Expanding super-resolution imaging versatility in organisms with multi-confocal image scanning microscopy.

Abstract

Resolving complex three-dimensional (3D) subcellular dynamics noninvasively in live tissues demands imaging tools that balance spatiotemporal resolution, field-of-view and phototoxicity. Image scanning microscopy (ISM), as an advancement of confocal laser scanning microscopy, provides a 2-fold 3D resolution enhancement. Nevertheless, the relatively low imaging speed has been the major obstacle for ISM to be further employed in in vivo imaging of biological tissues. Our proposed solution, multi-confocal image scanning microscopy (MC-ISM), aims to overcome the limitations of existing techniques in terms of spatiotemporal resolution balancing by optimizing pinhole diameter and pitch, eliminating out-of-focus signals, and introducing a frame reduction reconstruction algorithm. The imaging speed is increased by 16 times compared with multifocal structured illumination microscopy. We further propose a single-galvo scan, akin to the Archimedes spiral in spinning disk confocal systems, to ensure a high-speed and high-accuracy scan without the galvanometer's inertial motion. Benefitting from its high photon efficiency, MC-ISM allows continuous imaging of mitochondria dynamics in live cells for 1000 frames without apparent phototoxicity, reaching an imaging depth of 175 μm. Noteworthy, MC-ISM enables the observation of the inner membrane structure of living mitochondria in Arabidopsis hypocotyl for the first time, demonstrating its outstanding performance.

Plant phenotyping relevance

生体組織の高速度・高分解能イメージング手法を開発し、Arabidopsisの生細胞ミトコンドリア動態・膜構造の観察に適用しており、植物状態の取得法が中心である。

Code and data availability

This paper describes a super-resolution microscopy method (MC-ISM) with an Arabidopsis hypocotyl mitochondria imaging demonstration, but it contains no plant-phenotyping measurements, trait datasets, or phenotyping analysis. The authors do release a paper-specific public code/data repository (reconstruction algorithms,

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