Untargeted in silico compound classification – A novel metabolomics method to assess the chemodiversity in bryophytes

In plant ecology, biochemical analyses of bryophytes and vascular plants are often taken on dried herbarium specimen as species typically grow in distant and inaccessible locations where it is difficult to collect and preserve fresh plant material on-site. Here, we present a novel untargeted in silico compound classification framework to annotate metabolites using an untargeted DIA-LC/MS-SWATH-QToF ecometabolomics analytical method. At a global level, we perform a detailed comparative investigation of the chemical diversity and the composition of metabolite families in ten different species of bryophytes comparing fresh and dried specimen stored in an herbarium for half a year. Shannon and Pielou's diversity indices, hierarchical clustering, sPLS-DA, dbRDA, ANOVA with post-hoc Tukey HSD, heatmaps and sunburst plots were used to determine differences in the composition of metabolite families with regard to herbarium conditions and ecological characteristics. We annotate metabolite families related to structural protection of membranes and cell walls (glycerophospholipids, carbohydrates), chemical defense (polyphenols, steroids), ROS protection (alkaloids, amino acids, flavonoids), nutrition status (nitrogen- and phosphate-containing glycerophospholipids, carbohydrates), and photosynthesis. Changes in the composition of metabolite families also explained ecological functioning like physiological adaptations of bryophytes to dry environments (proteins, peptides, flavonoids, terpenes), light availability (flavonoids, terpenes, carbohydrates), temperature (flavonoids), and biotic interactions (steroids, terpenes). The results from this study allow to construct chemical traits that can be attributed to biogeochemistry, habitat conditions, environmental changes and biotic interactions. Our classification framework can further be used to assist phylogenetic analysis and to facilitate the complex annotation in ecometabolomics. The insights revealed by our framework allow to construct new research hypotheses and enable detailed follow-up studies.