Revealing real-time 3D in vivo pathogen dynamics in plants by label-free optical coherence tomography

Abstract

Abstract Microscopic imaging for studying plant-pathogen interactions is limited by its reliance on invasive histological techniques, like clearing and staining, or, for in vivo imaging, on complicated generation of transgenic pathogens. We present real-time 3D in vivo visualization of pathogen dynamics with label-free optical coherence tomography. Based on intrinsic signal fluctuations as tissue contrast we image filamentous pathogens and a nematode in vivo in 3D in plant tissue. We analyze 3D images of lettuce downy mildew infection ( Bremia lactucae ) to obtain hyphal volume and length in three different lettuce genotypes with different resistance levels showing the ability for precise (micro) phenotyping and quantification of the infection level. In addition, we demonstrate in vivo longitudinal imaging of the growth of individual pathogen (sub)structures with functional contrast on the pathogen micro-activity revealing pathogen vitality thereby opening a window on the underlying molecular processes.

Plant phenotyping relevance

植物病原体を対象としたラベルフリーOCTによるリアルタイム3D画像化を開発し、感染植物の病原体量・感染レベル・活性を定量する手法として実証しているため、植物フェノタイピング手法が中心である。

Code and data availability

The authors explicitly deposited supporting code for dynamic OCT processing, segmentation, and data analysis, together with a representative selection of the dynamic OCT volumes (the paper's plant-pathogen phenotyping data), in a freely-accessible Zenodo repository (10.5281/zenodo.11428245). This is a paper-specific,公开