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相关概念视频

Proteomics01:33

Proteomics

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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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Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization
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通过数据依赖获取而没有动态排除的痕迹样本蛋白质组量化.

Ci Wu1, Jiao Lei2, Fei Meng2

  • 1Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Georgetown University, Washington D.C. 20007, United States.

Analytical chemistry
|November 30, 2023
PubMed
概括
此摘要是机器生成的。

轮数据依赖采集 (turboDDA) 提高了微量蛋白质组学的灵敏度和量化准确性. 这种方法提高了的识别和可重复性,为分析有限的生物样本显示了前景.

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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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科学领域:

  • 蛋白质组学是指蛋白质组学.
  • 质谱测量质量谱测量
  • 分析化学 分析化学

背景情况:

  • 蛋白质组学中的微量样本分析受到灵敏度,准确性和可重现性的挑战.
  • 样品制备方面的技术进步尚未完全克服这些局限性.

研究的目的:

  • 评估轮数据依赖获取 (turboDDA) 对于微量样本定量蛋白质组学的适用性.
  • 在敏感性,量化准确性和可重现性方面,将turboDDA与动态排除的数据依赖采集 (DEDDA) 进行比较.

主要方法:

  • 系统地优化了turboDDA的采集参数.
  • 使用微量未标记的人类细胞消化剂对DEDDA进行基准测试.
  • 使用 iTRAQ 标记的三种蛋白质组模型 (酵母,人,大肠杆菌) 评估干扰效应和前体强度分数 (PIF) 切断影响的评估.

主要成果:

  • 与DEDDA相比,TurboDDA对未分离和分离的微量样本都表现出更高的灵敏度.
  • TurboDDA 提高了 iTRAQ 标记的微量样本的量化准确性和可重复性.
  • 更严格的PIF截止值提高了量化准确性,但减少了这两种方法的标识.

结论:

  • TurboDDA是微量样本定量蛋白质组学的有希望的策略,提供了更高的灵敏度和准确性.
  • 该研究强调了与定量蛋白质组学中PIF截止严格性相关的权衡.
  • 图尔博DDA显示了对有限的生物样本,如癌细胞系的差异分析的潜力.