From models to crop species: caveats and solutions for translational metabolomics

Metabolomics to understand metabolic regulation underpinning fruit ripening, development, and quality

Classically fruit ripening and development was studied using genetic approaches, with understanding of metabolic changes that occurred in concert largely focused on a handful of metabolites including sugars, organic acids, cell wall components, and phytohormones. The advent and widespread application of metabolomics has, however, led to far greater understanding of metabolic components that play a crucial role not only in this process but also in influencing the organoleptic and nutritive properties of the fruits. Here we review how the study of natural variation, mutants, transgenics, and gene-edited fruits has led to a considerable increase in our understanding of these aspects. We focus on fleshy fruits such as tomato but also review berries, receptacle fruits, and stone-bearing fruits. Finally, we offer a perspective as to how comparative analyses and machine learning will likely further improve our comprehension of the functional importance of various metabolites in the future.

Kiwifruit Metabolomics-An Investigation of within Orchard Metabolite Variability of Two Cultivars of Actinidia chinensis

Plant metabolomics within field-based food production systems is challenging owing to environmental variability and the complex architecture and metabolic growth cycles of plants. Kiwifruit cultivars of Actinidia chinensis are vigorous perennial vines grown as clones in highly structured orchard environments, intensively managed to maximize fruit yield and quality. To understand the metabolic responses of vines to orchard management practices, we needed to better understand the various sources of metabolic variability encountered in the orchard. Triplicate composite leaf, internode and fruit (mature and immature) samples were collected from each of six Actinidia chinensis var. deliciosa 'Hayward' and A. chinensis var. chinensis 'Zesy002' kiwifruit vines at three times during the growing season and measured by LC-MS. In general, there was more variation in metabolite concentrations within vines than between vines, with 'Hayward' showing a greater percentage of within-vine variability than 'Zesy002' (c. 90 vs. 70% respectively). In specific tissues, the sampler, infection by Pseudomonas syringae var. actinidiae and the rootstock also influenced metabolite variability. A similar pattern of metabolic variability was observed from quantitative analysis of specific carbohydrates and phytohormones. High within-vine metabolic variability indicates that it is more important to obtain sufficient replicate samples than to sample from multiple vines. These data provide an objective basis for optimizing metabolite sampling strategies within kiwifruit orchards.

Mass spectrometry-based metabolomics: a guide for annotation, quantification and best reporting practices

Mass spectrometry-based metabolomics approaches can enable detection and quantification of many thousands of metabolite features simultaneously. However, compound identification and reliable quantification are greatly complicated owing to the chemical complexity and dynamic range of the metabolome. Simultaneous quantification of many metabolites within complex mixtures can additionally be complicated by ion suppression, fragmentation and the presence of isomers. Here we present guidelines covering sample preparation, replication and randomization, quantification, recovery and recombination, ion suppression and peak misidentification, as a means to enable high-quality reporting of liquid chromatography- and gas chromatography-mass spectrometry-based metabolomics-derived data.

Photorespiration: The Futile Cycle?

Photorespiration, or C₂ photosynthesis, is generally considered a futile cycle that potentially decreases photosynthetic carbon fixation by more than 25%. Nonetheless, many essential processes, such as nitrogen assimilation, C₁ metabolism, and sulfur assimilation, depend on photorespiration. Most studies of photosynthetic and photorespiratory reactions are conducted with magnesium as the sole metal cofactor despite many of the enzymes involved in these reactions readily associating with manganese. Indeed, when manganese is present, the energy efficiency of these reactions may improve. This review summarizes some commonly used methods to quantify photorespiration, outlines the influence of metal cofactors on photorespiratory enzymes, and discusses why photorespiration may not be as wasteful as previously believed.

Metabolite Profiling and Network Analysis Reveal Coordinated Changes in Low-N Tolerant and Low-N Sensitive Maize Genotypes under Nitrogen Deficiency and Restoration Conditions

Nitrogen (N), applied in the form of a nitrogenous fertilizer, is one of the main inputs for agricultural production. Food production is closely associated with the application of N. However, the application of nitrogenous fertilizers to agricultural fields is associated with heavy production of nitrous oxide because agricultural crops can only utilize 30-40% of applied N, leaving behind unused 60-70% N in the environment. The global warming effect of this greenhouse gas is approximately 300 times more than of carbon dioxide. Under the present scenario of climate change, it is critical to maintain the natural balance between food production and environmental sustainability by targeting traits responsible for improving nitrogen-use-efficiency (NUE). Understanding of the molecular mechanisms behind the metabolic alterations due to nitrogen status needs to be addressed. Additionally, mineral nutrient deficiencies and their associated metabolic networks have not yet been studied well. Given this, the alterations in core metabolic pathways of low-N tolerant (LNT) and low-N sensitive (LNS) genotypes of maize under N-deficiency and their efficiency of recovering the changes upon resupplying N were investigated by us, using the GC-MS and LC-MS based metabolomic approach. Significant genotype-specific changes were noted in response to low-N. The N limitation affected the whole plant metabolism, most significantly the precursors of primary metabolic pathways. These precursors may act as important targets for improving the NUE. Limited availability of N reduced the levels of N-containing metabolites, organic acids and amino acids, but soluble sugars increased. Major variations were encountered in LNS, as compared to LNT. This study has revealed potential metabolic targets in response to the N status, which are indeed the prospective targets for crop improvement.

Exploiting Natural Variation in Tomato to Define Pathway Structure and Metabolic Regulation of Fruit Polyphenolics in the Lycopersicum Complex

While the structures of plant primary metabolic pathways are generally well defined and highly conserved across species, those defining specialized metabolism are less well characterized and more highly variable across species. In this study, we investigated polyphenolic metabolism in the lycopersicum complex by characterizing the underlying biosynthetic and decorative reactions that constitute the metabolic network of polyphenols across eight different species of tomato. For this purpose, GC-MS- and LC-MS-based metabolomics of different tissues of Solanum lycopersicum and wild tomato species were carried out, in concert with the evaluation of cross-hybridized microarray data for MapMan-based transcriptomic analysis, and publicly available RNA-sequencing data for annotation of biosynthetic genes. The combined data were used to compile species-specific metabolic networks of polyphenolic metabolism, allowing the establishment of an entire pan-species biosynthetic framework as well as annotation of the functions of decoration enzymes involved in the formation of metabolic diversity of the flavonoid pathway. The combined results are discussed in the context of the current understanding of tomato flavonol biosynthesis as well as a global view of metabolic shifts during fruit ripening. Our results provide an example as to how large-scale biology approaches can be used for the definition and refinement of large specialized metabolism pathways.

Cross-Species Comparison of Fruit-Metabolomics to Elucidate Metabolic Regulation of Fruit Polyphenolics Among Solanaceous Crops

Many solanaceous crops are an important part of the human daily diet. Fruit polyphenolics are plant specialized metabolites that are recognized for their human health benefits and their defensive role against plant abiotic and biotic stressors. Flavonoids and chlorogenates are the major polyphenolic compounds found in solanaceous fruits that vary in quantity, physiological function, and structural diversity among and within plant species. Despite their biological significance, the elucidation of metabolic shifts of polyphenols during fruit ripening in different fruit tissues, has not yet been well-characterized in solanaceous crops, especially at a cross-species and cross-cultivar level. Here, we performed a cross-species comparison of fruit-metabolomics to elucidate the metabolic regulation of fruit polyphenolics from three representative crops of Solanaceae (tomato, eggplant, and pepper), and a cross-cultivar comparison among different pepper cultivars (Capsicum annuum cv.) using liquid chromatography-mass spectrometry (LC-MS). We observed a metabolic trade-off between hydroxycinnamates and flavonoids in pungent pepper and anthocyanin-type pepper cultivars and identified metabolic signatures of fruit polyphenolics in each species from each different tissue-type and fruit ripening stage. Our results provide additional information for metabolomics-assisted crop improvement of solanaceous fruits towards their improved nutritive properties and enhanced stress tolerance.

Application of in vivo solid phase microextraction (SPME) in capturing metabolome of apple (Malus ×domestica Borkh.) fruit

An in vivo direct-immersion SPME sampling coupled to comprehensive two-dimensional gas chromatography – time-of-flight mass spectrometry (GCxGC-ToFMS) was employed to capture real-time changes in the metabolome of ‘Honeycrisp’ apples during ripening on the tree. This novel sampling approach was successful in acquiring a broad metabolic fingerprint, capturing unique metabolites and detecting changes in metabolic profiles associated with fruit maturation. Several metabolites and chemical classes, including volatile esters, phenylpropanoid metabolites, 1-octen-3-ol, hexanal, and (2E,4E)-2,4-hexadienal were found to be up-regulated in response to fruit maturation. For the first time, Amaryllidaceae alkaloids, metabolites with important biological activities, including anti-cancer, anti-viral, anti-parasitic, and acetylcholinesterase (AChE) inhibitory activity, were detected in apples. Considering the elimination of oxidative degradation mechanisms that adversely impact the representativeness of metabolome obtained ex vivo, and further evidence that lipoxygenase (LOX) pathway contributes to volatile production in intact fruit, in vivo DI-SPME represents an attractive approach for global plant metabolite studies.

The Importance of Experimental Design, Quality Assurance, and Control in Plant Metabolomics Experiments

The output of metabolomics relies to a great extent upon the methods and instrumentation to identify, quantify, and access spatial information on as many metabolites as possible. However, the most modern machines and sophisticated tools for data analysis cannot compensate for inappropriate harvesting and/or sample preparation procedures that modify metabolic composition and can lead to erroneous interpretation of results. In addition, plant metabolism has a remarkable degree of complexity, and the number of identified compounds easily surpasses the number of samples in metabolomics analyses, increasing false discovery risk. These aspects pose a large challenge when carrying out plant metabolomics experiments. In this chapter, we address the importance of a proper experimental design taking into consideration preventable complications and unavoidable factors to achieve success in metabolomics analysis. We also focus on quality control and standardized procedures during the metabolomics workflow.

Plant metabolism as studied by NMR spectroscopy

The study of plant metabolism impacts a broad range of domains such as plant cultural practices, plant breeding, human or animal nutrition, phytochemistry and green biotechnologies. Plant metabolites are extremely diverse in terms of structure or compound families as well as concentrations. This review attempts to illustrate how NMR spectroscopy, with its broad variety of experimental approaches, has contributed widely to the study of plant primary or specialized metabolism in very diverse ways. The review presents recent developments of one-dimensional and multi-dimensional NMR methods to study various aspects of plant metabolism. Through recent examples, it highlights how NMR has proved to be an invaluable tool for the global characterization of sample composition within metabolomic studies, and shows some examples of use for targeted phytochemistry, with a special focus on compound identification and quantitation. In such cases, NMR approaches are often used to provide snapshots of the plant sample composition. The review also covers dynamic aspects of metabolism, with a description of NMR techniques to measure metabolic fluxes - in most cases after stable isotope labelling. It is mainly intended for NMR specialists who would be interested to learn more about the potential of their favourite technique in plant sciences and about specific details of NMR approaches in this field. Therefore, as a practical guide, a paragraph on the specific precautions that should be taken for sample preparation is also included. In addition, since the quality of NMR metabolic studies is highly dependent on approaches to data processing and data sharing, a specific part is dedicated to these aspects. The review concludes with perspectives on the emerging methods that could change significantly the role of NMR in the field of plant metabolism by boosting its sensitivity. The review is illustrated throughout with examples of studies selected to represent diverse applications of liquid-state or HR-MAS NMR.

A Systematic Investigation of the Best Buffers for Use in Screening by MALDI-Mass Spectrometry

Matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS) offers a label-free alternative for the screening of biochemical targets in both 1536- and 6144-assay formats, as well as potentially providing increased sensitivity, reproducibility, and the simultaneous detection of multiple assay components within a specified m/z range. Ion suppression effects are one of the principal limitations reported for MS analysis. Within MALDI-MS screening, it has been identified that certain biochemical components incorporated into the assay (e.g., the buffers used to preserve the physiological conditions of the enzyme, salts, and other additives) induce suppression of the analyte ion signals monitored. This poorly understood phenomenon of ion suppression is a key reason the screening community has been reluctant to shift their investigations toward MS methods with reduced sample cleanup. Using acetylcholine as an assay substrate mimic, we have generated robust data to quantify the degree to which the most highly used components (base buffers, additional components, detergents, cell culture media, and other additives) within current screening assays are compatible with MALDI-MS. Here, the most suitable buffers and components, along with their identified optimal concentrations in terms of limiting ion suppression effects, are proposed for use in screening assays measured by MALDI-MS.

Metabolomics-Inspired Insight into Developmental, Environmental and Genetic Aspects of Tomato Fruit Chemical Composition and Quality

Tomato was one of the first plant species to be evaluated using metabolomics and remains one of the best characterized, with tomato fruit being both an important source of nutrition in the human diet and a valuable model system for the development of fleshy fruits. Additionally, given the broad habitat range of members of the tomato clade and the extensive use of exotic germplasm in tomato genetic research, it represents an excellent genetic model system for understanding both metabolism per se and the importance of various metabolites in conferring stress tolerance. This review summarizes technical approaches used to characterize the tomato metabolome to date and details insights into metabolic pathway structure and regulation that have been obtained via analysis of tissue samples taken under different developmental or environmental circumstance as well as following genetic perturbation. Particular attention is paid to compounds of importance for nutrition or the shelf-life of tomatoes. We propose furthermore how metabolomics information can be coupled to the burgeoning wealth of genome sequence data from the tomato clade to enhance further our understanding of (i) the shifts in metabolic regulation occurring during development and (ii) specialization of metabolism within the tomato clade as a consequence of either adaptive evolution or domestication.

Liquid Chromatography-Mass Spectrometry Metabolic and Lipidomic Sample Preparation Workflow for Suspension-Cultured Mammalian Cells using Jurkat T lymphocyte Cells

Metabolomics is the comprehensive study of metabolism as it pertains to an organism or biological system. Lipidomics, a subset discipline of metabolomics, encompasses the study of cellular lipid functions: including pathways, networks, and interactions. The abundance of metabolites and lipids, along with their contribution to health and disease, makes metabolomics a valuable tool for biomarker research. Disease biomarker identification requires a reproducible, sensitive, and accurate analytical platform. Although transcriptomic and proteomic areas have well-established protocols for sample preparation and data processing, the metabolomics field is still developing comparable standardized conventions. Furthermore, of the few comparative LC-MS metabolomic studies that have been applied to mammalian cell cultures, most are targeted to adherent cell lines. The purpose of this work was to optimize a sample preparation workflow for the cellular metabolomic analysis of suspension-cultured mammalian cells using commercially available Jurkat T lymphocytes as a model system. The current investigation evaluated commonly used sample preparation techniques for reproducibility, accuracy, and applicability to untargeted biomarker discovery. Results show ammoniated cell rinsing solutions to be an effective means to remove extracellular components present in the media without causing ion suppression or affecting the integrity of the cellular membrane. Additionally, a novel workflow was designed to allow for the combined analysis of metabolites and lipids from mammalian suspension cells from a single cell pellet. The Folch lipid extraction protocol was coupled to an 80% MeOH metabolite isolation to ensure high extraction efficiency for phospholipids and triacylglycerides. While the workflow was tailored to cells in suspension, it could also be applied to adherent cell lines.

Crop improvement using life cycle datasets acquired under field conditions

Crops are exposed to various environmental stresses in the field throughout their life cycle. Modern plant science has provided remarkable insights into the molecular networks of plant stress responses in laboratory conditions, but the responses of different crops to environmental stresses in the field need to be elucidated. Recent advances in omics analytical techniques and information technology have enabled us to integrate data from a spectrum of physiological metrics of field crops. The interdisciplinary efforts of plant science and data science enable us to explore factors that affect crop productivity and identify stress tolerance-related genes and alleles. Here, we describe recent advances in technologies that are key components for data driven crop design, such as population genomics, chronological omics analyses, and computer-aided molecular network prediction. Integration of the outcomes from these technologies will accelerate our understanding of crop phenology under practical field situations and identify key characteristics to represent crop stress status. These elements would help us to genetically engineer "designed crops" to prevent yield shortfalls because of environmental fluctuations due to future climate change.

Metabolomics-assisted refinement of the pathways of steroidal glycoalkaloid biosynthesis in the tomato clade

Steroidal glycoalkaloids (SGAs) are nitrogen-containing secondary metabolites of the Solanum species, which are known to have large chemical and bioactive diversity in nature. While recent effort and development on LC/MS techniques for SGA profiling have elucidated the main pathways of SGA metabolism in tomato, the problem of peak annotation still remains due to the vast diversity of chemical structure and similar on overlapping of chemical formula. Here we provide a case study of peak classification and annotation approach by integration of species and tissue specificities of SGA accumulation for provision of comprehensive pathways of SGA biosynthesis. In order to elucidate natural diversity of SGA biosynthesis, a total of 169 putative SGAs found in eight tomato accessions (Solanum lycopersicum, S. pimpinellifolium, S. cheesmaniae, S. chmielewskii, S. neorickii, S. peruvianum, S. habrochaites, S. pennellii) and four tissue types were used for correlation analysis. The results obtained in this study contribute annotation and classification of SGAs as well as detecting putative novel biosynthetic branch points. As such this represents a novel strategy for peak annotation for plant secondary metabolites.

Systems Analysis of the Response of Photosynthesis, Metabolism, and Growth to an Increase in Irradiance in the Photosynthetic Model Organism Chlamydomonas reinhardtii

We investigated the systems response of metabolism and growth after an increase in irradiance in the nonsaturating range in the algal model Chlamydomonas reinhardtii. In a three-step process, photosynthesis and the levels of metabolites increased immediately, growth increased after 10 to 15 min, and transcript and protein abundance responded by 40 and 120 to 240 min, respectively. In the first phase, starch and metabolites provided a transient buffer for carbon until growth increased. This uncouples photosynthesis from growth in a fluctuating light environment. In the first and second phases, rising metabolite levels and increased polysome loading drove an increase in fluxes. Most Calvin-Benson cycle (CBC) enzymes were substrate-limited in vivo, and strikingly, many were present at higher concentrations than their substrates, explaining how rising metabolite levels stimulate CBC flux. Rubisco, fructose-1,6-biosphosphatase, and seduheptulose-1,7-bisphosphatase were close to substrate saturation in vivo, and flux was increased by posttranslational activation. In the third phase, changes in abundance of particular proteins, including increases in plastidial ATP synthase and some CBC enzymes, relieved potential bottlenecks and readjusted protein allocation between different processes. Despite reasonable overall agreement between changes in transcript and protein abundance (R2 = 0.24), many proteins, including those in photosynthesis, changed independently of transcript abundance.

Genome-enabled plant metabolomics

The grand challenge currently facing metabolomics is that of comprehensitivity whilst next generation sequencing and advanced proteomics methods now allow almost complete and at least 50% coverage of their respective target molecules, metabolomics platforms at best offer coverage of just 10% of the small molecule complement of the cell. Here we discuss the use of genome sequence information as an enabling tool for peak identity and for translational metabolomics. Whilst we argue that genome information is not sufficient to compute the size of a species metabolome it is highly useful in predicting the occurrence of a wide range of common metabolites. Furthermore, we describe how via gene functional analysis in model species the identity of unknown metabolite peaks can be resolved. Taken together these examples suggest that genome sequence information is current (and likely will remain), a highly effective tool in peak elucidation in mass spectral metabolomics strategies.

Rationales and approaches for studying metabolism in eukaryotic microalgae

The generation of efficient production strains is essential for the use of eukaryotic microalgae for biofuel production. Systems biology approaches including metabolite profiling on promising microalgal strains, will provide a better understanding of their metabolic networks, which is crucial for metabolic engineering efforts. Chlamydomonas reinhardtii represents a suited model system for this purpose. We give an overview to genetically amenable microalgal strains with the potential for biofuel production and provide a critical review of currently used protocols for metabolite profiling on Chlamydomonas. We provide our own experimental data to underpin the validity of the conclusions drawn.

Analysis of metabolic flux using dynamic labelling and metabolic modelling

Metabolic fluxes and the capacity to modulate them are a crucial component of the ability of the plant cell to react to environmental perturbations. Our ability to quantify them and to attain information concerning the regulatory mechanisms that control them is therefore essential to understand and influence metabolic networks. For all but the simplest of flux measurements labelling methods have proven to be the most informative. Both steady-state and dynamic labelling approaches have been adopted in the study of plant metabolism. Here the conceptual basis of these complementary approaches, as well as their historical application in microbial, mammalian and plant sciences, is reviewed, and an update on technical developments in label distribution analyses is provided. This is supported by illustrative cases studies involving the kinetic modelling of secondary metabolism. One issue that is particularly complex in the analysis of plant fluxes is the extensive compartmentation of the plant cell. This problem is discussed from both theoretical and experimental perspectives, and the current approaches used to address it are assessed. Finally, current limitations and future perspectives of kinetic modelling of plant metabolism are discussed.

Utility of metabolomics toward assessing the metabolic basis of quality traits in apple fruit with an emphasis on antioxidants

A gas chromatography-mass spectrometry approach was employed to evaluate the use of metabolite patterns to differentiate fruit from six commercially grown apple cultivars harvested in 2008. Principal component analysis (PCA) of apple fruit peel and flesh data indicated that individual cultivar replicates clustered together and were separated from all other cultivar samples. An independent metabolomics investigation with fruit harvested in 2003 confirmed the separate clustering of fruit from different cultivars. Further evidence for cultivar separation was obtained using a hierarchical clustering analysis. An evaluation of PCA component loadings revealed specific metabolite classes that contributed the most to each principal component, whereas a correlation analysis demonstrated that specific metabolites correlate directly with quality traits such as antioxidant activity, total phenolics, and total anthocyanins, which are important parameters in the selection of breeding germplasm. These data sets lay the foundation for elucidating the metabolic basis of commercially important fruit quality traits.

Analysis of constituents for phenotyping drought tolerance in crop improvement

Investigators now have a wide range of analytical tools to use in measuring metabolites, proteins and transcripts in plant tissues. These tools have the potential to assist genetic studies that seek to phenotype genetic lines for heritable traits that contribute to drought tolerance. To be useful for crop breeding, hundreds or thousands of genetic lines must be assessed. This review considers the utility of assaying certain constituents with roles in drought tolerance for phenotyping genotypes. Abscisic acid (ABA), organic and inorganic osmolytes, compatible solutes, and late embryogenesis abundant proteins, are considered. Confounding effects that require appropriate tissue and timing specificity, and the need for high-throughput and analytical cost efficiency are discussed. With future advances in analytical methods and the value of analyzing constituents that provide information on the underlying mechanisms of drought tolerance, these approaches are expected to contribute to development crops with improved drought tolerance.

Tomato fruit photosynthesis is seemingly unimportant in primary metabolism and ripening but plays a considerable role in seed development

Fruit of tomato (Solanum lycopersicum), like those from many species, have been characterized to undergo a shift from partially photosynthetic to truly heterotrophic metabolism. While there is plentiful evidence for functional photosynthesis in young tomato fruit, the rates of carbon assimilation rarely exceed those of carbon dioxide release, raising the question of its role in this tissue. Here, we describe the generation and characterization of lines exhibiting a fruit-specific reduction in the expression of glutamate 1-semialdehyde aminotransferase (GSA). Despite the fact that these plants contained less GSA protein and lowered chlorophyll levels and photosynthetic activity, they were characterized by few other differences. Indeed, they displayed almost no differences in fruit size, weight, or ripening capacity and furthermore displayed few alterations in other primary or intermediary metabolites. Although GSA antisense lines were characterized by significant alterations in the expression of genes associated with photosynthesis, as well as with cell wall and amino acid metabolism, these changes were not manifested at the phenotypic level. One striking feature of the antisense plants was their seed phenotype: the transformants displayed a reduced seed set and altered morphology and metabolism at early stages of fruit development, although these differences did not affect the final seed number or fecundity. Taken together, these results suggest that fruit photosynthesis is, at least under ambient conditions, not necessary for fruit energy metabolism or development but is essential for properly timed seed development and therefore may confer an advantage under conditions of stress.

Transcriptional and metabolic programs following exposure of plants to UV-B irradiation

In order to adapt to environmental changes of light species and intensity, higher plants furnish complicate signaling systems such as the UVR/COP/HY5 cascade which links several diverse classes of photoreceptors. In addition UV-B light provokes accelerated production of UV-B protectants such as flavonoids and vitamins. Following intensive research efforts, genes in the UV-B signaling cascade have been characterized via forward genetics approaches following mutant screens relying on sensitivity to UV-B irradiation. However detailed processes of the linkage between light signaling and the upregulation of metabolite accumulation remain unclear. Here we review both the light signal cascades and metabolite pathways responding to UV-B exposure. Finally we generate co-expression network analysis using published data in order to find novel candidate genes which link light signaling and transcriptional regulation to metabolic biosynthesis in attempt to describe how these processes are interlinked.