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Microscopy Method Supports 3D, Multitargeted Cell Imaging at Nanoscale

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HOUSTON, Dec. 10, 2024 — A new microscopy platform could improve investigations into the mechanisms that drive cellular behavior by providing fast, precise 3D imaging of multiple cellular structures at the nanoscale, while allowing flexible control of the extracellular environment.

The microscopy method is called soTILT3D — short for single-objective tilted light sheet with 3D point spread functions (PSFs). It was developed by a team at Rice University to address the constraints of existing fluorescence microscopy and single-molecule super-resolution microscopy techniques.

“Our goal with soTILT3D was to create a flexible imaging tool that overcomes limitations of traditional super-resolution microscopy,” professor Anna-Karin Gustavsson, who led the research, said. “We hope these advancements will enhance studies in biology, biophysics, and biomedicine, where intricate interactions at the nanoscale are key to understanding cellular function in health and pathogenesis.”
A prototype of the single-objective tilted light sheet with 3D point spread functions (soTILT3D) microscopy platform. Courtesy of Jeff Fitlow/Rice University.
A prototype of the single-objective tilted light sheet with 3D point spread functions (soTILT3D) microscopy platform. Courtesy of Rice University/Jeff Fitlow.

The soTILT3D microscopy platform provides a steerable, dithered, single-objective tilted light sheet for optical sectioning to reduce fluorescence background, and a pipeline for 3D nanoprinting microfluidic systems to reflect the light sheet into the sample. These features are combined with PSF engineering for nanoscale localization of individual molecules in 3D, as well as deep learning for analysis of overlapping emitters, active 3D stabilization for drift correction and long-term imaging, and Exchange-PAINT for sequential, multitarget imaging without chromatic offsets.

By integrating an angled light sheet, a nanoprinted microfluidic system, and computational tools, the soTILT3D platform enhances imaging precision and speed, allowing for clearer visualization of cellular structures at the nanoscale.

The system uses a single-objective, tilted light sheet to selectively illuminate thin slices of a sample. By reducing background fluorescence from out of focus areas, soTILT3D enhances the contrast, sharpening the image of the sample. This feature is especially useful when studying thick biological samples such as mammalian cells.

“The light sheet is formed using the same objective lens as used in the microscope for imaging, and it is fully steerable, dithered to remove shadowing artifacts that are common in light sheet microscopy, and angled to enable imaging all the way down to the coverslip,” Gustavsson said. “This allows us to image entire samples from top to bottom with improved precision.”

A custom-designed microfluidic system with an embedded, customizable micromirror provides precise control over the extracellular environment and allows for rapid, controlled solution exchange. The fast solution exchange feature can be used to test how drug treatments affect cells in real time.

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“The design and geometry of the microfluidic chip and nanoprinted insert with the micromirror can be easily adapted for various samples and length scales, providing versatility in different experimental setups,” researcher Nahima Saliba said.

The microfluidic device supports automated Exchange-PAINT imaging, allowing different targets to be visualized sequentially, without the color offsets common in multicolor approaches when imaging is performed in-depth at the nanoscale. The single-objective tilted light sheet and the microfluidic chip fabrication scheme provide the background reduction and solution exchange necessary to perform high-density, 3D, Exchange-PAINT imaging in thick mammalian cells.

The system uses deep learning to analyze higher fluorophore concentrations and improve imaging speed. It uses algorithms for real-time drift correction to enable stable, high-precision imaging over extended periods of time.

“The platform’s PSF engineering enables 3D imaging of single molecules, while deep learning handles dense emitter conditions which conventional algorithms have trouble with, which significantly improves the acquisition speed,” Saliba said.
A sample image created by the soTILT3D microscopy system. Courtesy of the Gustavsson Lab/Rice University.
A sample image created by the soTILT3D microscopy system. Courtesy of Rice University/Gustavsson Lab.

The angled light sheet in the soTILT3D platform improves the signal-to-background ratio for cellular imaging by up to six times, compared to traditional epi-illumination methods. The result is increased contrast and precise nanoscale localization.

“This level of detail reveals intricate aspects of 3D cell architecture that have been traditionally difficult to observe with conventional approaches,” researcher Gabriella Gagliano said.

Compared to traditional methods, the soTILT3D microscopy platform provides a tenfold increase in speed when combined with high emitter density and deep learning analysis. This allows researchers to capture detailed images of complex structures like the nuclear lamina, mitochondria, and cell membrane proteins across entire cells in a fraction of the usual time.

The platform supports whole-cell, 3D, multitarget imaging. It can acquire the distributions of multiple proteins within an entire cell and measure nanoscale distances between them, enabling researchers to visualize the spatial arrangement of closely situated proteins with precision and accuracy.

Single-molecule, super-resolution imaging of whole mammalian cells is often stymied by high fluorescence backgrounds and slow acquisition speeds, especially when multiple targets are imaged in 3D. The soTILT3D microscopy platform addresses these constraints. It offers a simple, flexible approach to 3D super-resolution imaging and single particle tracking that can be adapted and used for various single-molecule imaging applications to improve the speed, efficiency, and precision of nanoscale investigations of cellular structures and molecular dynamics.

The research was published in Nature Communications (www.doi.org/10.1038/s41467-024-54609-z).

Published: December 2024
Glossary
superresolution
Superresolution refers to the enhancement or improvement of the spatial resolution beyond the conventional limits imposed by the diffraction of light. In the context of imaging, it is a set of techniques and algorithms that aim to achieve higher resolution images than what is traditionally possible using standard imaging systems. In conventional optical microscopy, the resolution is limited by the diffraction of light, a phenomenon described by Ernst Abbe's diffraction limit. This limit sets a...
nano
An SI prefix meaning one billionth (10-9). Nano can also be used to indicate the study of atoms, molecules and other structures and particles on the nanometer scale. Nano-optics (also referred to as nanophotonics), for example, is the study of how light and light-matter interactions behave on the nanometer scale. See nanophotonics.
microfluidics
Microfluidics is a multidisciplinary field that involves the manipulation and control of very small fluid volumes, typically in the microliter (10-6 liters) to picoliter (10-12 liters) range, within channels or devices with dimensions on the microscale. It integrates principles from physics, chemistry, engineering, and biotechnology to design and fabricate systems that handle and analyze fluids at the micro level. Key features and aspects of microfluidics include: Miniaturization:...
lab-on-a-chip
A lab-on-a-chip (LOC) is a miniaturized device that integrates various laboratory functions and capabilities onto a single, compact chip. Also known as microfluidic devices, lab-on-a-chip systems are designed to perform a variety of tasks traditionally carried out in conventional laboratories, but on a much smaller scale. These devices use microfabrication techniques to create channels, chambers, and other structures that facilitate the manipulation of fluids, samples, and reactions at the...
deep learning
Deep learning is a subset of machine learning that involves the use of artificial neural networks to model and solve complex problems. The term "deep" in deep learning refers to the use of deep neural networks, which are neural networks with multiple layers (deep architectures). These networks, often called deep neural networks or deep neural architectures, have the ability to automatically learn hierarchical representations of data. Key concepts and components of deep learning include: ...
fluorescence
Fluorescence is a type of luminescence, which is the emission of light by a substance that has absorbed light or other electromagnetic radiation. Specifically, fluorescence involves the absorption of light at one wavelength and the subsequent re-emission of light at a longer wavelength. The emitted light occurs almost instantaneously and ceases when the excitation light source is removed. Key characteristics of fluorescence include: Excitation and emission wavelengths: Fluorescent materials...
Research & TechnologyeducationAmericasRice University3D imagingsuperresolutionMicroscopylight sheet microscopynanoImagingLight SourcesOpticsmirrorsmicrofluidicsBiophotonicsbioimagingmedicallab-on-a-chipdeep learningmolecular microscopyfluorescence

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