Centre for Integrative Biology (CBI), Department of Integrated Structural Biology, IGBMC, CNRS, Inserm, Université de Strasbourg, 1 rue Laurent Fries, 67404, Illkirch, France.
Institute of Genetics and of Molecular and Cellular Biology (IGBMC), 1 rue Laurent Fries, Illkirch, France.
Commun Biol. 2022 Oct 17;5(1):1100. doi: 10.1038/s42003-022-04040-1.
Single molecule localization microscopy (SMLM) with a dichroic image splitter can provide invaluable multi-color information regarding colocalization of individual molecules, but it often suffers from technical limitations. Classical demixing algorithms tend to give suboptimal results in terms of localization precision and correction of chromatic errors. Here we present an image splitter based multi-color SMLM method (splitSMLM) that offers much improved localization precision and drift correction, compensation of chromatic distortions, and optimized performance of fluorophores in a specific buffer to equalize their reactivation rates for simultaneous imaging. A novel spectral demixing algorithm, SplitViSu, fully preserves localization precision with essentially no data loss and corrects chromatic errors at the nanometer scale. Multi-color performance is further improved by using optimized fluorophore and filter combinations. Applied to three-color imaging of the nuclear pore complex (NPC), this method provides a refined positioning of the individual NPC proteins and reveals that Pom121 clusters act as NPC deposition loci, hence illustrating strength and general applicability of the method.
单分子定位显微镜(SMLM)与二向色分光镜图像分离器相结合,可以提供关于单个分子共定位的非常有价值的多色信息,但它通常受到技术限制。经典的去混合算法在定位精度和颜色误差校正方面往往不能达到最优效果。在这里,我们提出了一种基于图像分离器的多色 SMLM 方法(splitSMLM),它提供了更高的定位精度和漂移校正、颜色失真补偿以及优化了特定缓冲液中荧光染料的性能,以平衡它们的重新激活率,从而实现同时成像。一种新颖的光谱去混合算法 SplitViSu 可以在基本不损失数据的情况下完全保留定位精度,并在纳米尺度上校正颜色误差。通过使用优化的荧光染料和滤光片组合,多色性能得到进一步提高。该方法应用于核孔复合体(NPC)的三色成像,提供了对单个 NPC 蛋白的精细定位,并揭示了 Pom121 簇作为 NPC 沉积部位的作用,从而说明了该方法的优势和广泛适用性。