Analysis of LC-MS data for characterizing the metabolic changes in response to radiation

Recent advances in mass spectrometry-based metabolomics have created the potential to measure the levels of hundreds of metabolites that are the end products of cellular regulatory processes. In this study, we investigate the metabolic changes in genetically engineered cell lines in response to radiation exposure. "Shrinkage t" statistic and partial least-squares-discriminant analysis methods are utilized to identify peaks whose signal intensities were significantly altered by radiation. This is accomplished through pairwise comparison of radiation treated cell lines at various time points following radiation against untreated cell lines. A pathway analysis is performed following identification of the metabolites represented by the selected peaks. The results indicate an ATM regulated induction of major pathways in response to radiation treatment.