Jeong Uidon, Go Ga-Eun, Jeong Dokyung, Lee Dongmin, Kim Min Jeong, Kang Minjae, Kim Namyoon, Jung Jaehwang, Kim Wookrae, Lee Myungjun, Kim Doory
Department of Chemistry, Hanyang University, Seoul 04763, Republic of Korea.
MI Equipment R&D Team, Mechatronics Research, Samsung Electronics Co., Ltd., Hwaseong 18848, Republic of Korea.
Nanophotonics. 2024 Jan 4;13(2):195-207. doi: 10.1515/nanoph-2023-0709. eCollection 2024 Jan.
The recent advances in super-resolution fluorescence microscopy, including single-molecule localization microscopy (SMLM), has enabled the study of previously inaccessible details, such as the organization of proteins within cellular compartments and even nanostructures in nonbiological nanomaterials, such as the polymers and semiconductors. With such developments, the need for the development of various computational nanostructure analysis methods for SMLM images is also increasing; however, this has been limited to protein cluster analysis. In this study, we developed an edge structure analysis method for pointillistic SMLM images based on the line edge roughness and power spectral density analyses. By investigating the effect of point properties in SMLM images, such as the size, density, and localization precision on the roughness measurement, we successfully demonstrated this analysis method for experimental SMLM images of actual samples, including the semiconductor line patterns, cytoskeletal elements, and cell membranes. This systematic investigation of the effect of each localization rendering parameter on edge roughness measurement provides a range for the optimal rendering parameters that preserve the relevant nanoscale structure of interest. These new methods are expected to expand our understanding of the targets by providing valuable insights into edge nanoscale structures that have not been previously obtained quantitatively.
超分辨率荧光显微镜技术的最新进展，包括单分子定位显微镜（SMLM），使得人们能够研究以前无法获取的细节，例如细胞区室内蛋白质的组织，甚至非生物纳米材料（如聚合物和半导体）中的纳米结构。随着这些进展，开发用于SMLM图像的各种计算纳米结构分析方法的需求也在增加；然而，这一直局限于蛋白质簇分析。在本研究中，我们基于线边缘粗糙度和功率谱密度分析，开发了一种用于点彩SMLM图像的边缘结构分析方法。通过研究SMLM图像中点特性（如大小、密度和定位精度）对粗糙度测量的影响，我们成功地将这种分析方法应用于实际样品的实验SMLM图像，包括半导体线图案、细胞骨架元件和细胞膜。对每个定位渲染参数对边缘粗糙度测量影响的系统研究，为保留相关感兴趣纳米级结构的最佳渲染参数提供了一个范围。这些新方法有望通过提供对以前未进行定量获取的边缘纳米级结构的宝贵见解，来扩展我们对目标的理解。
