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SWATH 无标记蛋白质组学在囊性纤维化研究中的应用。

SWATH label-free proteomics for cystic fibrosis research.

机构信息

D3Pharmachemistry, Fondazione Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy; Dipartimento di Chimica, Università degli Studi di Genova, Via Dodecaneso 31, 16146 Genova, Italy.

U.O.C. Genetica Medica, IRCCS Istituto Giannina Gaslini, Via Gerolamo Gaslini 5, 16147 Genova, Italy.

出版信息

J Cyst Fibros. 2019 Jul;18(4):501-506. doi: 10.1016/j.jcf.2018.10.004. Epub 2018 Oct 19.

Abstract

BACKGROUND

Label-free proteomics is a powerful tool for biological investigation. The SWATH protocol, relying on the Pan Human ion library, currently represents the state-of-the-art methodology for this kind of analysis. We recently discovered that this tool is not perfectly suitable for proteomics research in the CF field, as it lacks assays for several proteins crucial for the CF biology, including CFTR.

METHODS

We extensively investigated the proteome of a very popular model for in vitro research on CF, CFBE41o-, and we used the corresponding data to improve the power of SWATH proteomics for CF investigation. We then used this improved tool to explore in depth the proteome of primary bronchial epithelial (BE) cells deriving from four CF individuals compared with that of four corresponding non-CF controls. By means of advanced bioinformatics tools, we outlined the presence of a number of protein networks being significantly altered by CF.

RESULTS

Our analysis on patients' BE cells identified 154 proteins dysregulated by the CF pathology (94 upregulated and 60 downregulated). Some known CFTR interactors are present among them, but our analysis also revealed the alteration of other proteins not previously known to be related with CF.

CONCLUSIONS

The present work outlines the power of SWATH label free proteomics applied to CF research.

摘要

背景

无标记蛋白质组学是生物研究的有力工具。SWATH 协议依赖于全人类离子文库,目前代表了这种分析的最新方法。我们最近发现,该工具并不完全适用于 CF 领域的蛋白质组学研究,因为它缺乏对包括 CFTR 在内的几种对 CF 生物学至关重要的蛋白质的检测。

方法

我们广泛研究了 CF 体外研究中非常流行的模型 CFBE41o-的蛋白质组,并使用相应的数据来提高 SWATH 蛋白质组学在 CF 研究中的能力。然后,我们使用这个改进的工具深入研究了来自四个 CF 个体的原代支气管上皮 (BE) 细胞的蛋白质组与四个相应的非 CF 对照的蛋白质组。通过先进的生物信息学工具,我们概述了存在一些蛋白质网络被 CF 显著改变。

结果

我们对患者 BE 细胞的分析确定了 154 种由 CF 病理失调的蛋白质(94 种上调和 60 种下调)。其中存在一些已知的 CFTR 相互作用蛋白,但我们的分析还揭示了其他以前与 CF 无关的蛋白质的改变。

结论

本研究概述了 SWATH 无标记蛋白质组学应用于 CF 研究的强大功能。

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