Integrative Approaches to Enhance Understanding of Plant Metabolic Pathway Structure and Regulation

The natural variance of Arabidopsis secondary metabolism on extended darkness

In plants due to their sessile nature, secondary metabolites are important components against different abiotic and biotic stress, such as extended darkness. For this reason, the variation of secondary metabolite content of the Arabidopsis thaliana HapMap natural population following 0-and 6-d darkness treatment were detected and the raw data of different accessions at two timepoints were deposited in the Zenodo database. Moreover, the annotated secondary metabolites of these samples are presented in this data descriptor, which we believe will be a usefully re-usable resource for future integrative analysis with dark-treated transcripts, proteins or other phenotypic data in order to comprehensively illustrate the multiomic landscape of Arabidopsis in response to the stresses exerted by extended darkness.

Using precision phenotyping to inform de novo domestication

An update on the use of precision phenotyping to assess the potential of lesser cultivated species as candidates for de novo domestication or similar development for future agriculture.

Mass spectrometry-based forest tree metabolomics

Research in forest tree species has advanced slowly when compared with other agricultural crops and model organisms, mainly due to the long-life cycles, large genome sizes, and lack of genomic tools. Additionally, trees are complex matrices, and the presence of interferents (e.g., oleoresins and cellulose) challenges the analysis of tree tissues with mass spectrometry (MS)-based analytical platforms. In this review, advances in MS-based forest tree metabolomics are discussed. Given their economic and ecological significance, particular focus is given to Pinus, Quercus, and Eucalyptus forest tree species to better understand their metabolite responses to abiotic and biotic stresses in the current climate change scenario. Furthermore, MS-based metabolomics technologies produce large and complex datasets that require expertize to adequately manage, process, analyze, and store the data in dedicated repositories. To ensure that the full potential of forest tree metabolomics data are translated into new knowledge, these data should comply with the FAIR principles (i.e., Findable, Accessible, Interoperable, and Re-usable). It is essential that adequate standards are implemented to annotate metadata from forest tree metabolomics studies as is already required by many science and governmental agencies and some major scientific publishers. © 2019 John Wiley & Sons Ltd. Mass Spec Rev 40:126-157, 2021.

Simultaneous introduction of multiple biomacromolecules into plant cells using a cell-penetrating peptide nanocarrier

Plant cells contain groups of biomolecules that participate together in a particular biological process. Exogenous codelivery of multiple biomolecules is an essential step for elucidation of the biological significance of these molecules and enables various biotechnological applications in plants. However, the currently existing biomolecule delivery methods face difficulties in delivering multiple components into plant cells, mediating transgene expression, and maintaining the stability of the numerous components and lead to delays in biomolecular function. Cell-penetrating peptides (CPPs) have demonstrated remarkable abilities to introduce diverse biomolecules into various plant species. Here, we employed the engineered CPP KH₉-BP100 as a carrier to deliver multiple biomolecules into plant cells and performed a bimolecular fluorescence complementation assay to assess the simultaneous introduction of multiple biomolecules. We demonstrate that multiple biomolecule/CPP cargos can be simultaneously internalized by a particular plant cell, albeit with different efficiencies. We present a cutting-edge technique for codelivery of multiple biomolecules into plant cells that can be used for elucidation of functional correlations and for metabolic engineering.

Effects of cadmium, inorganic mercury and methyl-mercury on the physiology and metabolomic profiles of shoots of the macrophyte Elodea nuttallii

Macrophytes are known to bioaccumulate metals, but a thorough understanding of tolerance strategies and molecular impact of metals in aquatic plants is still lacking. The present study aimed to compare Hg and Cd effects in a representative macrophyte, Elodea nuttallii using physiological endpoints and metabolite profiles in shoots and cytosol. Exposure 24 h to methyl-Hg (30 ng L^-1), inorganic Hg (70 ng L^-1) and Cd (280 μg L^-1) did not affect photosynthesis, or antioxidant enzymes despite the significant accumulation of metals, confirming a sublethal stress level. In shoots, Cd resulted in a higher level of regulation of metabolites than MeHg, while MeHg resulted in the largest number of regulated metabolites and IHg treatment regulated no metabolites significantly. In cytosol, Cd regulated more metabolites than IHg and only arginine, histidine and mannose were reduced by MeHg exposure. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of data suggested that exposure to MeHg resulted in biochemical changes including aminoacyl-tRNA biosynthesis, glycine, serine and threonine metabolism, nitrogen metabolism, arginine and proline metabolism, cyanoamino acid metabolism, while the treatment of Cd stress caused significant variations in aminoacyl-tRNA biosynthesis and branched-chain amino acids pathways. Data supports an impact of MeHg on N homeostasis, while Cd resulted in an osmotic stress-like pattern and IHg had a low impact. Marked differences in the responses to MeHg and IHg exposure were evidenced, supporting different molecular toxicity pathways and main impact of MeHg on non-soluble compartment, while main impact of IHg was on soluble compartment. Metabolomics was used for the first time in this species and proved to be very useful to confirm and complement recent knowledge gained by transcriptomics and proteomics, highlighting the high interest of multi-omics approaches to identify early impact of environmental pollution.

Metabolomics Provides Valuable Insight for the Study of Durum Wheat: A Review

Metabolomics is increasingly being applied in various fields offering a highly informative tool for high-throughput diagnostics. However, in plant sciences, metabolomics is underused, even though plant studies are relatively easy and cheap when compared to those on humans and animals. Despite their importance for human nutrition, cereals, and especially wheat, remain understudied from a metabolomics point of view. The metabolomics of durum wheat has been essentially neglected, although its genetic structure allows the inference of common mechanisms that can be extended to other wheat and cereal species. This review covers the present achievements in durum wheat metabolomics highlighting the connections with the metabolomics of other cereal species (especially bread wheat). We discuss the metabolomics data from various studies and their relationships to other "-omics" sciences, in terms of wheat genetics, abiotic and biotic stresses, beneficial microbes, and the characterization and use of durum wheat as feed, food, and food ingredient.

Identification and characterization of metabolite quantitative trait loci in tomato leaves and comparison with those reported for fruits and seeds

INTRODUCTION

To date, most studies of natural variation and metabolite quantitative trait loci (mQTL) in tomato have focused on fruit metabolism, leaving aside the identification of genomic regions involved in the regulation of leaf metabolism.

OBJECTIVE

This study was conducted to identify leaf mQTL in tomato and to assess the association of leaf metabolites and physiological traits with the metabolite levels from other tissues.

METHODS

The analysis of components of leaf metabolism was performed by phenotypying 76 tomato ILs with chromosome segments of the wild species Solanum pennellii in the genetic background of a cultivated tomato (S. lycopersicum) variety M82. The plants were cultivated in two different environments in independent years and samples were harvested from mature leaves of non-flowering plants at the middle of the light period. The non-targeted metabolite profiling was obtained by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). With the data set obtained in this study and already published metabolomics data from seed and fruit, we performed QTL mapping, heritability and correlation analyses.

RESULTS

Changes in metabolite contents were evident in the ILs that are potentially important with respect to stress responses and plant physiology. By analyzing the obtained data, we identified 42 positive and 76 negative mQTL involved in carbon and nitrogen metabolism.

CONCLUSIONS

Overall, these findings allowed the identification of S. lycopersicum genome regions involved in the regulation of leaf primary carbon and nitrogen metabolism, as well as the association of leaf metabolites with metabolites from seeds and fruits.

Computational Approaches to Design and Test Plant Synthetic Metabolic Pathways

Successfully designed and implemented plant-specific synthetic metabolic pathways hold promise to increase crop yield and nutritional value. Advances in synthetic biology have already demonstrated the capacity to design artificial biological pathways whose behavior can be predicted and controlled in microbial systems. However, the transfer of these advances to model plants and crops faces the lack of characterization of plant cellular pathways and increased complexity due to compartmentalization and multicellularity. Modern computational developments provide the means to test the feasibility of plant synthetic metabolic pathways despite gaps in the accumulated knowledge of plant metabolism. Here, we provide a succinct systematic review of optimization-based and retrobiosynthesis approaches that can be used to design and in silico test synthetic metabolic pathways in large-scale plant context-specific metabolic models. In addition, by surveying the existing case studies, we highlight the challenges that these approaches face when applied to plants. Emphasis is placed on understanding the effect that metabolic designs can have on native metabolism, particularly with respect to metabolite concentrations and thermodynamics of biochemical reactions. In addition, we discuss the computational developments that may help to transform the identified challenges into opportunities for plant synthetic biology.

Trait discovery and editing in tomato

Tomato (Solanum lycopersicum), which is used for both processing and fresh markets, is a major crop species that is the top ranked vegetable produced over the world. Tomato is also a model species for research in genetics, fruit development and disease resistance. Genetic resources available in public repositories comprise the 12 wild related species and thousands of landraces, modern cultivars and mutants. In addition, high quality genome sequences are available for cultivated tomato and for several wild relatives, hundreds of accessions have been sequenced, and databases gathering sequence data together with genetic and phenotypic data are accessible to the tomato community. Major breeding goals are productivity, resistance to biotic and abiotic stresses, and fruit sensorial and nutritional quality. New traits, including resistance to various biotic and abiotic stresses and root architecture, are increasingly being studied. Several major mutations and quantitative trait loci (QTLs) underlying traits of interest in tomato have been uncovered to date and, thanks to new populations and advances in sequencing technologies, the pace of trait discovery has considerably accelerated. In recent years, clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 gene editing (GE) already proved its remarkable efficiency in tomato for engineering favorable alleles and for creating new genetic diversity by gene disruption, gene replacement, and precise base editing. Here, we provide insight into the major tomato traits and underlying causal genetic variations discovered so far and review the existing genetic resources and most recent strategies for trait discovery in tomato. Furthermore, we explore the opportunities offered by CRISPR/Cas9 and their exploitation for trait editing in tomato.

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.

Data-Mining Bioinformatics: Connecting Adenylate Transport and Metabolic Responses to Stress

Adenine nucleotides are essential in countless processes within the cellular metabolism. In plants, ATP is mainly produced in chloroplasts and mitochondria through photophosphorylation and oxidative phosphorylation, respectively. Thus, efficient adenylate transport systems are required for intracellular energy partitioning between the cell organelles. Adenylate carriers present in different subcellular compartments have been previously identified and biochemically characterized in plants. Here, by using data-mining bioinformatics tools, we propose how, and to what extent, these carriers integrate energy metabolism within a plant cell under different environmental conditions. We demonstrate that the expression pattern of the corresponding genes is variable under different environmental conditions, suggesting that specific adenylate carriers have distinct and nonredundant functions in plants.

Putting primary metabolism into perspective to obtain better fruits

Background

One of the key goals of fruit biology is to understand the factors that influence fruit growth and quality, ultimately with a view to manipulating them for improvement of fruit traits.

Scope

Primary metabolism, which is not only essential for growth but is also a major component of fruit quality, is an obvious target for improvement. However, metabolism is a moving target that undergoes marked changes throughout fruit growth and ripening.

Conclusions

Agricultural practice and breeding have successfully improved fruit metabolic traits, but both face the complexity of the interplay between development, metabolism and the environment. Thus, more fundamental knowledge is needed to identify further strategies for the manipulation of fruit metabolism. Nearly two decades of post-genomics approaches involving transcriptomics, proteomics and/or metabolomics have generated a lot of information about the behaviour of fruit metabolic networks. Today, the emergence of modelling tools is providing the opportunity to turn this information into a mechanistic understanding of fruits, and ultimately to design better fruits. Since high-quality data are a key requirement in modelling, a range of must-have parameters and variables is proposed.

Combined Drought and Heat Activates Protective Responses in Eucalyptus globulus That Are Not Activated When Subjected to Drought or Heat Stress Alone

Aiming to mimic a more realistic field condition and to determine convergent and divergent responses of individual stresses in relation to their combination, we explored physiological, biochemical, and metabolomic alterations after drought and heat stress imposition (alone and combined) and recovery, using a drought-tolerant Eucalyptus globulus clone. When plants were exposed to drought alone, the main responses included reduced pre-dawn water potential (Ψpd) and gas exchange. This was accompanied by increases in malondialdehyde (MDA) and total glutathione, indicative of oxidative stress. Abscisic acid (ABA) levels increased while the content of jasmonic acid (JA) fell. Metabolic alterations included reductions in the levels of sugar phosphates accompanied by increases in starch and non-structural carbohydrates. Levels of α-glycerophosphate and shikimate were also reduced while free amino acids increased. On the other hand, heat alone triggered an increase in relative water content (RWC) and Ψpd. Photosynthetic rate and pigments were reduced accompanied by a reduction in water use efficiency. Heat-induced a reduction of salicylic acid (SA) and JA content. Sugar alcohols and several amino acids were enhanced by the heat treatment while starch, fructose-6-phosphate, glucose-6-phosphate, and α-glycerophosphate were reduced. Contrary to what was observed under drought, heat stress activated the shikimic acid pathway. Drought-stressed plants subject to a heat shock exhibited a sharp decrease in gas exchange, Ψpd and JA, no alterations in electrolyte leakage, MDA, starch, and pigments and increased glutathione pool in relation to control. Comparing this with drought stress alone, subjecting drought stressed plants to an additional heat stress alleviated Ψpd and MDA, maintained an increased glutathione pool and reduced starch content and non-structural carbohydrates. A novel response triggered by the combined stress was the accumulation of cinnamate. Regarding recovery, most of the parameters affected by each stress condition reversed after re-establishment of control growing conditions. These results highlight that the combination of drought and heat provides significant protection from more detrimental effects of drought-stressed eucalypts, confirming that combined stress alter plant metabolism in a novel manner that cannot be extrapolated by the sum of the different stresses applied individually.

Data Reduction Approaches for Dissecting Transcriptional Effects on Metabolism

The availability of high-throughput data from transcriptomics and metabolomics technologies provides the opportunity to characterize the transcriptional effects on metabolism. Here we propose and evaluate two computational approaches rooted in data reduction techniques to identify and categorize transcriptional effects on metabolism by combining data on gene expression and metabolite levels. The approaches determine the partial correlation between two metabolite data profiles upon control of given principal components extracted from transcriptomics data profiles. Therefore, they allow us to investigate both data types with all features simultaneously without doing preselection of genes. The proposed approaches allow us to categorize the relation between pairs of metabolites as being under transcriptional or post-transcriptional regulation. The resulting classification is compared to existing literature and accumulated evidence about regulatory mechanism of reactions and pathways in the cases of Escherichia coli, Saccharomycies cerevisiae, and Arabidopsis thaliana.

The natural variance of the Arabidopsis floral secondary metabolites

Application of mass spectrometry-based metabolomics enables the detection of genotype-related natural variance in metabolism. Differences in secondary metabolite composition of flowers of 64 Arabidopsis thaliana (Arabidopsis) natural accessions, representing a considerable portion of the natural variation in this species are presented. The raw metabolomic data of the accessions and reference extracts derived from flavonoid knockout mutants have been deposited in the MetaboLights database. Additionally, summary tables of floral secondary metabolite data are presented in this article to enable efficient re-use of the dataset either in metabolomics cross-study comparisons or correlation-based integrative analysis of other metabolomic and phenotypic features such as transcripts, proteins and growth and flowering related phenotypes.

Relationships between drought, heat and air humidity responses revealed by transcriptome-metabolome co-analysis

BACKGROUND

Elevated temperature and reduced water availability are frequently linked abiotic stresses that may provoke distinct as well as interacting molecular responses. Based on non-targeted metabolomic and transcriptomic measurements from Arabidopsis rosettes, this study aims at a systematic elucidation of relevant components in different drought and heat scenarios as well as relationships between molecular players of stress response.

RESULTS

In combined drought-heat stress, the majority of single stress responses are maintained. However, interaction effects between drought and heat can be discovered as well; these relate to protein folding, flavonoid biosynthesis and growth inhibition, which are enhanced, reduced or specifically induced in combined stress, respectively. Heat stress experiments with and without supplementation of air humidity for maintenance of vapor pressure deficit suggest that decreased relative air humidity due to elevated temperature is an important component of heat stress, specifically being responsible for hormone-related responses to water deprivation. Remarkably, this "dry air effect" is the primary trigger of the metabolomic response to heat. In contrast, the transcriptomic response has a substantial temperature component exceeding the dry air component and including up-regulation of many transcription factors and protein folding-related genes. Data level integration independent of prior knowledge on pathways and condition labels reveals shared drought and heat responses between transcriptome and metabolome, biomarker candidates and co-regulation between genes and metabolic compounds, suggesting novel players in abiotic stress response pathways.

CONCLUSIONS

Drought and heat stress interact both at transcript and at metabolite response level. A comprehensive, non-targeted view of this interaction as well as non-interacting processes is important to be taken into account when improving tolerance to abiotic stresses in breeding programs. Transcriptome and metabolome may respond with different extent to individual stress components. Their contrasting behavior in response to temperature stress highlights that the protein folding machinery effectively shields the metabolism from stress. Disentangling the complex relationships between transcriptome and metabolome in response to stress is an enormous challenge. As demonstrated by case studies with supporting evidence from additional data, the large dataset provided in this study may assist in determining linked genetic and metabolic features as candidates for future mechanistic analyses.

Current understanding of the pathways of flavonoid biosynthesis in model and crop plants

Flavonoids are a signature class of secondary metabolites formed from a relatively simple collection of scaffolds. They are extensively decorated by chemical reactions including glycosylation, methylation, and acylation. They are present in a wide variety of fruits and vegetables and as such in Western populations it is estimated that 20-50 mg of flavonoids are consumed daily per person. In planta they have demonstrated to contribute to both flower color and UV protection. Their consumption has been suggested to presenta wide range of health benefits. Recent technical advances allowing affordable whole genome sequencing, as well as a better inventory of species-by-species chemical diversity, have greatly advanced our understanding as to how flavonoid biosynthesis pathways vary across species. In parallel, reverse genetics combined with detailed molecular phenotyping is currently allowing us to elucidate the functional importance of individual genes and metabolites and by this means to provide further mechanistic insight into their biological roles. Here we provide an inventory of current knowledge of pathways of flavonoid biosynthesis in both the model plant Arabidopsis thaliana and a range of crop species, including tomato, maize, rice, and bean.

From chromatogram to analyte to metabolite. How to pick horses for courses from the massive web resources for mass spectral plant metabolomics

The grand challenge currently facing metabolomics is the expansion of the coverage of the metabolome from a minor percentage of the metabolic complement of the cell toward the level of coverage afforded by other post-genomic technologies such as transcriptomics and proteomics. In plants, this problem is exacerbated by the sheer diversity of chemicals that constitute the metabolome, with the number of metabolites in the plant kingdom generally considered to be in excess of 200 000. In this review, we focus on web resources that can be exploited in order to improve analyte and ultimately metabolite identification and quantification. There is a wide range of available software that not only aids in this but also in the related area of peak alignment; however, for the uninitiated, choosing which program to use is a daunting task. For this reason, we provide an overview of the pros and cons of the software as well as comments regarding the level of programing skills required to effectively exploit their basic functions. In addition, the torrent of available genome and transcriptome sequences that followed the advent of next-generation sequencing has opened up further valuable resources for metabolite identification. All things considered, we posit that only via a continued communal sharing of information such as that deposited in the databases described within the article are we likely to be able to make significant headway toward improving our coverage of the plant metabolome.

Integrated genomics-based mapping reveals the genetics underlying maize flavonoid biosynthesis

BACKGROUND

Flavonoids constitute a diverse class of secondary metabolites which exhibit potent bioactivities for human health and have been indicated to play an important role in plant development and defense. However, accumulation and variation of flavonoid content in diverse maize lines and the genes responsible for their biosynthesis in this important crop remain largely unknown. In this study, we combine genetic mapping, metabolite profiling and gene regulatory network analysis to further enhance understanding of the maize flavonoid pathway.

RESULTS

We repeatedly detected 25 QTL corresponding to 23 distinct flavonoids across different environments or populations. In addition, a total of 39 genes were revealed both by an expression based network analysis and genetic mapping. Finally, the function of three candidate genes, including two UDP-glycosyltransferases (UGT) and an oxygenase which belongs to the flavone synthase super family, was revealed via preliminary molecular functional characterization.

CONCLUSION

We explored the genetic influences on the flavonoid biosynthesis based on integrating the genomic, transcriptomic and metabolomic information which provided a rich source of potential candidate genes. The integrated genomics based genetic mapping strategy is highly efficient for defining the complexity of functional genetic variants and their respective regulatory networks as well as in helping to select candidate genes and allelic variance before embarking on laborious transgenic validations.

Genome-metabolite associations revealed low heritability, high genetic complexity, and causal relations for leaf metabolites in winter wheat (Triticum aestivum)

We investigated associations between the metabolic phenotype, consisting of quantitative data of 76 metabolites from 135 contrasting winter wheat (Triticum aestivum) lines, and 17 372 single nucleotide polymorphism (SNP) markers. Metabolite profiles were generated from flag leaves of plants from three different environments, with average repeatabilities of 0.5-0.6. The average heritability of 0.25 was unaffected by the heading date. Correlations among metabolites reflected their functional grouping, highlighting the strict coordination of various routes of the citric acid cycle. Genome-wide association studies identified significant associations for six metabolic traits, namely oxalic acid, ornithine, L-arginine, pentose alcohol III, L-tyrosine, and a sugar oligomer (oligo II), with between one and 17 associated SNPs. Notable associations with genes regulating transcription or translation explained between 2.8% and 32.5% of the genotypic variance (pG). Further candidate genes comprised metabolite carriers (pG 32.5-38.1%), regulatory proteins (pG 0.3-11.1%), and metabolic enzymes (pG 2.5-32.5%). The combinatorial use of genomic and metabolic data to construct partially directed networks revealed causal inferences in the correlated metabolite traits and associated SNPs. The evaluated causal relationships will provide a basis for predicting the effects of genetic interferences on groups of correlated metabolic traits, and thus on specific metabolic phenotypes.

Characterization of a recently evolved flavonol-phenylacyltransferase gene provides signatures of natural light selection in Brassicaceae

Incidence of natural light stress renders it important to enhance our understanding of the mechanisms by which plants protect themselves from harmful effects of UV-B irradiation, as this is critical for fitness of land plant species. Here we describe natural variation of a class of phenylacylated-flavonols (saiginols), which accumulate to high levels in floral tissues of Arabidopsis. They were identified in a subset of accessions, especially those deriving from latitudes between 16° and 43° North. Investigation of introgression line populations using metabolic and transcript profiling, combined with genomic sequence analysis, allowed the identification of flavonol-phenylacyltransferase 2 (FPT2) that is responsible for the production of saiginols and conferring greater UV light tolerance in planta. Furthermore, analysis of polymorphism within the FPT duplicated region provides an evolutionary framework of the natural history of this locus in the Brassicaceae.