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免疫电子显微镜:从样品制备到高分辨率成像的全面指南

Immunoelectron microscopy: a comprehensive guide from sample preparation to high-resolution imaging.

作者信息

Wu Jinsai, Su Bo, Gu Leiyan, Zhang Jie, Shi Qiuxiao, Hu Danrong

机构信息

Histology and Imaging Platform, Core Facilities of West China Hospital, Chengdu, 610041, People's Republic of China.

Department of Pathophysiology, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, 610041, People's Republic of China.

出版信息

Discov Nano. 2025 Sep 8;20(1):154. doi: 10.1186/s11671-025-04346-z.

Abstract

Immunoelectron Microscopy (IEM) is a technique that combines specific immunolabeling with high-resolution electron microscopic imaging to achieve precise spatial localization of biomolecules at the subcellular scale (< 10 nm) by using high-electron-density markers such as colloidal gold and quantum dots. As a core tool for analyzing the distribution of proteins, organelle interactions, and localization of disease pathology markers, it has irreplaceable value, especially in synapse research, pathogen-host interaction mechanism, and tumor microenvironment analysis. According to the differences in labeling sequence and sample processing, the IEM technology system can be divided into two categories: the first is pre-embedding labeling, which optimizes the labeling efficiency through the pre-exposure of antigenic epitopes and is especially suitable for the detection of low-abundance and sensitive antigens; the second is post-embedding labeling, which relies on the low-temperature resin embedding (e.g., LR White, Lowicryl) or the Tokuyasu frozen ultrathin sectioning technology, which can improve the deep-end labeling while maintaining the ultrastructural integrity of the tissue. The accessibility of deep antigens is enhanced while maintaining ultrastructural integrity. The two techniques have significant complementarities: the former has high labeling efficiency but limited cellular structure preservation, while the latter has better tissue structure preservation but needs to balance the problems of resin penetration and antigenic epitope masking. This article provides a systematic analysis of the entire IEM workflow, focusing on the synergistic strategies for fixation and dehydration, experimental method selection, and specific application cases. It also introduces a quantitative analysis framework based on systematic random sampling (SUR) and deep learning algorithms (such as Gold Digger), including FIB-SEM 3D reconstruction (with isotropic resolution reaching 5 nm) and correlative light and electron microscopy (CLEM) multimodal integration strategies for functional-structural co-localization. Through technological innovation and cross-platform integration, IEM is driving the advancement of ultrastructural pathology diagnostics and precision nanomedicine to new heights.

摘要

免疫电子显微镜技术(IEM)是一种将特异性免疫标记与高分辨率电子显微镜成像相结合的技术,通过使用胶体金和量子点等高电子密度标记物,在亚细胞尺度(<10纳米)上实现生物分子的精确定位。作为分析蛋白质分布、细胞器相互作用和疾病病理标记物定位的核心工具,它具有不可替代的价值,尤其在突触研究、病原体-宿主相互作用机制和肿瘤微环境分析中。根据标记顺序和样品处理的不同,IEM技术体系可分为两类:第一类是包埋前标记,通过抗原表位的预暴露优化标记效率,特别适用于低丰度和敏感抗原的检测;第二类是包埋后标记,依赖低温树脂包埋(如LR White、Lowicryl)或Tokuyasu冷冻超薄切片技术,可在保持组织超微结构完整性的同时提高深部标记效果。在保持超微结构完整性的同时增强深部抗原的可及性。这两种技术具有显著的互补性:前者标记效率高,但细胞结构保存有限,而后者组织结构保存较好,但需要平衡树脂渗透和抗原表位掩盖的问题。本文对整个IEM工作流程进行了系统分析,重点关注固定和脱水的协同策略、实验方法选择及具体应用案例。还介绍了一种基于系统随机抽样(SUR)和深度学习算法(如Gold Digger)的定量分析框架,包括FIB-SEM三维重建(各向同性分辨率达5纳米)和用于功能-结构共定位的相关光电子显微镜(CLEM)多模态整合策略。通过技术创新和跨平台整合,IEM正推动超微结构病理学诊断和精准纳米医学迈向新高度。

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