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密度分布图:亚细胞分布分析和定量生物医学成像的新工具。

Density Distribution Maps: A Novel Tool for Subcellular Distribution Analysis and Quantitative Biomedical Imaging.

机构信息

Department of Medical and Surgical Sciences (DIMEC), Alma Mater Studiorum, University of Bologna, I-40138 Bologna, Italy.

Interdepartmental Centre Alma Mater Research Institute on Global Challenges and Climate Change (Alma Climate), University of Bologna, I-40126 Bologna, Italy.

出版信息

Sensors (Basel). 2021 Feb 2;21(3):1009. doi: 10.3390/s21031009.

Abstract

Subcellular spatial location is an essential descriptor of molecules biological function. Presently, super-resolution microscopy techniques enable quantification of subcellular objects distribution in fluorescence images, but they rely on instrumentation, tools and expertise not constituting a default for most of laboratories. We propose a method that allows resolving subcellular structures location by reinforcing each single pixel position with the information from surroundings. Although designed for entry-level laboratory equipment with common resolution powers, our method is independent from imaging device resolution, and thus can benefit also super-resolution microscopy. The approach permits to generate density distribution maps (DDMs) informative of both objects' absolute location and self-relative displacement, thus practically reducing location uncertainty and increasing the accuracy of signal mapping. This work proves the capability of the DDMs to: (a) improve the informativeness of spatial distributions; (b) empower subcellular molecules distributions analysis; (c) extend their applicability beyond mere spatial object mapping. Finally, the possibility of enhancing or even disclosing latent distributions can concretely speed-up routine, large-scale and follow-up experiments, besides representing a benefit for all spatial distribution studies, independently of the image acquisition resolution. DDMaker, a Software endowed with a user-friendly Graphical User Interface (GUI), is also provided to support users in DDMs creation.

摘要

亚细胞空间位置是分子生物学功能的一个重要描述符。目前,超分辨率显微镜技术能够定量荧光图像中亚细胞物体的分布,但它们依赖于仪器、工具和专业知识,而这些并不是大多数实验室的默认配置。我们提出了一种方法,通过用周围环境的信息来增强每个单个像素的位置,从而可以确定亚细胞结构的位置。虽然我们的方法是为具有常见分辨率的入门级实验室设备设计的,但它不依赖于成像设备的分辨率,因此也可以受益于超分辨率显微镜。该方法允许生成密度分布图(DDM),这些图提供有关物体绝对位置和自身相对位移的信息,从而实际上降低了位置不确定性并提高了信号映射的准确性。这项工作证明了 DDM 的以下能力:(a) 提高空间分布的信息量;(b) 增强对亚细胞分子分布的分析;(c) 扩展其应用范围,超越单纯的空间对象映射。最后,增强甚至揭示潜在分布的可能性可以具体加快常规、大规模和后续实验的速度,并且代表了所有空间分布研究的一个优势,而与图像采集分辨率无关。我们还提供了一个配备用户友好图形用户界面(GUI)的软件 DDMaker,以支持用户创建 DDM。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3511/7867329/2239c30aa5d6/sensors-21-01009-g0A1.jpg

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