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根据细胞密度对其进行分类。

Sorting cells by their density.

作者信息

Norouzi Nazila, Bhakta Heran C, Grover William H

机构信息

Department of Bioengineering, University of California, Riverside, Riverside, CA, United States of America.

出版信息

PLoS One. 2017 Jul 19;12(7):e0180520. doi: 10.1371/journal.pone.0180520. eCollection 2017.

Abstract

Sorting cells by their type is an important capability in biological research and medical diagnostics. However, most cell sorting techniques rely on labels or tags, which may have limited availability and specificity. Sorting different cell types by their different physical properties is an attractive alternative to labels because all cells intrinsically have these physical properties. But some physical properties, like cell size, vary significantly from cell to cell within a cell type; this makes it difficult to identify and sort cells based on their sizes alone. In this work we continuously sort different cells types by their density, a physical property with much lower cell-to-cell variation within a cell type (and therefore greater potential to discriminate different cell types) than other physical properties. We accomplish this using a 3D-printed microfluidic chip containing a horizontal flowing micron-scale density gradient. As cells flow through the chip, Earth's gravity makes each cell move vertically to the point where the cell's density matches the surrounding fluid's density. When the horizontal channel then splits, cells with different densities are routed to different outlets. As a proof of concept, we use our density sorter chip to sort polymer microbeads by their material (polyethylene and polystyrene) and blood cells by their type (white blood cells and red blood cells). The chip enriches the fraction of white blood cells in a blood sample from 0.1% (in whole blood) to nearly 98% (in the output of the chip), a 1000x enrichment. Any researcher with access to a 3D printer can easily replicate our density sorter chip and use it in their own research using the design files provided as online Supporting Information. Additionally, researchers can simulate the performance of a density sorter chip in their own applications using the Python-based simulation software that accompanies this work. The simplicity, resolution, and throughput of this technique make it suitable for isolating even rare cell types in complex biological samples, in a wide variety of different research and clinical applications.

摘要

根据细胞类型对细胞进行分选是生物学研究和医学诊断中的一项重要能力。然而,大多数细胞分选技术依赖于标记或标签,其可用性和特异性可能有限。根据不同细胞类型的不同物理特性进行分选是一种有吸引力的替代标记的方法,因为所有细胞本质上都具有这些物理特性。但是某些物理特性,如细胞大小,在同一细胞类型内的细胞之间差异很大;这使得仅根据细胞大小来识别和分选细胞变得困难。在这项工作中,我们通过密度对不同细胞类型进行连续分选,密度是一种物理特性,在同一细胞类型内细胞间的差异比其他物理特性小得多(因此具有更大的区分不同细胞类型的潜力)。我们使用一个3D打印的微流控芯片来实现这一点,该芯片包含一个水平流动的微米级密度梯度。当细胞流过芯片时,地球引力使每个细胞垂直移动到细胞密度与周围流体密度相匹配的位置。当水平通道随后分开时,不同密度的细胞被引导至不同的出口。作为概念验证,我们使用密度分选芯片根据材料(聚乙烯和聚苯乙烯)对聚合物微珠进行分选,并根据类型(白细胞和红细胞)对血细胞进行分选。该芯片将血样中白细胞的比例从0.1%(全血中)提高到近98%(芯片输出中),富集了1000倍。任何能够使用3D打印机的研究人员都可以轻松复制我们的密度分选芯片,并使用在线支持信息中提供的设计文件在自己的研究中使用它。此外,研究人员可以使用这项工作附带的基于Python的模拟软件来模拟密度分选芯片在其自身应用中的性能。这项技术的简单性、分辨率和通量使其适用于在各种不同的研究和临床应用中分离复杂生物样品中甚至罕见的细胞类型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/646a/5516969/c41d685d0440/pone.0180520.g001.jpg

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