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OmniSegger:一种用于细菌细胞的延时图像分析流程。

OmniSegger: A time-lapse image analysis pipeline for bacterial cells.

作者信息

Lo Teresa W, Cutler Kevin J, James Choi H, Wiggins Paul A

机构信息

Department of Physics, University of Washington, Seattle, Washington, United States of America.

Department of Bioengineering, University of Washington, Seattle, Washington, United States of America.

出版信息

PLoS Comput Biol. 2025 May 28;21(5):e1013088. doi: 10.1371/journal.pcbi.1013088. eCollection 2025 May.

Abstract

Time-lapse microscopy is a powerful tool to study the biology of bacterial cells. The development of pipelines that facilitate the automated analysis of these datasets is a long-standing goal of the field. In this paper, we describe the OmniSegger pipeline developed as an open-source, modular, and holistic suite of algorithms whose input is raw microscopy images and whose output is a wide range of quantitative cellular analyses, including dynamical cell cytometry data and cellular visualizations. The updated version described in this paper introduces two principal refinements: (i) robustness to cell morphologies and (ii) support for a range of common imaging modalities. To demonstrate robustness to cell morphology, we present an analysis of the proliferation dynamics of Escherchia coli treated with a drug that induces filamentation. To demonstrate extended support for new image modalities, we analyze cells imaged by five distinct modalities: phase-contrast, two brightfield modalities, and cytoplasmic and membrane fluorescence. Together, this pipeline should greatly increase the scope of tractable analyses for bacterial microscopists.

摘要

延时显微镜是研究细菌细胞生物学的强大工具。开发便于对这些数据集进行自动分析的流程是该领域长期以来的目标。在本文中,我们描述了OmniSegger流程,它是作为一套开源、模块化且全面的算法套件开发的,其输入是原始显微镜图像,输出是广泛的细胞定量分析结果,包括动态细胞流式数据和细胞可视化。本文描述的更新版本引入了两项主要改进:(i)对细胞形态的鲁棒性,以及(ii)对一系列常见成像模式的支持。为了证明对细胞形态的鲁棒性,我们对用诱导丝状化的药物处理过的大肠杆菌的增殖动力学进行了分析。为了证明对新图像模式的扩展支持,我们分析了通过五种不同模式成像的细胞:相差、两种明场模式以及细胞质和膜荧光。总之,该流程应能极大地扩大细菌显微镜学家可处理分析的范围。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ae8/12140430/7cc514bc2b85/pcbi.1013088.g002.jpg

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