Thul Peter J, Lindskog Cecilia
Science for Life Laboratory, School of Biotechnology, KTH - Royal Institute of Technology, Stockholm, SE, 171 21, Sweden.
Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Rudbeck Laboratory, Uppsala University, Uppsala, SE, 751 85, Sweden.
Protein Sci. 2018 Jan;27(1):233-244. doi: 10.1002/pro.3307. Epub 2017 Oct 10.
The correct spatial distribution of proteins is vital for their function and often mis-localization or ectopic expression leads to diseases. For more than a decade, the Human Protein Atlas (HPA) has constituted a valuable tool for researchers studying protein localization and expression in human tissues and cells. The centerpiece of the HPA is its unique antibody collection for mapping the entire human proteome by immunohistochemistry and immunocytochemistry. By these approaches, more than 10 million images showing protein expression patterns at a single-cell level were generated and are publicly available at www.proteinatlas.org. The antibody-based approach is combined with transcriptomics data for an overview of global expression profiles. The present article comprehensively describes the HPA database functions and how users can utilize it for their own research as well as discusses the future path of spatial proteomics.
蛋白质正确的空间分布对其功能至关重要,蛋白质定位错误或异位表达往往会导致疾病。十多年来,人类蛋白质图谱(HPA)一直是研究人员研究蛋白质在人体组织和细胞中定位与表达的宝贵工具。HPA的核心是其独特的抗体库,可通过免疫组织化学和免疫细胞化学对整个人类蛋白质组进行图谱绘制。通过这些方法,生成了超过1000万张显示单细胞水平蛋白质表达模式的图像,可在www.proteinatlas.org上公开获取。基于抗体的方法与转录组学数据相结合,以全面了解整体表达谱。本文全面描述了HPA数据库的功能以及用户如何将其用于自己的研究,并讨论了空间蛋白质组学的未来发展方向。