MET-XAlign: A Metabolite Cross Alignment Tool for LC-MS based Comparative Metabolomics
Wenchao Zhang, Zhentian Lei, David Huhman, Lloyd W. Sumner, and Patrick X. Zhao
Plant Biology Division, The Samuel Roberts Noble Foundation, 2510 Sam Noble Parkway, Ardmore, OK 73401, USA
Comparative metabolomics based on LC-MS has been widely used to identify biomarkers by comparing the shared differences among the detected biological meaningful features from hundreds to thousands of LC-MS samples that produced from multiple well designed experiments. However, there still are several challenges in this field, the first challenge is that there is no universal LC-MS libraries that can be used to elucidate the metabolite chemical structure and then to identify the metabolite; the second challenge is that the detected fragmentation pattern spectrum for the same potential metabolite can greatly vary from experiment to experiment, from instrument to instrument; the third challenge is that the observed retention time for the same analyte can be affected by experiment conditions. So, an efficient Tool that can align the same potential metabolite across not only from different samples, but also from different biological experiments, different instruments, is more attractive and urgent. Here, a novel Tool entitled as MET-XAlign is described, which can combine with our another developed Tool entitled as MET-COFEA and realize the potential extracted and annotated metabolite alignment in LC-MS based comparative metabolomics. The user can configure the optimal parameters for each biological experiment and run MET-COFEA separately to analyze the corresponding samples at pipeline mode, which will extract and annotate all of metabolites associated feature list and output them as database files. Finally, all of the exported database files from MET-COFEA can be aggregated and analyzed in MET-XAlign according to the user configured alignment parameters. The approach that combination of MET-COFEA with MET-XAlign makes it possible to align the potential same metabolite compound(known or unknown) not only across different samples, but also across different biological experiments, different ESI models, even different instruments, which can in turn be expected to help the biomarker identification in comparative metabolomics. MET-XAlign has been successfully developed with core algorithm coding in C++ and visualization part coding in .NET.