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By standard convention, in order to increase the efficacy of metabolite detection from cell culture lysates, metabolite extracts from a large quantity of cells are utilized for multiple reaction monitoring-based metabolomic studies. Metabolomics from a small number of cell extracts offers a potential economical alternative to increased cell numbers, in turn increasing the utility of cell culture-based metabolomics. However, the effect of reduced cell numbers on targeted metabolomic profiling is relatively unstudied. Considering the limited knowledge available of the feasibility and accuracy of microscale cell culture metabolomics, the present study analyzes differences in metabolomic profiles of different cell numbers of three pancreatic cancer cell lines. Specifically, it examines the effects of reduced cell numbers on metabolite profiles by obtaining extracts either directly from microscale culture plates or through serial dilution of increased numbers of cellular metabolite extracts. Our results indicate reduced cell numbers only modestly affect the number of metabolites detected (93% of metabolites detected in cell numbers as low as 10 4  cells and 97% for 10 5  cells), independent of the method used to obtain the cells. However, metabolite peak intensities were differentially affected by the reduced cell numbers, with some peak intensities inversely proportional to the cell numbers. To help eliminate such potential inverse relationships, peak intensities for increased cell numbers were excluded from the comparative analysis. Overall, metabolite profiles from microscale culture plates were observed to differ from the serial dilution samples, which may be attributable to the medium-to-cell-number ratios. Finally, findings identify perturbations in metabolomic profiling for cellular extracts from reduced cell numbers, which offer future applications in microscale metabolomic evaluations.

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Validation of Metabolic Alterations in Microscale Cell Culture Lysates Using Hydrophilic Interaction Liquid Chromatography (HILIC)-Tandem Mass Spectrometry-Based Metabolomics