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dc.contributor.advisorGang, David R.en_US
dc.contributor.authorXie, Zhengzhi
dc.creatorXie, Zhengzhien_US
dc.date.accessioned2011-12-06T13:43:20Z
dc.date.available2011-12-06T13:43:20Z
dc.date.issued2007en_US
dc.identifier.urihttp://hdl.handle.net/10150/195218
dc.description.abstractSpecialized metabolism (secondary metabolism) in glandular trichomes of sweet basil (Ocimum basilicum L.) and accumulation of specialized metabolites (secondary metabolites) in rhizomes of turmeric (Curcuma longa L.) was investigated using proteomic and metabolomic approaches, respectively. In an effort to further clarify the regulation of metabolism in the glandular trichomes of sweet basil, we utilized a proteomics-based approach that applied MudPIT (multidimensional protein identification technology) and GeLC-MS/MS (gel enhanced LC-MS/MS) to protein samples from isolated trichomes of four different basil lines: MC, SW, SD, and EMX-1. Phosphorylation, ubiquitination and methylation of proteins in these samples were detected using X!tandem. Significant differences in distribution of the 755 non-redundant protein entries demonstrated that the proteomes of the glandular trichomes of the four basil lines were quite distinct. Correspondence between proteomic, EST, and metabolic profiling data demonstrated that both transcriptional regulation and post-transcriptional regulation contribute to the chemical diversity. One very interesting finding was that precursors for different classes of terpenoids, including mono- and sesquiterpenoids, appear to be almost exclusively supplied by the MEP (2-C-methyl-D-erythritol 4- phosphate) pathway, but not the mevolonate pathway, in basil glandular trichomes. Our results suggest that carbon flow can be readily redirected between the phenylpropanoid and terpenoid pathways in this specific cell type. To investigate the impact of genetic, developmental and environmental factors on the accumulation of phytochemicals in rhizomes of turmeric, we performed metabolomic analysis in a 2x2x4 full factorial design experiment using GC-MS, LC-MS, and LC-PDA. Our results showed that growth stage had the largest effect on levels of the three major curcuminoids. Co-regulated metabolite modules were detected, which provided valuable information for identification of phytochemicals and investigation of their biosynthesis. Based on LC-MS/MS data, 4 new diarylheptanoids were tentatively identified in turmeric rhizomes using Tandem-MSASC, a home-made software tool that automatically recognizes spectra of unknown compounds using three approaches. Based on our metabolomic results, we proposed two new strategies, “metabolomics-guided discovery” and “correlation bioassay”, to identify bioactive constituents from plant extracts based on information provided by metabolomic investigation.
dc.language.isoENen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectGlandular trichomeen_US
dc.subjectOcimum basilicumen_US
dc.subjectproteomicsen_US
dc.subjectRhizomeen_US
dc.subjectCurcumaen_US
dc.titleInvestigation of Plant Specialized Metabolism (Secondary Metabolism) Using Metabolomic and Proteomic Approachesen_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.contributor.chairGang, David R.en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.contributor.committeememberJacobson, Myron K.en_US
dc.contributor.committeememberYang, Danzhouen_US
dc.identifier.proquest2302en_US
thesis.degree.disciplinePharmaceutical Sciencesen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.namePhDen_US
refterms.dateFOA2018-06-23T20:01:31Z
html.description.abstractSpecialized metabolism (secondary metabolism) in glandular trichomes of sweet basil (Ocimum basilicum L.) and accumulation of specialized metabolites (secondary metabolites) in rhizomes of turmeric (Curcuma longa L.) was investigated using proteomic and metabolomic approaches, respectively. In an effort to further clarify the regulation of metabolism in the glandular trichomes of sweet basil, we utilized a proteomics-based approach that applied MudPIT (multidimensional protein identification technology) and GeLC-MS/MS (gel enhanced LC-MS/MS) to protein samples from isolated trichomes of four different basil lines: MC, SW, SD, and EMX-1. Phosphorylation, ubiquitination and methylation of proteins in these samples were detected using X!tandem. Significant differences in distribution of the 755 non-redundant protein entries demonstrated that the proteomes of the glandular trichomes of the four basil lines were quite distinct. Correspondence between proteomic, EST, and metabolic profiling data demonstrated that both transcriptional regulation and post-transcriptional regulation contribute to the chemical diversity. One very interesting finding was that precursors for different classes of terpenoids, including mono- and sesquiterpenoids, appear to be almost exclusively supplied by the MEP (2-C-methyl-D-erythritol 4- phosphate) pathway, but not the mevolonate pathway, in basil glandular trichomes. Our results suggest that carbon flow can be readily redirected between the phenylpropanoid and terpenoid pathways in this specific cell type. To investigate the impact of genetic, developmental and environmental factors on the accumulation of phytochemicals in rhizomes of turmeric, we performed metabolomic analysis in a 2x2x4 full factorial design experiment using GC-MS, LC-MS, and LC-PDA. Our results showed that growth stage had the largest effect on levels of the three major curcuminoids. Co-regulated metabolite modules were detected, which provided valuable information for identification of phytochemicals and investigation of their biosynthesis. Based on LC-MS/MS data, 4 new diarylheptanoids were tentatively identified in turmeric rhizomes using Tandem-MSASC, a home-made software tool that automatically recognizes spectra of unknown compounds using three approaches. Based on our metabolomic results, we proposed two new strategies, “metabolomics-guided discovery” and “correlation bioassay”, to identify bioactive constituents from plant extracts based on information provided by metabolomic investigation.


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