A new computational pipeline for analyzing three-dimensional imaging data can help biologists more accurately and quickly see how the cells in a plant’s leaves respond to the environment and identify plants that more efficiently use water, according to researchers.
A team of computer scientists and biologists from Penn State developed a 3D imaging model to study how tiny structures called stomatal guard cells, which are involved in plant photosynthesis and transpiration, interact with neighboring cells when undergoing physical changes. The model is more efficient and accurate than existing methods of analyzing cellular geometry and mechanics, and the researchers found that the guard cells behaved in unexpected ways. The research will help biologists run experiments more efficiently and identify plants, including important agricultural crops, that can better adapt to a changing climate.
“Currently, it takes experts five to eight hours to manually label just the guard cells in a single 3D image set,” said Dolzodmaa Davaasuren, a doctoral candidate in Penn State’s College of Information Sciences and Technology who led development of the pipeline. “Our team wanted to automate processes so we could study more images.”
The researchers built and tested their pipeline using the model plant Arabidopsis thaliana, commonly known as thale cress. They used a specialized confocal microscope to take 3D images of guard cells on the leaves of the plant. Guard cells surround stomatal pores and regulate how much carbon dioxide and water vapor pass through the pores. The team collected images before and after ablating, or using a laser beam to poke holes in, neighboring cells that were touching guard cells to see how stomatal volume changed.
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Image: Arabidopsis thaliana, allotment garden in Szczecin, West Pomeranian Voivodeship, Poland. (Credit: Salicyna via Wikimedia Commons)