2021 Vol. 7, No. 4

Cover Story

When imaging the nucleus structure of a cell, the out-of-focus fluorescence acts as background and hinders the detection of weak signals. Light-sheet fluorescence microscopy (LSFM) is a wide-field imaging approach which has the best of both background removal and imaging speed. However, the commonly adopted orthogonal excitation/detection scheme is hard to be applied to single cell imaging due to steric hindrance. For LSFMs capable of high spatiotemporal single cell imaging, the complex instrument design and operation largely limit their throughput of data collection. Here, the authors propose an approach for high-throughput background-free fluorescence imaging of single cells facilitated by the Immersion Tilted Light Sheet Microscopy (ImTLSM). ImTLSM is based on a light-sheet projected off the optical axis of a water immersion objective. With the illumination objective and the detection objective placed opposingly, ImTLSM can rapidly patrol and optically section multiple individual cells while maintaining single-molecule detection sensitivity and resolution. Further, the simplicity and robustness of ImTLSM in operation and maintenance enables high-throughput image collection to establish background removal datasets for deep learning. Using a deep learning model to train the mapping from epi-illumination images to ImTLSM illumination images, namely PN-ImTLSM, the authors demonstrated cross-modality fluorescence imaging, transforming the epi-illumination image to approach the background removal performance obtained with ImTLSM. They demonstrated that PN-ImTLSM can be generalized to large-field homogeneous illumination imaging, thereby further improving the imaging throughput. In addition, compared to commonly used background removal methods, PN-ImTLSM showed much better performance for areas where the background intensity changes sharply in space, facilitating high-density single-molecule localization microscopy. In summary, PN-ImTLSM paves the way for background-free fluorescence imaging on ordinary inverted microscopes.

REVIEW
Advancing biological super-resolution microscopy through deep learning: a brief review
Adaptive optics in super-resolution microscopy
Ferroptosis and its emerging role in tumor
Mutual interaction of microbiota and host immunity during health and diseases
PROTOCOL
An efficient method for the site-specific 99mTc labeling of nanobody
METHOD
Instant multicolor super-resolution microscopy with deep convolutional neural network
RESEARCH ARTICLE
PN-ImTLSM facilitates high-throughput low background single-molecule localization microscopy deep in the cell
Structural modeling of Nav1.5 pore domain in closed state