Metabolomics reveals comprehensive reprogramming involving two independent metabolic responses of Arabidopsis to UV-B light

Analysis of T-DNA alleles of flavonoid biosynthesis genes in Arabidopsis ecotype Columbia

BACKGROUND

The flavonoid pathway is a long-standing and important tool for plant genetics, biochemistry, and molecular biology. Numerous flavonoid mutants have been identified in Arabidopsis over the past several decades in a variety of ecotypes. Here we present an analysis of Arabidopsis lines of ecotype Columbia carrying T-DNA insertions in genes encoding enzymes of the central flavonoid pathway. We also provide a comprehensive summary of various mutant alleles for these structural genes that have been described in the literature to date in a wide variety of ecotypes.

FINDINGS

The confirmed knockout lines present easily-scorable phenotypes due to altered pigmentation of the seed coat (or testa). Knockouts for seven alleles for six flavonoid biosynthetic genes were confirmed by PCR and characterized by UPLC for altered flavonol content.

CONCLUSION

Seven mutant lines for six genes of the central flavonoid pathway were characterized in ecotype, Columbia. These lines represent a useful resource for integrating biochemical and physiological studies with genomic, transcriptomic, and proteomic data, much of which has been, and continues to be, generated in the Columbia background.

The use of metabolomics to dissect plant responses to abiotic stresses

Plant metabolism is perturbed by various abiotic stresses. As such the metabolic network of plants must be reconfigured under stress conditions in order to allow both the maintenance of metabolic homeostasis and the production of compounds that ameliorate the stress. The recent development and adoption of metabolomics and systems biology approaches enable us not only to gain a comprehensive overview, but also a detailed analysis of crucial components of the plant metabolic response to abiotic stresses. In this review we introduce the analytical methods used for plant metabolomics and describe their use in studies related to the metabolic response to water, temperature, light, nutrient limitation, ion and oxidative stresses. Both similarity and specificity of the metabolic responses against diverse abiotic stress are evaluated using data available in the literature. Classically discussed stress compounds such as proline, γ-amino butyrate and polyamines are reviewed, and the widespread importance of branched chain amino acid metabolism under stress condition is discussed. Finally, where possible, mechanistic insights into metabolic regulatory processes are discussed.

Global profiling of ultraviolet-induced metabolic disruption in Melissa officinalis by using gas chromatography-mass spectrometry

Melissa officinalis contains various secondary metabolites that have health benefits. Generally, irradiating plants with ultraviolet (UV)-B induces the accumulation of secondary metabolites in plants. To understand the effect of UV-B irradiation on the metabolism of M. officinalis, metabolomics based on gas chromatography-mass spectrometry (GC-MS) was used in this study. The GC-MS analysis revealed 37 identified metabolites from various chemical classes, including alcohols, amino acids, inorganic acids, organic acids, and sugars. The metabolite profiles of the groups of M. officinalis irradiated with UV-B were separated and differentiated according to their irradiation times (i.e., 0, 1, and 2 h), using principal component analysis (PCA) and hierarchical clustering analysis (HCA), respectively. The PCA score plots of PC1 and PC2 showed that the three groups with different irradiation times followed a certain trajectory with increasing UV-B irradiation. HCA revealed that metabolic patterns differed among the three groups, and the 1 h-irradiated group was more similar to the control group (0 h) than the 2 h-irradiated group. In particular, UV-B irradiation of plants led to a decrease in sugars such as fructose, galactose, sucrose, and trehalose and an increase in metabolites in the tricarboxylic acid cycle, the proline-linked pentose phosphate pathway, and the phenylpropanoid pathway. This study demonstrated that metabolite profiling with GC-MS is useful for gaining a holistic understanding of UV-induced changes in plant metabolism.

Exome sequencing and advances in crop improvement

Next-generation sequencing strategies have opened new vistas for molecular plant breeding. The sequence information obtained by the advent of next-generation sequencing provides a valuable tool not only for improving domesticated crops but also for investigating the natural evolution of crops. Such information provides an enormous potential for sustainable agriculture. In this review, we discuss how such sequencing approaches have transformed exome sequencing into a practical utility that has enormous potential for crop improvement in agriculture. Furthermore, we also describe the future of crop improvement beyond the exome sequencing strategies.

Two glycosyltransferases involved in anthocyanin modification delineated by transcriptome independent component analysis in Arabidopsis thaliana

To identify candidate genes involved in Arabidopsis flavonoid biosynthesis, we applied transcriptome coexpression analysis and independent component analyses with 1388 microarray data from publicly available databases. Two glycosyltransferases, UGT79B1 and UGT84A2 were found to cluster with anthocyanin biosynthetic genes. Anthocyanin was drastically reduced in ugt79b1 knockout mutants. Recombinant UGT79B1 protein converted cyanidin 3-O-glucoside to cyanidin 3-O-xylosyl(1→2)glucoside. UGT79B1 recognized 3-O-glucosylated anthocyanidins/flavonols and uridine diphosphate (UDP)-xylose, but not 3,5-O-diglucosylated anthocyanidins, indicating that UGT79B1 encodes anthocyanin 3-O-glucoside: 2''-O-xylosyltransferase. UGT84A2 is known to encode sinapic acid: UDP-glucosyltransferase. In ugt84a2 knockout mutants, a major sinapoylated anthocyanin was drastically reduced. A comparison of anthocyanin profiles in ugt84a knockout mutants indicated that UGT84A2 plays a major role in sinapoylation of anthocyanin, and that other UGT84As contribute the production of 1-O-sinapoylglucose to a lesser extent. These data suggest major routes from cyanidin 3-O-glucoside to the most highly modified cyanidin in the potential intricate anthocyanin modification pathways in Arabidopsis.

Recent advances of metabolomics in plant biotechnology

Biotechnology, including genetic modification, is a very important approach to regulate the production of particular metabolites in plants to improve their adaptation to environmental stress, to improve food quality, and to increase crop yield. Unfortunately, these approaches do not necessarily lead to the expected results due to the highly complex mechanisms underlying metabolic regulation in plants. In this context, metabolomics plays a key role in plant molecular biotechnology, where plant cells are modified by the expression of engineered genes, because we can obtain information on the metabolic status of cells via a snapshot of their metabolome. Although metabolome analysis could be used to evaluate the effect of foreign genes and understand the metabolic state of cells, there is no single analytical method for metabolomics because of the wide range of chemicals synthesized in plants. Here, we describe the basic analytical advancements in plant metabolomics and bioinformatics and the application of metabolomics to the biological study of plants.

Flavonoids: biosynthesis, biological functions, and biotechnological applications

Flavonoids are widely distributed secondary metabolites with different metabolic functions in plants. The elucidation of the biosynthetic pathways, as well as their regulation by MYB, basic helix-loop-helix (bHLH), and WD40-type transcription factors, has allowed metabolic engineering of plants through the manipulation of the different final products with valuable applications. The present review describes the regulation of flavonoid biosynthesis, as well as the biological functions of flavonoids in plants, such as in defense against UV-B radiation and pathogen infection, nodulation, and pollen fertility. In addition, we discuss different strategies and achievements through the genetic engineering of flavonoid biosynthesis with implication in the industry and the combinatorial biosynthesis in microorganisms by the reconstruction of the pathway to obtain high amounts of specific compounds.

Advances in omics and bioinformatics tools for systems analyses of plant functions

Omics and bioinformatics are essential to understanding the molecular systems that underlie various plant functions. Recent game-changing sequencing technologies have revitalized sequencing approaches in genomics and have produced opportunities for various emerging analytical applications. Driven by technological advances, several new omics layers such as the interactome, epigenome and hormonome have emerged. Furthermore, in several plant species, the development of omics resources has progressed to address particular biological properties of individual species. Integration of knowledge from omics-based research is an emerging issue as researchers seek to identify significance, gain biological insights and promote translational research. From these perspectives, we provide this review of the emerging aspects of plant systems research based on omics and bioinformatics analyses together with their associated resources and technological advances.

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.

Effects of abiotic stress on plants: a systems biology perspective

The natural environment for plants is composed of a complex set of abiotic stresses and biotic stresses. Plant responses to these stresses are equally complex. Systems biology approaches facilitate a multi-targeted approach by allowing one to identify regulatory hubs in complex networks. Systems biology takes the molecular parts (transcripts, proteins and metabolites) of an organism and attempts to fit them into functional networks or models designed to describe and predict the dynamic activities of that organism in different environments. In this review, research progress in plant responses to abiotic stresses is summarized from the physiological level to the molecular level. New insights obtained from the integration of omics datasets are highlighted. Gaps in our knowledge are identified, providing additional focus areas for crop improvement research in the future.

Analysis of the compartmentalized metabolome - a validation of the non-aqueous fractionation technique

With the development of high-throughput metabolic technologies, a plethora of primary and secondary compounds have been detected in the plant cell. However, there are still major gaps in our understanding of the plant metabolome. This is especially true with regards to the compartmental localization of these identified metabolites. Non-aqueous fractionation (NAF) is a powerful technique for the determination of subcellular metabolite distributions in eukaryotic cells, and it has become the method of choice to analyze the distribution of a large number of metabolites concurrently. However, the NAF technique produces a continuous gradient of metabolite distributions, not discrete assignments. Resolution of these distributions requires computational analyses based on marker molecules to resolve compartmental localizations. In this article we focus on expanding the computational analysis of data derived from NAF. Along with an experimental workflow, we describe the critical steps in NAF experiments and how computational approaches can aid in assessing the quality and robustness of the derived data. For this, we have developed and provide a new version (v1.2) of the BestFit command line tool for calculation and evaluation of subcellular metabolite distributions. Furthermore, using both simulated and experimental data we show the influence on estimated subcellular distributions by modulating important parameters, such as the number of fractions taken or which marker molecule is selected. Finally, we discuss caveats and benefits of NAF analysis in the context of the compartmentalized metabolome.

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

Although plant metabolomics is largely carried out on Arabidopsis it is essentially genome-independent, and thus potentially applicable to a wide range of species. However, transfer between species, or even between different tissues of the same species, is not facile. This is because the reliability of protocols for harvesting, handling and analysis depends on the biological features and chemical composition of the plant tissue. In parallel with the diversification of model species it is important to establish good handling and analytic practice, in order to augment computational comparisons between tissues and species. Liquid chromatography-mass spectrometry (LC-MS)-based metabolomics is one of the powerful approaches for metabolite profiling. By using a combination of different extraction methods, separation columns, and ion detection, a very wide range of metabolites can be analyzed. However, its application requires careful attention to exclude potential pitfalls, including artifactual changes in metabolite levels during sample preparation under variations of light or temperature and analytic errors due to ion suppression. Here we provide case studies with two different LC-MS-based metabolomics platforms and four species (Arabidopsis thaliana, Chlamydomonas reinhardtii, Solanum lycopersicum, and Oryza sativa) that illustrate how such dangers can be detected and circumvented.