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Proteomics

Proteomics

A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...

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Updated: Jul 12, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

一个超低输入空间组织蛋白质组学的框架.

Anuar Makhmut¹, Di Qin¹, Sonja Fritzsche¹

¹Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Spatial Proteomics Group, Berlin, Germany.

|November 1, 2023

概括

此摘要是机器生成的。

研究人员开发了一种新的空间蛋白质组学工作流程,用于分析超低输入的组织样本. 这种方法使单细胞和小细胞群的详细蛋白质组概况成为可能,促进疾病和生物标志物发现.

关键词:

在FFPE的FFPE.深度视觉蛋白质组学组织病理学组织病理学质谱测量质谱测量质谱测量质谱测量质量测量质谱测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量蛋白质组学蛋白质组学单细胞蛋白组学单细胞蛋白组学空间蛋白质组学空间蛋白质组学

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Last Updated: Jul 12, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

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Published on: July 6, 2022

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Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples

Published on: November 13, 2021

科学领域:

蛋白质组学是指蛋白质组学.
细胞生物学细胞生物学
质谱测量质量谱测量

背景情况:

空间蛋白质组学将显微镜和质谱学集成为细胞功能研究.
现有的工作流程缺乏优化,以保持形态和最大限度地保护蛋白质组覆盖范围从有限的细胞输入.

研究的目的:

开发和验证一个强大的,可扩展的工作流程,用于超低输入档案组织的空间蛋白质组分析.
为了使表型发现和从少数或单个细胞进行全面的蛋白质组概况.

主要方法:

为激光微切割,超低输入档案材料开发一个优化的工作流程.
在单细胞和小区域分辨率上使用小鼠肝脏组织进行基准测试.
应用于人类桃体组织,用于分析微区域和细胞.

主要成果:

从单个小鼠肝细胞中量化了多达2000种蛋白质,从50个细胞区域中量化了近5000种蛋白质.
分析了146个人类桃体微区域,识别了细胞类型特定的标记物,细胞因子和转录因子.
揭示了激活的生殖中心中的蛋白质组动态,突出显示了B细胞的增殖和体质突变.

结论:

开发的工作流对于超低输入空间蛋白质组学来说是强大的和可扩展的.
这种方法可以在复杂组织中进行详细的细胞类型特定蛋白质组分析.
对早期疾病概况,药物标和生物标志物发现有重大影响.