Algorithm Boosts Live-Cell Imaging's Capabilities

Superresolution radial fluctuations (SRRF), a superresolution algorithm, works by observing fluctuations in radial symmetry throughout the frames of an image. SRRF supports live-cell, superresolution microscopy on a range of microscopy platforms with commonly used fluorescent protein tags.

A new implementation of SRRF, called enhanced superresolution radial fluctuations (eSRRF), was introduced by a team at the Gulbenkian Science Institute. According to the research team, eSRRF provides substantial improvements to image fidelity, resolution, and user-friendliness, compared to the original SRRF.

“eSRRF opens up new possibilities in live-cell imaging,” researcher Hannah Heil said. “It’s not just about enhancing image resolution — eSRRF empowers researchers to optimize results based on quantitative image quality measures.”

3D, live-cell, superresolution imaging with eSRRF. Mitochondria dynamics observed in U2OS cells expressing TOM20-Halo, loaded with the fluorescent marker JF54, with a multifocus microscope are superresolved by 3D eSRRF processing of the data set. This allows a superresolved volumetric view of 20 × 20 × 3.6 μm³ at a rate of about 1 Hz in a living cell. Courtesy of the Gulbenkian Science Institute.

To help users attain the optimal image reconstruction settings, eSRRF offers an automated, data-driven approach to parameter optimization. eSRRF directly provides users with data set-specific insight into the relationship between image fidelity and resolution, enabling users to critically analyze results and make informed decisions on analysis settings. Users achieve optimal parameters by balancing the need for high reconstruction fidelity with the need for high spatial and temporal resolution.

By highlighting the optimal parameter range and acquisition configurations, eSRRF minimizes artifacts and nonlinearity, improving overall image fidelity. “Our method provides researchers with a dynamic tool that adapts to their needs, making the invisible visible,” Heil said.

The researchers further enhanced SRRF by enabling full 3D superresolution with eSRRF. To do so, they combined eSRRF with multifocus microscopy. They adapted a method to analyze the nearly simultaneous multiplane acquisition of MFM to enable the high-speed volume observation of fluorophore fluctuations in eSRRF.

eSRRF can realize live-cell, volumetric, superresolution imaging with an acquisition speed of about one volume per second, in addition to providing fast, 2D, superresolution imaging. The researchers implemented 3D eSRRF to demonstrate how it enables rapid, 3D, superresolution imaging in live cells.

To show the broad applicability of eSRRF, the researchers demonstrated it with a range of biological samples, from single cells to organisms. They used imaging techniques from widefield microscopy, total internal reflection fluorescence microscopy, light-sheet microscopy, structured detection microscopy, and single-molecule localization microscopy imaging modalities.

eSRRF showed robust performance over the different signal fluctuation dynamics displayed by various organic dyes and fluorescent proteins and over a wide range of marker densities, recovering high-fidelity, superresolution images even in challenging conditions.

By maximizing information extraction across varied experimental conditions while minimizing artifacts, eSRRF offers an accessible approach to superresolution. It can show users how to best analyze their data and help them determine the best conditions for live-cell, superresolution imaging that are also sensitive to the potential for phototoxicity.

The capabilities of eSRRF could make live-cell, superresolution microscopy more stable and reliable. The researchers expect that their strategy for eSRRF could be transferred to other superresolution methods that require an analytical component, for example, to SMLM approaches.

Researcher Ricardo Henrique said the new method for superresolution, live-cell imaging “is a window into the future of scientific exploration. eSRRF can potentially revolutionize several fields, from biology to medicine, paving the way for discoveries that were once beyond our visual reach.”

The research was published in Nature Methods (www.doi.org/10.1038/s41592-023-02057-w).