Expanding the Kendrick Mass Plot Toolbox in MZmine 2 to Enable Rapid Polymer Characterization in Liquid Chromatography−Mass Spectrometry Data Sets

Technological advances in mass spectrometry (MS) toward
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
ion 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.