Jiang, Xiaotong | Search NASA

DOE OSTI2023

The role of photorespiration in plant immunity

To defend themselves in the face of biotic stresses, plants employ a sophisticated immune system that requires the coordination of other biological and metabolic pathways. Photorespiration, a byproduct pathway of oxygenic photosynthesis that spans multiple cellular compartments and links primary metabolisms, plays important roles in defense responses. Hydrogen peroxide, whose homeostasis is strongly impacted by photorespiration, is a crucial signaling molecule in plant immunity. Photorespiratory metabolites, interaction between photorespiration and defense hormone biosynthesis, and other mechanisms, are also implicated. An improved understanding of the relationship between plant immunity and photorespiration may provide a much-needed knowledge basis for crop engineering to maximize photosynthesis without negative tradeoffs in plant immunity, especially because the photorespiratory pathway has become a major target for genetic engineering with the goal to increase photosynthetic efficiency.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

DeepLearnMOR: a deep-learning framework for fluorescence image-based classification of organelle morphology

Abstract The proper biogenesis, morphogenesis, and dynamics of subcellular organelles are essential to their metabolic functions. Conventional techniques for identifying, classifying, and quantifying abnormalities in organelle morphology are largely manual and time-consuming, and require specific expertise. Deep learning has the potential to revolutionize image-based screens by greatly improving their scope, speed, and efficiency. Here, we used transfer learning and a convolutional neural network (CNN) to analyze over 47,000 confocal microscopy images from Arabidopsis wild-type and mutant plants with abnormal division of one of three essential energy organelles: chloroplasts, mitochondria, or peroxisomes. We have built a deep-learning framework, DeepLearnMOR (Deep Learning of the Morphology of Organelles), which can rapidly classify image categories and identify abnormalities in organelle morphology with over 97% accuracy. Feature visualization analysis identified important features used by the CNN to predict morphological abnormalities, and visual clues helped to better understand the decision-making process, thereby validating the reliability and interpretability of the neural network. This framework establishes a foundation for future larger-scale research with broader scopes and greater data set diversity and heterogeneity.

Plant Sciences↗