Morphological Plant Modeling: Unleashing Geometric and Topological Potential within the Plant Sciences

The geometries and topologies of leaves, flowers, roots, shoots, and their arrangements have fascinated plant biologists and mathematicians alike. As such, plant morphology is inherently mathematical in that it describes plant form and architecture with geometrical and topological techniques. Gaining an understanding of how to modify plant morphology, through molecular biology and breeding, aided by a mathematical perspective, is critical to improving agriculture, and the monitoring of ecosystems is vital to modeling a future with fewer natural resources. In this white paper, we begin with an overview in quantifying the form of plants and mathematical models of patterning in plants. We then explore the fundamental challenges that remain unanswered concerning plant morphology, from the barriers preventing the prediction of phenotype from genotype to modeling the movement of leaves in air streams. We end with a discussion concerning the education of plant morphology synthesizing biological and mathematical approaches and ways to facilitate research advances through outreach, cross-disciplinary training, and open science. Unleashing the potential of geometric and topological approaches in the plant sciences promises to transform our understanding of both plants and mathematics

Image-based plant wilting estimation

Abstract Background Environmental stress due to climate or pathogens is a major threat to modern agriculture. Plant genetic resistance to these stresses is one way to develop more resilient crops, but accurately quantifying plant phenotypic responses can be challenging. Here we develop and test a set of metrics to quantify plant wilting, which can occur in response to abiotic stress such as heat or drought, or in response to biotic stress caused by pathogenic microbes. These metrics can be useful in genomic studies to identify genes and genomic regions underlying plant resistance to a given stress. Results We use two datasets: one of tomatoes inoculated with Ralstonia solanacearum, a soilborne pathogen that causes bacterial wilt disease, and another of soybeans exposed to water stress. For both tomato and soybean, the metrics predict the visual wilting score provided by human experts. Specific to the tomato dataset, we demonstrate that our metrics can capture the genetic difference of bacterium wilt resistance among resistant and susceptible tomato genotypes. In soybean, we show that our metrics can capture the effect of water stress. Conclusion Our proposed RGB image-based wilting metrics can be useful for identifying plant wilting caused by diverse stresses in different plant species

Imaging and Analysis Platform for Automatic Phenotyping and Trait Ranking of Plant Root Systems1[W][OA]

The ability to nondestructively image and automatically phenotype complex root systems, like those of rice (Oryza sativa), is fundamental to identifying genes underlying root system architecture (RSA). Although root systems are central to plant fitness, identifying genes responsible for RSA remains an underexplored opportunity for crop improvement. Here we describe a nondestructive imaging and analysis system for automated phenotyping and trait ranking of RSA. Using this system, we image rice roots from 12 genotypes. We automatically estimate RSA traits previously identified as important to plant function. In addition, we expand the suite of features examined for RSA to include traits that more comprehensively describe monocot RSA but that are difficult to measure with traditional methods. Using 16 automatically acquired phenotypic traits for 2,297 images from 118 individuals, we observe (1) wide variation in phenotypes among the genotypes surveyed; and (2) greater intergenotype variance of RSA features than variance within a genotype. RSA trait values are integrated into a computational pipeline that utilizes supervised learning methods to determine which traits best separate two genotypes, and then ranks the traits according to their contribution to each pairwise comparison. This trait-ranking step identifies candidate traits for subsequent quantitative trait loci analysis and demonstrates that depth and average radius are key contributors to differences in rice RSA within our set of genotypes. Our results suggest a strong genetic component underlying rice RSA. This work enables the automatic phenotyping of RSA of individuals within mapping populations, providing an integrative framework for quantitative trait loci analysis of RSA

Reshaping Plant Biology: Qualitative and Quantitative Descriptors for Plant Morphology

International audienceAn emerging challenge in plant biology is to develop qualitative and quantitative measures to describe the appearance of plants through the integration of mathematics and biology. A major hurdle in developing these metrics is finding common terminology across fields. In this review, we define approaches for analyzing plant geometry, topology, and shape, and provide examples for how these terms have been and can be applied to plants. In leaf morphological quantifications both geometry and shape have been used to gain insight into leaf function and evolution. For the analysis of cell growth and expansion, we highlight the utility of geometric descriptors for understanding sepal and hypocotyl development. For branched structures, we describe how topology has been applied to quantify root system architecture to lend insight into root function. Lastly, we discuss the importance of using morphological descriptors in ecology to assess how communities interact, function, and respond within different environments. This review aims to provide a basic description of the mathematical principles underlying morphological quantifications

Revisiting the Source of Wilt Symptoms: X-Ray Microcomputed Tomography Provides Direct Evidence That Ralstonia Biomass Clogs Xylem Vessels

Ralstonia causes wilt diseases by colonizing xylem vessels and disrupting water transport. The dogma is that bacterial biomass clogs vessels and reduces the flow of xylem sap due to Ralstonia abundance. However, the physiological mechanism of xylem disruption during bacterial wilt is untested. Using a tomato and Ralstonia pseudosolanacearum GMI1000 model, we visualized and quantified spatiotemporal dynamics of xylem disruption during bacterial wilt. First, we measured stomatal conductance of leaflets on mock-inoculated and wilt-symptomatic plants. Wilted leaflets had reduced stomatal conductance, as did turgid leaflets on the same petiole as wilted leaflets. Next, we used X-ray microcomputed tomography (X-ray microCT) and light microscopy to differentiate between mechanisms of xylem disruption: blockage by bacterial biomass, blockage by vascular tyloses, or sap displacement by gas embolisms. We imaged intact plant stems to quantify embolized vessels. Embolized vessels were rare, but infected plants with low bacterial populations had a nonsignificant trend of more vessel embolisms. To test whether vessels are clogged during bacterial wilt, we imaged excised stems after brief dehydration. Most vessels in mock-infected plants emptied their contents after excision, but nonconductive clogged vessels were abundant in infected plants by 2 days post infection. At wilt onset, when bacterial populations exceeded 5 × 108 CFU/g stem tissue, approximately half of the vessels were clogged with electron-dense bacterial biomass. We found no evidence of tyloses in X-ray microCT reconstructions or from light microscopy of preserved stems. Therefore, bacterial blockage of vessels appears to be the principal cause of xylem disruption during Ralstonia wilt. [Graphic: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2022

Trehalose increases tomato drought tolerance, induces defenses, and increases resistance to bacterial wilt disease.

Ralstonia solanacearum causes bacterial wilt disease, leading to severe crop losses. Xylem sap from R. solanacearum-infected tomato is enriched in the disaccharide trehalose. Water-stressed plants also accumulate trehalose, which increases drought tolerance via abscisic acid (ABA) signaling. Because R. solanacearum-infected plants suffer reduced water flow, we hypothesized that bacterial wilt physiologically mimics drought stress, which trehalose could mitigate. We found that R. solanacearum-infected plants differentially expressed drought-associated genes, including those involved in ABA and trehalose metabolism, and had more ABA in xylem sap. Consistent with this, treating tomato roots with ABA reduced both stomatal conductance and stem colonization by R. solanacearum. Treating roots with trehalose increased xylem sap ABA and reduced plant water use by lowering stomatal conductance and temporarily improving water use efficiency. Trehalose treatment also upregulated expression of salicylic acid (SA)-dependent tomato defense genes; increased xylem sap levels of SA and other antimicrobial compounds; and increased bacterial wilt resistance of SA-insensitive NahG tomato plants. Additionally, trehalose treatment increased xylem concentrations of jasmonic acid and related oxylipins. Finally, trehalose-treated plants were substantially more resistant to bacterial wilt disease. Together, these data show that exogenous trehalose reduced both water stress and bacterial wilt disease and triggered systemic disease resistance, possibly through a Damage Associated Molecular Pattern (DAMP) response pathway. This suite of responses revealed unexpected linkages between plant responses to biotic and abiotic stress and suggested that R. solanacearum-infected plants increase trehalose to improve water use efficiency and increase wilt disease resistance. The pathogen may degrade trehalose to counter these efforts. Together, these results suggest that treating tomatoes with exogenous trehalose could be a practical strategy for bacterial wilt management