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构建和筛选慢病毒分泌组文库。

Construction and Screening of a Lentiviral Secretome Library.

机构信息

State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China.

State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 38 Xueyuan Road, Haidian District, Beijing 100191, China.

出版信息

Cell Chem Biol. 2017 Jun 22;24(6):767-771.e3. doi: 10.1016/j.chembiol.2017.05.017. Epub 2017 Jun 9.

Abstract

Over 2,000 human proteins are predicted to be secreted, but the biological function of the many of these proteins is still unknown. Moreover, a number of these proteins may act as new therapeutic agents or be targets for the development of therapeutic antibodies. To further explore the extracellular proteome, we have developed a secretome-enriched open reading frame (ORF) library that can be readily screened for autocrine activity in cell-based phenotypic or reporter assays. Next-generation sequencing (NGS) and database analysis predict that the library contains approximately 900 ORFs encoding known secreted proteins (accounting for 77.8% of the library), as well as genes encoding potentially unknown secreted proteins. In a proof-of-principle study, human TF-1 cells were screened for proliferative factors, and the known cytokine GMCSF was identified as a dominant hit. This library offers a relatively low-cost and straightforward approach for functional autocrine screens of secreted proteins.

摘要

据预测,有超过 2000 个人类蛋白质是分泌性的,但这些蛋白质的许多功能仍然未知。此外,其中一些蛋白质可能作为新的治疗剂或成为治疗性抗体开发的靶点。为了进一步探索细胞外蛋白质组,我们开发了一种富含分泌蛋白的开放阅读框(ORF)文库,可以方便地在基于细胞的表型或报告基因检测中筛选自分泌活性。下一代测序(NGS)和数据库分析预测,该文库包含约 900 个编码已知分泌蛋白的 ORF(占文库的 77.8%),以及编码潜在未知分泌蛋白的基因。在一项原理验证研究中,用人 TF-1 细胞筛选增殖因子,发现已知细胞因子 GMCSF 是主要的作用靶点。该文库为分泌蛋白的功能自分泌筛选提供了一种相对低成本和直接的方法。

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