Deep machine learning for cell segmentation and quantitative analysis of radial plant growth.

Plants produce the major part of terrestrial biomass and are long-term deposits of atmospheric carbon. This capacity is to a large extent due to radial growth of woody species - a process driven by cambium stem cells located in distinct niches of shoot and root axes. In the model species Arabidopsis thaliana, thousands of cells are produced by the cambium in radial orientation generating a complex organ anatomy enabling long-distance transport, mechanical support and protection against biotic and abiotic stressors. These complex organ dynamics make a comprehensive and unbiased analysis of radial growth challenging and asks for tools for automated quantification. Here, we combined the recently developed PlantSeg and MorphographX image analysis tools, to characterize tissue morphogenesis of the Arabidopsis hypocotyl. After sequential training of segmentation models on ovules, shoot apical meristems and adult hypocotyls using deep machine learning, followed by the training of cell type classification models, our pipeline segments complex images of transverse hypocotyl sections with high accuracy and classifies central hypocotyl cell types. By applying our pipeline on both wild type and phloem intercalated with xylem (pxy) mutants, we also show that this strategy faithfully detects major anatomical aberrations. Collectively, we conclude that our established pipeline is a powerful phenotyping tool comprehensively extracting cellular parameters and providing access to tissue topology during radial plant growth.

Computational modeling of cambium activity provides a regulatory framework for simulating radial plant growth.

Precise organization of growing structures is a fundamental process in developmental biology. In plants, radial growth is mediated by the cambium, a stem cell niche continuously producing wood (xylem) and bast (phloem) in a strictly bidirectional manner. While this process contributes large parts to terrestrial biomass, cambium dynamics eludes direct experimental access due to obstacles in live-cell imaging. Here, we present a cell-based computational model visualizing cambium activity and integrating the function of central cambium regulators. Performing iterative comparisons of plant and model anatomies, we conclude that the receptor-like kinase PXY and its ligand CLE41 are part of a minimal framework sufficient for instructing tissue organization. By integrating tissue-specific cell wall stiffness values, we moreover probe the influence of physical constraints on tissue geometry. Our model highlights the role of intercellular communication within the cambium and shows that a limited number of factors are sufficient to create radial growth by bidirectional tissue production.