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Dorrestein, P.

Publications and source records attributed to Dorrestein, P..

20 records · Page 2Linked to original sources

Did a plant-herbivore arms race drive chemical diversity in Euphorbia?

The genus Euphorbia is among the most diverse and species-rich plant genera on Earth, exhibiting a near-cosmopolitan distribution and extraordinary chemical diversity, especially across highly toxic macro-and polycyclic diterpenoids. However, very little is known about drivers and evolutionary origins of chemical diversity within Euphorbia. Here, we investigate 43 Euphorbia species to understand how geographic separation over evolutionary time has impacted chemical differentiation. We show that the structurally highly diverse Euphorbia diterpenoids are significantly reduced in species native to the Americas, compared to the Eurasian and African continents, where the genus originated. The localization of these compounds to young stems and roots suggest ecological relevance in herbivory defense and immunomodulatory defense mechanisms match diterpenoid levels, indicating chemoevolutionary adaptation to reduced herbivory pressure.\n\nOne Sentence SummaryGlobal chemo-evolutionary adaptation of Euphorbia affected immunomodulatory defense mechanisms.

evolutionary biology↗

Significance estimation for large scale untargeted metabolomics annotations

The annotation of small molecules in untargeted mass spectrometry relies on the matching of fragment spectra to reference library spectra. While various spectrum-spectrum match scores exist, the field lacks statistical methods for estimating the false discovery rates (FDR) of these annotations. We present empirical Bayes and target-decoy based methods to estimate the false discovery rate. Relying on estimations of false discovery rates, we explore the effect of different spectrum-spectrum match criteria on the number and the nature of the molecules annotated. We show that the spectral matching settings needs to be adjusted for each project. By adjusting the scoring parameters and thresholds, the number of annotations rose, on average, by +139% (ranging from -92% up to +5705%) when compared to a default parameter set available at GNPS. The FDR estimation methods presented will enable a user to define the scoring criteria for large scale analysis of untargeted small molecule data that has been essential in the advancement of large scale proteomics, transcriptomics, and genomics science.

bioinformatics↗