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Redirecting tropane alkaloid metabolism reveals pyrrolidine alkaloid diversity in Atropa belladonna.

  • Hannah M Parks‎ et al.
  • The New phytologist‎
  • 2023‎

Plant-specialized metabolism is complex, with frequent examples of highly branched biosynthetic pathways, and shared chemical intermediates. As such, many plant-specialized metabolic networks are poorly characterized. The N-methyl Δ1 -pyrrolinium cation is a simple pyrrolidine alkaloid and precursor of pharmacologically important tropane alkaloids. Silencing of pyrrolidine ketide synthase (AbPyKS) in the roots of Atropa belladonna (Deadly Nightshade) reduces tropane alkaloid abundance and causes high N-methyl Δ1 -pyrrolinium cation accumulation. The consequences of this metabolic shift on alkaloid metabolism are unknown. In this study, we utilized discovery metabolomics coupled with AbPyKS silencing to reveal major changes in the root alkaloid metabolome of A. belladonna. We discovered and annotated almost 40 pyrrolidine alkaloids that increase when AbPyKS activity is reduced. Suppression of phenyllactate biosynthesis, combined with metabolic engineering in planta, and chemical synthesis indicates several of these pyrrolidines share a core structure formed through the nonenzymatic Mannich-like decarboxylative condensation of the N-methyl Δ1 -pyrrolinium cation with 2-O-malonylphenyllactate. Decoration of this core scaffold through hydroxylation and glycosylation leads to mono- and dipyrrolidine alkaloid diversity. This study reveals the previously unknown complexity of the A. belladonna root metabolome and creates a foundation for future investigation into the biosynthesis, function, and potential utility of these novel alkaloids.


Topological data analysis reveals a core gene expression backbone that defines form and function across flowering plants.

  • Sourabh Palande‎ et al.
  • PLoS biology‎
  • 2023‎

Since they emerged approximately 125 million years ago, flowering plants have evolved to dominate the terrestrial landscape and survive in the most inhospitable environments on earth. At their core, these adaptations have been shaped by changes in numerous, interconnected pathways and genes that collectively give rise to emergent biological phenomena. Linking gene expression to morphological outcomes remains a grand challenge in biology, and new approaches are needed to begin to address this gap. Here, we implemented topological data analysis (TDA) to summarize the high dimensionality and noisiness of gene expression data using lens functions that delineate plant tissue and stress responses. Using this framework, we created a topological representation of the shape of gene expression across plant evolution, development, and environment for the phylogenetically diverse flowering plants. The TDA-based Mapper graphs form a well-defined gradient of tissues from leaves to seeds, or from healthy to stressed samples, depending on the lens function. This suggests that there are distinct and conserved expression patterns across angiosperms that delineate different tissue types or responses to biotic and abiotic stresses. Genes that correlate with the tissue lens function are enriched in central processes such as photosynthetic, growth and development, housekeeping, or stress responses. Together, our results highlight the power of TDA for analyzing complex biological data and reveal a core expression backbone that defines plant form and function.


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