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SPPUSM:一种MS/MS光谱融合策略,用于改进低输入和单细胞蛋白质组识别
Yongle Chen1, Zhuokun Du1, Hongxian Zhao1
1State Key Laboratory of Proteomics, Beijing Institute of Lifeomics, National Center for Protein Sciences Beijing, Beijing Proteome Research Center, Beijing, 102206, PR China.
Analytica chimica acta
|October 12, 2023
概括
一个名为SPPUSM的新策略合并未识别的光谱,以改善低输入和单细胞蛋白质组分析. 这种方法增强了蛋白质识别,为生物和疾病研究提供了更高的灵敏度.
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
- 单细胞分析的方法
背景情况:
- 大量测量掩盖了细胞异质性,这对于理解生物过程和疾病至关重要.
- 微量样本或单细胞的蛋白质组分析落后于核酸分析,原因是蛋白质的非放大性和质谱学灵敏度极限.
研究的目的:
- 开发MS/MS光谱融合策略,SPPUSM (同一个前体产生的未识别的光谱融合),以增强低输入和单细胞蛋白质组数据分析.
- 在具有挑战性的样本类型中改善蛋白质识别和蛋白质组覆盖率.
主要方法:
- 从多个测试文件中提取未识别的MS/MS光谱.
- 根据前体质量和保留时间 (RT) 在不同文件中对同一前体离子的MS / MS光谱进行匹配和合并.
- 在数据库中搜索合并的光谱,以增加识别.
主要成果:
- 使用SPPUSM,对1 ngHeLa的蛋白质识别得到了高达18.2%的改进.
- 通过"陷数据库"策略证明了边际错误率.
- 在单细胞蛋白质组 (SCP) 数据中显示了28%-61%的蛋白质识别增强.
- 鉴定出较少的丰度,表明增强的敏感性.
结论:
- 在低输入和单细胞样本中,SPPUSM有效地提高了蛋白质识别和蛋白质组覆盖率.
- 该方法为微量生物材料中更敏感的蛋白质组分析提供了显著的潜力.
- 通过克服当前的灵敏度限制,SPPUSM在单细胞蛋白质组分析领域取得了进展.
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