Pushing Imaging Limits with Super-Resolution Microscopy

To unravel the complexities of biological phenomena, scientists have long relied on microscopy to visualize the intricate details of their specimens, including tissue architecture, cell morphology, and subcellular structures. However, the properties of light limit traditional imaging techniques. As technology advances, new microscopy methods such as super-resolution microscopy push these boundaries and allow researchers to view biological samples with unprecedented resolution.

In this Innovation Spotlight, Paul Scagnetti, chief executive officer of Oxford Nanoimaging (ONI), discusses how super-resolution microscopy compares to other imaging methods and how novel, user-friendly platforms are making super-resolution techniques more accessible to researchers.

What is super-resolution microscopy?

Super-resolution microscopy enables scientists to look beyond the limit of traditional microscopes, which are unable to resolve objects smaller than 250nm due to the properties of light. It encompasses various techniques able to overcome the so-called diffraction limit and improve resolution—the ability to distinguish two nearby points as distinct objects—by up to two orders of magnitude. The latest advancements can resolve structures below 10nm (ten thousand times smaller than the width of a human hair) and locate single molecules with high accuracy.

There are different super-resolution microscopy approaches to study cells and tissues at the nanoscale. The three pioneering techniques introduced in the 2000s were single-molecule localization microscopy (SMLM), structured illumination microscopy (SIM), and stimulated emission depletion (STED). They use different principles to control molecule activation or light shape. Together with advanced software, super-resolution microscopy produces beautifully detailed, informative images fueling groundbreaking discoveries in life sciences research.

How do SMLM techniques generally work, and what are some of the key methods within this family?

In fluorescence microscopy, a fluorophore is attached to the molecule of interest and imaged with a camera. Imagine looking at a Christmas tree. With a conventional microscope, the lights appear blurry, and it is impossible to discern details. With SMLM microscopes, each branch and its parts are resolved with incredible precision. Fluorophores are randomly activated over time, so each one blinks at a separate time from its neighbors. Once they all blink, the camera and software pinpoint their coordinates with high precision. What looked like a single blurry light is now resolved to individual points. This breakthrough technology enables a much deeper understanding of molecular behavior, pathological processes, and therapeutic mechanisms of action.

The main SMLM techniques include direct stochastic optical reconstruction microscopy (dSTORM), point accumulation for imaging in nanoscale topography (PAINT), and photoactivated localization microscopy (PALM). dSTORM relies on the random switching of conventional fluorophores on fixed cells, which allows the method to achieve 20nm resolutions. Moreover, PAINT uses transient fluorophore-target binding through DNA pairs, enabling the detection of multiple targets in one sample. Alternatively, PALM leverages photoactivatable fluorophores to resolve spatial details, facilitating single-particle studies in solution or live cells.

How do SMLM methods differ from conventional fluorescence and confocal microscopy techniques?

Conventional fluorescence imaging illuminates the entire sample at once, while confocal microscopy collects light from a single section to reduce out-of-focus signal. Both are diffraction-limited techniques, and thus any subcellular details become blurry. SMLM overcomes the diffraction limit by triggering the random activation of fluorophores over time to build a complete high-resolution picture of the structure underneath. This enables scientists to visualize structures with at least ten times better resolutions, gaining novel insights across applications such as molecular research, biomarker discovery, and drug delivery.

From a practical standpoint, sample preparation is very similar, whereby molecules are labeled with SMLM-compatible fluorophores. Advanced data processing tools, such as those that use machine learning and other algorithms, are applied to SMLM data to obtain detailed images and quantitative information on molecular structures, interactions, and single-molecule behavior.

What are the advantages of SMLM compared to electron microscopy (EM)?

For decades, EM has been the go-to imaging method to visualize small biological structures with great detail. Although it achieves significantly better resolution than fluorescence microscopy, EM remains a complex technique with niche expertise needed for sample preparation, imaging, and analysis. Perhaps the biggest limitation of EM is that samples are generally observed as sections or molecules removed from their native state. SMLM enables analysis at similar resolutions, but molecules can be studied in their native state, and their spatial relation to other proteins can be understood. There are methods within SMLM, such as PALM, that are live cell compatible. Overall, super-resolution microscopy is more accessible and can uncover rare phenotypes and subtle differences imperceptible to the trained eye.

What are some examples of biological structures and phenomena that scientists can examine using SMLM techniques?

The precision of single-molecule microscopy has unlocked new frontiers in biomedical research, capturing biological structures and the spatial distribution of molecules with unprecedented detail. Scientists are using SMLM to understand crucial interactions (e.g., between cancer and immune cells), to monitor single-cell receptor profiles, or to measure differences in patients’ responses to therapy. SMLM’s incredible sensitivity allows the identification of novel cancer markers or the measurement of subtle protein state changes in neurological diseases. It is also emerging as a tool for the characterization of antibody affinity and specificity to improve therapeutic antibody discovery pipelines.

An area where SMLM is making strides is in the analysis of small particles, such as extracellular vesicles (EVs) or therapeutic vehicle lipid nanoparticles (LNPs). SMLM allows researchers to understand very heterogeneous and small EV populations, quantify their molecular content, and understand how they get taken up by target cells. For LNPs, in-depth characterization with SMLM enables scientists to access crucial information, including size, cargo loading, and surface modification, at extremely high resolution. This is enhancing research aimed at optimizing drug or mRNA loading and delivery to cells and tissues.

What are the major obstacles facing novice researchers interested in employing SMLM techniques, and how have recent advancements addressed these challenges?

Single-molecule microscopes have historically required specialized labs and highly trained staff, making SMLM inaccessible and sparingly used. The latest efforts in the field have focused on making tools accessible to scientists everywhere. Platforms like ONI’s Aplo Scope are disrupting the market with next-generation instruments able to observe and measure molecules in cells and tissues with unparalleled power and ease of use. It offers live cell imaging and SMLM at 20nm resolution, smoothly transitioning from capturing live cells to zooming into the nanoscale in real time. Aplo means simple, as it delivers SMLM with a uniquely compact design, intuitive interface, and automated workflows. The Aplo Platform is the ultimate end-to-end solution, including robust benchtop SMLM, application-specific kits, automated fluidic control, and cloud-based software to deliver true sample-to-answer results.

Users of any skill level can benefit greatly from easy-to-use platforms built to bring reliability and high throughput to labs worldwide. Scientists can obtain meaningful, instantly shareable molecular data without having to worry about complex hardware or analysis setups. We are putting tremendous effort into ensuring SMLM workflows produce results as repeatable as sequencing and mass spectrometry, crucial to any life science tool. SMLM is becoming faster, more powerful, and intuitive to use, bringing new depths of information to accelerate the path from discovery to life-changing therapies.

How do you see SMLM evolving over the next decade?

I think SMLM will become as important to researchers as DNA sequencing, mass spectrometry, and other fundamental life science tools. We are enabling a novel way to better understand mechanisms of action at the molecular scale. The techniques are becoming robust workflows, and scientists who did not think of using SMLM because of complexity and the amount of time per analysis will use it much more routinely.

SMLM will enable researchers to watch therapeutic molecules in action and understand how they work. In some cases, it will allow them to observe that a therapeutic molecule is not working or not getting to the cell of interest and then be able to move on to more promising therapeutic molecules. Much of the characterization of mechanisms of action has been limited by the resolution at which molecules can be observed and by the ability to watch them dynamically. The fundamental, game-changing promise of SMLM is the ability to understand biology at the molecular level in its native state—not isolated molecules, but molecules interacting in their natural context.