Combining deep learning approaches and point spread function engineering for simultaneous 3D position and 3D orientation measurements of fluorescent single molecules.

Point Spread Function (PSF) engineering is an effective method to increase the sensitivity of single-molecule fluorescence images to specific parameters. Classical phase mask optimization approaches have enabled the creation of new PSFs that can achieve, for example, localization precision of a few nanometers axially over a capture range of several microns with bright emitters. However, for complex high-dimensional optimization problems, classical approaches are difficult to implement and can be very time-consuming for computation. The advent of deep learning methods and their application to single-molecule imaging has provided a way to solve these problems. Here, we propose to combine PSF engineering and deep learning approaches to obtain both an optimized phase mask and a neural network structure to obtain the 3D position and 3D orientation of fixed fluorescent molecules. Our approach allows us to obtain an axial localization precision around 30 nanometers, as well as an orientation precision around 5 degrees for orientations and positions over a one micron depth range for a signal-to-noise ratio consistent with what is typical in single-molecule cellular imaging experiments.

Multiplexed PSF Engineering for Three-Dimensional Multicolor Particle Tracking.

Three-dimensional spatiotemporal tracking of microscopic particles in multiple colors is a challenging optical imaging task. Existing approaches require a trade-off between photon efficiency, field of view, mechanical complexity, spectral specificity, and speed. Here, we introduce multiplexed point-spread-function engineering that achieves photon-efficient, 3D multicolor particle tracking over a large field of view. This is accomplished by first chromatically splitting the emission path of a microscope to different channels, engineering the point-spread function of each, and then recombining them onto the same region of the camera. We demonstrate our technique for simultaneously tracking five types of emitters in vitro as well as colocalization of DNA loci in live yeast cells.

Single-Molecule Tracking and Its Application in Biomolecular Binding Detection.

In the past two decades significant advances have been made in single-molecule detection, which enables the direct observation of single biomolecules at work in real time and under physiological conditions. In particular, the development of single-molecule tracking (SMT) microscopy allows us to monitor the motion paths of individual biomolecules in living systems, unveiling the localization dynamics and transport modalities of the biomolecules that support the development of life. Beyond the capabilities of traditional camera-based tracking techniques, state-of-the-art SMT microscopies developed in recent years can record fluorescence lifetime while tracking a single molecule in the 3D space. This multiparameter detection capability can open the door to a wide range of investigations at the cellular or tissue level, including identification of molecular interaction hotspots and characterization of association/dissociation kinetics between molecules. In this review, we discuss various SMT techniques developed to date, with an emphasis on our recent development of the next generation 3D tracking system that not only achieves ultrahigh spatiotemporal resolution but also provides sufficient working depth suitable for live animal imaging. We also discuss the challenges that current SMT techniques are facing and the potential strategies to tackle those challenges.

Precise Three-Dimensional Scan-Free Multiple-Particle Tracking over Large Axial Ranges with Tetrapod Point Spread Functions.

We employ a novel framework for information-optimal microscopy to design a family of point spread functions (PSFs), the Tetrapod PSFs, which enable high-precision localization of nanoscale emitters in three dimensions over customizable axial (z) ranges of up to 20 µm with a high numerical aperture objective lens. To illustrate, we perform flow profiling in a microfluidic channel and show scan-free tracking of single quantum-dot-labeled phospholipid molecules on the surface of living, thick mammalian cells.

Heterochromatic Nonlinear Optical Responses in Upconversion Nanoparticles for Super-Resolution Nanoscopy.

Point spread function (PSF) engineering by an emitter's response can code higher-spatial-frequency information of an image for microscopy to achieve super-resolution. However, complexed excitation optics or repetitive scans are needed, which explains the issues of low speed, poor stability, and operational complexity associated with the current laser scanning microscopy approaches. Here, the diverse emission responses of upconversion nanoparticles (UCNPs) are reported for super-resolution nanoscopy to improve the imaging quality and speed. The method only needs a doughnut-shaped scanning excitation beam at an appropriate power density. By collecting the four-photon emission of single UCNPs, the high-frequency information of a super-resolution image can be resolved through the doughnut-emission PSF. Meanwhile, the two-photon state of the same nanoparticle is oversaturated, so that the complementary lower-frequency information of the super-resolution image can be simultaneously collected by the Gaussian-like emission PSF. This leads to a method of Fourier-domain heterochromatic fusion, which allows the extended capability of the engineered PSFs to cover both low- and high-frequency information to yield optimized image quality. This approach achieves a spatial resolution of 40 nm, 1/24th of the excitation wavelength. This work suggests a new scope for developing nonlinear multi-color emitting probes in super-resolution nanoscopy.

2.5D microscopy: Fast, high-throughput imaging via volumetric projection for quantitative subcellular analysis.

Imaging-based single-cell analysis is essential to study the expression level and functions of biomolecules at subcellular resolution. However, its low throughput has prevented the measurement of numerous cellular features from multiples cells in a rapid and efficient manner. Here we report 2.5D microscopy that significantly improves the throughput of fluorescence imaging systems while maintaining high-resolution and single-molecule sensitivity. Instead of sequential z-scanning, volumetric information is projected onto a 2D image plane in a single shot by engineering the emitted fluorescence light. Our approach provides an improved imaging speed and uniform focal response within a specific imaging depth, which enabled us to perform quantitative single-molecule RNA measurements over a 2×2 mm2 region within an imaging depth of ~5 µm for mammalian cells in <10 min and immunofluorescence imaging at a >30 Hz volumetric frame rate with reduced photobleaching. Our microscope also offers the ability of multi-color imaging, depth control and super-resolution imaging.

Enhanced lateral resolution in continuous wave stimulated emission depletion microscopy using tightly focused annular radially polarized excitation beam.

The lateral resolution of continuous wave (CW) stimulated emission depletion (STED) microscopy is enhanced about 12% by applying annular-shaped amplitude modulation to the radially polarized excitation beam. A focused annularly filtered radially polarized excitation beam provides a more condensed point spread function (PSF), which contributes to enhance effective STED resolution of CW STED microscopy. Theoretical analysis shows that the FWHM of the effective PSF on the detection plane is smaller than for conventional CW STED. Simulation shows the donut-shaped PSF of the depletion beam and confocal optics suppress undesired PSF sidelobes. Imaging experiments agree with the simulated resolution improvement.

Engineering and Optimization of Quasi-Nondiffracting Helicon-Like Beams With an Evolutionary Algorithm.

Nondiffracting beams maintain their intensity profiles over a large propagation distance without substantial diffraction and exhibit unique propagation trajectories, leading to scientific impacts in various fields. However, the nonlocalized intensity distribution of non-diffracting beams is restrictive for many practical applications. Thus, strategies to optimize the beam profiles remain much in demand. In this report, we demonstrate an evolutionary algorithmic framework for optical beam engineering and optimization and experimentally validate it by realizing quasi-nondiffracting radially self-accelerating (or self-rotating) beams in a high-resolution imaging system. The work reports a tightly confined side-lobe-suppressed helicon-like beam that largely maintains its properties of radial self-acceleration and non-diffraction in the 3-D space. The optimization method represents a new methodological avenue that can be extended to a broad range of beam engineering problems.