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The discovery of bioactive natural products is often challenged by the complexity of isolating and characterizing active compounds within diverse mixtures. Previously, we introduced a 1H NMR-based weighted gene correlation network analysis (WGCNA) approach to identify spectral features linked to growth inhibitory activity of Piper (Piperaceae) leaf extracts against model plant, fungal, and bacterial organisms. This method enabled us to prioritize specific spectral features linked to bioactivity, offering a targeted approach to natural product discovery. In this study, we validate the predictive capacity of the WGCNA by isolating the compounds responsible for the bioactivity-associated resonances and confirming their antifungal efficacy. Using growth inhibition assays, we verified that the isolated compounds, including three novel antifungal agents, exhibited significant bioactivity. Notably, one of these compounds contains a rare imidazolium heterocyclic motif, marking a new structural class in Piper. These findings substantiate the 1H NMR-based WGCNA as a reliable tool for identifying structural types associated with biological activity, streamlining the process of discovering bioactive natural products in complex extracts. 

A novel meroterpenoid cabagranin D was isolated with related neolignans cabagranins A–C from the leaves ofPiper cabagranum(Costa Rica). Cabagranins A–C represent the first examples of 3,3′-neolignans isolated from the plant genusPiper, and the meroterpenoid cabagranin D displays an unprecedented Diels–Alder conjugate of an unsubstituted phenylpropenone and α-phellandrene. Details of the full structural elucidation of these compounds and a discussion of their potential biosynthetic relationships are presented. 

Plant–insect interactions are common and important in basic and applied biology. Trait and genetic variation can affect the outcome and evolution of these interactions, but the relative contributions of plant and insect genetic variation and how these interact remain unclear and are rarely subject to assessment in the same experimental context. Here, we address this knowledge gap using a recent host-range expansion onto alfalfa by the Melissa blue butterfly. Common garden rearing experiments and genomic data show that caterpillar performance depends on plant and insect genetic variation, with insect genetics contributing to performance earlier in development and plant genetics later. Our models of performance based on caterpillar genetics retained predictive power when applied to a second common garden. Much of the plant genetic effect could be explained by heritable variation in plant phytochemicals, especially saponins, peptides, and phosphatidyl cholines, providing a possible mechanistic understanding of variation in the species interaction. We find evidence of polygenic, mostly additive effects within and between species, with consistent effects of plant genotype on growth and development across multiple butterfly species. Our results inform theories of plant–insect coevolution and the evolution of diet breadth in herbivorous insects and other host-specific parasites.