Dispersion Indices for Universal Quantification of Fluorescently-Labelled Subcellular Structure Spatial Distributions

Andrew Martin,Sue Zhang,Amanda Williamson, Brett Tingley, Mira Pickus,David Zurakowski,Hadi T Nia,Orian Shirihai,Xue Han,Mark W Grinstaff

bioRxiv the preprint server for biology（2024）

Department of Biomedical Engineering | Department of Chemistry | Boston Children's Hospital | UCLA

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Abstract

Image analysis of subcellular structures and biological processes relies on specific, context-dependent pipelines, which are labor-intensive, constrained by the intricacies of the specific biological system, and inaccessible to broader applications. Here we introduce the application of dispersion indices, a statistical tool traditionally employed by economists, to analyze the spatial distribution and heterogeneity of subcellular structures. This computationally efficient high-throughput approach, termed GRID (Generalized Readout of Image Dispersion), is highly generalizable, compatible with open-source image analysis software, and adaptable to diverse biological scenarios. GRID readily quantifies diverse structures and processes to include autophagic puncta, mitochondrial clustering, and microtubule dynamics. Further, GRID is versatile, applicable to both 2D cell cultures and 3D multicellular organoids, and suitable for high-throughput screening and performance metric measurements, such as half-maximal effective concentration (EC50) values. The approach enables mechanistic analysis of critical subcellular structure processes of relevance for diseases ranging from metabolic and neuronal diseases to cancer as well as a first-pass screening method for identifying biologically active agents for drug discovery.

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【要点】：本文提出了一种名为GRID的高通量图像分析方法，利用分散指数统计工具分析亚细胞结构的空间分布和异质性，实现了一般化、高效率的生物图像分析。

【方法】：作者采用分散指数作为分析工具，通过GRID方法对亚细胞结构进行量化，该方法易于与开源图像分析软件兼容，并适用于多种生物学场景。

【实验】：研究通过2D细胞培养和3D多细胞器官模型，利用GRID方法分析了自噬小点、线粒体聚集和微管动态等多种亚细胞结构，并在高通量筛选和性能指标测量中应用了该技术，如半最大效应浓度（EC50）值。实验结果证明了GRID方法在分析关键亚细胞结构过程以及作为发现生物活性药物的初步筛选方法方面的有效性。数据集名称在论文中未明确提及。

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