Literature DB >> 24413339

A metabolomics investigation into the effects of HIV protease inhibitors on HPV16 E6 expressing cervical carcinoma cells.

Dong-Hyun Kim1, J William Allwood, Rowan E Moore, Emma Marsden-Edwards, Warwick B Dunn, Yun Xu, Lynne Hampson, Ian N Hampson, Royston Goodacre.   

Abstract

Recently, it has been reported that anti-viral drugs, such as indinavir and lopinavir (originally targeted for HIV), also inhibit E6-mediated proteasomal degradation of mutant p53 in E6-transfected C33A cells. In order to understand more about the mode-of-action(s) of these drugs the metabolome of HPV16 E6 expressing cervical carcinoma cell lines was investigated using mass spectrometry (MS)-based metabolic profiling. The metabolite profiling of C33A parent and E6-transfected cells exposed to these two anti-viral drugs was performed by ultra performance liquid chromatography (UPLC)-MS and gas chromatography (GC)-time of flight (TOF)-MS. Using a combination of univariate and multivariate analyses, these metabolic profiles were investigated for analytical and biological reproducibility and to discover key metabolite differences elicited during anti-viral drug challenge. This approach revealed both distinct and common effects of these two drugs on the metabolome of two different cell lines. Finally, intracellular drug levels were quantified, which suggested in the case of lopinavir that increased activity of membrane transporters may contribute to the drug sensitivity of HPV infected cells.

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Year:  2014        PMID: 24413339     DOI: 10.1039/c3mb70423h

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  5 in total

1.  Metabolic effects of an aspartate aminotransferase-inhibitor on two T-cell lines.

Authors:  Henrik Antti; Magnus Sellstedt
Journal:  PLoS One       Date:  2018-12-07       Impact factor: 3.240

2.  Untargeted analysis of plasma samples from pre-eclamptic women reveals polar and apolar changes in the metabolome.

Authors:  Katrin N Sander; Dong-Hyun Kim; Catharine A Ortori; Averil Y Warren; Uchenna C Anyanwagu; Daniel P Hay; Fiona Broughton Pipkin; Raheela N Khan; David A Barrett
Journal:  Metabolomics       Date:  2019-11-27       Impact factor: 4.290

3.  Machine learning prediction of antiviral-HPV protein interactions for anti-HPV pharmacotherapy.

Authors:  Hui-Heng Lin; Qian-Ru Zhang; Xiangjun Kong; Liuping Zhang; Yong Zhang; Yanyan Tang; Hongyan Xu
Journal:  Sci Rep       Date:  2021-12-21       Impact factor: 4.379

4.  Metabolomics Analysis Reveals the Participation of Efflux Pumps and Ornithine in the Response of Pseudomonas putida DOT-T1E Cells to Challenge with Propranolol.

Authors:  Ali Sayqal; Yun Xu; Drupad K Trivedi; Najla AlMasoud; David I Ellis; Nicholas J W Rattray; Royston Goodacre
Journal:  PLoS One       Date:  2016-06-22       Impact factor: 3.240

5.  Metabolic Fingerprinting of Pseudomonas putida DOT-T1E Strains: Understanding the Influence of Divalent Cations in Adaptation Mechanisms Following Exposure to Toluene.

Authors:  Ali Sayqal; Yun Xu; Drupad K Trivedi; Najla AlMasoud; David I Ellis; Royston Goodacre
Journal:  Metabolites       Date:  2016-04-26
  5 in total

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