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定量无标记单细胞在 3D 仿生基质中的追踪。

Quantitative label-free single cell tracking in 3D biomimetic matrices.

机构信息

Institute of Biochemistry, Faculty of Biosciences, Pharmacy and Psychology, Universität Leipzig, Leipzig, 04103, Germany.

Institute of Computer Science, Faculty of Mathematics and Computer Science, Universität Leipzig, Leipzig, 04103, Germany.

出版信息

Sci Rep. 2017 Oct 26;7(1):14135. doi: 10.1038/s41598-017-14458-x.

Abstract

Live cell imaging enables an observation of cell behavior over a period of time and is a growing field in modern cell biology. Quantitative analysis of the spatio-temporal dynamics of heterogeneous cell populations in three-dimensional (3D) microenvironments contributes a better understanding of cell-cell and cell-matrix interactions for many biomedical questions of physiological and pathological processes. However, current live cell imaging and analysis techniques are frequently limited by non-physiological 2D settings. Furthermore, they often rely on cell labelling by fluorescent dyes or expression of fluorescent proteins to enhance contrast of cells, which frequently affects cell viability and behavior of cells. In this work, we present a quantitative, label-free 3D single cell tracking technique using standard bright-field microscopy and affordable computational resources for data analysis. We demonstrate the efficacy of the automated method by studying migratory behavior of a large number of primary human macrophages over long time periods of several days in a biomimetic 3D microenvironment. The new technology provides a highly affordable platform for long-term studies of single cell behavior in 3D settings with minimal cell manipulation and can be implemented for various studies regarding cell-matrix interactions, cell-cell interactions as well as drug screening platform for primary and heterogeneous cell populations.

摘要

活细胞成像能够观察细胞在一段时间内的行为,是现代细胞生物学中一个不断发展的领域。在三维(3D)微环境中对异质细胞群体的时空动态进行定量分析,有助于更好地理解细胞-细胞和细胞-基质相互作用,从而解决许多生理和病理过程中的生物医学问题。然而,目前的活细胞成像和分析技术经常受到非生理 2D 环境的限制。此外,它们通常依赖于荧光染料对细胞的标记或荧光蛋白的表达来增强细胞的对比度,这经常会影响细胞的活力和行为。在这项工作中,我们使用标准的明场显微镜和负担得起的计算资源,提出了一种定量的、无标记的 3D 单细胞跟踪技术,用于数据分析。我们通过在仿生 3D 微环境中对大量原代人巨噬细胞进行长时间(数天)的迁移行为研究,证明了该自动化方法的有效性。这项新技术为在 3D 环境中进行单细胞行为的长期研究提供了一个极具性价比的平台,对细胞的操作最小化,并可用于各种关于细胞-基质相互作用、细胞-细胞相互作用以及原代和异质细胞群体的药物筛选平台的研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1463/5658366/c0c8ecc4323f/41598_2017_14458_Fig1_HTML.jpg

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