Microscopy Method Images Suspended Cells in 3D Using Optical Tweezers

Optical sectioning enables 3D bioimaging, but it requires non-optical techniques, such as sample adhesion and mechanical scanning, to hold and manipulate cells. In situ living cells may lack mechanical attachment or support, and may experience stress from artificial adhesion.

A non-contact solution for optical sectioning could broaden the use of 3D imaging to include live cells suspended in high-fluidity environments, such as water or air. Extending optical sectioning to these nonadherent targets is essential for bioimaging cellular structure and dynamics.

Researchers at the Xi’an Institute of Optics and Precision Mechanics (XIOPM) of the Chinese Academy of Sciences, working with a team at the Swiss Federal Institute of Technology, Lausanne (EPFL), developed a method to visualize suspended cells in 3D. Their approach couples structured illumination microscopy (SIM) with holographic optical tweezers. The holographic tweezers enable multiple cells to be manipulated simultaneously using customized structured light.

The developed method, called optical tweeze-sectioning microscopy (OTSM), uses optical processes for both cell immobilization and axial scanning, eliminating the need to affix the samples. OSTM acquires three-step phase-shifting images at each slice of the sample and reconstructs the slices into optical sectioning 3D images. It is an all-optical method and achieves sample scanning through optical delivery of the cells, instead of through translation stages.

To demonstrate OTSM, the researchers used an array of optical traps to capture multiple suspended yeast cells. OTSM enabled precise geometric trapping of 12 suspended live yeast cells into hexagonal, pentagonal, and ring shapes.

To alleviate the risk of photodamage, the researchers used a biocompatible near-infrared wavelength (1064 nm) for the optical traps. They used petal-like traps with a wider lateral dimension than standard Gaussian traps, which reduced the power density experienced by the cells. There was no observable damage to the cells during the experiment, even at the highest power (100 mW).

The team showed that OTSM could achieve full-volume imaging by using axial scanning to capture three-step phase-shifted images at each depth. The holographic optical trapping method trapped cells within structured illumination stripe periods, significantly reducing motion blur and ensuring stable axial scanning. SIM reconstruction produced high-resolution slices, enabling contact-free, high-fidelity 3D image reconstruction. The reconstructed images revealed distinct cellular features with dark shells enclosing bright cores.

The researchers developed a formula to quantify the effect of residual stripes in the reconstructed images — meeting a challenge specific to SIM-based optical scanning. They demonstrated that the effect could be minimized by preprocessing raw images with a background filter.

They showed that the position fluctuations of the cells could be optically squeezed to tens of nm, which is sufficient to implement optical scanning with SIM. Holographic optical trapping suppressed the motion of the suspended cells so that their positional fluctuations were smaller than the imaging resolution and the stripe period of structured illumination, which is essential for SIM.

The OTSM microscopy method enables assembly with controllable distances between cells and the imaging of multiple desired targets, while excluding undesired ones, offering a versatile platform for studying intercellular interaction and biomechanics.

OTSM technology overcomes the limitations of conventional bioimaging techniques that rely on static samples and mechanical scanning. “It promotes the integration of structured illumination microscopy and optical manipulation, and the cross-disciplinary fusion of optical tweezers with other imaging techniques to meet the demands for isotropic resolution, large field of view, and superresolution imaging,” professor Baoli Yao said.


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Optofluidic Antenna Enhances Single-Molecule Sensitivity in Liquid

Single-emitter fluorescence detection is used in diverse fields, from biophysics to quantum optics, to precisely observe processes at the single-molecule level. When performed under fluidic conditions, diffusion can restrict the observation time and detected photon counts, hampering the investigation of both slow and fast phenomena occurring in the molecule.

To enhance the optical signal from emitters in a liquid and allow longer observation times, researchers at the Max Planck Institute for the Science of Light (MPL) and the University of Düsseldorf developed and characterized an optofluidic antenna (OFA). The optical design of the OFA was adopted from a planar dielectric antenna.

The OFA expands the time range for studying biomolecular dynamics beyond the limit imposed by the translational diffusion time in a laser focus. It collects the photons emitted by individual fluorescent molecules with approximately 85% efficiency, enabling a time resolution in the microsecond (μs) range and allowing conformational changes of individual biomolecules to be observed with the highest temporal resolution.

The fabrication of the OFA device is inexpensive and straightforward. The antenna consists of a glass substrate and a layer of water that is several hundred nanometers thick and contains the molecules to be examined. The layer of water is created by a micropipette positioned just a few hundred nanometers above the substrate.

The axial boundary of the water layer forces the molecules to diffuse through the center of the laser focus, increasing the brightness of the laser light. The water-air interface slows the diffusion of the molecules and the antenna’s geometry increases the probability that a molecule will return to focus.

The researchers characterized the OFA using single-molecule, multi-parameter fluorescence detection (sm-MFD), fluorescence correlation spectroscopy (FCS), and Förster resonance energy transfer (FRET).

Using the OFA, they examined the change in conformity of a DNA four-way junction with a molecular mass of about 100 kilodalton (kDa), which is comparable to the size of many proteins and biomolecular machinery used for single-molecule studies. They examined both the slow (milliseconds) and fast (50 μs) dynamics of the DNA four-way junction with real-time resolution.

The researchers marked two legs of the DNA four-way junction with a FRET pair. The number of photons emitted by each of the two FRET partners changed with the distance between the two legs. The FRET trajectories revealed the absence of an intermediate conformational state and provided an upper limit for its lifespan. The OFA tracked the dynamics of DNA four-way crossing with a temporal resolution of just a few microseconds.

The OFA was found to enhance the fluorescence signal detected from molecules by about 5x per passage. It led to about 7x more frequent returns to the observation volume and it significantly lengthened the diffusion time. The OFA’s efficient collection of photons — an increase of about 2.2-fold — provides access to the optimal photon budget.

“Our optofluidic antenna works so well due to the improved photon collection efficiency from slower diffusing molecules in the spatially limited channel,” professor Stephan Götzinger said.

The OFA operates in a broad spectral domain and is fault-tolerant to antenna dimensions. It can be readily implemented in existing inverted microscopes and is compatible with other microscopy methods, such as dark-field and interferometric scattering for nanoparticle analysis. It can also be combined with platforms such as plasmonic systems, and with methods that slow down the translational diffusion of analytes, such as trapping, immobilization, and tethering mechanisms.

The sensitive, contact-free optical measurements achieved with the OFA provide access to both faster and slower dynamics of biological entities than a regular, bulk fluidic environment. Ease of implementation and compatibility with various microscopy modalities make the OFA a convenient platform for achieving more sensitive single molecule-fluorescence measurements for a range of studies.

“The antenna is a powerful device for investigations in the life sciences,” professor Vahid Sandoghdar said. “It is not only easy to use, but can also be easily integrated into many existing microscopy setups.”

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Imageomics Applies AI and Vision Advancements to Biological Questions

Researchers at Ohio State University are pioneering the field of “imageomics.” Founded on advancements in machine learning and computer vision, the researchers are using imageomics to explore fundamental questions about biological processes by combining images of living organisms with computer-enabled analysis.

The field was the subject of a presentation by Wei-Lun Chao, an investigator at Ohio State University’s Imageomics Institute and a distinguished assistant professor, during the annual meeting of the American Association for the Advancement of Science (AAAS). The presentation focused on the field’s application for micro- to macro-level problems by turning research questions into computable problems.

“Nowadays we have many rapid advances in machine learning and computer vision techniques,” said Chao. “If we use them appropriately, they could really help scientists solve critical but laborious problems.”

Imageomics researchers suggest that with the aid of machine and computer vision techniques, including pattern recognition and multi-modal alignment, the rate and efficiency of next-generation scientific discoveries could be expanded exponentially. This includes creating foundation models that will leverage data from multiple sources to enable various tasks and the development of machine learning models that are able to identify and discover traits to make it easier for computers to recognize and classify objects in images.

“Traditional methods for image classification with trait detection require a huge amount of human annotation, but our method doesn’t,” said Chao. “We were inspired to develop our algorithm through how biologists and ecologists look for traits to differentiate various species of biological organisms.”

Conventional machine learning-based image classifiers have achieved higher accuracy by analyzing an image as a whole, and then labeling it a certain object category. However, Chao’s team takes a more proactive approach, using a method that teaches the algorithm to actively look for traits like colors and patterns in any image that are specific to an object’s class – such as its animal species – while it’s being analyzed. In this way, imageomics can offer biologists a more detailed account of what is and is not revealed in the image, paving the way to quicker and more accurate visual analysis.

According to Chao, the technique and approach have been tested and shown to handle challenging recognition tasks, such as butterfly mimicries, in which species are differentiated by fine details and variety in their wing patterns and coloring. The ease with which the algorithm can be used could also allow imageomics to be integrated into a variety of other diverse purposes, ranging from climate to material science research, he said.

Chao said that one of the most challenging parts of fostering imageomics research is integrating different parts of scientific culture to collect enough data and form novel scientific hypotheses from them. That being said, he is enthusiastic about its potential to allow for the natural world to be seen within multiple fields.

“What we really want is for AI to have strong integration with scientific knowledge, and I would say imageomics is a great starting point towards that,” he said.


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Imaging Technology Shows How RNA in Cells Can Affect Health

 

Insight into the cellular distribution of RNA, which is closely linked to cell functions, could help scientists better understand the relation between cellular processes and disease. Potentially, this could lead to more targeted treatments for neurodegenerative disorders and aging.

While many methods have been developed to study RNA distribution within cells, only a few have been applied on a transcriptome-wide scale.

To capture the transcriptome of target cell types at the tissue level and RNA content within subcellular compartments, a research team at the UT Southwestern Medical Center, led by professor Haiqi Chen, developed Photoselection of Transcriptome over Nanoscale (PHOTON).

PHOTON combines high-resolution imaging with high-throughput sequencing to achieve spatial transcriptome profiling of RNA at subcellular resolution. It identifies RNA molecules at their native locations within cells, showing where different RNA species are distributed spatially in response to cellular cues.

To build PHOTON, the researchers designed DNA-based molecular cages that bound to all the RNA in cells. The molecular cages open when they are exposed to light, allowing for further chemical labeling.

After observing microscopically that the cells bound to the molecular cages, the researchers shined a narrow, 200-300-nm, near-ultraviolet (NUV) laser beam on regions of interest, such as specific organelles. The light caused the molecular cages to open, allowing only the RNA molecules located in the illuminated regions to be labeled. The researchers then collected the labeled RNA molecules and sequenced them to learn their identities and functions.

The team used PHOTON to examine RNAs present in the nucleolus and mitochondria, showing that RNAs identified through PHOTON closely matched those in published databases that were produced by isolating the organelles from the cells.

The researchers applied PHOTON to stress granules — transient, membraneless structures formed by cells when the cells are under stress. Although most stress granule RNAs that were identified matched those in published databases, the researchers found some discrepancies using PHOTON.

At the tissue scale, PHOTON accurately captured the transcriptome of cells within their native tissue microenvironment. At the subcellular scale, it enabled selective sequencing of the RNA content in the nucleoli, the mitochondria, and the stress granules.

The researchers used PHOTON to investigate whether m6A, a chemical modification found on some RNA molecules, played a role in moving RNAs into stress granules. By analyzing RNA molecules identified through PHOTON, the researchers found that the RNAs in the stress granules carried significantly more m6A than those outside the granules, suggesting that m6A contributes to the movement of specific RNAs into stress granules.

The researchers showed that PHOTON could be flexibly applied across regions of interest that spanned different scales, from specific regions of mouse ovarian tissue to various subcellular compartments. In-line image segmentation enabled the researchers to generate regions of interest based on an extensive range of spatial features, and automated the targeted photocleavage process over large numbers of cells or features.

These results show that PHOTON has the potential to uncover connections between spatial and transcriptomic information at diverse length scales.

Existing techniques to spatially identify RNA species can be prohibitively expensive and typically require specialized technical expertise and sophisticated image processing and data analysis to complete.

Chen said that he and his colleagues plan to use PHOTON to study the distributions of RNA in various conditions, particularly in neurodegenerative disease and aging. By comparing distributions in diseased cells to those in healthy cells, Chen said, researchers may be able to identify new targets for therapies to treat these conditions.

“Aging and many neurodegenerative diseases impose significant stress on cells, causing a subset of cellular RNA to redistribute into various subcellular compartments such as the stress granules,” Chen said. “PHOTON allows us to detect the spatial redistribution of cellular RNA in diseases versus health, helping us understand how these diseases cause damage to cellular functions.”

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Quantum Sensor Generates Own Light Source to Detect Biomolecules

The development of a compact, self-illuminating plasmonic sensor could make high-performing optical biosensors more accessible for rapid diagnostics and environmental monitoring and in point-of-care settings. The plasmonic biosensor can focus light waves down to a scale small enough to detect proteins and amino acids, without needing a bulky, expensive external light source.

By exploiting a quantum phenomenon called inelastic electron tunneling, researchers at the École Polytechnique Fédérale de Lausanne (EPFL), aided by colleagues at ETH Zurich, ICFO, and Yonsei University, created a biosensor that requires only a steady flow of electrons, in the form of an applied electrical voltage, to illuminate and detect molecules.

As an electron passes through a multilayer (metal-insulator-metal) film in the sensor structure, it transfers some of its energy to a plasmon, which then emits a photon. The intensity and spectrum of the light changes in response to contact with a biomolecule.

“If you think of an electron as a wave, rather than a particle, that wave has a certain low probability of ‘tunneling’ to the other side of an extremely thin insulating barrier while emitting a photon of light,” researcher Mikhail Masharin said. “What we have done is create a nanostructure that both forms part of this insulating barrier and increases the probability that light emission will take place.”

The multilayer structure has an aluminum electrode as the bottom layer, with a thin isolating layer of alumina, formed by thermal oxidation of the film, acting as a tunneling barrier. The upper electrode consists of a doubly periodic metasurface made of resonant gold nanowire antennas.

The plasmonic metasurface serves a dual purpose. It both creates the conditions for quantum tunneling and controls the resulting light emission, simultaneously providing enhanced electron-to-light conversion and far-field light emission. This dual capability is due to the arrangement of the gold nanowires, which act as nanoantennas to concentrate the light at the nm volumes required to detect biomolecules efficiently.

The optically resonant, doubly periodic nanowire metasurface provides uniform emission over large areas, amplified by the nanoantennas that simultaneously enhance the spectral and refractive index sensitivity.

“Inelastic electron tunneling is a very low-probability process, but if you have a low-probability process occurring uniformly over a very large area, you can still collect enough photons,” researcher Jihye Lee said. “This is where we have focused our optimization, and it turns out to be a very promising new strategy for biosensing.”

The researchers tested the biosensor with various analytes including thin layers of polymer and biomolecules. They observed that both the intensity and the spectral profile of the emitted light were modulated by the local refractive index changes produced by the presence of the analyte.

“Tests showed that our self-illuminating biosensor can detect amino acids and polymers at picogram concentrations — that’s one-trillionth of a gram — rivaling the most advanced sensors available today,” researcher Hatice Altug said.

The biosensor provides an integrated, nanoscale light source without requiring any labels. With plasmonic antennas serving both as a sensing element and a light source, the sensor has a considerably smaller device footprint compared with designs involving the integration of plasmonic structures on top of LEDs or photodetectors.

In addition to being compact and sensitive, the quantum platform is scalable and compatible with sensor manufacturing methods. Less than one square millimeter of active area is required for sensing, demonstrating the potential for its use in handheld biosensors. Because it removes the need for an external light source, the on-chip, optical biosensor could be appropriate for various point-of-care applications.

“Our work delivers a fully integrated sensor that combines light generation and detection on a single chip,” researcher Ivan Sinev said. “With potential applications ranging from point-of-care diagnostics to detecting environmental contaminants, this technology represents a new frontier in high-performance sensing systems.”

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Deep Learning-Trained Imager Magnifies Subwavelength Objects

An optical imaging system from UCLA goes beyond the traditional diffraction limit to enable imaging at subwavelength resolution. The new imager will make direct imaging of phase objects with subwavelength resolution less challenging for bioimaging, sensing, material characterization, and other applications that frequently use phase imaging.

The imager, developed in the lab of UCLA professor Aydogan Ozcan, enables subwavelength imaging of phase and amplitude objects. To enable the imager to recover high-frequency information corresponding to the subwavelength features of an object, the research team uses all-optical diffractive encoding and decoding with a solid-immersion layer.

The imager’s thin, high-index, solid-immersion layer transmits high-frequency information about the object to a spatially-optimized diffractive encoder. The encoder converts and encodes the high-frequency information into low-frequency spatial modes for transmission through air.

A diffractive decoder, which is jointly trained with the encoder surface, processes the encoded spatial information that is propagated through the air to create a magnified image of the input object. The magnified image reveals subwavelength features that would normally be washed out due to diffraction limitations.

To demonstrate the subwavelength diffractive imager, the researchers fabricated a multilayer, monolithic design that operates at the terahertz (THz) part of the spectrum. They tested this monolithic diffractive encoder-decoder pair with a customized, high-resolution THz imaging system. The experimental results confirmed that the 3D-fabricated, solid-immersion diffractive imager can resolve phase objects by directly performing transformations through the diffractive encoder-decoder pair.

At THz frequencies, the imager can resolve features as small as λ/3.4 (where λ is the illumination wavelength) by directly transforming them into magnified features at the output.

The trained subwavelength diffractive imager generalized to previously unseen objects from the same distribution as the objects used in training, demonstrating internal generalization. It also generalized to new types of objects from completely different datasets, demonstrating external generalization capability.

The user can operate the subwavelength imager at different parts of the electromagnetic spectrum by physically scaling — that is, by expanding or shrinking — the optimized diffractive features of the encoder and decoder surfaces in proportion to the illumination wavelength. This can be done without needing to redesign the diffractive features of the system.

The subwavelength imager offers the advantage of directly performing quantitative phase retrieval, eliminating the need for lengthy computer processing, which consumes a lot of power.

The researchers believe that the solid-immersion diffractive imager, with its compact size, cost-effectiveness, and ability to capture subwavelength features, could lead to significant advancements in bioimaging, sensing, and material inspection, among many other applications.

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Gamma Light, Sound Could Lessen Neurodegenerative Effects

An MIT study shows how 40 Hz sensory stimulation with light and sound helps sustain myelination, an essential process in the brain that insulates the signal-sending branches of neurons, called axons, with protective myelin sheaths.

Often called the brain’s “white matter,” myelin ensures electrical signal transmission in brain circuits. Demyelination, characterized by the loss of the myelin sheath and the oligodendrocyte cells that form it, leads to impaired axonal function, resulting in brain atrophy and neurodegeneration.

Early-stage trials in Alzheimer’s disease patients and studies in mouse models of the disease have suggested that exposure to light and sound at the gamma band frequency of 40 Hz can have a positive impact on the pathology and symptoms from neurodegenerative disorders.

“Gamma stimulation promotes a healthy environment,” said researcher Daniela Rodrigues Amorim. “There are several ways we are seeing different effects.”

The researchers used the cuprizone mouse model of demyelination to investigate the ways in which gamma sensory stimulation may promote myelination and reduce neuroinflammation. They divided the mice into four groups: mice that were fed a normal diet; mice that received no cuprizone but did receive gamma stimulation; mice that received cuprizone and constant, but not 40 Hz, stimulation; and mice that received cuprizone and 40 Hz stimulation.

The cuprizone-fed mice that received 40 Hz stimulation retained significantly more myelin, rivaling the myelin health of mice never fed cuprizone in some areas.

The team also investigated whether oligodendrocyte cells had higher survival rates in mice exposed to 40 Hz sensory stimulation. The number of oligodendrocyte cells was much closer to healthy levels in mice fed cuprizone and treated with gamma stimulation than in cuprizone-fed mice not exposed to gamma stimulation.

Electrophysiological testing of the neural axons showed that electrical performance improved in the cuprizone-fed mice that received gamma stimulation, compared to the cuprizone-fed mice not treated with 40 Hz stimulation.

To further explore how 40 Hz sensory stimulation might protect myelin, the researchers evaluated the protein expression from all four mouse groups. An analysis of the mice’s brain tissue identified distinct differences in protein expression between the cuprizone-fed mice exposed to control stimulation and the cuprizone-fed mice that received gamma stimulation.

The gamma-treated, cuprizone-fed mice showed an increase in microtubule-associated protein 2 (MAP2), a protein that helps preserve the functional integrity of myelin. Synaptic plasticity, also associated with the preservation of myelin, was better preserved in the mice exposed to 40 Hz stimulation. Exposure to gamma stimulation also helped to decrease oligodendrocyte cell death, which is linked to demyelination, by reducing ferroptosis.

The team assessed gene expression in the mice using single-cell RNA sequencing technology and found that gamma stimulation had an anti-inflammatory effect in the brain. When exposed to 40 Hz light and sound, fewer cells became inflammatory. Direct observation of tissue showed that microglia became more proficient at clearing away myelin debris, a key step in repairing myelin, in the gamma-stimulated group.

The results of the study suggest that 40 Hz sensory stimulation with light and sound could be therapeutic for numerous disorders that exhibit myelin degeneration, including multiple sclerosis and Alzheimer’s disease. The course of these neurological conditions comprises severe neurodegenerative processes, including neuroinflammation, profound myelin damage, and brain atrophy.

Cognito Therapeutics, the spin-off company that licensed MIT’s sensory stimulation technology, published phase II human trial results in the Journal of Alzheimer’s Disease in early 2024, which indicated that 40 Hz light and sound stimulation significantly slowed the loss of myelin in volunteers with Alzheimer’s. In 2024, the lab of professor Li-Huei Tsai also published a study showing that gamma sensory stimulation helped mice withstand neurological effects of chemotherapy medicines, including by preserving myelin.

“Previous publications from our lab have mainly focused on neuronal protection,” Tsai said. “But this study shows that it’s not just the gray matter, but also the white matter that’s protected by this method.”


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