Plantmetabolomics.org: mass spectrometry-based Arabidopsis metabolomics--database and tools update

Decoding Metabolic Reprogramming in Plants under Pathogen Attacks, a Comprehensive Review of Emerging Metabolomics Technologies to Maximize Their Applications

In their environment, plants interact with a multitude of living organisms and have to cope with a large variety of aggressions of biotic or abiotic origin. What has been known for several decades is that the extraordinary variety of chemical compounds the plants are capable of synthesizing may be estimated in the range of hundreds of thousands, but only a fraction has been fully characterized to be implicated in defense responses. Despite the vast importance of these metabolites for plants and also for human health, our knowledge about their biosynthetic pathways and functions is still fragmentary. Recent progress has been made particularly for the phenylpropanoids and oxylipids metabolism, which is more emphasized in this review. With an increasing interest in monitoring plant metabolic reprogramming, the development of advanced analysis methods should now follow. This review capitalizes on the advanced technologies used in metabolome mapping in planta, including different metabolomics approaches, imaging, flux analysis, and interpretation using bioinformatics tools. Advantages and limitations with regards to the application of each technique towards monitoring which metabolite class or type are highlighted, with special emphasis on the necessary future developments to better mirror such intricate metabolic interactions in planta.

Creation of a Plant Metabolite Spectral Library for Untargeted and Targeted Metabolomics

Large-scale high throughput metabolomic technologies are indispensable components of systems biology in terms of discovering and defining the metabolite parts of the system. However, the lack of a plant metabolite spectral library limits the metabolite identification of plant metabolomic studies. Here, we have created a plant metabolite spectral library using 544 authentic standards, which increased the efficiency of identification for untargeted metabolomic studies. The process of creating the spectral library was described, and the mzVault library was deposited in the public repository for free download. Furthermore, based on the spectral library, we describe a process of creating a pseudo-targeted method, which was applied to a proof-of-concept study of Arabidopsis leaf extracts. As authentic standards become available, more metabolite spectra can be easily incorporated into the spectral library to improve the mzVault package.

Metabolomic analysis of untargeted bovine uterine secretions in dairy cows with endometritis using ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry

Endometritis is among the most common bovine uterine diseases; as a cause of infertility, it affects the progress of the cattle industry. In this study, we used a novel technique based on ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry for comparative metabolomics of uterine secretions in healthy cows and cows with endometritis, classified based on clinical symptoms. Univariate and multivariate statistical analyses revealed significant differences between the two groups (n = 12). Compared with healthy uterine secretion samples, in the clinical endometritis samples, coumaric acid, benzoic acid, and equol were downregulated. However, l-phenylalanine, glutamine, succinic acid, linoleate, arachidonic acid, and other metabolites were upregulated, revealing variations between healthy cows and cows with endometritis (p < 0.05). This metabolomic approach may provide an in-depth understanding of endometritis pathobiology, along with a theoretical framework for the diagnosis and treatment of this bovine disease.

UPLC-HRMS-based untargeted metabolic profiling reveals changes in chickpea (Cicer arietinum) metabolome following long-term drought stress

Genetic improvement for drought tolerance in chickpea requires a solid understanding of biochemical processes involved with different physiological mechanisms. The objective of this study is to demonstrate genetic variations in altered metabolic levels in chickpea varieties (tolerant and sensitive) grown under contrasting water regimes through ultrahigh-performance liquid chromatography/high-resolution mass spectrometry-based untargeted metabolomic profiling. Chickpea plants were exposed to drought stress at the 3-leaf stage for 25 days, and the leaves were harvested at 14 and 25 days after the imposition of drought stress. Stress produced significant reduction in chlorophyll content, F_v /F_m , relative water content, and shoot and root dry weight. Twenty known metabolites were identified as most important by 2 different methods including significant analysis of metabolites and partial least squares discriminant analysis. The most pronounced increase in accumulation due to drought stress was demonstrated for allantoin, l-proline, l-arginine, l-histidine, l-isoleucine, and tryptophan. Metabolites that showed a decreased level of accumulation under drought conditions were choline, phenylalanine, gamma-aminobutyric acid, alanine, phenylalanine, tyrosine, glucosamine, guanine, and aspartic acid. Aminoacyl-tRNA and plant secondary metabolite biosynthesis and amino acid metabolism or synthesis pathways were involved in producing genetic variation under drought conditions. Metabolic changes in light of drought conditions highlighted pools of metabolites that affect the metabolic and physiological adjustment in chickpea that reduced drought impacts.

Patterns of metabolite changes identified from large-scale gene perturbations in Arabidopsis using a genome-scale metabolic network

Metabolomics enables quantitative evaluation of metabolic changes caused by genetic or environmental perturbations. However, little is known about how perturbing a single gene changes the metabolic system as a whole and which network and functional properties are involved in this response. To answer this question, we investigated the metabolite profiles from 136 mutants with single gene perturbations of functionally diverse Arabidopsis (Arabidopsis thaliana) genes. Fewer than 10 metabolites were changed significantly relative to the wild type in most of the mutants, indicating that the metabolic network was robust to perturbations of single metabolic genes. These changed metabolites were closer to each other in a genome-scale metabolic network than expected by chance, supporting the notion that the genetic perturbations changed the network more locally than globally. Surprisingly, the changed metabolites were close to the perturbed reactions in only 30% of the mutants of the well-characterized genes. To determine the factors that contributed to the distance between the observed metabolic changes and the perturbation site in the network, we examined nine network and functional properties of the perturbed genes. Only the isozyme number affected the distance between the perturbed reactions and changed metabolites. This study revealed patterns of metabolic changes from large-scale gene perturbations and relationships between characteristics of the perturbed genes and metabolic changes.

Metabolomic Characterization of Knockout Mutants in Arabidopsis: Development of a Metabolite Profiling Database for Knockout Mutants in Arabidopsis

Despite recent intensive research efforts in functional genomics, the functions of only a limited number of Arabidopsis (Arabidopsis thaliana) genes have been determined experimentally, and improving gene annotation remains a major challenge in plant science. As metabolite profiling can characterize the metabolomic phenotype of a genetic perturbation in the plant metabolism, it provides clues to the function(s) of genes of interest. We chose 50 Arabidopsis mutants, including a set of characterized and uncharacterized mutants, that resemble wild-type plants. We performed metabolite profiling of the plants using gas chromatography-mass spectrometry. To make the data set available as an efficient public functional genomics tool for hypothesis generation, we developed the Metabolite Profiling Database for Knock-Out Mutants in Arabidopsis (MeKO). It allows the evaluation of whether a mutation affects metabolism during normal plant growth and contains images of mutants, data on differences in metabolite accumulation, and interactive analysis tools. Nonprocessed data, including chromatograms, mass spectra, and experimental metadata, follow the guidelines set by the Metabolomics Standards Initiative and are freely downloadable. Proof-of-concept analysis suggests that MeKO is highly useful for the generation of hypotheses for genes of interest and for improving gene annotation. MeKO is publicly available at http://prime.psc.riken.jp/meko/.

MS-based metabolomics facilitates the discovery of in vivo functional small molecules with a diversity of biological contexts

In vivo small molecules as necessary intermediates are involved in numerous critical metabolic pathways and biological processes associated with many essential biological functions and events. There is growing evidence that MS-based metabolomics is emerging as a powerful tool to facilitate the discovery of functional small molecules that can better our understanding of development, infection, nutrition, disease, toxicity, drug therapeutics, gene modifications and host-pathogen interaction from metabolic perspectives. However, further progress must still be made in MS-based metabolomics because of the shortcomings in the current technologies and knowledge. This technique-driven review aims to explore the discovery of in vivo functional small molecules facilitated by MS-based metabolomics and to highlight the analytic capabilities and promising applications of this discovery strategy. Moreover, the biological significance of the discovery of in vivo functional small molecules with different biological contexts is also interrogated at a metabolic perspective.

Metabolomics in plant environmental physiology

Changes in plant metabolism are at the heart of plant developmental processes, underpinning many of the ways in which plants respond to the environment. As such, the comprehensive study of plant metabolism, or metabolomics, is highly valuable in identifying phenotypic effects of abiotic and biotic stresses on plants. When study is in reference to analysing samples that are relevant to environmental or ecologically based hypotheses, it is termed 'environmental metabolomics'. The emergence of environmental metabolomics as one of the latest of the omics technologies has been one of the most critically important recent developments in plant physiology. Its applications broach the entire landscape of plant ecology, from the understanding of plant plasticity and adaptation through to community composition and even genetic modification in crops. The multitude of novel studies published utilizing metabolomics methods employ a variety of techniques, from the initial stages of tissue sampling, through to sample preservation, transportation, and analysis. This review introduces the concept and applications of plant environmental metabolomics as an ecologically important investigative tool. It examines the main techniques used in situ within field sites, with particular reference to sampling and processing, and those more appropriate for use in laboratory-based settings with emphasis on secondary metabolite analysis.

Understanding the molecular signatures in leaves and flowers by desorption electrospray ionization mass spectrometry (DESI MS) imaging

The difference in size, shape, and chemical cues of leaves and flowers display the underlying genetic makeup and their interactions with the environment. The need to understand the molecular signatures of these fragile plant surfaces is illustrated with a model plant, Madagascar periwinkle (Catharanthus roseus (L.) G. Don). Flat, thin layer chromatographic imprints of leaves/petals were imaged using desorption electrospray ionization mass spectrometry (DESI MS), and the results were compared with electrospray ionization mass spectrometry (ESI MS) of their extracts. Tandem mass spectrometry with DESI and ESI, in conjunction with database records, confirmed the molecular species. This protocol has been extended to other plants. Implications of this study in identifying varietal differences, toxic metabolite production, changes in metabolites during growth, pest/pathogen attack, and natural stresses are shown with illustrations. The possibility to image subtle features like eye color of petals, leaf vacuole, leaf margin, and veins is demonstrated.

Phytochemical genomics--a new trend

Phytochemical genomics is a recently emerging field, which investigates the genomic basis of the synthesis and function of phytochemicals (plant metabolites), particularly based on advanced metabolomics. The chemical diversity of the model plant Arabidopsis thaliana is larger than previously expected, and the gene-to-metabolite correlations have been elucidated mostly by an integrated analysis of transcriptomes and metabolomes. For example, most genes involved in the biosynthesis of flavonoids in Arabidopsis have been characterized by this method. A similar approach has been applied to the functional genomics for production of phytochemicals in crops and medicinal plants. Great promise is seen in metabolic quantitative loci analysis in major crops such as rice and tomato, and identification of novel genes involved in the biosynthesis of bioactive specialized metabolites in medicinal plants.

Recent progress in the development of metabolome databases for plant systems biology

Metabolomics has grown greatly as a functional genomics tool, and has become an invaluable diagnostic tool for biochemical phenotyping of biological systems. Over the past decades, a number of databases involving information related to mass spectra, compound names and structures, statistical/mathematical models and metabolic pathways, and metabolite profile data have been developed. Such databases complement each other and support efficient growth in this area, although the data resources remain scattered across the World Wide Web. Here, we review available metabolome databases and summarize the present status of development of related tools, particularly focusing on the plant metabolome. Data sharing discussed here will pave way for the robust interpretation of metabolomic data and advances in plant systems biology.

Medicinal plants: a public resource for metabolomics and hypothesis development

Specialized compounds from photosynthetic organisms serve as rich resources for drug development. From aspirin to atropine, plant-derived natural products have had a profound impact on human health. Technological advances provide new opportunities to access these natural products in a metabolic context. Here, we describe a database and platform for storing, visualizing and statistically analyzing metabolomics data from fourteen medicinal plant species. The metabolomes and associated transcriptomes (RNAseq) for each plant species, gathered from up to twenty tissue/organ samples that have experienced varied growth conditions and developmental histories, were analyzed in parallel. Three case studies illustrate different ways that the data can be integrally used to generate testable hypotheses concerning the biochemistry, phylogeny and natural product diversity of medicinal plants. Deep metabolomics analysis of Camptotheca acuminata exemplifies how such data can be used to inform metabolic understanding of natural product chemical diversity and begin to formulate hypotheses about their biogenesis. Metabolomics data from Prunella vulgaris, a species that contains a wide range ofantioxidant, antiviral, tumoricidal and anti-inflammatory constituents, provide a case study of obtaining biosystematic and developmental fingerprint information from metabolite accumulation data in a little studied species. Digitalis purpurea, well known as a source of cardiac glycosides, is used to illustrate how integrating metabolomics and transcriptomics data can lead to identification of candidate genes encoding biosynthetic enzymes in the cardiac glycoside pathway. Medicinal Plant Metabolomics Resource (MPM) [1] provides a framework for generating experimentally testable hypotheses about the metabolic networks that lead to the generation of specialized compounds, identifying genes that control their biosynthesis and establishing a basis for modeling metabolism in less studied species. The database is publicly available and can be used by researchers in medicine and plant biology.