Implementation and Optimization of a Random Illumination Microscope: towards Robustness for Microscopy Core Facility

Abstract

Super-resolution microscopy has become an indispensable tool for investigating molecular architectures in their native cellular environment. However, most super-resolution techniques face limitations that prevent rapid, deep imaging of live samples. Random Illumination Microscopy (RIM), based on natural laser speckle illumination, is a method of choice to overcome these challenges. RIM combines laser speckle illumination at the optical resolution with an algorithm that exploits the statistical invariance of speckle patterns.

In this approach, a stack of hundreds of random speckle images is acquired using a random diffusive element and then processed to reconstruct the super-resolved optical section. The invariant statistical properties of speckle patterns, which persist even as they diffuse through biological samples, enable deep-tissue imaging. Additionally, the wide-field configuration of both illumination and detection ensures high acquisition speeds and minimal sample photodamage.

Here, we present the implementation of our RIM prototype within a microscopy core facility. We describe the system setup, characterization, and optimization, identifying the key elements required for its reliable operation. As a proof of concept, we also provide biological examples demonstrating the prototype's performance in resolving subcellular structures.