Evaluating line-broadening factors on a reference spectrum as a bucketing method for NMR based metabolomics.

Metabolomics based nuclear magnetic resonance (NMR) is widely used in disease mechanism analysis and drug discovery. One of the most important factors in NMR based metabolomics study is the accuracy of spectra bucketing which plays a critical role in data interpretation. Though various methods have been developed for automatic bucketing, the most popular approach is still the traditional rectangular bucketing method which is mainly due to the requirement of user expertise for the automatic bucketing methods. In this study, we developed a new automatic bucketing method that not only efficiently increases peak bucketing accuracy but also allows the bucketing process to be conveniently visualized and adjusted by the end-users. This method applied the line broadening (lb) factor to the average spectrum for a study set which serves as the reference spectrum, and the peak width of the reference spectrum was then set as the peak bucketing pattern. The approach to pick the bucket boundaries is simple but powerful after the line broadening factor was applied. The line broadening factors from 0 to 2 l b were tested using mouse fecal samples and the 1 l b method showed similar peak patterns and data interpretation results compared with a careful manual bucketing pattern. Besides this, the new method generated bucketing patterns could be easily visualized using the Amix software and revised by general users without excessive data science and NMR instrumentation expertise. In summary, our study showed a powerful and convenient tool in NMR peak auto bucketing with flexible visualization and adjustment ability for metabolomics studies.