Relieving the transfusion tissue traffic jam: a network model of radial transport in conifer needles

Abstract

The linear geometry of conifer leaves (e.g., pine needles) imposes architectural constraints on solute transport. The needles structural solution to prevent axial stagnation, however, introduces an additional challenge to radial transport by restricting loading and unloading of sugar and water, respectively, to a narrow zone at the periphery of the vascular bundle. Moreover, a Casparian strip blocks apoplastic flow through the endodermis between the vasculature and photosynthetic tissue, forcing countercurrents of water and sugar to travel simultaneously through the cell lumen at this interface. In between these two potential bottlenecks is the transfusion tissue, a distinctive anatomical feature of conifer needles. Here we develop a network-based mathematical model to explore how the structure of the intervening transfusion tissue facilitates radial transport of sugar and water. To describe extravascular transport with cellular resolution, we construct networks from images of Pinus pinea needles obtained through X-ray CT, as well as fluorescence and electron microscopy. Our results show that the physical separation of sugar and water pathways within the transfusion tissue mitigates the consequences of constricting flow at both the vascular access points and the endodermis. SIGNIFICANCEThe efficiency with which plants transport water and sugar across many scales affects their survival and success. At the leaf scale, accommodating the opposing flows of water and sugar is a nontrivial challenge, especially when foliar geometry imposes architectural limitations (e.g., in linear leaves (needles) of conifers). The transfusion tissue is a characteristic component of the conifer needle which mediates the radial transport of sugar and water. Our network model shows that the transfusion tissue alleviates the sugar-water traffic jams that would otherwise develop between the vascular system and photosynthetic cells. Our mathematical model provides finer resolution than what is currently possible with experimental approaches.