Investigation of HIV Anti-viral Drug Effect on HPV16 E6 Expressing Cervical Carcinoma Cells Using Advanced Metabolomics Methods

  • Dong Hyun Kim

Student thesis: Phd


Metabolomics approaches have recently been used to understand the complex molecular interactions of biological systems. One popular area in which these methods are being developed is to understand the biochemical changes during abiotic and biotic stresses; for example, how a cell may respond to a drug. Since metabolites are the end products of gene expression, these can be used to indicate the result of the activities and interaction of the cell or organism with its environment. The investigation of the level and compositional changes of metabolites against metabolic stresses such as chemotherapeutic treatment (drug exposure) are required to understand more fully abiotic perturbation to biological systems. The aim of this project was to understand the metabolic effect that the anti-viral drugs indinavir and lopinavir (currently used by HIV patients) have on HPV-related cervical cancer cell lines by measuring changes in metabolism using a wide range of analytical techniques; including Fourier transform infrared (FT-IR) and Raman spectroscopies, and gas and liquid chromatography-mass spectrometry (GC and LC-MS). The analyses and interpretation of the large volumes of complex multidimensional data generated by metabolomics approaches were performed with a combination of multivariate data analysis techniques such as principal components analysis (PCA) and canonical variates analysis (CVA), as well as univariate approaches such as N-Way analysis of variance (ANOVA). By combining biochemical imaging, metabolite fingerprinting and footprinting, and metabolite profiling, with multi- and uni-variate analyses, the actions and effects of the anti-viral drugs were investigated. FT-IR spectroscopy was initially used to generate global biochemical finger- and foot-prints, and Raman spectroscopy was employed to investigate intracellular distribution of metabolites, and other cellular species, as well as the localisation of drug molecules within cells. FT-IR spectroscopy ascertained that the intra- and extra-cellular metabolomes were being directly influenced in a fashion that correlated with increasing anti-viral dosing; these effects were phenotypic rather than measurements of the drug level. Raman imaging spectroscopy indicated that the indinavir but not lopinavir was being compartmentalised within the cell nucleus, but only in HPV early protein 6 (E6) expressing cells. This observation was further confirmed by fractionation of cell samples into nuclear and cytoplasmic fractions and assessing the indinavir concentrations via LC-MS. Finally, LC-MS and GC-MS metabolite profiling were employed to investigate changes in the intracellular metabolome in response to the anti-viral compounds across a range of physiologically relevant concentrations and in the presence and absence of the E6 oncoprotein. General effects of both anti-viral compounds included the regulation of metabolites such as glutathione, octenedionoic and octadecenoic acids, which may be involved in stress related responses, reduced levels of sugars and sugar-phosphates indicating a potential arrest of glycolysis, and reduced levels of malic acid indicating potential decreased flux into the TCA cycle; all indicating that central metabolism was being reduced. Finally, LC-MS based quantification indicated that in the presence of E6, lopinavir was actively removed from the cell, whereas the indinavir intracellular concentration increased concomitantly with the level of dosing. These investigations have revealed that metabolomics approaches are an apt tool for the study of anti-viral effects within cell cultures, but improvements need to be made with respect to the major limitation of metabolite identification.
Date of Award1 Aug 2011
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorRoyston Goodacre (Supervisor)


  • HPV, Indinavir, Lopinavir, FT-IR, metabolic fingerprinting and footprinting, Raman chemical mapping, LC-MS, metabolic profiling

Cite this