Hongchao Ji1, Zhimin Zhang2, Hongmei Lu3. 1. College of Chemistry and Chemical Engineering, Central South University, Changsha, 410083, People's Republic of China. 2. College of Chemistry and Chemical Engineering, Central South University, Changsha, 410083, People's Republic of China. zmzhang@csu.edu.cn. 3. College of Chemistry and Chemical Engineering, Central South University, Changsha, 410083, People's Republic of China. hongmeilu@csu.edu.cn.
Abstract
INTRODUCTION: Untargeted and targeted analyses are two classes of metabolic study. Both strategies have been advanced by high resolution mass spectrometers coupled with chromatography, which have the advantages of high mass sensitivity and accuracy. State-of-art methods for mass spectrometric data sets do not always quantify metabolites of interest in a targeted assay efficiently and accurately. OBJECTIVES: TarMet can quantify targeted metabolites as well as their isotopologues through a reactive and user-friendly graphical user interface. METHODS: TarMet accepts vendor-neutral data files (NetCDF, mzXML and mzML) as inputs. Then it extracts ion chromatograms, detects peak position and bounds and confirms the metabolites via the isotope patterns. It can integrate peak areas for all isotopologues automatically. RESULTS: TarMet detects more isotopologues and quantify them better than state-of-art methods, and it can process isotope tracer assay well. CONCLUSION: TarMet is a better tool for targeted metabolic and stable isotope tracer analyses.
INTRODUCTION: Untargeted and targeted analyses are two classes of metabolic study. Both strategies have been advanced by high resolution mass spectrometers coupled with chromatography, which have the advantages of high mass sensitivity and accuracy. State-of-art methods for mass spectrometric data sets do not always quantify metabolites of interest in a targeted assay efficiently and accurately. OBJECTIVES: TarMet can quantify targeted metabolites as well as their isotopologues through a reactive and user-friendly graphical user interface. METHODS: TarMet accepts vendor-neutral data files (NetCDF, mzXML and mzML) as inputs. Then it extracts ion chromatograms, detects peak position and bounds and confirms the metabolites via the isotope patterns. It can integrate peak areas for all isotopologues automatically. RESULTS: TarMet detects more isotopologues and quantify them better than state-of-art methods, and it can process isotope tracer assay well. CONCLUSION: TarMet is a better tool for targeted metabolic and stable isotope tracer analyses.