-scale metabolic models to characterize their effects on reaction fluxes. Since some of these approaches have been applied in organisms other than plants, we provide a critical assessment of their applicability particularly in crops. In addition, we further dissect the inferred effects of genetic variants with respect to reaction rate constants, abundances of enzymes, and concentrations of metabolites, as main determinants of reaction fluxes and relate them with their combined effects on complex traits, like growth. Through this systematic review, we also provide a roadmap for future research to increase the predictive power of statistical approaches by coupling them with mechanistic models of metabolism.

Maize metabolome and proteome responses to controlled cold stress partly mimic early-sowing effects in the field and differ from those of Arabidopsis

In Northern Europe, sowing maize one-month earlier than current agricultural practices may lead to moderate chilling damage. However, studies of the metabolic responses to low, non-freezing, temperatures remain scarce. Here, genetically-diverse maize hybrids (Zea mays, dent inbred lines crossed with a flint inbred line) were cultivated in a growth chamber at optimal temperature and then three decreasing temperatures for 2 days each, as well as in the field. Leaf metabolomic and proteomic profiles were determined. In the growth chamber, 50% of metabolites and 18% of proteins changed between 20 and 16°C. These maize responses, partly differing from those of Arabidopsis to short-term chilling, were mapped on genome-wide metabolic maps. Several metabolites and proteins showed similar variation for all temperature decreases: seven MS-based metabolite signatures and two proteins involved in photosynthesis decreased continuously. Several increasing metabolites or proteins in the growth-chamber chilling conditions showed similar trends in the early-sowing field experiment, including trans-aconitate, three hydroxycinnamate derivatives, a benzoxazinoid, a sucrose synthase, lethal leaf-spot 1 protein, an allene oxide synthase, several glutathione transferases and peroxidases. Hybrid groups based on field biomass were used to search for the metabolite or protein responses differentiating them in growth-chamber conditions, which could be of interest for breeding.

Outgrowth of the axillary bud in rose is controlled by sugar metabolism and signalling

Shoot branching is a pivotal process during plant growth and development, and is antagonistically orchestrated by auxin and sugars. In contrast to extensive investigations on hormonal regulatory networks, our current knowledge on the role of sugar signalling pathways in bud outgrowth is scarce. Based on a comprehensive stepwise strategy, we investigated the role of glycolysis/the tricarboxylic acid (TCA) cycle and the oxidative pentose phosphate pathway (OPPP) in the control of bud outgrowth. We demonstrated that these pathways are necessary for bud outgrowth promotion upon plant decapitation and in response to sugar availability. They are also targets of the antagonistic crosstalk between auxin and sugar availability. The two pathways act synergistically to down-regulate the expression of BRC1, a conserved inhibitor of shoot branching. Using Rosa calluses stably transformed with GFP-fused promoter sequences of RhBRC1 (pRhBRC1), glycolysis/TCA cycle and the OPPP were found to repress the transcriptional activity of pRhBRC1 cooperatively. Glycolysis/TCA cycle- and OPPP-dependent regulations involve the -1973/-1611 bp and -1206/-709 bp regions of pRhBRC1, respectively. Our findings indicate that glycolysis/TCA cycle and the OPPP are integrative parts of shoot branching control and can link endogenous factors to the developmental programme of bud outgrowth, likely through two distinct mechanisms.

Age-dependent increase in α-tocopherol and phytosterols in maize leaves exposed to elevated ozone pollution

Tropospheric ozone is a major air pollutant that significantly damages crop production. Crop metabolic responses to rising chronic ozone stress have not been well studied in the field, especially in C4 crops. In this study, we investigated the metabolomic profile of leaves from two diverse maize (Zea mays) inbred lines and the hybrid cross during exposure to season-long elevated ozone (~100 nl L-1) in the field using free air concentration enrichment (FACE) to identify key biochemical responses of maize to elevated ozone. Senescence, measured by loss of chlorophyll content, was accelerated in the hybrid line, B73 × Mo17, but not in either inbred line (B73 or Mo17). Untargeted metabolomic profiling further revealed that inbred and hybrid lines of maize differed in metabolic responses to ozone. A significant difference in the metabolite profile of hybrid leaves exposed to elevated ozone occurred as leaves aged, but no age-dependent difference in leaf metabolite profiles between ozone conditions was measured in the inbred lines. Phytosterols and α-tocopherol levels increased in B73 × Mo17 leaves as they aged, and to a significantly greater degree in elevated ozone stress. These metabolites are involved in membrane stabilization and chloroplast reactive oxygen species (ROS) quenching. The hybrid line also showed significant yield loss at elevated ozone, which the inbred lines did not. This suggests that the hybrid maize line was more sensitive to ozone exposure than the inbred lines, and up-regulated metabolic pathways to stabilize membranes and quench ROS in response to chronic ozone stress.

Early-stage sugar beet taproot development is characterized by three distinct physiological phases

Despite the agronomic importance of sugar beet (Beta vulgaris L.), the early-stage development of its taproot has only been poorly investigated. Thus, the mechanisms that determine growth and sugar accumulation in sugar beet are largely unknown. In the presented study, a physiological characterization of early-stage sugar beet taproot development was conducted. Activities were analyzed for fourteen key enzymes of carbohydrate metabolism in developing taproots over the first 80 days after sowing. In addition, we performed in situ localizations of selected carbohydrate-metabolic enzyme activities, anatomical investigations, and quantifications of soluble carbohydrates, hexose phosphates, and phytohormones. Based on the accumulation dynamics of biomass and sucrose, as well as on anatomical parameters, the early phase of taproot development could be subdivided into three stages-prestorage, transition, secondary growth and sucrose accumulation stage-each of which was characterized by distinct metabolic and phytohormonal signatures. The enzyme activity signatures corresponding to these stages were also shown to be robustly reproducible in experiments conducted in two additional locations. The results from this physiological phenotyping approach contribute to the identification of the key regulators of sugar beet taproot development and open up new perspectives for sugar beet crop improvement concerning both physiological marker-based breeding and biotechnological approaches.

Modeling Plant Metabolism: From Network Reconstruction to Mechanistic Models

Mathematical modeling of plant metabolism enables the plant science community to understand the organization of plant metabolism, obtain quantitative insights into metabolic functions, and derive engineering strategies for manipulation of metabolism. Among the various modeling approaches, metabolic pathway analysis can dissect the basic functional modes of subsections of core metabolism, such as photorespiration, and reveal how classical definitions of metabolic pathways have overlapping functionality. In the many studies using constraint-based modeling in plants, numerous computational tools are currently available to analyze large-scale and genome-scale metabolic networks. For ¹³C-metabolic flux analysis, principles of isotopic steady state have been used to study heterotrophic plant tissues, while nonstationary isotope labeling approaches are amenable to the study of photoautotrophic and secondary metabolism. Enzyme kinetic models explore pathways in mechanistic detail, and we discuss different approaches to determine or estimate kinetic parameters. In this review, we describe recent advances and challenges in modeling plant metabolism.

Simple semi-high throughput determination of activity signatures of key antioxidant enzymes for physiological phenotyping

BACKGROUND

Reactive oxygen species (ROS) such as hydrogen peroxide and superoxide anions significantly accumulate during biotic and abiotic stress and cause oxidative damage and eventually cell death. There is accumulating evidence that ROS are also involved in regulating beneficial plant-microbe interactions, signal transduction and plant growth and development. Due to the relevance of ROS throughout the life cycle and for interaction with the multifactorial environment, the physiological phenotyping of the mechanisms controlling ROS homeostasis is of general importance.

RESULTS

In this study, we have developed a robust and resource-efficient experimental platform that allows the determination of the activities of the nine key ROS scavenging enzymes from a single extraction that integrates posttranscriptional and posttranslational regulations. The assays were optimized and adapted for a semi-high throughput 96-well assay format. In a case study, we have analyzed tobacco leaves challenged by pathogen infection, drought and salt stress. The three stress factors resulted in distinct activity signatures with differential temporal dynamics.

CONCLUSIONS

This experimental platform proved to be suitable to determine the antioxidant enzyme activity signature in different tissues of monocotyledonous and dicotyledonous model and crop plants. The universal enzymatic extraction procedure combined with the 96-well assay format demonstrated to be a simple, fast and semi-high throughput experimental platform for the precise and robust fingerprinting of nine key antioxidant enzymatic activities in plants.

Uncovering hidden genetic variation in photosynthesis of field-grown maize under ozone pollution

Ozone is the most damaging air pollutant to crops, currently reducing Midwest US maize production by up to 10%, yet there has been very little effort to adapt germplasm for ozone tolerance. Ozone enters plants through stomata, reacts to form reactive oxygen species in the apoplast and ultimately decreases photosynthetic C gain. In this study, 10 diverse inbred parents were crossed in a half-diallel design to create 45 F1 hybrids, which were tested for ozone response in the field using free air concentration enrichment (FACE). Ozone stress increased the heritability of photosynthetic traits and altered genetic correlations among traits. Hybrids from parents Hp301 and NC338 showed greater sensitivity to ozone stress, and disrupted relationships among photosynthetic traits. The physiological responses underlying sensitivity to ozone differed in hybrids from the two parents, suggesting multiple mechanisms of response to oxidative stress. FACE technology was essential to this evaluation because genetic variation in photosynthesis under elevated ozone was not predictable based on performance at ambient ozone. These findings suggest that selection under elevated ozone is needed to identify deleterious alleles in the world's largest commodity crop.

Transcription factors involved in the regulatory networks governing the Calvin-Benson-Bassham cycle

Transcription factors (TFs) play crucial roles in the regulation of photosynthesis; elucidating these roles will facilitate our understanding of photosynthesis and thus accelerate its improvement for enhancing crop yield. Promoter analysis of 52 nuclear-encoded Populus tomentosa Carr. genes involved in the Calvin-Benson-Bassham (CBB) cycle revealed 706 motifs and 326 potentially interacting TFs. A backward elimination random forest (BWERF) algorithm reduced the number of TFs to 40, involved in a three-layer gene regulatory network (GRN) including 46 photosynthesis genes (bottom layer), 25 TFs (second layer) and 15 TFs (top layer). Phenotype-genotype association identified 248 single-nucleotide polymorphisms (SNPs) within 72 genes associated with 11 photosynthesis traits. Of the regulatory pairs identified by the BWERF (202 pairs), 77 TF-target combinations harbored SNPs associated with the same trait, supporting similar mechanisms of phenotype modulation. We used expression quantitative trait nucleotide (eQTN) analysis to identify causal SNPs affecting gene expression, identifying 1851 eQTN signals for 50 eGenes (genes whose expressions are regulated by eQTNs). Distribution patterns identified 14 eQTNs from seven TFs associated with eight expression levels of their downstream targets (defined in the GRN), whereas seven TF-target pairs were also identified by phenotype-genotype associations. To further validate the roles of TFs at the metabolic level, we selected 6764 SNPs from 55 genes (identified by GRN-association or GRN-eQTN pairs or both) for metabolic association, identifying variants within 10 TFs affecting metabolic processes underlying the CBB cycle. Our study provides new insights into the photosynthesis pathway in poplar and may facilitate understanding of processes underlying photosynthesis improvement.

Large-scale metabolite quantitative trait locus analysis provides new insights for high-quality maize improvement

It is generally recognized that many favorable genes which were lost during domestication, including those related to both nutritional value and stress resistance, remain hidden in wild relatives. To uncover such genes in teosinte, an ancestor of maize, we conducted metabolite profiling in a BC₂ F₇ population generated from a cross between the maize wild relative (Zea mays ssp. mexicana) and maize inbred line Mo17. In total, 65 primary metabolites were quantified in four tissues (seedling-stage leaf, grouting-stage leaf, young kernel and mature kernel) with clear tissue-specific patterns emerging. Three hundred and fifty quantitative trait loci (QTLs) for these metabolites were obtained, which were distributed unevenly across the genome and included two QTL hotspots. Metabolite concentrations frequently increased in the presence of alleles from the teosinte genome while the opposite was observed for grain yield and shape trait QTLs. Combination of the multi-tissue transcriptome and metabolome data provided considerable insight into the metabolic variations between maize and its wild relatives. This study thus identifies favorable genes hidden in the wild relative which should allow us to balance high yield and quality in future modern crop breeding programs.

Understanding plant nitrogen nutrition through a laboratory experiment

Plant nitrogen nutrition is an essential topic in biology that should be included in scientific education. Nitrogen availability is one of the primary limiting factors for plant growth, and these organisms are the primary support for the pluricellular terrestrial life, since they are the fundamental group of autotrophs. For this reason, the use of nitrogen fertilizers is in the basis of the Green Revolution that led to an extraordinary increase in the food production during the twentieth century. To illustrate the importance of plant nitrogen nutrition, a new laboratory experience for students is presented in this manuscript. The aim of the following laboratory teaching activity is training of students through the evaluation of metabolic, biochemical, and molecular markers that are related to the nitrogen nutritional status of plants. For this purpose, cherry tomato plants (Solanum lycopersicum var. cerasiforme) were used, since they exhibit rapid growth and good differential biomass accumulation in response to changes in the nitrogen supply. The proposed laboratory experiment enables the development of the entire protocol for postgraduate students or in a reduced version for students from lower educational levels. © 2019 International Union of Biochemistry and Molecular Biology, 47(4):450-458, 2019.

Crop Biodiversity: An Unfinished Magnum Opus of Nature

Crop biodiversity is one of the major inventions of humanity through the process of domestication. It is also an essential resource for crop improvement to adapt agriculture to ever-changing conditions like global climate change and consumer preferences. Domestication and the subsequent evolution under cultivation have profoundly shaped the genetic architecture of this biodiversity. In this review, we highlight recent advances in our understanding of crop biodiversity. Topics include the reduction of genetic diversity during domestication and counteracting factors, a discussion of the relationship between parallel phenotypic and genotypic evolution, the role of plasticity in genotype × environment interactions, and the important role subsistence farmers play in actively maintaining crop biodiversity and in participatory breeding. Linking genotype and phenotype remains the holy grail of crop biodiversity studies.

Metabolite profiling and genome-wide association studies reveal response mechanisms of phosphorus deficiency in maize seedling

Inorganic phosphorus (Pi) is an essential element in numerous metabolic reactions and signaling pathways, but the molecular details of these pathways remain largely unknown. In this study, metabolite profiles of maize (Zea mays L.) leaves and roots were compared between six low-Pi-sensitive lines and six low-Pi-tolerant lines under Pi-sufficient and Pi-deficient conditions to identify pathways and genes associated with the low-Pi stress response. Results showed that under Pi deprivation the concentrations of nucleic acids, organic acids and sugars were increased, but that the concentrations of phosphorylated metabolites, certain amino acids, lipid metabolites and nitrogenous compounds were decreased. The levels of secondary metabolites involved in plant immune reactions, including benzoxazinoids and flavonoids, were significantly different in plants grown under Pi-deficient conditions. Among them, the 11 most stable metabolites showed significant differences under low- and normal-Pi conditions based on the coefficient of variation (CV). Isoleucine and alanine were the most stable metabolites for the identification of Pi-sensitive and Pi-resistant maize inbred lines. With the significant correlation between morphological traits and metabolites, five low-Pi-responding consensus genes associated with morphological traits and simultaneously involved in metabolic pathways were mined by combining metabolites profiles and genome-wide association study (GWAS). The consensus genes induced by Pi deficiency in maize seedlings were also validated by reverse-transcription quantitative polymerase chain reaction (RT-qPCR). Moreover, these genes were further validated in a recombinant inbred line (RIL) population, in which the glucose-6-phosphate-1-epimerase encoding gene mediated yield and correlated traits to phosphorus availability. Together, our results provide a framework for understanding the metabolic processes underlying Pi-deficient responses and give multiple insights into improving the efficiency of Pi use in maize.

Crop metabolomics: from diagnostics to assisted breeding

BACKGROUND

Until recently, plant metabolomics have provided a deep understanding on the metabolic regulation in individual plants as experimental units. The application of these techniques to agricultural systems subjected to more complex interactions is a step towards the implementation of translational metabolomics in crop breeding.

AIM OF REVIEW

We present here a review paper discussing advances in the knowledge reached in the last years derived from the application of metabolomic techniques that evolved from biomarker discovery to improve crop yield and quality.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Translational metabolomics applied to crop breeding programs.

Manipulation and prediction of spike morphology traits for the improvement of grain yield in wheat

In wheat (Triticum spp.), modifying inflorescence (spike) morphology can increase grain number and size and thus improve yield. Here, we demonstrated the potential for manipulating and predicting spike morphology, based on 44 traits. In 12 wheat cultivars, we observed that detillering (removal of branches), which alters photosynthate distribution, changed spike morphology. Our genome-wide association study detected close associations between carbon partitioning (e.g. tiller number, main shoot dry weight) and spike morphology (e.g. spike length, spikelet density) traits in 210 cultivars. Most carbon-partitioning traits (e.g. tiller dry weight, harvest index) demonstrated high prediction abilities (>0.5). For spike morphology, some traits (e.g. total and fertile spikelet number, spike length) displayed high prediction abilities (0.3-0.5), but others (e.g. spikelet fertility, spikelet density) exhibited low prediction abilities (<0.2). Grain size traits were closely correlated in field and greenhouse experiments. Stepwise regression analysis suggests that significantly associated traits in the greenhouse explain 35.35% of the variation in grain yield and 67.63% of the variation in thousand-kernel weight in the field. Therefore, the traits identified in this study affect spike morphology; these traits can be used to predict and improve plant architecture and thus increase yield.

Metabotyping of 30 maize hybrids under early-sowing conditions reveals potential marker-metabolites for breeding

INTRODUCTION

In Northern Europe, maize early-sowing used to maximize yield may lead to moderate damages of seedlings due to chilling without visual phenotypes. Genetic studies and breeding for chilling tolerance remain necessary, and metabolic markers would be particularly useful in this context.

OBJECTIVES

Using an untargeted metabolomic approach on a collection of maize hybrids, our aim was to identify metabolite signatures and/or metabolites associated with chilling responses at the vegetative stage, to search for metabolites differentiating groups of hybrids based on silage-earliness, and to search for marker-metabolites correlated with aerial biomass.

METHODS

Thirty genetically-diverse maize dent inbred-lines (Zea mays) crossed to a flint inbred-line were sown in a field to assess metabolite profiles upon cold treatment induced by a modification of sowing date, and characterized with climatic measurements and phenotyping.

RESULTS

NMR- and LC-MS-based metabolomic profiling revealed the biological variation of primary and specialized metabolites in young leaves of plants before flowering-stage. The effect of early-sowing on leaf composition was larger than that of genotype, and several metabolites were associated to sowing response. The metabolic distances between genotypes based on leaf compositional data were not related to the genotype admixture groups, and their variability was lower under early-sowing than normal-sowing. Several metabolites or metabolite-features were related to silage-earliness groups in the normal-sowing condition, some of which were confirmed the following year. Correlation networks involving metabolites and aerial biomass suggested marker-metabolites for breeding for chilling tolerance.

CONCLUSION

After validation in other experiments and larger genotype panels, these marker-metabolites can contribute to breeding.

Labeling Maize (Zea mays L.) Leaves with 15 NH4+ and Monitoring Nitrogen Incorporation into Amino Acids by GC/MS Analysis

The human body contains approximately 3.2% nitrogen (N), mainly present as protein and amino acids. Although N exists at a high concentration (78%) in the air, it is not readily available to animals and most plants. Plants are however able to take up both nitrate (NO₃^- ) and ammonium (NH₄⁺ ) ions from the soil and convert them to amino acids and proteins, which are excellent sources for all animals. Most N is available as the stable isotope ¹⁴ N, but a second form, ¹⁵ N, is present in very low concentrations. ¹⁵ N can be detected in extracts of plants by gas chromatography followed by mass spectrometry (GC/MS). In this protocol, the methods are described for tracing the pathway by which plants are able to take up ¹⁵ N-labeled nitrate and ammonium and convert them into amino acids and proteins. A protocol for extracting and quantifying amino acids and ¹⁵ N enrichment in maize (Zea mays L.) leaves labeled with ¹⁵ NH₄⁺ is described. Following amino acid extraction, purification, and separation by GC/MS, a calculation of the ¹⁵ N enrichment of each amino acid is carried out on a relative basis to identify any differences in the dynamics of amino acid accumulation. This will allow a study of the impact of genetic modifications or mutations on key reactions involved in primary nitrogen and carbon metabolism. © 2018 by John Wiley & Sons, Inc.

Unraveling lipid metabolism in maize with time-resolved multi-omics data

Maize is the cereal crop with the highest production worldwide, and its oil is a key energy resource. Improving the quantity and quality of maize oil requires a better understanding of lipid metabolism. To predict the function of maize genes involved in lipid biosynthesis, we assembled transcriptomic and lipidomic data sets from leaves of B73 and the high-oil line By804 in two distinct time-series experiments. The integrative analysis based on high-dimensional regularized regression yielded lipid-transcript associations indirectly validated by Gene Ontology and promoter motif enrichment analyses. The co-localization of lipid-transcript associations using the genetic mapping of lipid traits in leaves and seedlings of a B73 × By804 recombinant inbred line population uncovered 323 genes involved in the metabolism of phospholipids, galactolipids, sulfolipids and glycerolipids. The resulting association network further supported the involvement of 50 gene candidates in modulating levels of representatives from multiple acyl-lipid classes. Therefore, the proposed approach provides high-confidence candidates for experimental testing in maize and model plant species.

An integrated multi-layered analysis of the metabolic networks of different tissues uncovers key genetic components of primary metabolism in maize

Primary metabolism plays a pivotal role in normal plant growth, development and reproduction. As maize is a major crop worldwide, the primary metabolites produced by maize plants are of immense importance from both calorific and nutritional perspectives. Here a genome-wide association study (GWAS) of 61 primary metabolites using a maize association panel containing 513 inbred lines identified 153 significant loci associated with the level of these metabolites in four independent tissues. The genome-wide expression level of 760 genes was also linked with metabolite levels within the same tissue. On average, the genetic variants at each locus or transcriptional variance of each gene identified here were estimated to have a minor effect (4.4-7.8%) on primary metabolic variation. Thirty-six loci or genes were prioritized as being worthy of future investigation, either with regard to functional characterization or for their utility for genetic improvement. This target list includes the well-known opaque 2 (O2) and lkr/sdh genes as well as many less well-characterized genes. During our investigation of these 36 loci, we analyzed the genetic components and variations underlying the trehalose, aspartate and aromatic amino acid pathways, thereby functionally characterizing four genes involved in primary metabolism in maize.

Integration of multi-omics techniques and physiological phenotyping within a holistic phenomics approach to study senescence in model and crop plants

The study of senescence in plants is complicated by diverse levels of temporal and spatial dynamics as well as the impact of external biotic and abiotic factors and crop plant management. Whereas the molecular mechanisms involved in developmentally regulated leaf senescence are very well understood, in particular in the annual model plant species Arabidopsis, senescence of other organs such as the flower, fruit, and root is much less studied as well as senescence in perennials such as trees. This review addresses the need for the integration of multi-omics techniques and physiological phenotyping into holistic phenomics approaches to dissect the complex phenomenon of senescence. That became feasible through major advances in the establishment of various, complementary 'omics' technologies. Such an interdisciplinary approach will also need to consider knowledge from the animal field, in particular in relation to novel regulators such as small, non-coding RNAs, epigenetic control and telomere length. Such a characterization of phenotypes via the acquisition of high-dimensional datasets within a systems biology approach will allow us to systematically characterize the various programmes governing senescence beyond leaf senescence in Arabidopsis and to elucidate the underlying molecular processes. Such a multi-omics approach is expected to also spur the application of results from model plants to agriculture and their verification for sustainable and environmentally friendly improvement of crop plant stress resilience and productivity and contribute to improvements based on postharvest physiology for the food industry and the benefit of its customers.

Agricultural practices to improve nitrogen use efficiency through the use of arbuscular mycorrhizae: Basic and agronomic aspects

Nitrogen cycling in agroecosystems is heavily dependent upon arbuscular mycorrhizal fungi (AMF) present in the soil microbiome. These fungi develop obligate symbioses with various host plant species, thus increasing their ability to acquire nutrients. However, AMF are particularly sensitive to physical, chemical and biological disturbances caused by human actions that limit their establishment. For a more sustainable agriculture, it will be necessary to further investigate which agricultural practices could be favorable to maximize the benefits of AMF to improve crop nitrogen use efficiency (NUE), thus reducing nitrogen (N) fertilizer usage. Direct seeding, mulch-based cropping systems prevent soil mycelium disruption and increase AMF propagule abundance. Such cropping systems lead to more efficient root colonization by AMF and thus a better establishment of the plant/fungal symbiosis. In addition, the use of continuous cover cropping systems can also enhance the formation of more efficient interconnected hyphal networks between mycorrhizae colonized plants. Taking into account both fundamental and agronomic aspects of mineral nutrition by plant/AMF symbioses, we have critically described, how improving fungal colonization through the reduction of soil perturbation and maintenance of an ecological balance could be helpful for increasing crop NUE.

The imbalance between C and N metabolism during high nitrate supply inhibits photosynthesis and overall growth in maize (Zea mays L.)

Nitrogen (N) is an important regulator of photosynthetic carbon (C) flow in plants, and an adequate balance between N and C metabolism is needed for correct plant development. However, an excessive N supply can alter this balance and cause changes in specific organic compounds associated with primary and secondary metabolism, including plant growth regulators. In previous work, we observed that high nitrate supply (15 mM) to maize plants led to a decrease in leaf expansion and overall biomass production, when compared with low nitrate supply (5 mM). Thus, the aim of this work is to study how overdoses of nitrate can affect photosynthesis and plant development. The results show that high nitrate doses greatly increased amino acid production, which led to a decrease in the concentration of 2-oxoglutarate, the main source of C skeletons for N assimilation. The concentration of 1-aminocyclopropane-1-carboxylic acid (and possibly its product, ethylene) also rose in high nitrate plants, leading to a decrease in leaf expansion, reducing the demand for photoassimilates by the growing tissues and causing the accumulation of sugars in source leaves. This accumulation of sugars, together with the decrease in 2-oxoglutarate levels and the reduction in chlorophyll concentration, decreased plant photosynthetic rates. This work provides new insights into how high nitrate concentration alters the balance between C and N metabolism, reducing photosynthetic rates and disrupting whole plant development. These findings are particularly relevant since negative effects of nitrate in contexts other than root growth have rarely been studied.

Plant genome-scale reconstruction: from single cell to multi-tissue modelling and omics analyses

In this review, we present the latest developments in plant systems biology with particular emphasis on plant genome-scale reconstructions and multi-omics analyses. Understanding multicellular metabolism is far from trivial and 'omics' data are difficult to interpret in the absence of a systems framework. 'Omics' data appropriately integrated with genome-scale reconstructions and modelling facilitates our understanding of how individual components interact and influence overall cell, tissue or organisms function. Here we present examples of how plant metabolic reconstructions and modelling are used as a systems-based framework for improving our understanding of the plant metabolic processes in single cells and multiple tissues.

Biosensor-Mediated In Situ Imaging Defines the Availability Period of Assimilatory Glutamine in Maize Seedling Leaves Following Nitrogen Fertilization

The amino acid glutamine (Gln) is an important assimilatory intermediate between root-derived inorganic nitrogen (N) (i.e., ammonium) and downstream macromolecules, and is a central regulator in plant N physiology. The timing of Gln accumulation after N uptake by roots has been well characterized. However, the duration of availability of accumulated Gln at a sink tissue has not been well defined. Measuring Gln availability would require temporal measurements of both Gln accumulation and its reciprocal depletion. Furthermore, as Gln varies spatially within a tissue, whole-organ in situ visualization would be valuable. Here, the accumulation and subsequent disappearance of Gln in maize seedling leaves (Zea mays L.) was imaged in situ throughout the 48 h after N application to roots of N-deprived plants. Free Gln was imaged by placing leaves onto agar embedded with bacterial biosensor cells (GlnLux) that emit luminescence in the presence of leaf-derived Gln. Seedling leaves 1, 2, and 3 were imaged simultaneously to measure Gln availability across tissues that potentially vary in N sink strength. The results show that following root N fertilization, free Gln accumulates and then disappears with an availability period of up to 24 h following peak accumulation. The availability period of Gln was similar in all seedling leaves, but the amount of accumulation was leaf specific. As Gln is not only a metabolic intermediate, but also a signaling molecule, the potential importance of regulating its temporal availability within plant tissues is discussed.