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Analysis of organic compounds in the rhizosphere soil of Cyperusrotundus using LC-MS: Development of methods for the attempted identification of possible oviposition attractants of gravid Anopheles gambiae mosquitoes in western Kenya
KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH).
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The present study aimed to develop an extraction, sample preparation and analysis method for the rhizosphere soil of the grass Cyperus rotundus in an attempt to identify possible oviposition attractants of the Anopheles gambiae mosquito. Reversed Phase High Performance Liquid Chromatography (RP-HPLC) coupled online with Electrospray Ionization Mass spectrometry (ESI-MS) was used for the separation and detection of the extracted samples. Multiple extraction batches were done, altering parameters and techniques along the way. Ultrasound-Assisted Extraction (UAE) of the soil with a 50:50 (v/v) mixture of methanol and water was determined to be the most effective of the attempted methods. Purifying soil extracts with Solid Phase Extraction (SPE) showed to have an impact on the signal intensities in the chromatogram as well as reducing the intensity of system peaks eluting at the dead-time. This indicates that more polar compounds were removed during the SPE purification. A comparison was done between an extraction of soil soaked in water for five days and soil extracted without prior wetting. A difference could be seen and was shown by comparing chromatograms and mass spectra from the two samples. Tandem MS experiments were done for multiple precursor ions in order to identify the compounds by comparison in databases Human Metabolome Database (HMDB), Metlin and Massbank, but no matches in the databases were found. The tandem MS results were also used for comparison of consecutive chromatographic peaks with similar MS1-spectra. An identification method should be developed before the method presented in this work is validated and optimized further.

Place, publisher, year, edition, pages
2018.
National Category
Chemical Sciences
Identifiers
URN: urn:nbn:se:kth:diva-233767OAI: oai:DiVA.org:kth-233767DiVA, id: diva2:1242507
Available from: 2018-08-28 Created: 2018-08-28 Last updated: 2018-08-28Bibliographically approved

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