Multiscale asymptotic analysis reveals how cell growth and subcellular compartments affect tissue-scale hormone transport

Kiradjiev, K. B.; Band, L. R.

Abstract

Determining how cell-scale processes lead to tissue-scale patterns is key to understanding how hormones and morphogens are distributed within biological tissues and control developmental processes. In this article, we use multiscale asymptotic analysis to derive a continuum approximation for hormone transport in a long file of cells to determine how subcellular compartments and cell growth and division affect tissue-scale hormone transport. Focusing our study on plant tissues, we begin by presenting a discrete multicellular ODE model tracking the hormone concentration in each cell’s cytoplasm, subcellular vacuole, and surrounding apoplast, represented by separate compartments in the cell-file geometry. We allow the cells to grow at a rate that can depend both on space and time, accounting for both cytoplasmic and vacuolar expansion. Multiscale asymptotic analysis enables us to systematically derive the corresponding continuum model, obtaining an effective reaction–advection–diffusion equation and revealing how the effective diffusivity, effective advective velocity, and the effective sink term depend on the parameters in the cell-scale model. The continuum approximation reveals how subcellular compartments, such as vacuoles, can act as storage vessels, that significantly alter the effective properties of hormone transport, such as the effective diffusivity and the induced effective velocity. Furthermore, we show how cell growth and spatial variance across cell lengths affect the effective diffusivity and the induced effective velocity, and how these affect the tissue-scale hormone distribution. In particular, we find that cell growth naturally induces an effective velocity in the direction of growth, whereas spatial variance across cell lengths induces effective velocity due to the presence of an extra compartment, such as the apoplast and the vacuole, and variations in the relative sizes between the compartments across the file of cells. It is revealed that hormone transport is faster across cells of decreasing lengths than cells with increasing lengths. We also investigate the effect of cell division on transport dynamics, assuming that each cell divides as soon as it doubles in size, and find that increasing the time between successive cell divisions decreases the growth rate, which enhances the effect of cell division in slowing hormone transport. Motivated by recent experimental discoveries, we discuss particular applications for transport of gibberellic acid (GA), an important growth hormone, within the Arabidopsis root. The model reveals precisely how membrane proteins that mediate facilitated GA transport affect the effective tissue-scale transport. However, the results are general enough to be relevant to other plant hormones, or other substances that are transported in a similar way in any type of cells.

Citation

Kiradjiev, K. B., & Band, L. R. (2023). Multiscale asymptotic analysis reveals how cell growth and subcellular compartments affect tissue-scale hormone transport. Bulletin of Mathematical Biology, 85, Article 101. https://doi.org/10.1007/s11538-023-01199-4

• Journal Article Type: Article
• Acceptance Date: Aug 14, 2023
• Online Publication Date: Sep 13, 2023
• Publication Date: 2023-10
• Deposit Date: Sep 14, 2023
• Publicly Available Date: Sep 14, 2023
• Journal: Bulletin of Mathematical Biology
• Print ISSN: 0092-8240
• Electronic ISSN: 1522-9602
• Publisher: Springer Verlag
• Peer Reviewed: Peer Reviewed
• Volume: 85
• Article Number: 101
• DOI: https://doi.org/10.1007/s11538-023-01199-4
• Keywords: hormone transport; multiscale analysis; subcellular compartment; reaction-advection- diffusion equation; cell growth and division
• Public URL: https://nottingham-repository.worktribe.com/output/25350384
• Publisher URL: https://link.springer.com/article/10.1007/s11538-023-01199-4
• Additional Information: Received: 15 March 2023; Accepted: 14 August 2023; First Online: 13 September 2023