Systems biology approaches for studying sphingolipid signaling

The importance of sphingolipid metabolism and bioactive sphingolipid products in cancer development and disease progression is now well established (see other chapters in this volume). However, much remains unknown in terms of the signaling mechanisms and downstream pathways affected by sphingolipids in cancers, such as which sphingolipid pathway is involved, which sphingolipid species contributes to a specific cancer's biologic response, and which regulatory pathways are modulated by these bioactive sphingolipids. Due to the connectivity of sphingolipid metabolic network, it is difficult to address the above questions using conventional experimental approaches because manipulation of any one enzyme often results in a metabolic "ripple effect" across the network that are not easy to predict. In this chapter, we introduce a systems biology framework for deciphering signaling roles of distinct sphingolipid species and enzymes and for exploring novel mechanisms involving these pathways. These approaches have been successfully developed, applied, and validated in yeast systems. One component of the framework involves systematically perturbing sphingolipid metabolism using physiological and pharmacological approaches while monitoring lipidomic and transcriptomic responses to the perturbations are monitored; then different computational models are designed and applied to reveal relationship between specific sphingolipid species with transcriptomic modules, as a means to reveal signaling roles of distinct sphingolipid species. This component has successfully identified specific signaling pathways regulated by phytosphingosine-1-phosphate and clearly demonstrated that distinct ceramides encode disparate cellular signals. Another component of the framework concentrates on systematically identifying novel genes that could influence the activity of sphingolipid pathways. More specifically, we mined the literatures of yeast genes, constructed an Ontology Fingerprint of for each gene and developed an Ontology Fingerprint derived gene network, which were used to discover novel genes that modulates the activities of the sphingolipid pathway. This approach expanded our knowledge of the sphingolipid pathway by finding novel genes whose functions have not been associated with the pathway before. In summary, we show that systems biology approaches can effectively complement the experimental research and have a great potential to enhance the research of sphingolipids in cancers.