Application of Optical Topometry to Analysis of the Plant Epidermis

Abstract

The plant epidermis regulates key physiological functions contributing to photosynthetic rate, plant productivity, and ecosystem stability. Yet, quantitative characterization of this interface between a plant and its aerial environment is laborious and destructive with current techniques, making large-scale characterization of epidermal cell parameters impractical. Here, we present our exploration of optical topometry (OT) for the analysis of plant organ surfaces. OT is a mature, confocal microscopybased implementation of surface metrology that generates nanometer-scale digital characterizations of any surface. We report epidermal analyses in Arabidopsis (Arabidopsis thaliana) and other species as well as dried herbarium specimens and fossilized plants. We evaluate the technology's analytical potential for identifying an array of epidermal characters, including cell type distributions, variation in cell morphology and stomatal depth, differentiation of herbarium specimens, and real-time deformations in living tissue following detachment. As applied to plant material, OT is very fast and nondestructive, yielding richly mineable data sets describing living tissues and rendering a variety of their characteristics accessible for statistical, quantitative genetic, and structural analysis.High-throughput methodologies are enabling ever more precise and integrated analyses of plant genomes, transcriptomes, proteomes, and metabolomes. However, connecting such comprehensive molecular data sets to the higher orders of plant organization that they control depends upon capturing correspondingly precise and authentic quantitative depictions of plant cell biology, anatomy, and developmental features. Highthroughput phenotyping techniques, enabling the speed and accuracy of data acquisition characteristic of omic technologies, are now needed if we are to forge mechanistic links between macroscopic plant phenotypes and their molecular underpinnings.This report addresses the challenge of structurally phenotyping the plant epidermis. A widely used and cost-effective method for quantifying epidermal phenotypes employs nail polish and/or dental resin to create an impression of the tissue surface, followed by imaging under light microscopy (Geisler et al., 2000;Delgado et al., 2011). Resultant images are then manually quantified using image analysis software such as ImageJ or Cell Profiler, yielding outputs such as cell sizes, stomatal index (number of stomata per total cell number), or stomatal density (number of stomata per unit area). Methods appropriate for smaller scale studies involve tissue fixation and staining or transgenic marker lines (Dow et al., 2014;Lawson et al., 2014). These current methods share common disadvantages of tedious sample preparation and low throughput. More elaborate methods involving fluorescence and electron microscopy are encumbered by the additional disadvantage of higher imaging equipment costs (Salomon et al., 2010). Finally, nearly all of these methods are somewhat or completely destructive, allo...

Optical topometry and machine learning to rapidly phenotype stomatal patterning traits for QTL mapping in maize

“…S3). This proof-of-concept built upon previous applications in individual genotypes of Arabidopsis (Haus et al, 2018), tobacco (Głowacka et al, 2018) and other dicot species (Haus et al, 2015). Each field of view could be acquired in less than 1 minute, so sampling four or five fields of view per leaf allowed 60 leaves to be comfortably screened with a single microscope in a standard 8-hr work day.…”

“…Optical topometry (OT) is a rare example of a new methodology proposed to accelerate the acquisition of epidermal patterning data through rapid image acquisition. OT is a non-destructive method for use on fresh or frozen leaf samples, which requires no sample preparation beyond sticking a piece of leaf to a microscope slide with double-sided sticky tape (Haus et al, 2015). It gathers focused pixels across plains of the leaf surface in less than one minute per field of view.…”

Long-Distance and Trans-Generational Stomatal Patterning by CO2 Across Arabidopsis Organs

“…All measurements were taken with a Nanofocus μsurf explorer ® optical topometer at 50× magnification with a 0.8 numerical aperture. Leaf epicuticular wax accumulation was estimated using the reflective intensity of an optical topometry surface measurement (Haus et al, 2015). Stomata and pavement cells were counted with ImageJ software cell counter tool.…”

Correlation and co-localization of QTL for stomatal density and canopy temperature under drought stress in Setaria

“…The youngest fully expanded leaf was excised from the plant 17 -22 days after sowing, covered in wet paper towel, sealed in airtight bags, and stored at 4 o C. Within 48 hours, a sample was excised with a razor blade from midway along the leaf to provide a cross-section from one leaf margin to the midrib (approximately 20-30 mm length, 3-20 mm wide). This sample was attached to a glass microscope slide using double-sided adhesive tape and the abaxial surface immediately imaged using an μsurf explorer optical topometer (Nanofocus, Oberhausen, Germany (Haus et al, 2015). Four fields of view in a transect from the midrib to the edge of a single leaf were imaged using a 20x magnification objective lens.…”

“…This is in part because standard protocols for measuring stomatal density are still laborious and time consuming, which slows the application of quantitative, forward, and reverse genetics approaches to identifying candidate genes and confirming their function. Therefore, improved methods for acquiring and analyzing images of stomatal guard cell complexes and other cell types in the epidermis are an area of active research (Haus et al, 2015;Dittberner et al, 2018;Fetter et al, 2019;Li et al, 2019). In addition, alternative approaches to rapidly screen stomatal conductance or rates of transpiration at the leaf and canopy scales (including temperature as a proxy) have also been developed and used to reveal genetic variation in traits related to drought stress and WUE (Liu et al, 2011;Bennett et al, 2012;Awika et al, 2017;Prado et al, 2018;Deery et al, 2019;Vialet-Chabrand and Lawson, 2019).…”