High-throughput microscopy image analysis of plant stomata

Abstract

High-oil tobacco varieties have been recently engineered to produce increased leaf oil content for future food and fuel needs. An engineered variety of Nicotiana tabacum produces ~30 percent of leaf dry weight in lipids in the form of triacylglycerol (TAG), a significant increase relative to the less than 1 percent storage oil normally found in wild-type leaves. This high-oil tobacco also accumulates oil bodies in stomatal guard cells. In order to understand the impact of oil on guard cell shape, aperture, and dynamics, we have co-opted computer vision tools in PlantCV to create an accurate, flexible, and high-throughput method for microscopy image analysis of stomata. To this end, leaf impressions are made with silicone putty; clear nail polish peels of the putty impressions are imaged using light microscopy. Binary thresholding followed by point-and-click regions of interest and morphology calculations provide stomatal counts, aperture, and other shape characteristics. Applying this method to high-oil tobacco demonstrated reduced stomatal aperture but the same number of stomata per unit leaf area, providing a mechanistic explanation of high-oil tobacco responses to high temperature and water deficit stresses.

Plant phenotyping relevance

植物の気孔形態・開度・密度を画像から抽出する高スループット手法の開発と適用が中心であり、単なる生物学的測定ではない。

Code and data availability

The supplied blocks are only a conference abstract describing a PlantCV-based stomata microscopy method. No public dataset, image collection, author code deposit, or supplement with paper-specific assets is mentioned; PlantCV is a generic third-party library, not a paper-specific asset.

No evidence-backed public reproduction asset is currently recorded.