Expansion light sheet fluorescence microscopy of extended biological samples: Applications and perspectives

Expansion and Light-Sheet Microscopy for Nanoscale 3D Imaging

Expansion Microscopy (ExM) and Light-Sheet Fluorescence Microscopy (LSFM) are forefront imaging techniques that enable high-resolution visualization of biological specimens. ExM enhances nanoscale investigation using conventional fluorescence microscopes, while LSFM offers rapid, minimally invasive imaging over large volumes. This review explores the joint advancements of ExM and LSFM, focusing on the excellent performance of the integrated modality obtained from the combination of the two, which is refer to as ExLSFM. In doing so, the chemical processes required for ExM, the tailored optical setup of LSFM for examining expanded samples, and the adjustments in sample preparation for accurate data collection are emphasized. It is delve into various specimen types studied using this integrated method and assess its potential for future applications. The goal of this literature review is to enrich the comprehension of ExM and LSFM, encouraging their wider use and ongoing development, looking forward to the upcoming challenges, and anticipating innovations in these imaging techniques.

Airy beam light sheet microscopy boosted by deep learning deconvolution

Common light sheet microscopy comes with a trade-off between light sheet width defining the optical sectioning and the usable field of view arising from the divergence of the illuminating Gaussian beam. To overcome this, low-diverging Airy beams have been introduced. Airy beams, however, exhibit side lobes degrading image contrast. Here, we constructed an Airy beam light sheet microscope, and developed a deep learning image deconvolution to remove the effects of the side lobes without knowledge of the point spread function. Using a generative adversarial network and high-quality training data, we significantly enhanced image contrast and improved the performance of a bicubic upscaling. We evaluated the performance with fluorescently labeled neurons in mouse brain tissue samples. We found that deep learning-based deconvolution was about 20-fold faster than the standard approach. The combination of Airy beam light sheet microscopy and deep learning deconvolution allows imaging large volumes rapidly and with high quality.

Automatic detector synchronization for long-term imaging using confocal light-sheet microscopy

Light sheet fluorescence microscopy (LSFM) is an important tool in developmental biology. In this microscopy technique confocal line detection is often used to improve image contrast. To this end, the image of the illuminating scanned focused laser beam must be mapped onto a line detector. This is not trivial for long-term observations, since the spatial position of the laser beam and therefore its image on the detector may drift. The problem is aggravated in two-photon excitation LSFM, since pulsed laser light sources exhibit a lower laser beam pointing stability than continuous wave lasers. Here, we present a procedure for automatic synchronization between the excitation laser and detector, which does not require any additional hardware components and can therefore easily be integrated into existing systems. Since the recorded images are affected by noise, a specific, noise-tolerant focus metric was developed for calculating the relative displacement, which also allows for autofocusing in the detection direction. Furthermore, we developed an image analysis approach to determine a possible tilt of the excitation laser, which is executed in parallel to the autofocusing and enables the measurement of three solid angles. This allows to automatically correct for the tilting during a measurement. We demonstrated our approach by the observation of the migration of oligodendrocyte precursor cells in two-day-old fluorescent Tg(olig2:eGFP) reporter zebrafish larvae over a time span of more than 20 hours.

Imaging three-dimensional brain organoid architecture from meso- to nanoscale across development

Organoids are stem cell-derived three-dimensional cultures offering a new avenue to model human development and disease. Brain organoids allow the study of various aspects of human brain development in the finest details in vitro in a tissue-like context. However, spatial relationships of subcellular structures, such as synaptic contacts between distant neurons, are hardly accessible by conventional light microscopy. This limitation can be overcome by systems that quickly image the entire organoid in three dimensions and in super-resolution. To that end we have developed a system combining tissue expansion and light-sheet fluorescence microscopy for imaging and quantifying diverse spatial parameters during organoid development. This technique enables zooming from a mesoscopic perspective into super-resolution within a single imaging session, thus revealing cellular and subcellular structural details in three spatial dimensions, including unequivocal delineation of mitotic cleavage planes as well as the alignment of pre- and postsynaptic proteins. We expect light-sheet fluorescence expansion microscopy to facilitate qualitative and quantitative assessment of organoids in developmental and disease-related studies.