单分子定位显微镜在全细胞成像中通量及分辨率优化

在生物学研究和医学领域中，细胞成像技术是揭示生物分子机制和细胞结构的关键手段。近二十年来，超分辨显微技术的发展打破了光学系统的衍射极限，使得研究人员能够近乎分子层面地观察核孔、染色质复合体和细胞骨架等生物结构，极大地促进了对生命基本单位的理解，推动了疾病机理研究、药物开发和诊断技术的进步。特别是，单分子定位显微技术（Single-Molecule Localization Microscopy, SMLM）凭借其高分辨率成像能力，成为生物医学领域不可或缺的工具，为生物学研究和医学应用开辟了新的高分辨率视角。然而，尽管SMLM在提高成像分辨率方面取得了重大进展，它在成像通量和大景深下的成像精度方面仍面临挑战。现有的单分子定位方法在有效成像视场（约30-40 μm）和景深（约1 μm）方面的局限性，显著制约了其在全细胞层面应用的潜力，亟需突破这一瓶颈以拓展其在全细胞成像方面的应用范围。

因此，本文在提升全细胞成像的通量和成像分辨率上开展了一系列研究，具体包括搭建一套自适应三维SMLM系统以实现大视场照明，精确建模并优化点扩散函数（Point Spread Function, PSF），校正视场相关像差并结合对空间位置信息敏感的深度学习网络FD-DeepLoc和可变形镜（Deformable Mirror, DM）优化的大景深PSF，实现在高通量下全细胞超分辨成像。为进一步提升全细胞成像分辨率，我们采取了远程聚焦技术，通过DM优化的PSF快速扫描轴向重聚焦的光学切面，并精确校正DM调制离焦项引入的残余像差及样品诱导的像差，保证了在大景深下保持高分辨率成像能力。

我们对比了FD-DeepLoc与当前先进的网络分析方法DECODE和基于三次样条拟合的软件SMAP，以评估它们在处理高通量数据方面的表现。FD-DeepLoc在模拟数据上的定位精度和实际生物样本（如核孔复合物和线粒体）的分辨率提升方面均表现出明显的优势。对比基于传统散光模式下三维超分辨成像，FD-DeepLoc实现了成像通量100倍的提升，覆盖了约180×180×5 μm³的全画幅视场。并展示了在视场中广泛分布的神经元细胞血影蛋白高通量成像，以及对高通量数据采集的上百个细胞线粒体进行了超分辨重建和线粒体形态分析。

进一步的，采用DM优化在2 μm轴向范围内具有均匀定位精度的PSF进行远程聚焦成像，并精确校正由重聚焦和样本引入的像差。我们实现了核孔复合物、微管和线粒体等细胞结构沿轴向的均匀数据采集，并通过FD-DeepLoc网络进行了高精度的定位分析。与直接使用DM优化的6 μm大景深PSF进行全细胞成像（其分辨率约为50 nm）相比，远程聚焦技术显著提升了全细胞成像的分辨率至大约35 nm。为细胞内部结构的精细成像提供了更高的分辨率。

综上所述，本文设计并搭建了一套针对高通量超分辨成像的SMLM系统，实现精确PSF建模及优化方法，并对视场相关的像差进行精确校正。我们提出了对空间位置信息敏感的深度学习网络FD-DeepLoc，实现大视场下高通量的数据分析。此外，通过优化远程聚焦技术，我们能够在进行全细胞大景深成像的同时保持高分辨率。本文研究的进展将推动自适应光学技术在SMLM中的广泛应用，特别是在需要大景深与高分辨率成像的生物学应用场景。

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