Super Resolution Radial Fluctuations (SRRF) - ImageJ Plugin

About SRRF

SRRF (pronounced as surf) is part of the NanoJ project - a collection of analytical methods dedicated to super-resolution and advanced imaging compatible with ImageJ. Both SRRF and NanoJ are developed by the Henriques Laboratory in the MRC Laboratory for Molecular Cell Biology at UCL.

SRRF is as a novel open-source and high-performance analytical approach for Live-cell Super-Resolution Microscopy, provided as a fast GPU-enabled ImageJ plugin. SRRF is capable of extracting high-fidelity super-resolution information in modern microscopes (TIRF, widefield and confocals) using conventional fluorophores such as GFP. In addition, SRRF is capable of live-cell imaging over timescales ranging from minutes to hours, using sample illumination orders of magnitude lower than methods such as PALM, STORM or STED.

Example SRRF analysis of live-cell spinning disk data

Microtubules labelled with tubulin-GFP and imaging performed on a spinning disk confocal microscope. Z sections were taken at 300nm intervals, with each SRRF image produced from SRRF analysis of 100 raw frames acquired at each interval; for comparison the average of these 100 spinning disk frames is displayed on the left. The right hand panel shows the cumulative projections of the SRRF and spinning disk images colour-coded by z position.

Features

  • Super-resolution with standard microscopes: SRRF is capable of super-resolving cellular structures imaged with widefield, TIRF or confocal modern microscopes without the need for specialized optics. Additionally, SRRF has sample illumination intensity requirements orders of magnitude lower than other super-resolution methods such as PALM, STORM or STED.
  • Super-resolution with conventional fluorophores such as GFP: we have shown that SRRF is able to produce super-resolution images from samples labelled with a wide range of conventional fluorophores, such as GFP.
  • Live-cell super-resolution with minimal phototoxicity: as SRRF is able to extract high-fidelity super-resolution information from low signal-to-noise ratio samples, it requires lower sample illumination than most other super-resolution methods. For this reason, SRRF enables live-cell imaging over timescales ranging from minutes to hours. Imaged cells generally remain capable of undergoing mitosis, mitochondrial motility and cytoskeletal reorganisation as expected in normal healthy conditions.
  • Speed: SRRF is very fast!! It has been fully optimized to take advantage of GPU high-performance computing in modern graphics cards. However, its analytical framework has been developed to work in almost any computer, independently of its architecture. SRRF, generally will process images and generate super-resolution data in real-time.
  • Drift correction: drift is a major challenge in super-resolution microscopy and in most cases the limiting factor for resolution. Since the acquisition can take from several minutes to hours, drifts of even a few tens of nanometers can drastically deteriorate resolution, or worse, create anomalies in reconstructed images (e.g. artifactual doubling of filamentary structures). SRRF provides an easy drift correction method based on dynamics sample tracking (cross-correlation).
  • Availability, ease of use and open-source: both the software and its source code are freely available as a Fiji or ImageJ plugin. This allows maximal dissemination of the software in the biological research community, optimal usability, and will offer users the ability to modify and improve the software at will.

Start using SRRF

To get set up and start using SRRF please find tutorials on how to install and run NanoJ-SRRF here.

Also: Check out the SRRF paper in Nature Communications

Abstract:

Despite significant progress, high-speed live-cell super-resolution studies remain limited to specialized optical setups, generally requiring intense phototoxic illumination. Here, we describe a new analytical approach, super-resolution radial fluctuations (SRRF), provided as a fast graphics processing unit-enabled ImageJ plugin. In the most challenging data sets for super-resolution, such as those obtained in low-illumination live-cell imaging with GFP, we show that SRRF is generally capable of achieving resolutions better than 150 nm. Meanwhile, for data sets similar to those obtained in PALM or STORM imaging, SRRF achieves resolutions approaching those of standard single-molecule localization analysis. The broad applicability of SRRF and its performance at low signal-to-noise ratios allows super-resolution using modern widefield, confocal or TIRF microscopes with illumination orders of magnitude lower than methods such as PALM, STORM or STED. We demonstrate this by super-resolution live-cell imaging over timescales ranging from minutes to hours.