LC–MS-based absolute metabolite quantification:Application to metabolic flux measurement in trypanosomes

Human African trypanosomiasis is a neglected tropical disease caused by the protozoan parasite, Trypanosoma brucei. In the mammalian bloodstream, the trypanosome’s metabolism differs significantly from that of its host. For example, the parasite relies exclusively on glycolysis for energy source. Recently, computational and mathematical models of trypanosome metabolism have been generated to assist in understanding the parasite metabolism with the aim of facilitating drug development. Optimisation of these models requires quantitative information, including metabolite concentrations and/or metabolic fluxes that have been hitherto unavailable on a large scale. Here, we have implemented an LC–MS-based method that allows large scale quantification of metabolite levels by using U-13C-labelled E. coli extracts as internal standards. Known amounts of labelled E. coli extract were added into the parasite samples, as well as calibration standards, and used to obtain calibration curves enabling us to convert intensities into concentrations. This method allowed us to reliably quantify the changes of 43 intracellular metabolites and 32 extracellular metabolites in the medium over time. Based on the absolute quantification, we were able to compute consumption and production fluxes. These quantitative data can now be used to optimise computational models of parasite metabolism

Metabolomics profiling of extracellular metabolites in CHO-K1 cells cultured in different types of growth media

An efficient mammalian cell system for producing bioproducts should retain high cell viability and efficient use of energy sources rendering the need to understand the effects of various variables on the cell system. In this study, global metabolite (metabolomics) analysis approach was used to try and understand the relationships between types of media used, culture growth behavior and productivity. CHO-KI cells producing IGF-1 were obtained from ATCC and grown in T-flask (37 °C, 5 % CO(2)) until 70–80 % confluent in RPMI 1640 and Ham’s F12, respectively. Samples were taken at 8-hourly intervals for routine cell counting, biochemical responses, insulin like growth factor—1 (IGF-1) protein concentration and global metabolite analysis (gas chromatography mass spectrometry, GCMS). Conditioned media from each time point were spun down before injection into GCMS. Data from GCMS were then transferred to SIMCA-P + Version 12 for chemometric evaluation using principal component analysis. The results showed that while routine analysis gave only subtle differences between the media, global metabolite analysis was able to clearly separate the culture based on growth media with growth phases as confounding factor. Different types of media also appeared to affect IGF-1 production. Asparagine was found to be indicative of healthiness of cells and production of high IGF-1. Meanwhile identification of ornithine and lysine in death phase was found to be associated with apoptosis and oversupplied nutrient respectively. Using the biomarkers revealed in the study, several bioprocessing strategies including medium improvement and in-time downstream processing can be potentially implemented to achieve efficient CHO culture system