Structured illumination microscopy (SIM) has become the most powerful super-resolution technique for live cell imaging, due to its inherent advantages of high speed, low phototoxicity, and compatibility with various dyes. With the advancement of SIM, researchers have proposed a range of algorithms such as Open-SIM, fairSIM, Hessian-SIM, HiFi-SIM, etc. These open source software solutions have also spurred hardware innovations, including SLM-SIM, DMD-SIM, and commercial systems such as Airy-SIM. The convergence of algorithms and hardware has fostered an open and collaborative environment in the field of SIM.
In 2008, Gustafsson introduced the concept of 3D structured illumination microscopy (3DSIM), which offers twice the axial resolution of 2D SIM, effectively eliminating common defocus artifacts encountered in 2D SIM and enabling whole-cell imaging. . However, due to its inherent complexity, the development of 3DSIM has lagged behind its 2D counterpart. Existing 3DSIM algorithms are either proprietary to commercial systems or rely on traditional Weiner-3DSIM approaches, resulting in limited usability and the presence of significant artifacts. Therefore, there is an urgent need for open source and robust 3DSIM software to meet the growing demands for advancements in this field.
Building on their previously proposed 2DSIM reconstruction platform, Open-SIM (IEEE JSTQE 2018), Xi Peng’s research group has recently introduced a new open source 3DSIM reconstruction platform, Open-3DSIM, which was published in the prestigious journal Nature Methods. Unlike Open-SIM, Open-3DSIM offers three platforms (MATLAB, Fiji and Exe) to meet various user needs. It provides high-fidelity reconstruction with minimal artifacts, even under low signal-to-noise ratio (SNR) conditions. Notably, Open-3DSIM integrates dipole orientation imaging, expanding its capabilities to include polarization imaging.
To improve the performance of Open-3DSIM, Peng’s research group designed an adaptive parameter estimation method that collaboratively estimates parameters using ± first and ± second frequency peaks. This new approach significantly improves the accuracy of 3DSIM parameter estimation, especially under challenging conditions of low SNR and low modulation. Additionally, a series of frequency domain filters were designed to remove artifacts and preserve weak information. These include notch functions to attenuate hexagonal artifacts, primary filter functions to remove sidelobes and ringing artifacts, and secondary filter functions to retain delicate details. These optimizations ensure faithful reconstructions while effectively removing background blur and various artifacts. Therefore, Open-3DSIM has overall superiority over existing reconstruction algorithms (AO-3DSIM, 4BSIM, SIMnoise, etc.) and commercial reconstruction software (e.g., GE|OMX). Notably, under extremely low SNR conditions, Open-3DSIM demonstrates similar root mean square error (MAE) and signal-to-noise ratio (SNR) to other algorithms, highlighting its outstanding performance in low SNR scenarios.
Furthermore, Peng’s research group introduced the polarization information into the post-processing stage of 3DSIM reconstruction, enabling the acquisition of dipole orientation maps for various biological samples without requiring hardware modifications. The exceptional qualities of Open-3DSIM, including its low artifact levels and high resolution, facilitated successful three-color imaging reconstructions of Cos-7 cells. Additionally, the research team analyzed the three-dimensional structure of mitochondria, capturing their dynamic separation and fusion processes. Additionally, in 5-µm-thick mouse kidney slices, they obtained valuable information about the three-dimensional dipolar orientation of microfilament organelles. Open-3DSIM encompasses six dimensions (XYZλθT), enabling super-resolution imaging in lateral and vertical directions, multicolor imaging, time-lapse observations, and dipole orientation analysis. This comprehensive capability makes Open-3DSIM a valuable tool for multidimensional imaging studies of subcellular organelles.
Open-3DSIM exhibits remarkable versatility by being compatible not only with a single microscopy platform, but also with a wide range of commercial or custom 3DSIM systems, including but not limited to GE|OMX and Nikon|N -SIM. Moreover, it integrates perfectly with various image optimization techniques based on regularization, deconvolution or machine learning. This compatibility, combined with its exceptional performance, modular design and exceptional usability, makes Open-3DSIM a robust software foundation for the next generation of 3DSIM development.
Peng envisions Open-3DSIM serving as the international standard for 3DSIM reconstruction, thereby catalyzing the advancement of super-resolution multidimensional live-cell imaging technology. Through its widespread adoption, Peng aims to foster collaborative research and promote rapid progress in this transformative field.
This work was published online in Natural methods on July 20, 2023, with Cao Ruijie, a doctoral student from the School of Future Technology, Peking University, as the first author. Peng is the corresponding author of the article. The authors thank the National Protein Science Center of Peking University and Dr. Christopher Leterrier of Aix Marseille University for providing the N-SIM data for the article. The author also thanks Professor Li Hui (Suzhou Institute of Biomedical Engineering, Chinese Academy of Sciences), Professor Marcel Mueller (KU Leuven) and Professor Lin Shao (Yale University) for their invaluable expertise, insightful analysis and their constructive comments which greatly contributed to the refinement of this article.
– This press release was provided by Peking University
