Medicinal plants: a public resource for metabolomics and hypothesis development

Calotropis procera accumulates Uzarigenin and Calotropagenin in response to environmental lighting and drought

Calotropis procera (C. procera) was evaluated as a pharmaceutically useful plant and for its therapeutic effects in the most significant studies. Uzarigenin and Calotropagenin are significant components of this plant that have pharmacological effects on certain systems, including the digestive, immunological, and focal, and peripheral sensory systems. In this study, pathway genes are extracted from high throughput data acc.no. SRR1554320. Seven critical enzymes are involved in studying the effects of sunlight on the formation of Uzaragenin and Calotropagenin in C. procera before and after irrigation. Molecular identification and NCBI submission of six enzyme genes were successful; HSD (acc.no. OQ091761) for 3β-hydroxystroid dehydrogenase, OR (acc.no. OQ091762) for 5beta-pregnan oxidoreductase, MO (acc.no. OQ091763) for Pregnan monooxygenase, HOX (acc.no. OQ091764) for Steroid hydroxylase, MAT (acc.no. OQ091765) for Melonyletransferase, UHOX (acc.no. OQ091766) for Uzarigenin hydroxylase. During dawn after irrigation, the Uzargenin pathway showed the highest activity, however midday after irrigation was the lowest. The most period that showed high activity for the Uzargenin pathway was dawn after irrigation, however, midday after irrigation was the lowest. This data is confirmed by chromatography analysis (UPLC) to calculate the accumulation of Uzarigenin and Calotropagenin in different periods.

Identification of key genes involved in secondary metabolite biosynthesis in Digitalis purpurea

The medicinal plant Digitalis purpurea produces cardiac glycosides that are useful in the pharmaceutical industry. These bioactive compounds are in high demand due to ethnobotany's application to therapeutic procedures. Recent studies have investigated the role of integrative analysis of multi-omics data in understanding cellular metabolic status through systems metabolic engineering approach, as well as its application to genetically engineering metabolic pathways. In spite of numerous omics experiments, most molecular mechanisms involved in metabolic pathways biosynthesis in D. purpurea remain unclear. Using R Package Weighted Gene Co-expression Network Analysis, co-expression analysis was performed on the transcriptome and metabolome data. As a result of our study, we identified transcription factors, transcriptional regulators, protein kinases, transporters, non-coding RNAs, and hub genes that are involved in the production of secondary metabolites. Since jasmonates are involved in the biosynthesis of cardiac glycosides, the candidate genes for Scarecrow-Like Protein 14 (SCL14), Delta24-sterol reductase (DWF1), HYDRA1 (HYD1), and Jasmonate-ZIM domain3 (JAZ3) were validated under methyl jasmonate treatment (MeJA, 100 μM). Despite early induction of JAZ3, which affected downstream genes, it was dramatically suppressed after 48 hours. SCL14, which targets DWF1, and HYD1, which induces cholesterol and cardiac glycoside biosynthesis, were both promoted. The correlation between key genes and main metabolites and validation of expression patterns provide a unique insight into the biosynthesis mechanisms of cardiac glycosides in D. purpurea.

Crosstalk of Multi-Omics Platforms with Plants of Therapeutic Importance

From time immemorial, humans have exploited plants as a source of food and medicines. The World Health Organization (WHO) has recorded 21,000 plants with medicinal value out of 300,000 species available worldwide. The promising modern "multi-omics" platforms and tools have been proven as functional platforms able to endow us with comprehensive knowledge of the proteome, genome, transcriptome, and metabolome of medicinal plant systems so as to reveal the novel connected genetic (gene) pathways, proteins, regulator sequences and secondary metabolite (molecule) biosynthetic pathways of various drug and protein molecules from a variety of plants with therapeutic significance. This review paper endeavors to abridge the contemporary advancements in research areas of multi-omics and the information involved in decoding its prospective relevance to the utilization of plants with medicinal value in the present global scenario. The crosstalk of medicinal plants with genomics, transcriptomics, proteomics, and metabolomics approaches will be discussed.

TOMATOMET: A metabolome database consists of 7118 accurate mass values detected in mature fruits of 25 tomato cultivars

The total number of low-molecular-weight compounds in the plant kingdom, most of which are secondary metabolites, is hypothesized to be over one million, although only a limited number of plant compounds have been characterized. Untargeted analysis, especially using mass spectrometry (MS), has been useful for understanding the plant metabolome; however, due to the limited availability of authentic compounds for MS-based identification, the identities of most of the ion peaks detected by MS remain unknown. Accurate mass values of peaks obtained by high accuracy mass measurement and, if available, MS/MS fragmentation patterns provide abundant annotation for each peak. Here, we carried out an untargeted analysis of compounds in the mature fruit of 25 tomato cultivars using liquid chromatography-Orbitrap MS for accurate mass measurement, followed by manual curation to construct the metabolome database TOMATOMET (http://metabolites.in/tomato-fruits/). The database contains 7,118 peaks with accurate mass values, in which 1,577 ion peaks are annotated as members of a chemical group. Remarkably, 71% of the mass values are not found in the accurate masses detected previously in Arabidopsis thaliana, Medicago truncatula or Jatropha curcas, indicating significant chemical diversity among plant species that remains to be solved. Interestingly, substantial chemical diversity exists also among tomato cultivars, indicating that chemical profiling from distinct cultivars contributes towards understanding the metabolome, even in a single organ of a species, and can prioritize some desirable metabolic targets for further applications such as breeding.

Wound Healing Activity of the Essential Oil of Bursera morelensis, in Mice

Bursera morelensis is used in Mexican folk medicine to treat wounds on the skin. It is an endemic tree known as “aceitillo”, and the antibacterial and antifungal activity of its essential oil has been verified; it also acts as an anti-inflammatory. All of these reported biological activities make the essential oil of B. morelensis a candidate to accelerate the wound-healing process. The objective was to determine the wound-healing properties of B. morelensis’ essential oil on a murine model. The essential oil was obtained by hydro-distillation, and the chemical analysis was performed by gas chromatography-mass spectrometry (GC-MS). In the murine model, wound-healing efficacy (WHE) and wound contraction (WC) were evaluated. Cytotoxic activity was evaluated in vitro using peritoneal macrophages from BALB/c mice. The results showed that 18 terpenoid-type compounds were identified in the essential oil. The essential oil had remarkable WHE regardless of the dose and accelerated WC and was not cytotoxic. In vitro tests with fibroblasts showed that cell viability was dose-dependent; by adding 1 mg/mL of essential oil (EO) to the culture medium, cell viability decreased below 80%, while, at doses of 0.1 and 0.01 mg/mL, it remained around 90%; thus, EO did not intervene in fibroblast proliferation, but it did influence fibroblast migration when wound-like was done in monolayer cultures. The results of this study demonstrated that the essential oil was a pro-wound-healing agent because it had good healing effectiveness with scars with good tensile strength and accelerated repair. The probable mechanism of action of the EO of B. morelensis, during the healing process, is the promotion of the migration of fibroblasts to the site of the wound, making them active in the production of collagen and promoting the remodeling of this collagen.

Camptotheca acuminata 10-hydroxycamptothecin O-methyltransferase: an alkaloid biosynthetic enzyme co-opted from flavonoid metabolism

The medicinal plant Camptotheca acuminata accumulates camptothecin, 10-hydroxycamptothecin, and 10-methoxycamptothecin as its major bioactive monoterpene indole alkaloids. Here, we describe identification and functional characterization of 10-hydroxycamptothecin O-methyltransferase (Ca10OMT), a member of the Diverse subclade of class II OMTs. Ca10OMT is highly active toward both its alkaloid substrate and a wide range of flavonoids in vitro and in this way contrasts with other alkaloid OMTs in the subclade that only utilize alkaloid substrates. Ca10OMT shows a strong preference for the A-ring 7-OH of flavonoids, which is structurally equivalent to the 10-OH of 10-hydroxycamptothecin. The substrates of other alkaloid OMTs in the subclade bear little similarity to flavonoids, but the 3-D positioning of the 7-OH, A- and C-rings of flavonoids is nearly identical to the 10-OH, A- and B-rings of 10-hydroxycamptothecin. This structural similarity likely explains the retention of flavonoid OMT activity by Ca10OMT and also why kaempferol and quercetin aglycones are potent inhibitors of its 10-hydroxycamptothecin activity. The catalytic promiscuity and strong inhibition of Ca10OMT by flavonoid aglycones in vitro prompted us to investigate the potential physiological roles of the enzyme in vivo. Based on its regioselectivity, kinetic parameters and absence of 7-OMT flavonoids in vivo, we conclude that the major and likely only substrate of Ca10OMTin vivo is 10-hydroxycamptothecin. This is likely accomplished by Ca10OMT being kept spatially separated at the tissue levels from potentially inhibitory flavonoid aglycones, and flavonoid aglycones being rapidly glycosylated to non-inhibitory flavonoid glycosides.

Gene Discovery of Characteristic Metabolic Pathways in the Tea Plant (Camellia sinensis) Using 'Omics'-Based Network Approaches: A Future Perspective

Characteristic secondary metabolites, including flavonoids, theanine and caffeine, in the tea plant (Camellia sinensis) are the primary sources of the rich flavors, fresh taste, and health benefits of tea. The decoding of genes involved in these characteristic components is still significantly lagging, which lays an obstacle for applied genetic improvement and metabolic engineering. With the popularity of high-throughout transcriptomics and metabolomics, 'omics'-based network approaches, such as gene co-expression network and gene-to-metabolite network, have emerged as powerful tools for gene discovery of plant-specialized (secondary) metabolism. Thus, it is pivotal to summarize and introduce such system-based strategies in facilitating gene identification of characteristic metabolic pathways in the tea plant (or other plants). In this review, we describe recent advances in transcriptomics and metabolomics for transcript and metabolite profiling, and highlight 'omics'-based network strategies using successful examples in model and non-model plants. Further, we summarize recent progress in 'omics' analysis for gene identification of characteristic metabolites in the tea plant. Limitations of the current strategies are discussed by comparison with 'omics'-based network approaches. Finally, we demonstrate the potential of introducing such network strategies in the tea plant, with a prospects ending for a promising network discovery of characteristic metabolite genes in the tea plant.

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.

Integrating metabolomics and transcriptomics data to discover a biocatalyst that can generate the amine precursors for alkamide biosynthesis

The Echinacea genus is exemplary of over 30 plant families that produce a set of bioactive amides, called alkamides. The Echinacea alkamides may be assembled from two distinct moieties, a branched-chain amine that is acylated with a novel polyunsaturated fatty acid. In this study we identified the potential enzymological source of the amine moiety as a pyridoxal phosphate-dependent decarboxylating enzyme that uses branched-chain amino acids as substrate. This identification was based on a correlative analysis of the transcriptomes and metabolomes of 36 different E. purpurea tissues and organs, which expressed distinct alkamide profiles. Although no correlation was found between the accumulation patterns of the alkamides and their putative metabolic precursors (i.e., fatty acids and branched-chain amino acids), isotope labeling analyses supported the transformation of valine and isoleucine to isobutylamine and 2-methylbutylamine as reactions of alkamide biosynthesis. Sequence homology identified the pyridoxal phosphate-dependent decarboxylase-like proteins in the translated proteome of E. purpurea. These sequences were prioritized for direct characterization by correlating their transcript levels with alkamide accumulation patterns in different organs and tissues, and this multi-pronged approach led to the identification and characterization of a branched-chain amino acid decarboxylase, which would appear to be responsible for generating the amine moieties of naturally occurring alkamides.

Omics data input for metabolic modeling

Recent advancements in high-throughput large-scale analytical methods to sequence genomes of organisms, and to quantify gene expression, proteins, lipids and metabolites have changed the paradigm of metabolic modeling. The cost of data generation and analysis has decreased significantly, which has allowed exponential increase in the amount of omics data being generated for an organism in a very short time. Compared to progress made in microbial metabolic modeling, plant metabolic modeling still remains limited due to its complex genomes and compartmentalization of metabolic reactions. Herein, we review and discuss different omics-datasets with potential application in the functional genomics. In particular, this review focuses on the application of omics-datasets towards construction and reconstruction of plant metabolic models.

Modern plant metabolomics: advanced natural product gene discoveries, improved technologies, and future prospects

Plant metabolomics has matured and modern plant metabolomics has accelerated gene discoveries and the elucidation of a variety of plant natural product biosynthetic pathways. This review covers the approximate period of 2000 to 2014, and highlights specific examples of the discovery and characterization of novel genes and enzymes associated with the biosynthesis of natural products such as flavonoids, glucosinolates, terpenoids, and alkaloids. Additional examples of the integration of metabolomics with genome-based functional characterizations of plant natural products that are important to modern pharmaceutical technology are also reviewed. This article also provides a substantial review of recent technical advances in mass spectrometry imaging, nuclear magnetic resonance imaging, integrated LC-MS-SPE-NMR for metabolite identifications, and X-ray crystallography of microgram quantities for structural determinations. The review closes with a discussion on the future prospects of metabolomics related to crop species and herbal medicine.

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.

Relative mass defect filtering of mass spectra: a path to discovery of plant specialized metabolites

The rapid identification of novel plant metabolites and assignments of newly discovered substances to natural product classes present the main bottlenecks to defining plant specialized phenotypes. Although mass spectrometry provides powerful support for metabolite discovery by measuring molecular masses, ambiguities in elemental formulas often fail to reveal the biosynthetic origins of specialized metabolites detected using liquid chromatography-mass spectrometry. A promising approach for mining liquid chromatography-mass spectrometry metabolite profiling data for specific metabolite classes is achieved by calculating relative mass defects (RMDs) from molecular and fragment ions. This strategy enabled the rapid recognition of an extensive range of terpenoid metabolites in complex plant tissue extracts and is independent of retention time, abundance, and elemental formula. Using RMD filtering and tandem mass spectrometry data analysis, 24 novel elemental formulas corresponding to glycosylated sesquiterpenoid metabolites were identified in extracts of the wild tomato Solanum habrochaites LA1777 trichomes. Extensive isomerism was revealed by ultra-high-performance liquid chromatography, leading to evidence of more than 200 distinct sesquiterpenoid metabolites. RMD filtering led to the recognition of the presence of glycosides of two unusual sesquiterpenoid cores that bear limited similarity to known sesquiterpenes in the genus Solanum. In addition, RMD filtering is readily applied to existing metabolomics databases and correctly classified the annotated terpenoid metabolites in the public metabolome database for Catharanthus roseus.

A mini review on pyridoacridines: Prospective lead compounds in medicinal chemistry

Natural products are increasingly being considered “critical and important” in drug discovery paradigms as a number of them such as camptothecin, penicillin, and vincristine serve as “lead molecules” for the discovery of potent compounds of therapeutic interests namely irinotecan, penicillin G, vinblastine respectively. Derived compounds of pharmacological interests displayed a wide variety of activity viz. anticancer, anti-inflammatory, antimicrobial, anti-protozoal, etc.; when modifications or derivatizations are performed on a parent moiety representing the corresponding derivatives. Pyridoacridine is such a moiety which forms the basic structure of numerous medicinally important natural products such as, but not limited to, amphimedine, ascididemin, eilatin, and sampangine. Interestingly, synthetic analogues of natural pyridoacridine exhibit diverse pharmacological activities and in view of these, natural pyridoacridines can be considered as “lead compounds”. This review additionally provides a brief but critical account of inherent structure activity relationships among various subclasses of pyridoacridines. Furthermore, the current aspects and future prospects of natural pyridoacridines are detailed for further reference and consideration.

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.

A global approach to analysis and interpretation of metabolic data for plant natural product discovery

Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publicly available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these datasets with transcriptomic data to create hypotheses concerning specialized metabolisms that generate the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software.

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.