Metabolic profiling of the fission yeast S. pombe: quantification of compounds under different temperatures and genetic perturbation

Abstract

Metabolomics is a rapidly growing branch of post-genomic chemical biology. The fission yeast Schizosaccharomyces pombe is an excellent eukaryotic model organism. Although the entire S. pombegenome has been sequenced and detailed transcriptomic analyses were performed, little metabolic profiling has been done. Here we report the first global semi-quantitative analysis of the S. pombe metabolome using liquid chromatographyhigh-resolution mass spectrometry. Procedures to obtain metabolic compounds from S. pombe extracts were established. One hundred and twenty-three distinct metabolites were identified while approximately 1900 peaks from the ∼6000 observed were assigned. A software system (MZviewer) was developed to visualize semi-quantitative metabolome data using a dynamically generated scatter plot. We examined the metabolome of S. pombe cells exponentially grown in synthetic culture medium (EMM2) at two different temperatures, 26 °C and 36 °C. The profiles were similar except for varying amounts of certain amino acids and a significant increase in several compounds at 36 °C, such as trehalose (200-fold), glycerophosphoethanolamine (50-fold), arabitol (16-fold), ribulose (8-fold), and ophthalmic acid (5-fold). Reproducibility was demonstrated using a deletion mutant sib1Δ that lacked ferrichrome synthetase and showed no significant metabolic effects except the disappearance of the hexapeptide ferrichrome and the appearance of a putative dipeptide precursor. Taking advantage of the metabolic profile similarity at 26 °C and 36 °C, we analyzed the metabolome of a temperature-sensitive hcs1-143 mutant defective in the HMG-CoA synthase. As expected, HMG-CoA was decreased. In addition, extensive secondary metabolic effects, including a decrease in urea cycle intermediates and an increase in acetylated compounds, were observed. These findings confirm that S. pombe can be applied as an appropriate model to monitor metabolic responses to environmental conditions as well as genetic perturbations.