现代仪器与医疗

单分子定位超分辨成像全链条解决方案

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胡芬 ¹^,² , 王波 ¹ , 解钊 ¹ , 黎继强 ¹ , 陈明鑫 ¹ , 刘帅 ¹ , 杨建宇 ¹ , 李任植 ³ , 潘雷霆 ¹^,²^,⁴^,^*

现代仪器与医疗 | 技术进展 2025,31(4): 45-57

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现代仪器与医疗 |技术进展 2025 , 31 (4) : 45 -57

单分子定位超分辨成像全链条解决方案

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胡芬¹^,², 王波¹, 解钊¹, 黎继强¹, 陈明鑫¹, 刘帅¹, 杨建宇¹, 李任植³, 潘雷霆¹^,²^,⁴^,^*

作者信息

^1.弱光非线性光子学教育部重点实验室，南开大学物理科学学院，泰达应用物理研究院，天津　300071

^2.纳微成像（天津）生物科技有限公司，天津　300192

^3.塔什干中亚大学医学院，塔什干　111221，乌兹别克斯坦

^4.极端光学协同创新中心，山西大学，太原　030006

通讯作者:

潘雷霆，男，博士研究生，教授，研究方向：生物医学光学

作者简介:

胡芬，女，博士研究生，副教授，研究方向：生物医学光学

Full-chain solution for single-molecule localization super-resolution microscopy

Fen Hu¹^,², Bo Wang¹, Zhao Xie¹, Jiqiang Li¹, Mingxin Chen¹, Shuai Liu¹, Jianyu Yang¹, Imshik Lee³, Leiting Pan¹^,²^,⁴^,^*

Affiliations

^1.Key Laboratory of Weak-Light Nonlinear Photonics, Ministry of Education, School of Physics, TEDA Institute of Applied Physics, Nankai University, Tianjin 300071, China

^2.Tianjin Nano-Microimaging Biotechnology Co., Ltd., Tianjin 300192, China

^3.Medical School, Central Asian University, Tashkent 111221, Uzbekistan

^4.Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan 030006, China

出版时间: 2025-08-10 doi: 10.11876/mimt202504005

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摘要

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单分子定位超分辨成像（single molecular localization microscopy，SMLM）作为一项突破光学衍射极限的技术，实现了纳米级空间分辨率，为生命科学研究提供了颠覆性的成像手段。然而，SMLM在实际应用中仍面临诸多挑战，如硬件系统高度依赖进口、制样流程繁琐、双色成像探针缺乏、数据分析挖掘不足等。这些瓶颈限制了SMLM设备的利用率，阻碍了其广泛应用和产业化发展。本文提出一套SMLM“九要素”全链条解决方案，包括硬件系统、软件控制和图像重建3个“硬实力”要素和精准制样、闪烁探针、数据分析挖掘、特色试剂耗材、特异性抗体和实际应用6个“软实力”要素。其中，“硬实力”可通过采购与集成市场化成熟组件实现快速部署，“软实力”则需依赖长期技术沉淀与领域认知积累。该方案的提出可推动SMLM从“高端仪器”向“高效工具”转化，促进超分辨成像技术的普惠化应用，为高端显微成像设备的使用提供新思路。

关键词

超分辨成像 / 单分子定位 / 全链条解决方案 / 自动化制样

Abstract

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Single-molecule localization microscopy (SMLM), as a groundbreaking technology surpassing the optical diffraction limit, achieves nanoscale spatial resolution (～20 nm) and has revolutionized biological imaging. However, its widespread application faces critical challenges including reliance on imported hardware systems, complex sample preparation protocols, lack of dual-color imaging fluorescent probes, and insufficient data analysis and mining, leading to underutilization of existing equipment. This review proposes a comprehensive full-chain solution addressing nine critical elements of SMLM, which include three “hard skills” — hardware systems, software control, and image reconstruction; and six “soft skills” — precise sample preparation, blinking probes, data analysis and mining, specialized reagents and consumables, specific antibodies, and practical applications. The “hard skills” can be rapidly deployed through the procurement and integration of mature commercial components, whereas the “soft skills” rely on long-term technological accumulation and deep domain knowledge. This solution aims to promote the transformation of SMLM from a “high-end instrument” into an “efficient tool”, facilitating the broader application of super-resolution imaging technologies and offering new perspectives for the use of advanced microscopy systems.

Key words

Super-resolution microscopy / Single-molecule localization / Full-chain solution / Automated sample preparation

引用本文

胡芬, 王波, 解钊, 黎继强, 陈明鑫, 刘帅, 杨建宇, 李任植, 潘雷霆. 单分子定位超分辨成像全链条解决方案. 现代仪器与医疗, 2025 , 31 (4) : 45 -57 . DOI: 10.11876/mimt202504005

Fen Hu, Bo Wang, Zhao Xie, Jiqiang Li, Mingxin Chen, Shuai Liu, Jianyu Yang, Imshik Lee, Leiting Pan. Full-chain solution for single-molecule localization super-resolution microscopy[J]. Modern Instruments & Medical Treatment, 2025 , 31 (4) : 45 -57 . DOI: 10.11876/mimt202504005

基金

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国家重点研发计划(2022YFC3400600)
国家自然科学基金(32227802; 12174208)
天津市自然科学基金(23JCYBJC01250)

参考文献

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2025年第31卷第4期

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文章信息

doi: 10.11876/mimt202504005

首发时间：2026-10-23
出版时间：2025-08-10

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出版历史

基金

国家重点研发计划(2022YFC3400600)

国家自然科学基金(32227802; 12174208)

天津市自然科学基金(23JCYBJC01250)

作者信息

^1.弱光非线性光子学教育部重点实验室，南开大学物理科学学院，泰达应用物理研究院，天津　300071

^2.纳微成像（天津）生物科技有限公司，天津　300192

^3.塔什干中亚大学医学院，塔什干　111221，乌兹别克斯坦

^4.极端光学协同创新中心，山西大学，太原　030006

通讯作者:

潘雷霆，男，博士研究生，教授，研究方向：生物医学光学

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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