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Investigation of biochemical strategies leading to metabolome complexity of two closely related Coccinia species through LC-QTOF-MS-based metabolite fingerprinting

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dc.contributor.advisor Madala, N. E.
dc.contributor.advisor Mhlongo, M. I.
dc.contributor.advisor Mathomu, L. M.
dc.contributor.author Nengovhela, Ndamulel
dc.date 2021
dc.date.accessioned 2021-12-10T15:54:34Z
dc.date.available 2021-12-10T15:54:34Z
dc.date.issued 2021-04
dc.identifier.citation Nengovhela, N. (2021) Investigation of biochemical strategies leading to metabolome complexity of two closely related Coccinia species through LC-QTOF-MS-based metabolite fingerprinting. University of Venda, South Africa.<http://hdl.handle.net/11602/1805>.
dc.identifier.uri http://hdl.handle.net/11602/1805
dc.description MSc (Biochemistry) en_ZA
dc.description Department of Biochemistry
dc.description.abstract Medicinal plants play an important role in both health and the livelihood of people. These plants have been used for medicinal purposes since time memorial, and they are deemed safer than their synthetic counterparts. One such plant is Coccinia grandis (Ivy Gourd), which has been used in traditional medicine as a household remedy for various diseases. Coccinia grandis have been reported to possess antidiabetic properties. This is owing to the presence of secondary metabolites which are naturally produced by plants for adaptation to their immediate environment. Secondary metabolites are a diverse group of chemical compounds which include flavonoids, glycosides and hydroxycinnamic acids. These biologically active compounds chemically and structurally complex and their characterization pose undisputed analytical challenges. Mass spectrometry techniques have however, over the years been developed as feasible technique to assist in the characterisation and structural elucidation of plant metabolites. Liquid Chromatography Mass Spectrometry (LC-MS) is the most widely and preferred analytical platform due to its high sensitivity, resolution and detection specificity. Moreover, MS is able to produce accurate mass, unfragmented and fragmented data, which is important for compound characterization and structural elucidation. As such, in the current study LC-MS based metabolomics approach was used to screen for phytochemicals from commercially cultivated C. grandis and its widely growing relative, Coccinia rehmannii which has no reported medical use in literature. To establish the chemo-taxonomic relationship between these two species, multivariate statistical modelling revealed differential metabolites distribution pattern between them. The results revealed that these two closely related plant species possess a wide variety of important secondary metabolites such as flavonoids and hydroxycinnamic acids. Some interesting subtle differences were also noted, for instance the flavonoids composition of these plants were to have different glycosylation patterns (Chapter 3). Here, it was noted that flavonoids attached to di- or tri- saccharides are prone to isomerization, a phenomenon termed glyco-isomerization. Apart from positional migration of sugar moieties, acylation of sugars by other biologically active molecules such as derivatives of cinnamic acids (i.e. caffeic and coumaric acid) was also noted ix as a contributor towards glyco-isomerization. Here, C. rehmannii was found to attach these cinnamic acid derivatives to its flavonoids, a phenomenon which was absent in C. grandis. It was then concluded that C. rehmannii produce more flavonoid molecules than C. grandis. Apart from flavonoids composition, hydroxycinnamoyl conjugation was revealed to be a discriminatory chemical factor between these two closely related Coccinia species. Through UHPLC-qTOF-MS/MS metabolite fingerprinting, C. grandis was found to produce different chlorogenic acids, thus cinnamic acids conjugated to a quinic acid (Chapter 4). Ironically, only few chlorogenic acids were found in C. rehmannii. The findings revealed that the two closely related species utilise Hydroxycinnamic acid (HCA) conjugations as another strategy to diversify their metabolite composition, a phenomenon which has not been suggested in chemo taxonomical studies. Furthermore, the current study revealed that these two plants use both glyco-isomerization and conjugation as an evolutionary strategy to maximise their metabolome complexity. This was further highlighted in (Chapter 5) where LC-MS analyses of C. grandis revealed multiple peaks sharing same precursor ion (with molecular formula C27H30O16) and associated fragmentation patterns. Further analyses revealed all six peaks to be Rutin, a most common and highly pharmacologically acclaimed flavonoid molecule. As demonstrated herein, these results also had analytical implications, such that subsequent developments of other specific methods such as multiple reaction monitoring (MRM) could not distinguish these compounds. In conclusion, the two Coccinia species contain a wide range of phytochemicals, dominated by flavonoids and hydroxycinnamic acids derivatives. This study further demonstrated LC-MS as an effective tool in comparing metabolite profiles between C. rehmannii and C. grandis certified by the varying amount and composition of flavonoids and hydroxycinnamic acids derivatives between the two species. Two biochemical phenomenon known as glyco-isomerization and conjugation were shown to be well co-ordinated strategies used by these plants to diversify their metabolite composition. LC-MS in combination with multivariate data models was effective in the investigation of metabolites distribution patterns between the two species. en_ZA
dc.description.sponsorship NRF en_ZA
dc.format.extent I online resource (xv, 115 leaves) : color illustrations
dc.language.iso en en_ZA
dc.rights University of Venda
dc.subject Biochemical en_ZA
dc.subject Strategies en_ZA
dc.subject Metabolome en_ZA
dc.subject Coccinia en_ZA
dc.subject Metabolite en_ZA
dc.title Investigation of biochemical strategies leading to metabolome complexity of two closely related Coccinia species through LC-QTOF-MS-based metabolite fingerprinting en_ZA
dc.type Dissertation en_ZA


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