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Expanding the Kendrick mass plot toolbox in MZmine 2 to enable a rapid polymer characterization in liquid chromatography-mass spectrometry data sets.

Technological advances in mass spectrometry (MS) towards more accurate and faster data acquisition result in highly informative but also more complex data sets. Especially the hyphenation of liquid chromatography (LC) and MS yields large data files containing a high amount of compound specific information. Using electrospray-ionization for compounds such as polymers enables highly sensitive detection, yet results in very complex spectra, containing multiply charged ions and adducts. Recent years have seen the development of novel or updated data mining strategies to reduce the MS spectra complexity and to ultimately simplify the data analysis workflow. Among other techniques, the Kendrick mass defect analysis, which graphically highlights compounds containing a given repeating unit has been revitalized with applications in multiple fields of study, such as lipids and polymers. Especially for the latter, various data mining concepts have been developed, which extend regular Kendrick mass defect analysis to multiply charged series. The aim of this work is to collect and subsequently implement these concepts in one of the most popular open-source MS data mining software, i.e., MZmine 2, to make them rapidly available for different MS based measurement techniques and various vendor formats, with a special focus on hyphenated techniques such as LC-MS. In combination with already existing data mining modules, an example data set was processed and simplified, enabling an ever faster evaluation and polymer characterization.