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文库筛选项目中的深度测序:它能带来哪些见解?

Deep sequencing in library selection projects: what insight does it bring?

作者信息

Glanville J, D'Angelo S, Khan T A, Reddy S T, Naranjo L, Ferrara F, Bradbury A R M

机构信息

Program in Computational and Systems Immunology, Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, USA.

University of New Mexico Comprehensive Cancer Center, and Division of Molecular Medicine, University of New Mexico School of Medicine, Albuquerque, NM, USA.

出版信息

Curr Opin Struct Biol. 2015 Aug;33:146-60. doi: 10.1016/j.sbi.2015.09.001.

Abstract

High throughput sequencing is poised to change all aspects of the way antibodies and other binders are discovered and engineered. Millions of available sequence reads provide an unprecedented sampling depth able to guide the design and construction of effective, high quality naïve libraries containing tens of billions of unique molecules. Furthermore, during selections, high throughput sequencing enables quantitative tracing of enriched clones and position-specific guidance to amino acid variation under positive selection during antibody engineering. Successful application of the technologies relies on specific PCR reagent design, correct sequencing platform selection, and effective use of computational tools and statistical measures to remove error, identify antibodies, estimate diversity, and extract signatures of selection from the clone down to individual structural positions. Here we review these considerations and discuss some of the remaining challenges to the widespread adoption of the technology.

摘要

高通量测序有望改变抗体及其他结合分子的发现与工程改造方式的方方面面。数以百万计的可用序列读数提供了前所未有的采样深度,能够指导设计和构建包含数百亿个独特分子的高效、高质量天然文库。此外,在筛选过程中,高通量测序能够对富集克隆进行定量追踪,并在抗体工程的阳性选择过程中对氨基酸变异进行位置特异性指导。这些技术的成功应用依赖于特定的PCR试剂设计、正确的测序平台选择,以及有效使用计算工具和统计方法来去除错误、鉴定抗体、估计多样性,并从克隆直至单个结构位置提取选择特征。在此,我们综述这些注意事项,并讨论该技术广泛应用中尚存的一些挑战。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a815/4648538/507be7c528c7/nihms726106f1.jpg

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