A main determinant of the spatial resolution of live-cell super-resolution (SR) microscopes is the maximum photon flux that can be collected. To further increase the effective resolution for a given photon flux, we take advantage of a priori knowledge about the sparsity and continuity of biological structures to develop a deconvolution algorithm that increases the resolution of SR microscopes nearly twofold. Our method, sparse structured illumination microscopy (Sparse-SIM), achieves ~60-nm resolution at a frame rate of up to 564 Hz, allowing it to resolve intricate structures, including small vesicular fusion pores, ring-shaped nuclear pores formed by nucleoporins and relative movements of inner and outer mitochondrial membranes in live cells. Sparse deconvolution can also be used to increase the three-dimensional resolution of spinning-disc confocal-based SIM, even at low signal-to-noise ratios, which allows four-color, three-dimensional live-cell SR imaging at ~90-nm resolution. Overall, sparse deconvolution will be useful to increase the spatiotemporal resolution of live-cell fluorescence microscopy.

活细胞超分辨率 (SR) 显微镜的空间分辨率的一个主要决定因素是可以收集的最大光子通量。为了进一步提高给定光子通量的有效分辨率，我们利用关于生物结构稀疏性和连续性的先验知识来开发一种反卷积算法，该算法将 SR 显微镜的分辨率提高了近两倍。我们的方法，稀疏结构照明显微镜 (Sparse-SIM)，以高达 564 Hz 的帧速率实现了约 60 nm 的分辨率，使其能够解析复杂的结构，包括小泡状融合孔、由核孔蛋白形成的环形核孔以及活细胞中线粒体内外膜的相对运动。稀疏反卷积还可用于提高基于旋转圆盘共焦 SIM 的三维分辨率，即使在低信噪比的情况下，也可以实现约 90-90 的四色三维活细胞 SR 成像纳米分辨率。总体而言，稀疏反卷积将有助于提高活细胞荧光显微镜的时空分辨率。