Year: 2023
Type: article
Abstract: To understand how tissue-level structure and function manifests from the organization of subcellular cytoskeletal and signaling events, one must ultimately study these processes in their native tissue contexts. The most common approach for in vivo imaging is 2-photon laser scanning microscopy, often with a surgically implanted optical window [1]. More recently, 3-photon illumination has permitted ultradeep (∼1 mm) imaging with improved signal to background ratios [2]. However, even with adaptive optics [3], imaging is often limited to optically advantageous tissues such as the brain, observation remains prohibitively slow, and the resulting anisotropic resolution complicates quantitative image analysis at subcellular scales [4, 5]. Innovations in tissue clearing provides an opportunity to overcome these challenges. Broadly speaking, tissue clearing aims to homogenize the optical properties of a chemically fixed tissue by removing its lipids and immersing its proteinaceous remains in a solution with a matched refractive index. Today, multiple clearing mechanisms exist (including hyperhydrating, hydrogel, and organic solvent-based approaches), and each is accompanied with tissue- and labeling-specific advantages and disadvantages [6-9]. Nonetheless, most optical systems are not designed to accommodate the refractive index of chemically cleared specimens, resulting in deleterious aberrations, reduced sensitivity, and the inability to resolve subcellular structures in all three spatial dimensions. To quantitatively evaluate cell biological architectures in chemically cleared tissues, we developed an optimized imaging technology that we refer to as Cleared Tissue Axially Swept Light-Sheet Microscopy (CT-ASLM) [10-12]. In CT-ASLM, we deterministically scan a diffraction-limited light-sheet in its propagation direction synchronously with the rolling shutter readout of a scientific CMOS camera. To operate in a solvent-independent manner, CT-ASLM includes long working distance (10 mm) multi-immersion objectives with a numerical aperture of 0.7. CT-ASLM is ∼40x faster than a laser scanning confocal microscope, provides superior optical sectioning, a large field of view (342-400 microns), and a high isotropic resolution of ∼310-360 nm, depending upon the solvent refractive index. This is the highest axial resolution afforded by any light-sheet microscope in the absence of structured illumination, stimulated depletion, or localization approaches, thereby enabling the observation of fine morphological detail in all three spatial dimensions. To maximally leverage this imaging system necessitates highly transparent and uniformly labeled specimens. Thus, we quantitatively evaluated clearing and labeling methodologies on diverse tissue types, including lungs, livers, kidneys, and bladders. Distinct biological structures were visualized with self-labeling technologies (e.g., HaloTag) [13], indirect immunofluorescence, feature rich biochemically reactive conjugates (e.g., NHS-ester, hydrazide) [14], and affinity-based reagents (e.g., SYBR Green, ToPro-3). Clearing efficacy was estimated by measuring the Shannon Entropy of the Discrete Cosine Transform as a function of depth. Resolution was evaluated using Fourier-based methods such as decorrelation analysis [15]. For immunofluorescence, specificity was confirmed with tissues lacking the antigen, and by omitting the primary antibody in tissues positive for the antigen. The formation of non-specific aggregates was measured using particle detection routines and reduced by a factor of 10,000 after optimization of labeling conditions. As a result of this analytically driven optimization scheme, we now can robustly label and image single cells with high contrast, minimal background, and subcellular detail, deep within terminally differentiated tissues.
Source: Microscopy and Microanalysis
Authors: Hazel Borges, Jinlong Lin, Zach Marin, Kevin M Dean
Institution: The University of Texas Southwestern Medical Center
Language: English
Subfield: Biophysics
Domain: Life Sciences
Open Access status: bronze
OpenAlex ID: W4385072839