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Dataset Establishment Of Secondary Metabolites From Corals And Sponges And Its Chemotaxonomic Significance

Posted on:2013-04-05Degree:MasterType:Thesis
Country:ChinaCandidate:K ZhaoFull Text:PDF
GTID:2234330377952586Subject:Pharmaceutical Engineering
Abstract/Summary:PDF Full Text Request
Corals, sponges and other invertebrates in the tropical marine coral reefecosystems are rich in secondary metabolites with novel structures and remarkableactivities. These have become hot biological resources for the research anddevelopment of marine drugs. However, the knowledge about the distribution, geneticrelationship and laws of evolution in many corals, sponges and other speciesup to now was deficiency due to the lag of species classification and identification.The classification of these species was unclear, confusing or even wrong that affectedthe research of the marine natural products and marine medicinal biological resources.At present, the secondary metabolites of corals, sponges have become the main sourceof marine natural products. The numerous structures with specificity, complexity anddiversity provided a compound basis for species classification and identification fromthe chemical viewpoint. Therefore, to sort systematically the marine natural products,to find the compound distribution regularity in species, and further to carry outchemotaxonomic studies based on the existing database should provide evidence andcomplement for the traditional morphological taxonomy and modern molecularsystematics.This paper explored the chemotaxonomy of corals and sponges. Achemotaxonomic dataset was established firstly on the base of secondary metabolitesisolated from corals and sponges during the past few decades internationally. Thedataset involved1781characteristic compounds from sponges (10orders,39families,91genera), and724characteristic compounds from corals (4orders,20families,38genera). The phylogenetic relationships among the different species of corals in genusEunicea, Pseudopterogorgia and Plexaura were discussed, and the chemotaxonomicsignificance of the secondary metabolites based on the dataset was illustrated. Theresults provide support, proof and complement for the morphological and molecular taxonomy. The existence and distribution of the secondary metabolites were inferredfor the species that have not been studied by natural product scientists yet. Newevidences from the chemotaxonomic viewpoint were obtained for the contentiousissue in taxonomy.The phylogenetic relationships of corals including11species of genus Eunicea,5species of genus Pseudopterogorgia, and4species of genus Plexaura were discussedfrom chemotaxonomic viewpoint, respectively, giving support to the results from themorphological and molecular taxonomy. The new taxonomic evidences fromchemotaxonomic viewpoint were suggested for the morphological similar species P.americana and P. acerosa, and P. kallos and P. bipinnata. And the genus classificationof P. flexuosas was redefined by chemotaxonomy.Based on the characteristic secondary metabolites in sponges,14memberedmacrocycles latrunculins should be regarded as chemotaxonomic marker in familyPodospongiidae. According to the norditerpenes, norsesterterpenes and their cyclicperoxides in sponges, it was proposed that the family Podospongiidae should belongto suborder Mycalina. And the distribution of polyepoxysqualene-derived triterpenesin sponges provided a proof for the genus Ptilocaulis belonging to family Raspailiidaethat was suggested by molecular taxonomy.We established a chemotaxonomic dataset for the first time and provided datasupport for the classification and identification of medicinal marine biologicalresources. The phylogenetic relationship of the representative species of corals andsponges was analyzed for the first time from the chemotaxonomic viewpointaccording to the dataset. Moreover, the morphological and molecular taxonomy ofmedicinal marine biological species were proved, corrected and predicted based onthe dataset.
Keywords/Search Tags:coral, sponge, secondary metabolite, chemotaxonomy, dataset
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