Spatial Proteomics towards cellular Resolution.

IF 3.8 3区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Expert Review of Proteomics Pub Date : 2024-12-25 DOI:10.1080/14789450.2024.2445809

Yumi Kwon, James M Fulcher, Ljiljana Paša-Tolić, Wei-Jun Qian

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引用次数: 0

Abstract

Introduction: Spatial biology is an emerging interdisciplinary field facilitating biological discoveries through the use of spatial omics technologies. Recent advancements in spatial transcriptomics, spatial genomics (e.g. genetic mutations and epigenetic marks), multiplexed immunofluorescence, and spatial metabolomics/lipidomics have enabled high-resolution spatial profiling of gene expression, genetic variation, protein expression, and metabolites/lipids profiles in tissue. These developments contribute to a deeper understanding of the spatial organization within tissue microenvironments at the molecular level.

Areas covered: This report provides an overview of the untargeted, bottom-up mass spectrometry (MS)-based spatial proteomics workflow. It highlights recent progress in tissue dissection, sample processing, bioinformatics, and liquid chromatography (LC)-MS technologies that are advancing spatial proteomics toward cellular resolution.

Expert opinion: The field of untargeted MS-based spatial proteomics is rapidly evolving and holds great promise. To fully realize the potential of spatial proteomics, it is critical to advance data analysis and develop automated and intelligent tissue dissection at the cellular or subcellular level, along with high-throughput LC-MS analyses of thousands of samples. Achieving these goals will necessitate significant advancements in tissue dissection technologies, LC-MS instrumentation, and computational tools.

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面向细胞分辨率的空间蛋白质组学。

空间生物学是一个新兴的跨学科领域，通过使用空间组学技术促进生物学发现。空间转录组学、空间基因组学（如基因突变和表观遗传标记）、多重免疫荧光和空间代谢组学/脂质组学的最新进展使高分辨率的基因表达、遗传变异、蛋白质表达和组织中代谢物/脂质谱的空间分析成为可能。这些发展有助于在分子水平上对组织微环境中的空间组织有更深的理解。涵盖领域：本报告概述了非靶向，自下而上的质谱（MS）为基础的空间蛋白质组学工作流程。它强调了组织解剖，样品处理，生物信息学和液相色谱(LC)-质谱技术的最新进展，这些技术正在推动空间蛋白质组学向细胞分辨率发展。专家意见：基于非靶向ms的空间蛋白质组学领域正在迅速发展，前景广阔。为了充分发挥空间蛋白质组学的潜力，在细胞或亚细胞水平上推进数据分析和开发自动化和智能组织解剖，以及对数千个样品进行高通量LC-MS分析至关重要。实现这些目标将需要在组织解剖技术、LC-MS仪器和计算工具方面取得重大进展。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Expert Review of Proteomics 生物-生化研究方法

CiteScore

7.60

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： Expert Review of Proteomics (ISSN 1478-9450) seeks to collect together technologies, methods and discoveries from the field of proteomics to advance scientific understanding of the many varied roles protein expression plays in human health and disease. The journal coverage includes, but is not limited to, overviews of specific technological advances in the development of protein arrays, interaction maps, data archives and biological assays, performance of new technologies and prospects for future drug discovery. The journal adopts the unique Expert Review article format, offering a complete overview of current thinking in a key technology area, research or clinical practice, augmented by the following sections: Expert Opinion - a personal view on the most effective or promising strategies and a clear perspective of future prospects within a realistic timescale Article highlights - an executive summary cutting to the author''s most critical points.