从单个患者衍生的神经圈获得个性化神经生物学见解的优化管道
Guillaume Nugue1, Michele Martins1, Gabriela Vitória2
1Department of Biochemistry, Institute of Chemistry, Universidade Federal do Rio de Janeiro, Rio de Janeiro 21941-909, Brazil.
Journal of proteomics
|December 10, 2024
概括
这项研究优化了使用Tandem Mass Tag (TMT) 标签诱导多能干细胞衍生神经圈的蛋白质分析. 它确定了有效的蛋白质提取方法,以获得强大的神经生物学见解,并推进了体外神经模型.
科学领域:
- 神经科学是一个神经科学.
- 蛋白质组学是指蛋白质组学.
- 干细胞生物学 干细胞生物学
背景情况:
- 诱导多能干细胞 (iPSCs) 为模拟神经发育和神经疾病提供了强大的工具.
- 传统的二维细胞培养缺乏复杂性,无法完全复制体内神经环境.
- 来自iPSC的3D神经圈模型为研究神经过程提供了一个更具生理相关性的平台.
研究的目的:
- 为了完善IPSC衍生神经圈的蛋白质组分析工作流程.
- 评估和比较各种蛋白质提取协议,以优化蛋白质基因分析.
- 通过使用Tandem Mass Tag (TMT) 标签,增强神经圈中差异表达蛋白质的识别.
主要方法:
- 使用单个患者衍生的神经圈,由神经前代细胞,早期神经元和辐射质组成.
- 采用双重质量标签 (TMT) 进行多重蛋白质组分析的10个复合标签.
- 评估了十种不同的蛋白质提取协议,评估成本,蛋白质产量和差异蛋白质检测.
主要成果:
- 识别了SPEED和S-Trap协议作为高通量蛋白质组研究的高效.
- 确定FASP协议在最大化产量方面表现出色.
- 证明TMT标签在增强蛋白质识别,特别是低丰度蛋白质的有效性,并使有限样本的预分离成为可能.
结论:
- 使用TMT标记的优化蛋白质组工作流程显著提升了体外神经建模.
- 选择蛋白质提取协议应该与特定的研究目标保持一致,同时考虑产量和吞吐量等因素.
- 这项研究有助于从iPSC衍生的神经圈获得更准确的神经生物学见解,减少对动物模型的依赖.
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