Department of Physiology, Wayne State University School of Medicine, 540 E. Canfield, 5245, 5215 Scott Hall, Detroit, MI, 48201, USA.
NanoBioScience Institute, Wayne State University, Detroit, MI, 48201, USA.
Histochem Cell Biol. 2020 Jun;153(6):469-480. doi: 10.1007/s00418-020-01869-7. Epub 2020 Mar 19.
Expensive and time-consuming approaches of immunoelectron microscopy of biopsy tissues continues to serve as the gold-standard for diagnostic pathology. The recent development of the new approach of expansion microscopy (ExM) capable of fourfold lateral expansion of biological specimens for their morphological examination at approximately 70 nm lateral resolution using ordinary diffraction limited optical microscopy, is a major advancement in cellular imaging. Here we report (1) an optimized fixation protocol for retention of cellular morphology while obtaining optimal expansion, (2) an ExM procedure for up to eightfold lateral and over 500-fold volumetric expansion, (3) demonstrate that ExM is anisotropic or differential between tissues, cellular organelles and domains within organelles themselves, and (4) apply image analysis and machine learning (ML) approaches to precisely assess differentially expanded cellular structures. We refer to this enhanced ExM approach combined with ML as differential expansion microscopy (DiExM), applicable to profiling biological specimens at the nanometer scale. DiExM holds great promise for the precise, rapid and inexpensive diagnosis of disease from pathological specimen slides.
昂贵且耗时的活检组织免疫电子显微镜方法仍然是诊断病理学的金标准。最近，一种新的扩展显微镜（ExM）方法的发展，能够将生物样本进行四倍的横向扩展，以便在普通的具有衍射极限的光学显微镜下以约 70nm 的横向分辨率对其进行形态学检查，这是细胞成像领域的重大进展。在这里，我们报告了（1）一种优化的固定方案，用于在获得最佳扩展的同时保留细胞形态，（2）一种最多可进行八倍横向和超过 500 倍体积扩展的 ExM 程序，（3）证明 ExM 在组织、细胞细胞器及其自身细胞器内的域之间是各向异性或有差异的，（4）应用图像分析和机器学习（ML）方法来精确评估差异扩展的细胞结构。我们将这种增强的 ExM 方法与 ML 结合称为差异扩展显微镜（DiExM），可用于在纳米尺度上对生物样本进行分析。DiExM 有望实现从病理标本玻片上进行精确、快速和廉价的疾病诊断。
