C4 plants have traditionally been classified into NADP-malic enzyme (NADP-ME), NAD-malic enzyme (NAD-ME), and phosphoenolpyruvate carboxykinase (PEPCK) subtypes based on the predominant C4 acid decarboxylating enzyme. To investigate the relative contributions of malate and aspartate to C4 pathway fluxes in each subtype, we performed 13CO2 pulse-chase labelling experiments on four C4 grass species: Zea mays and Setaria viridis (NADP-ME), Panicum miliaceum (NAD-ME), and Megathyrsus maximus (PEPCK). Only a proportion (8-50%) of the total malate pool in the leaves is photosynthetically active, whereas essentially all of the aspartate pool is photosynthetically active. Estimates of metabolic fluxes indicate that approximately two-thirds of the C4 pathway flux is via malate in Z. mays and the remaining third via aspartate, while in S. viridis 50% of the flux is via malate and 50% via aspartate. In P. miliaceum and M. maximus, 91% and 85% of the flux is via aspartate and the remaining 9% and 15% via malate, respectively. The results demonstrate the feasibility of using non-radioactive 13CO2 in pulse-chase labelling experiments to study C4 photosynthesis and to detect C4 pathway fluxes in C3 plants engineered to perform C4 photosynthesis.

The NADPH-dependent thioredoxin reductase/thioredoxin (NTR/TRX) system plays a central role in maintaining redox homeostasis of the cell by transferring electrons from NADPH to target proteins though NTR and TRX, thereby modulating cysteine redox states and regulating enzyme activity. However, the specific contribution of the extraplastidial NTR/TRX system to plant acclimation to elevated CO2 (eCO2) remains poorly understood. Here, we investigated the physiological and metabolic responses of Arabidopsis mutants deficient in mitochondrial TRXo1 (trxo1) or in the cytosolic/mitochondrial/nuclear thioredoxin reductases NTRA/NTRB (ntrantrb) alongside the wild-type (WT), grown under ambient (aCO2; 400 ppm) and eCO2 (800 ppm) CO2 conditions. The stomatal closure induced by abscisic acid or eCO2 was partially compromised in ntrantrb double mutant. The stomatal density decreased in WT and ntrantrb plants under eCO2, while did not change in trxo1 lines. The mutants showed much higher increases in rosette biomass under eCO2 compared to WT. This was associated with alterations in both primary and secondary metabolisms, but not to the level of NAD(P)(H), and reduced glutathione/oxidized glutathione (GSH : GSSG) ratio. Our results indicate that TRXo1 and NTRA/B play key roles in regulating stomatal development/movement and both primary and secondary metabolisms, thereby impacting plant acclimation to eCO2.

The Anaphase-Promoting Complex/Cyclosome (APC/C) is an E3 ubiquitin ligase that plays a crucial role in ubiquitin-dependent proteolysis of key cell cycle regulators, which is completed by the 26S proteasome. Previously, SAMBA, a plant-specific regulator of the APC/C, was identified in Arabidopsis as a critical factor controlling organ size through the regulation of cell proliferation. Here, by assessing its role in the crop tomato (Solanum lycopersicum), we confirm that SAMBA is a conserved APC/C regulator in plants and shows additional roles, including the modulation of fruit shape and changes in sugar metabolism. Two slsamba genome-edited lines were produced and characterized, and showed delayed growth, reduced plant size, and altered fruit morphology, which were linked to changes in cell division and expansion. Notably, untargeted metabolomics revealed altered flavonoid profiles, along with elevated Brix values in the fruits, indicating a sweeter taste. Accordingly, transcriptomics uncovered a change in temporal gene expression gradients during early fruit development, correlating with the alterations in sugar metabolism and revealing changes in cell wall biosynthesis genes. This study provides the first evidence of SAMBA's role in regulating fruit development, metabolic content, and ultimately, quality. These important findings offer potential applications for improving the nutritional quality and overall performance of tomatoes.

Diketopiperazines (DKPs) are chemically and functionally diverse cyclic dipeptides associated primarily with microbes. Few DKPs have been reported from plants and animals; the best characterized is cyclo(His-Pro), found in the mammalian central nervous system, where it arises from the proteolytic cleavage of a thyrotropin-releasing tripeptide hormone. Herein, we report the identification of cyclo(His-Pro) in Arabidopsis (Arabidopsis thaliana), where its levels increase upon abiotic stress conditions, including high salt, heat, and cold. To screen for potential protein targets, we used isothermal shift assays, which examine changes in protein-melting stability upon ligand binding. Among the identified proteins, we focused on the glycolytic enzyme, cytosolic glyceraldehyde-3-phosphate dehydrogenase (GAPC1). Binding between the GAPC1 protein and cyclo(His-Pro) was validated using nano-differential scanning fluorimetry and microscale thermophoresis, and we could further demonstrate that cyclo(His-Pro) inhibits GAPC1 activity with an IC50 of ∼200 μm. This inhibition was conserved in human GAPDH. Inhibition of glyceraldehyde-3-phosphate dehydrogenase activity has previously been reported to reroute carbon from glycolysis toward the pentose phosphate pathway. Accordingly, cyclo(His-Pro) supplementation augmented NADPH levels, increasing the NADPH/NADP+ ratio. Phenotypic screening revealed that plants supplemented with cyclo(His-Pro) were more tolerant to high-salt stress, as manifested by higher biomass, which we show is dependent on GAPC1/2. Our work reports the identification and functional characterization of cyclo(His-Pro) as a modulator of glyceraldehyde-3-phosphate dehydrogenase in plants.

The evolution of the seed habit marks a pivotal innovation of the spermatophytes. Angiosperms further refined this trait by coupling the development of seed accessory structures to fertilization, optimizing resource allocation. Here, we demonstrate that post-fertilization auxin production is an evolutionarily conserved mechanism for seed initiation in angiosperms. We also provide evidence that this pathway likely emerged from a switch from maternal to paternal control after the divergence of angiosperms from their gymnosperm ancestors. Our study thus brings new insights into the evolutionary origins of the endosperm, which was a determining feature for the rapid rise to dominance of flowering plants. ### Competing Interest Statement The authors have declared no competing interest.

Enhancing crops productivity to ensure food security is one of the major challenges encountering agriculture today. A promising solution is the use of biostimulants, which encompass molecules that enhance plant fitness, growth, and productivity. The regulatory metabolite zaxinone and its mimics (MiZax3 and MiZax5) showed promising results in improving the growth and yield of several crops. Here, the impact of their exogenous application on soil and rice root microbiota was investigated. Plants grown in native paddy soil were treated with zaxinone, MiZax3, and MiZax5 and the composition of bacterial and fungal communities in soil, rhizosphere, and endosphere at the tillering and the milky stage was assessed. Furthermore, shoot metabolome profile and nutrient content of the seeds were evaluated. Results show that treatment with zaxinone and its mimics predominantly influenced the root endosphere prokaryotic community, causing a partial depletion of plant-beneficial microbes at the tillering stage, followed by a recovery of the prokaryotic community structure during the milky stage. Our study provides new insights into the role of zaxinone and MiZax in the interplay between rice and its root-associated microbiota and paves the way for their practical application in the field as ecologically friendly biostimulants to enhance crop productivity.

Metabolomics has emerged as an indispensable tool for exploring complex biological questions, providing the ability to investigate a substantial portion of the metabolome. However, the vast complexity and structural diversity intrinsic to metabolites imposes a great challenge for data analysis and interpretation. Liquid chromatography mass spectrometry (LC-MS) stands out as a versatile technique offering extensive metabolite coverage. In this mini-review, we address some of the hurdles posed by the complex nature of LC-MS data, providing a brief overview of computational tools designed to help tackling these challenges. Our focus centers on two major steps that are essential to most metabolomics investigations: the translation of raw data into quantifiable features, and the extraction of structural insights from mass spectra to facilitate metabolite identification. By exploring current computational solutions, we aim at providing a critical overview of the capabilities and constraints of mass spectrometry-based metabolomics, while introduce some of the most recent trends in data processing and analysis within the field.

Plants synthesize specialized metabolites to facilitate environmental and ecological interactions. During evolution, plants diversified in their potential to synthesize these metabolites. Quantitative differences in metabolite levels of natural Arabidopsis (Arabidopsis thaliana) accessions can be employed to unravel the genetic basis for metabolic traits using genome-wide association studies (GWAS). Here, we performed metabolic GWAS on seeds of a panel of 315 A. thaliana natural accessions, including the reference genotypes C24 and Col-0, for polar and semi-polar seed metabolites using untargeted ultra-performance liquid chromatography-mass spectrometry. As a complementary approach, we performed quantitative trait locus (QTL) mapping of near-isogenic introgression lines between C24 and Col-0 for specific seed specialized metabolites. Besides common QTL between seeds and leaves, GWAS revealed seed-specific QTL for specialized metabolites, indicating differences in the genetic architecture of seeds and leaves. In seeds, aliphatic methylsulfinylalkyl and methylthioalkyl glucosinolates associated with the ALKENYL HYDROXYALKYL PRODUCING loci (GS-ALK and GS-OHP) on chromosome 4 containing alkenyl hydroxyalkyl producing 2 (AOP2) and 3 (AOP3) or with the GS-ELONG locus on chromosome 5 containing methylthioalkyl malate synthase (MAM1) and MAM3. We detected two unknown sulfur-containing compounds that were also mapped to these loci. In GWAS, some of the annotated flavonoids (kaempferol 3-O-rhamnoside-7-O-rhamnoside, quercetin 3-O-rhamnoside-7-O-rhamnoside) were mapped to transparent testa 7 (AT5G07990), encoding a cytochrome P450 75B1 monooxygenase. Three additional mass signals corresponding to quercetin-containing flavonols were mapped to UGT78D2 (AT5G17050). The association of the loci and associating metabolic features were functionally verified in knockdown mutant lines. By performing GWAS and QTL mapping, we were able to leverage variation of natural populations and parental lines to study seed specialized metabolism. The GWAS data set generated here is a high-quality resource that can be investigated in further studies.

In plants, L-serine (Ser) biosynthesis occurs through various pathways and is highly dependent on the atmospheric CO2 concentration, especially in C3 species, due to the association of the Glycolate Pathway of Ser Biosynthesis (GPSB) with photorespiration. Characterization of a second plant Ser pathway, the Phosphorylated Pathway of Ser Biosynthesis (PPSB), revealed that it is at the crossroads of carbon, nitrogen, and sulphur metabolism. The PPSB comprises three sequential reactions catalysed by 3-phosphoglycerate dehydrogenase (PGDH), 3-phosphoSer aminotransferase (PSAT) and 3-phosphoSer phosphatase (PSP). PPSB was overexpressed in plants exhibiting two different modes of photosynthesis: Arabidopsis (C3 metabolism), and maize (C4 metabolism), under ambient (aCO2) and elevated (eCO2) CO2 growth conditions. Overexpression in Arabidopsis of the PGDH1 gene alone or PGDH1, PSAT1 and PSP1 in combination increased the Ser levels but also the essential amino acids threonine (aCO2), isoleucine, leucine, lysine, phenylalanine, threonine and methionine (eCO2) compared to the wild-type. These increases translated into higher protein levels. Likewise, starch levels were also increased in the PPSB-overexpressing lines. In maize, PPSB-deficient lines were obtained by targeting PSP1 using Cas9 endonuclease. We concluded that the expression of PPSB in maize male gametophyte is required for viable pollen development. Maize lines overexpressing the AtPGDH1 gene only displayed higher protein levels but not starch at both aCO2 and eCO2 conditions, this translated into a significant rise in the nitrogen/carbon ratio. These results suggest that metabolic engineering of PPSB in crops could enhance nitrogen content, particularly under upcoming eCO2 conditions where the activity of GPSB is limited.

Photorespiration (PR) is the pathway that detoxifies the product of the oxygenation reaction of Rubisco. It has been hypothesized that in dynamic light environments, PR provides a photoprotective function. To test this hypothesis, we characterized plants with varying PR enzyme activities under fluctuating and non-fluctuating light conditions. Contrasting our expectations, growth of mutants with decreased PR enzyme levels was least affected in fluctuating light compared with wild type. Results for growth, photosynthesis and metabolites combined with thermodynamics-based flux analysis revealed two main causal factors for this unanticipated finding: reduced rates of photosynthesis in fluctuating light and complex re-routing of metabolic fluxes. Only in non-fluctuating light, mutants lacking the glutamate:glyoxylate aminotransferase 1 re-routed glycolate processing to the chloroplast, resulting in photooxidative damage through H2O2 production. Our results reveal that dynamic light environments buffer plant growth and metabolism against photorespiratory perturbations.

Summary MetPlast, is an R package that provides the functionalities necessary to analyze biological samples’ metabolic plasticity. This package takes advantage of the statistical framework provided by the Information Theory to quantify and defined metabolic plasticity parameters. Using previous implemented formula based on Shannon entropy we automatize the calculation and visualization of a set of metabolic plasticity indexes including metabolic diversity, metabolome specialization, and metabolite specialization. We use a publicly available metabolic data set on tomato domestication to demonstrate the power of the present tool to evaluate changes in metabolic plasticity parameters. Thus, MetPlast represents a new and invaluable member of the computational metabolomics toolbox, that will certainly help scientists to unveil hidden information in cell metabolomic landscape. Availability and implementation Freely available at https://github.com/danlucio86/MetPlast

The process of crop domestication leads to a dramatic reduction in the gene expression associated with metabolic diversity. Genes involved in specialized metabolism appear to be particularly affected. Although there is ample evidence of these effects at the genetic level, a reduction in diversity at the metabolite level has been taken for granted despite having never been adequately accessed and quantified. Here we leveraged the high coverage of ultra high performance liquid chromatography-high-resolution mass spectrometry based metabolomics to investigate the metabolic diversity in the common bean (Phaseolus vulgaris). Information theory highlights a shift towards lower metabolic diversity and specialization when comparing wild and domesticated bean accessions. Moreover, molecular networking approaches facilitated a broader metabolite annotation than achieved to date, and its integration with gene expression data uncovers a metabolic shift from specialized metabolism towards central metabolism upon domestication of this crop.

Coffee is one of the most traded commodities world-wide. As with 70% of land plants, coffee is associated with arbuscular mycorrhizal (AM) fungi, but the molecular bases of this interaction are unknown.We studied the mycorrhizal phenotype of two commercially important Coffea arabica cultivars ('Typica National' and 'Catimor Amarillo'), upon Funnelliformis mosseae colonisation grown under phosphorus limitation, using an integrated functional approach based on multi-omics, physiology and biochemistry.The two cultivars revealed a strong biomass increase upon mycorrhization, even at low level of fungal colonisation, improving photosynthetic efficiency and plant nutrition. The more important iconic markers of AM symbiosis were activated: We detected two gene copies of AM-inducible phosphate (Pt4), ammonium (AM2) and nitrate (NPF4.5) transporters, which were identified as belonging to the C. arabica parental species (C. canephora and C. eugenioides) with both copies being upregulated. Transcriptomics data were confirmed by ions and metabolomics analyses, which highlighted an increased amount of glucose, fructose and flavonoid glycosides.In conclusion, both coffee cultivars revealed a high responsiveness to the AM fungus along their root-shoot axis, showing a clear-cut re-organisation of the major metabolic pathways, which involve nutrient acquisition, carbon fixation, and primary and secondary metabolism.

Infections caused by Candida species increased, as well as species resistant to the most conventional antimicrobials. Thus, the search for new natural sources of antimicrobials without adverse effects also increased. In this case, Astronium urundeuva Engl., a medicinal plant with several pharmacological activities, including antifungal activity, emerges as a source of antifungal compounds. Here, we evaluated the antifungal activity of A. urundeuva and its derivatives free or loaded into a nanostructured lipid system and combination studies against Candida species. A. urundeuva component's purification and identification were performed through chromatographic and spectroscopic techniques, respectively. The major components identified were gallic acid ( 1 ), methyl gallate ( 2 ), ethyl gallate ( 3 ), and 1,2,3,4,6-penta- O -galoyl- β -D-glucose (PGG) ( 4 ). A. urundeuva extract, its aqueous fraction, and PGG ( 4 ) exhibited the same MIC values between 0.2 and 62.5 µg/mL against Candida species being classified as significant activity, while the amphotericin B MIC was 0.1–1.2 µg/mL. Combination assay demonstrated that may occur synergism (0.37) between gallic acid ( 1 ) x methyl gallate ( 2 ). Thus, the results demonstrated as PGG ( 4 ) much as the gallic acid ( 1 ) x methyl gallate ( 2 ) combined might be the main responsible for the antifungal activity against Candida species, mainly Candida glabrata ATCC 2001 and that the tested nanostructured system maintained the antifungal activity. Through the antifungal activity of the extract and purified compounds, the extract may be employed in the development of antifungal herbal medicine, because its purification process is simple and greener than pure compounds.

The diterpenoid paclitaxel (Taxol) is a chemotherapy medication widely used as a first-line treatment against several types of solid cancers.The supply of paclitaxel from natural sources is limited.However, missing knowledge about the genes involved in several specific metabolic steps of paclitaxel biosynthesis has rendered it difficult to engineer the full pathway.In this study, we used a combination of transcriptomics, cell biology, metabolomics, and pathway reconstitution to identify the complete gene set required for the heterologous production of paclitaxel.We identified the missing steps from the current model of paclitaxel biosynthesis and confirmed the activity of most of the missing enzymes via heterologous expression in Nicotiana benthamiana.Notably, we identified a new C4b-C20 epoxidase that could overcome the first bottleneck of metabolic engineering.We used both previously characterized and newly identified oxomutases/epoxidases, taxane 1b-hydroxylase, taxane 9a-hydroxylase, taxane 9a-dioxygenase, and phenylalanine-CoA ligase, to successfully biosynthesize the key intermediate baccatin III and to convert baccatin III into paclitaxel in N. benthamiana.In combination, these approaches establish a metabolic route to taxoid biosynthesis and provide insights into the unique chemistry that plants use to generate complex bioactive metabolites.

Protein-metabolite interactions (PMIs) are directly responsible for the regulation of numerous processes. From the direct regulation of enzymes to complex developmental processes intermediated by hormones, PMIs are central to understanding the molecular mechanisms of important physiological phenomena. Still, proving such interactions experimentally has proven an arduous task. We discuss here some of the current technologies contributing to expand our knowledge on PMIs, with particular emphasis on platforms and databases to explore the highly heterogenous nature of characterized PMIs, which is likely to be an essential resource on the development of new computational approaches to predict and validate interactions based on large-scale PMI screenings.

Metabolite profiling aiming at quantifying the metabolome of flowers is emerging as a suitable tool to understand the metabolic complexity of these reproductive organs and the associations between primary and secondary metabolites which characterize them. This chapter provides a general method for the combined analyses of primary and secondary metabolites via gas chromatography-mass spectrometry (GC-MS) and high-performance liquid chromatography-mass spectrometry (LC-MS) of flower samples. We describe the preparatory steps, the procedure of metabolites' extraction and finally provide examples of data representation. The method described here can be applied to the analysis of metabolomes of entire flowers, as well as specific flower organs.

Strawberry ripening involves a number of irreversible biochemical reactions that cause sensory changes through accumulation of sugars, acids and other compounds responsible for fruit color and flavor. The process, which is strongly dependent on methylation marks in other fruits such as tomatoes and oranges, is highly controlled and coordinated in strawberry. Repeated injections of the hypomethylating compound 5-azacytidine (AZA) into green and unripe Fragaria × ananassa receptacles fully arrested the ripening of the fruit. The process, however, was reversible since treated fruit parts reached full maturity within a few days after AZA treatment was stopped. Transcriptomic analyses showed that key genes responsible for the biosynthesis of anthocyanins, phenylpropanoids, and hormones such as abscisic acid (ABA) were affected by the AZA treatment. In fact, AZA downregulated genes associated with ABA biosynthetic genes but upregulated genes associated with its degradation. AZA treatment additionally downregulated a number of essential transcription factors associated with the regulation and control of ripening. Metabolic analyses revealed a marked imbalance in hormone levels, with treated parts accumulating auxins, gibberellins and ABA degradation products, as well as metabolites associated with unripe fruits. AZA completely halted strawberry ripening by altering the hormone balance, and the expression of genes involves in hormone biosynthesis and degradation processes. These results contradict those previously obtained in other climacteric and fleshly fruits, where AZA led to premature ripening. In any case, our results suggests that the strawberry ripening process is governed by methylation marks.

Abstract During the maturation phase of flower development, the onset of anthesis visibly marks the transition from buds to open flowers, during which petals stretch out, nectar secretion commences, and pollination occurs. Analysis of the metabolic changes occurring during this developmental transition has primarily focused on specific classes of metabolites, such as pigments and scent emission, and far less on the whole network of primary and secondary metabolites. To investigate the metabolic changes occurring at anthesis, we performed multi-platform metabolomics alongside RNA sequencing in individual florets harvested from the main inflorescence of Arabidopsis (Arabidopsis thaliana) ecotype Col-0. To trace metabolic fluxes at the level of the whole inflorescence and individual florets, we further integrated these studies with radiolabeled experiments. These extensive analyses revealed high-energy-level metabolism and transport of carbohydrates and amino acids, supporting intense metabolic rearrangements occurring at the time of this floral transition. These comprehensive data are discussed in the context of our current understanding of the metabolic shifts underlying flower opening. We envision that this analysis will facilitate the introgression of floral metabolic traits promoting pollination in crop species for which a comprehensive knowledge of flower metabolism is still limited.

The plant kingdom is thought to encompass about one million unique metabolite structures. Whilst considerable advances have been made with regard to quantification, metabolite annotation trails behind. Computational annotation workflows, as demonstrated here, can pave a route forward. High-resolution mass spectrometry (MS) data are generated (A) and processed (B); tandem MS (MS/MS) spectra are matched against experimental or in silico databases (e.g., spectra similarity) (C); matching scores are used to select potential hits (D); and molecular networks establish putative relationships between all spectra (E). COSMIC provides a confidence score of likely successful hits for the more comprehensive in silico approaches. Figure created with BioRender.com. The large chemical diversity in specialized metabolism is often built upon variations of a few aglycone structures. The application of COSMIC to explore databases of hypothetical structures can accelerate annotation of new metabolites. For example, the structure of saiginol A (A) can be used to identify other saiginol structures (B). Unlike experimental annotation, computational approaches are not reliant on the availability of standard compounds, which, proportionally to the number of metabolites in the plant kingdom, are highly limited. In silico databases open up the possibility to search for unknown compounds. However, the separation of correct and incorrect hits based on scores provided by in silico methods has been impossible, in contrast to similarity match against known standards. COSMIC provides a reliable scoring system to classify likely correct and incorrect hits in the more comprehensive in silico methods. Additionally, mis-annotations with high scores were highly similar with the true structure, still providing relevant structural information. For the annotation of structures that generate highly similar spectra (e.g., positional isomers varying only on a side group position), algorithms such as COSMIC return low scores despite their high similarities. This is, however, arguably a limitation of MS and not of the algorithm. It has been demonstrated that these methods perform much better for biological databases in relation to more generic chemical databases. Thus, the scoring might perform poorly for classes of metabolites with broad distribution of positional isomers already described in databases. Moreover, a more uniform transparency as to how the various algorithms aid in annotation would be beneficial. Ideally, chemical-based complementation experiments would be needed in order to validate computational-based annotations. Financial support of the Max Planck Society is acknowledged by all authors. Figures created with BioRender.com. No interests are declared.