Development of a multiple application LC-MS/MS method for targeted metabolic profiling of biological matrices

Abstract

Metabolomics is a growing field and a valuable instrument for the identification of dysregulation in the metabolome of a biological system. Different approaches and analytical platforms are available for metabolomics based studies. Although metabolomics is a promising diagnostic tool there are still obstacles to overcome. There is still no standardised totally comprehensive approach available to detect and quantify large numbers of metabolites. There is also no standardised sample preparation and metabolite extraction method established. Targeted metabolic profiling is a feasible approach to metabolomics and allows investigation into the metabolome with high specificity. The establishment of a metabolic profiling method will be of great benefit in the characterisation of diseases whose pathogenesis still remains poorly understood. Idiopathic pulmonary fibrosis (IPF) is a lung disease with a prevalence of between 1.25 and 23.4 per 100 000 population in Europe and 1 in every 32 000 population is South Africa. IPF is one of many diseases whose pathogenesis still remains poorly understood and alternative investigation is required in order to understanding the onset and progression of the disease. During this study the aim was to develop an LC-MS/MS based targeted metabolic profiling method that would be able to generate a metabolic profile for any disease state, together with a sample preparation and metabolite extraction method for various biological matrices. The aim of the study was achieved by developing an LC-MS/MS method using the Luna NH2 column (2 mm x 150 mm, 5 μm, 100 Å), as well as developing a standardised protein precipitation sample preparation procedure. After a quality assessment was performed on all aspects of the analytical process, including the range, linearity, limits of detection and quantification, accuracy and precision, the performance of the method was considered stable and adequate for use in metabolic profiling. As validation of the developed method, a targeted metabolic profile was generated for a fibrotic lung animal model (C57BL/6J bleomycin treated mouse model) resembling IPF. Since sampling lung tissue from IPF patients is an invasive approach, the alternative approach of using an animal model resembling the diseases state was used. A metabolic profile was generated for the C57BL/6J bleomycin treated animal model using the developed method and after univariate and multivariate statistical analysis was performed, several metabolites were identified as significant (p-values < 0.05). The metabolic profile was compared to a metabolic profile of a lipopolysaccharide induced lung inflammation mouse model to identity any correlation to an inflammation induced lung disease state. The metabolic profile of the C57BL/6J bleomycin treated mouse model was also compared to a transforming growth factor-β treated normal human lung fibroblast cellular model to identify any correlation to an in vitro IPF representation. The identified metabolites indicated a dysregulation in the glycolysis pathway as well as the methionine cycle, suggesting the key to understanding the pathogenesis of the disease may lie on an epigenetic level.