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      Identification of Nutritional Components in Black Sesame Determined by Widely Targeted Metabolomics and Traditional Chinese Medicines

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          Abstract

          Chemical composition of secondary metabolites is of great importance for quality control of agricultural products. Black sesame seeds are significantly more expensive than white sesame seeds, because it is thought that black sesame seeds are more beneficial to human health than white sesame seeds. However, the differences in nutrient composition between black sesame seeds and white sesame seeds are still unknown. The current study examined the levels of different metabolites in black and white sesame seeds via the use of a novel metabolomics strategy. Using widely targeted metabolomics data, we obtained the structure and content of 557 metabolites, out of which 217 metabolites were identified, and discovered 30 metabolic pathways activated by the secondary metabolites in both black and white sesame seeds. Our results demonstrated that the main pathways that were differentially activated included: phenylpropanoid biosynthesis, tyrosine metabolism, and riboflavin metabolism. More importantly, the biomarkers that were significantly different between black seeds and white sesame seeds are highly related to the functions recorded in traditional Chinese medicine. The results of this study may serve as a new theoretical reference for breeding experts to promote the genetic improvement of sesame seeds, and therefore the cultivation of higher quality sesame varieties.

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          Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism.

          Plant metabolites are important to world food security in terms of maintaining sustainable yield and providing food with enriched phytonutrients. Here we report comprehensive profiling of 840 metabolites and a further metabolic genome-wide association study based on ∼6.4 million SNPs obtained from 529 diverse accessions of Oryza sativa. We identified hundreds of common variants influencing numerous secondary metabolites with large effects at high resolution. We observed substantial heterogeneity in the natural variation of metabolites and their underlying genetic architectures among different subspecies of rice. Data mining identified 36 candidate genes modulating levels of metabolites that are of potential physiological and nutritional importance. As a proof of concept, we functionally identified or annotated five candidate genes influencing metabolic traits. Our study provides insights into the genetic and biochemical bases of rice metabolome variation and can be used as a powerful complementary tool to classical phenotypic trait mapping for rice improvement.
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            Asian medicine. The new face of traditional Chinese medicine.

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              Metabolomics in systems biology.

              The primary aim of "omic" technologies is the nontargeted identification of all gene products (transcripts, proteins, and metabolites) present in a specific biological sample. By their nature, these technologies reveal unexpected properties of biological systems. A second and more challenging aspect of omic technologies is the refined analysis of quantitative dynamics in biological systems. For metabolomics, gas and liquid chromatography coupled to mass spectrometry are well suited for coping with high sample numbers in reliable measurement times with respect to both technical accuracy and the identification and quantitation of small-molecular-weight metabolites. This potential is a prerequisite for the analysis of dynamic systems. Thus, metabolomics is a key technology for systems biology. The aim of this review is to (a) provide an in-depth overview about metabolomic technology, (b) explore how metabolomic networks can be connected to the underlying reaction pathway structure, and (c) discuss the need to investigate integrative biochemical networks.
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                Author and article information

                Journal
                Molecules
                Molecules
                molecules
                Molecules : A Journal of Synthetic Chemistry and Natural Product Chemistry
                MDPI
                1420-3049
                15 May 2018
                May 2018
                : 23
                : 5
                : 1180
                Affiliations
                [1 ]Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Wuhan 430062, China; beyondan_good@ 123456163.com
                [2 ]Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Wuhan 430062, China; xiaorongsara@ 123456163.com (X.H.); yanrinannan@ 123456126.com (R.Y.)
                [3 ]Laboratory of Quality and Safety Risk Assessment for Oilseed Products (Wuhan), Ministry of Agriculture, Wuhan 430062, China
                [4 ]Key Laboratory of Detection for Mycotoxins, Ministry of Agriculture, Wuhan 430062, China; zhangqi52x@ 123456126.com
                [5 ]Quality Inspection and Test Center for Oilseed Products, Ministry of Agriculture, Wuhan 430062, China; wangxiao0613@ 123456163.com (X.W.); maojin106@ 123456whu.edu.cn (J.M.); wxf0911@ 123456163.com (X.W.); xiupinwang@ 123456163.com (X.W.)
                [6 ]Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, Wuhan 430062, China
                Author notes
                [* ]Correspondence: liangxiao_zhang@ 123456hotmail.com (L.Z.); peiwuli@ 123456oilcrops.cn (P.L.); Tel.: +86-27-86812943 (P.L.); Fax: +86-27-86812862 (P.L.)
                [†]

                These authors contributed equally to this study.

                Author information
                https://orcid.org/0000-0002-9916-2952
                Article
                molecules-23-01180
                10.3390/molecules23051180
                6100530
                29762486
                8c792511-7bfc-40fe-b738-b498a57b9593
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 23 April 2018
                : 10 May 2018
                Categories
                Article

                sesame,widely targeted metabolomics,differential metabolites,specific nutrients,lc-ms/ms

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