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      The Durative Use of Suspension Cells and Callus for Volatile Oil by Comparative with Seeds and Fruits in Capparis spinosa L

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          Abstract

          Capparis spinosa is one of the most important eremophytes among the medicinal plants, and continued destruction of these plants poses a major threat to species survival. The development of methods to extract compounds, especially those of medicinal value, without harvesting the whole plant is an issue of considerable socioeconomic importance. On the basis of an established system for culture of suspension cells and callus in vitro, Gas Chromatograph-Mass Spectrometer (GC-MS) was used for the volatile oil composition analyzing in seed, fruit, suspension cells and callus. Fatty acids were the major component, and the highest content of alkanes was detected in seed, with <1.0% in suspension cells and callus. Esters, olefins and heterocyclic compounds were significantly higher in fruit than in the other materials. The content of acid esters in the suspension cells and callus was significantly higher than in seed and fruit. This indicated that the suspension cells and callus could be helpful for increasing the value of volatile oil and replacing seeds and fruit partially as a source of some compounds of the volatile oil and may also produce some new medical compounds. The above results give valuable information for sustainable use of C. spinosa and provide a foundation for use of the C. spinosa suspension cells and callus as an ongoing medical resource.

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          Most cited references23

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          PermutMatrix: a graphical environment to arrange gene expression profiles in optimal linear order.

          PermutMatrix is a work space designed to graphically explore gene expression data. It relies on the graphical approach introduced by Eisen and also offers several methods for the optimal reorganization of rows and columns of a numerical dataset. For example, several methods are proposed for optimal reorganization of the leaves of a hierarchical clustering tree, along with several seriation or unidimensional scaling methods that do not require any preliminary hierarchical clustering. This program, developed for MS Windows, with MS-Visual C++, has a clear and efficient graphical interface. Large datasets can be thoroughly and quickly analyzed.
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            A novel approach for nontargeted data analysis for metabolomics. Large-scale profiling of tomato fruit volatiles.

            To take full advantage of the power of functional genomics technologies and in particular those for metabolomics, both the analytical approach and the strategy chosen for data analysis need to be as unbiased and comprehensive as possible. Existing approaches to analyze metabolomic data still do not allow a fast and unbiased comparative analysis of the metabolic composition of the hundreds of genotypes that are often the target of modern investigations. We have now developed a novel strategy to analyze such metabolomic data. This approach consists of (1) full mass spectral alignment of gas chromatography (GC)-mass spectrometry (MS) metabolic profiles using the MetAlign software package, (2) followed by multivariate comparative analysis of metabolic phenotypes at the level of individual molecular fragments, and (3) multivariate mass spectral reconstruction, a method allowing metabolite discrimination, recognition, and identification. This approach has allowed a fast and unbiased comparative multivariate analysis of the volatile metabolite composition of ripe fruits of 94 tomato (Lycopersicon esculentum Mill.) genotypes, based on intensity patterns of >20,000 individual molecular fragments throughout 198 GC-MS datasets. Variation in metabolite composition, both between- and within-fruit types, was found and the discriminative metabolites were revealed. In the entire genotype set, a total of 322 different compounds could be distinguished using multivariate mass spectral reconstruction. A hierarchical cluster analysis of these metabolites resulted in clustering of structurally related metabolites derived from the same biochemical precursors. The approach chosen will further enhance the comprehensiveness of GC-MS-based metabolomics approaches and will therefore prove a useful addition to nontargeted functional genomics research.
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              An investigation of the storage and biosynthesis of phenylpropenes in sweet basil.

              Plants that contain high concentrations of the defense compounds of the phenylpropene class (eugenol, chavicol, and their derivatives) have been recognized since antiquity as important spices for human consumption (e.g. cloves) and have high economic value. Our understanding of the biosynthetic pathway that produces these compounds in the plant, however, has remained incomplete. Several lines of basil (Ocimum basilicum) produce volatile oils that contain essentially only one or two specific phenylpropene compounds. Like other members of the Lamiaceae, basil leaves possess on their surface two types of glandular trichomes, termed peltate and capitate glands. We demonstrate here that the volatile oil constituents eugenol and methylchavicol accumulate, respectively, in the peltate glands of basil lines SW (which produces essentially only eugenol) and EMX-1 (which produces essentially only methylchavicol). Assays for putative enzymes in the biosynthetic pathway leading to these phenylpropenes localized many of the corresponding enzyme activities almost exclusively to the peltate glands in leaves actively producing volatile oil. An analysis of an expressed sequence tag database from leaf peltate glands revealed that known genes for the phenylpropanoid pathway are expressed at very high levels in these structures, accounting for 13% of the total expressed sequence tags. An additional 14% of cDNAs encoded enzymes for the biosynthesis of S-adenosyl-methionine, an important substrate in the synthesis of many phenylpropenes. Thus, the peltate glands of basil appear to be highly specialized structures for the synthesis and storage of phenylpropenes, and serve as an excellent model system to study phenylpropene biosynthesis.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                25 November 2014
                : 9
                : 11
                : e113668
                Affiliations
                [1 ]College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, P. R. China
                [2 ]Key Laboratory of Molecular Biology, Physics of Ministry of Education, Huazhong University of Science and Technology, Wuhan, 430074, P. R. China
                [3 ]Hubei Collaborative Innovation Center for Green Transformation of Bio-Resources, Faculty of Life Science, Hubei University, Wuhan, 430062, P. R. China
                INRA, France
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: ML. Performed the experiments: YY YH WL HJ. Analyzed the data: YY LG HJ. Contributed reagents/materials/analysis tools: ML CF. Wrote the paper: YY HJ ML.

                Article
                PONE-D-14-30122
                10.1371/journal.pone.0113668
                4244143
                25422894
                f26b351d-ce9b-4d62-89e6-6f826b972f50
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 12 August 2014
                : 27 October 2014
                Page count
                Pages: 19
                Funding
                The research was supported by New Century Talents Support Program by the Chinese Natural Science Foundation (31270373), Ministry of Education of China (NCET110172). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Agriculture
                Agricultural Biotechnology
                Biotechnology
                Plant Biotechnology
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper.

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