Multimodal imaging unveils the hidden dimensions of plant physiology

from metabolic landscapes to mechanistic insights

authored by
André Gündel
supervised by
Hans-Peter Braun
Abstract

Images are worth a thousand words. The microscope marked a revolutionary moment in the history of natural sciences, and contemporary technologies like infrared (IR) and nuclear magnetic resonance (NMR) now enable us to explore the previously invisible in images. Computational tools allow in-depth analysis of intricate image data. The combined use of techniques such as IR and NMR Imaging, alongside molecular and metabolic tools, provides a powerful approach to understanding plant physiology (Chapter 2.6). I want to show you a comprehensive journey through the process of image acquisition and analysis. By describing deconvolutional data mining, I can show you how to enable imaging of multiple metabolites using a single infrared platform (Chapter 2.1). This strategy allows us to understand the assimilate allocation of major transport and storage compounds and offers a road map to analyse such IR images quantitatively. The complex interplay between physics and chemistry, especially in biological systems, presents a challenge for acquiring and interpreting the resulting data. Plants present a remarkable complexity, featuring a mosaic of diverse tissues and cells, each with their unique roles contributing to the overall functioning of the plant. Even seemingly inert cell tissues serve vital purposes. Imaging techniques are indispensable for unravelling the spatial variations within plants. Often, we lose topographical relations due to destructive sampling. Abstract chemical clusters can be defined by more sensitive non-topographic analytics and imaged even if single analytes tend to fall below their detection limit. Chapter 2.2 provides an insight into how exudate composition can be traced back to their original source tissues by a multimodal approach of mass spectrometry and IR imaging to provide a better context of composition and function. Computational modelling of plant physiology can provide insights into the chemistry of cell walls and derive conclusions with respect to the mechanical stability of the internodes in grasses against lodging. By integrating a mechanical model of the vascular structure with its chemistry, this work sheds light on the complexity of structural resource buildup and links its genetic regulation through KASP markers to traceable spectral characteristics and physical response (Chapter 2.3). Finally, we want to know how assimilates get where they are supposed to be. The terminal part of the assimilate allocation pathway is controlled by the post-phloem maternal filial transition tissues. Its functional role in metabolite delivery from maternal to filial organs is vital for developing seeds. This work focuses on two crucial aspects that require particular attention. First is the dual role of an important sucrose transporter SWEET11b in the allocation of sugars and cytokinin in barley grain (Chapter 2.4). Chemical imaging visualised a gradient in cytokinin distribution and evidenced its topographical link to sucrose gradients during grain filling. Second is the involvement of programmed cell death and vacuolar processing enzymes (VPE2) in assimilate release from the nucellar projection into the endosperm cavity (Chapter 2.5). Detailed analysis of mutants and transgenics helps to generate mechanistic views of the complex story. All of these studies highlight the power of advanced imaging technologies to unlock the secrets of plant development (Chapter 2.6). The whole plant will be affected in its distribution of sugars, as exemplified by the manipulation of maternal-filial interactions in seeds (Chapter 3.1). This discovery highlights the need to study local changes within a global framework of internal plant function. Such a strategy will enable us to identify regulatory responses in unforeseen locations and enhance our comprehension of the mechanisms that govern the sink-source relationships.

Organisation(s)
Institute of Plant Genetics
Type
Doctoral thesis
No. of pages
241
Publication date
2023
Publication status
Published
Electronic version(s)
https://doi.org/10.15488/15807 (Access: Open)