核孔复合物单分子定位超分辨图像的筛选和重构  

Screening and Reconstruction for Single-Molecular Localization Superresolution Images of Nuclear Pore Complexes

作　　者：侯梦迪 胡芬 杨建宇 董浩 潘雷霆 Hou Mengdi;Hu Fen;Yang Jianyu;Dong Hao;Pan Leiting(Key Laboratory of Weak-Light Nonlinear Photonics,Ministry of Education,School of Physics and TEDA Institute of Applied Physics,Nankai University,Tianjin 300071,China;Frontiers Science Center for Cell Responses,State Key Laboratory of Medicinal Chemical Biology,College of Life Sciences,Nankai University,Tianjin 300071,China;Shenzhen Research Institute of Nankai University,Shenzhen 518083,Guangdong,China;Collaborative Innovation Center of Extreme Optics,Shanxi University,Taiyuan 030006,Shanxi,China)

机构地区：[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]药物化学生物学全国重点实验室,南开大学生命科学学院,细胞应答交叉科学中心,天津300071 [3]南开大学深圳研究院,广东深圳518083 [4]山西大学极端光学协同创新中心,山西太原030006

出　　处：《中国激光》2024年第3期67-75,共9页Chinese Journal of Lasers

基　　金：国家重点研发计划(2022YFC3400600);国家自然科学基金(32227802,12174208);广东省基础与应用基础研究重大项目(2020B0301030009);南开大学中央高校基本科研业务费专项资金(2122021337,2122021405);高等学校学科创新引智计划(B23045)。

摘　　要：核孔复合物(NPC)是细胞核膜上由多种蛋白组装而成的复杂结构,在细胞核质交换和信息传递中起着关键作用。单分子定位超分辨成像(SMLM)以其特异性和高成像分辨率成为研究NPC超微结构的主要方法之一。然而,由于抗体标记不完全等因素导致的数据丢失,给后续分析带来了困难。笔者使用SMLM提供的定位信息,结合基于密度的空间聚类算法(DBSCAN)和层次聚类算法进行数据的提取和分类,建立了NPC筛选和定位的分析流程,并采用该处理流程得到了缺失较少且形貌比较均匀的核孔。进一步,基于最小二乘法原理对筛选得到的大量NPC进行质心对齐的重构处理,成功复现出了其经典的八重对称结构,并揭示了核孔蛋白Nup133与Nup98的精确相对位置关系。本研究通过建立核孔筛选和重构的标准流程,填补了SMLM数据的缺失。采用该流程对多种核孔蛋白进行分析,揭示它们的结构特性。所建流程为理解核孔的复杂结构提供了一种高通量的定量分析方法。Objective The nuclear pore complex(NPC)is an intricate structure comprising multiple distinct nuclear pore proteins known as nucleoporins(Nups).It plays a crucial role in the transformation of matter and information between the nucleus and cytoplasm.With a total molecular weight of 110‒125 MDa,the NPC is hailed as the holy grail of structural biology.Scientists have used such techniques as electron microscopy,atomic force microscopy,and cryoelectron microscopy to collectively reveal the composition,assembly,and ultrastructure of the NPC,providing a solid structural foundation for further exploration of its functions.The diameter of the NPC is approximately 130 nm.Therefore,single-molecule localization microscopy(SMLM)with an imaging resolution of 20 nm is an ideal tool for studying the ultrastructure of NPC.However,during long-term imaging,data loss may occur because of sparse blinking,and the dynamic activities of life also lead to heterogeneity in imaging results,posing challenges for data analysis.To address these issues,corresponding image reconstruction methods must be developed.Clustering algorithms are powerful tools for quantitative extraction,classification,and analysis of SMLM data.The unique clustered distribution structure of the NPC makes clustering methods highly suitable for structural analysis of the NPC.Therefore,to compensate for the limitations of SMLM data and obtain more detailed structural information about the NPC,a processing procedure for SMLM images of the NPC was developed in this study based on clustering algorithms.It involves screening out NPC structures with a more uniform morphology,followed by subjecting these structures to high-throughput statistical analysis and reconstruction.Methods After PFA fixation,permeabilization with a blocking buffer,and labeling with antibodies(Nup133 and Nup98),U2OS cells were imaged by a self-built SMLM imaging system.A total of 50000 frames were captured after appropriate fields of view were selected.Through localization and drift correction proce

关 键 词：生物光学 超分辨成像 单分子定位 核孔复合物 聚类算法 重构 

分 类 号：O436[机械工程—光学工程]