bioRxivPlant BiologyPreprint
Computational method for mapping mass signatures along developmental gradients reveals a novel role for a monosaccharide tetrose in maize salt-stress response.
Andrea M. SamaiD, Sinead B. Cahill, Shihong LuoiD, Abigail TripkaiD, Yifan MengiD, Sarah E. NolliD, Richard N. ZareiD, Pavak Kirit ShahiD, Alexandra Jazz DickinsoniD
Abstract
Metabolic processes are essential for regulating and maintaining developmental transitions, from stem cell quiescence through differentiation. However, the distinct metabolite-driven mechanisms that are critical for development remain poorly characterized due to inherent challenges in measuring their production, localization, and function in situ. We employed desorption electrospray ionization mass spectrometry imaging (DESI-MSI) to map metabolites in the developing maize root, which has a well-characterized longitudinal gradient that encompasses developmental transitions from quiescence through proliferation and maturation. DESI-MSI enables in situ analysis of the chemical composition of tissue sections with high spatial resolution ([~]50-100 {micro}m). To identify metabolites with specific developmental enrichment patterns, we developed a computational approach called Developmental Imaging Mass Spectrometry Pipeline for Linear Evaluation (DIMPLE). DIMPLE processes mass signatures along linear gradients, generating clusters of metabolites with specific developmental enrichment patterns in the maize root. We employed this method to compare developmental enrichment of metabolites in a salt-resilient maize variety, Oaxacan Green, and a salt-susceptible variety, B73. DIMPLE identifies specific differences in the mass signatures and the overall enrichment patterns between these varieties. DIMPLE also revealed a metabolite, D-erythrose, that had different localization patterns in these varieties. We found that in salt-sensitive maize varieties, treatment with D-erythrose improves stress tolerance by increasing primary root length. Overall, DIMPLE enables comprehensive and rapid analysis of metabolite patterns along a linear gradient, revealing new biology in plant growth and stress response.
- organism: plant (other)
- assay: metabolomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: spatial domain detection
- approach: deep learning
- approach: statistical model
- Citations
- 0
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