[Development of Plant Metabolomics and Medicinal Plant Genomics]

Insights into the nutritional properties and molecular basis of biosynthesis of amino acids and vitamins of Gastrodia elata offered by metabolomic and transcriptomic analysis

Gastrodia elata Blume (GE), a traditional and precious Chinese medicinal material, has been approved as a functional food. However, understanding GE's nutritional properties and its molecular basis remains limited. Here, metabolomic and transcriptomic analyses were performed on young and mature tubers of G. elata.f.elata (GEEy and GEEm) and G. elata.f.glauca (GEGy and GEGm). A total of 345 metabolites were detected, including 76 different amino acids and their derivatives containing all human essential amino acids (e.g., l-(+)-lysine, l-leucine), 13 vitamins (e.g., nicotinamide, thiamine), and 34 alkaloids (e.g., spermine, choline). GEGm has higher amino acid accumulation than GEEy, GEEm and GEGy, and vitamin contents were also slightly different in all four samples. Implying that GE, especially GEGm, is a kind of excellent complementary food as amino acid nutrition provider. From assembled 21,513 transcripts (genes) based on the transcriptome, we identified many genes that encode enzymes (e.g., pfkA, bglX, tyrAa, lysA, his B, aroA), which are responsible for the biosynthesis of amino acids and enzymes (e.g., nadA, URH1, NAPRT1, punA, rsgA) that related to vitamins metabolism. A total of 16 pairs of the differentially expressed genes (DEG) and differentially accumulated metabolites (DAM) (e.g., gene-tia006709 coding GAPDH and l-(+)-arginine, and gene-tia010180 coding tyrA and l-(+)-arginine) and three DEG-DAM pairs (e.g., gene-tia015379 coding NadA and nicotinate d-ribonucleoside) show significant similar positive or negative correlation based on three, and two comparisons of GEEy vs. GEGy, GEGy vs. GEGm, GEEy vs. GEGy and GEEm vs. GEGm, which involved into amino acid biosynthesis, and nicotinate nicotinamide metabolism, respectively. These results prove that the enzyme coded by these DEG promotes (positive correlation) or inhibits (negative correlation) the biosynthesis of parallel DAM in GE. Overall, the data and corresponding analysis in this study provide new insights into the nutritional properties of GE and the related molecular basis.

Omics Technologies to Enhance Plant Based Functional Foods: An Overview

Functional foods are natural products of plants that have health benefits beyond necessary nutrition. Functional foods are abundant in fruits, vegetables, spices, beverages and some are found in cereals, millets, pulses and oilseeds. Efforts to identify functional foods in our diet and their beneficial aspects are limited to few crops. Advances in sequencing and availability of different omics technologies have given opportunity to utilize these tools to enhance the functional components of the foods, thus ensuring the nutritional security. Integrated omics approaches including genomics, transcriptomics, proteomics, metabolomics coupled with artificial intelligence and machine learning approaches can be used to improve the crops. This review provides insights into omics studies that are carried out to find the active components and crop improvement by enhancing the functional compounds in different plants including cereals, millets, pulses, oilseeds, fruits, vegetables, spices, beverages and medicinal plants. There is a need to characterize functional foods that are being used in traditional medicines, as well as utilization of this knowledge to improve the staple foods in order to tackle malnutrition and hunger more effectively.

Development of selection method for Glycyrrhiza uralensis superior clones with high-glycyrrhizic acid contents using DNA sequence polymorphisms in glycyrrhizic acid biosynthetic genes

Glycyrrhiza plants are important resources for sweeteners and medicines, because underground parts of them contain glycyrrhizic acid (GL), which has sweet taste and various pharmacological activities (ex. anti-inflammatory, antiallergy, antiviral activity, etc.). Although such importance of them, their supply still depends principally on the collection of wild plants. Therefore, it is an important issue to develop stable and efficient production system of Glycyrrhiza plants. To overcome this problem, we established the hydroponic cultivation system of Glycyrrhiza uralensis and selected superior G. uralensis clones with high-GL contents in the containment greenhouse. In this study, we aimed to develop a method of selecting these superior G. uralensis clones by DNA sequence polymorphisms in biosynthetic genes. Among the DNA sequences of GL biosynthetic key enzyme gene (CYP88D6), we found Glycyrrhiza species and clone-specific polymorphisms in intronic regions. By using these polymorphisms, discrimination among Glycyrrhiza species and G. uralensis clones became possible. Furthermore, the appearance frequency of superior clone-specific alleles in cloned CYP88D6 sequences was correlated with GL contents in crude drugs collected from the Japanese market. We also observed the tendency that G. uralensis seedlings having superior clone-specific alleles of CYP88D6 gene showed higher secondary metabolite productivity than those without the alleles. These results indicated that superior clone-specific alleles of CYP88D6 gene could be applied as DNA markers for selecting G. uralensis clones accumulating high secondary metabolites.

[Predicting the Pharmacologic Activity of Natural Materials Based on Metabolomics]

Natural materials such as crude drugs and foods are mixtures composed of various metabolites. Metabolic profiling is often used to identify possible correlations between a compound's metabolic profile and pharmacologic activity. Direct-injection electron ionization-mass spectrometry (DI-EI-MS) is a novel metabolomics method useful for characterizing biological materials. This review demonstrates the establishment of a DI-EI-MS method for metabolic profiling using several closely related lichen species: Cladonia krempelhuberi, C. gracilis, C. pseudogymnopoda, and C. ramulosa. The qualitative DI-EI-MS method was used to profile major and/or minor constituents in extracts of lichen samples. Each lichen sample could be distinguished by altering the DI-EI-MS electron energy and examining the resulting data using one-way analysis of variance. We also attempted to predict pharmacologic activity using DI-EI-MS metabolomics. Blueberry leaf extracts inhibited the proliferation of adult T-cell leukemia (ATL) cells. Blueberry leaf extracts could be distinguished by principal component analysis based on the absolute intensity of characteristic fragment ions. Twenty cultivars were categorized into four species, and the most appropriate discriminative marker m/z value for identifying each cultivar was selected statistically. Components extracted based on DI-EI-MS analyses could be used to construct a model to predict ATL cell bioactivity. These data suggest that the novel DI-EI-MS metabolomics method is suitable for identifying species of natural materials and predicting their pharmacologic activity. This approach could enhance public health by facilitating evaluations of pharmacologic activity and functionality, leading to the elimination of counterfeit products.