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对于非目标代谢组的离子抑制校正和正常化

Iqbal Mahmud¹, Bo Wei¹, Lucas Veillon¹

¹Metabolomics Core Facility, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center (MDACC), Houston, TX, USA.

Nature communications

|February 5, 2025

概括

IROA的TruQuant工作流有效地纠正质谱代谢学中的离子抑制. 这种方法在各种分析条件下提高了测量准确度和精度,揭示了对细胞代谢的新见解.

科学领域:

分析化学分析化学
生物化学生化学
代谢学代谢学代谢学

背景情况:

离子抑制显著影响基于质谱 (MS) 的代谢学,降低准确度,精度和灵敏度.
准确量化代谢物对于理解生物过程和疾病机制至关重要.

研究的目的:

引入和评估IROA的TruQuant工作流程,用于测量和纠正MS代谢中的离子抑制.
通过使用双MSTUS规范化来执行代谢数据的稳健规范化.

主要方法:

使用稳定同位素标记的内部标准 (IROA-IS) 库和伴随算法.
评估了离子染色学 (IC),水友相互作用液体染色学 (HILIC) 和逆相液体染色学 (RPLC) -MS. 的工作流程.
在正和负电离模式下测试,使用干净和不干净的离子源,以及各种生物矩阵.

主要成果:

在所有测试条件下观察到离子抑制在1%至90%以上.
工作流有效地纠正了离子抑制,并将变化系数从1%降低到20%.
在研究卵巢癌细胞对L-asparaginase (ASNase) 的反应中得到了应用,揭示了新的代谢变化.

结论:

IROA的TruQuant工作流提供了在非目标代谢数据中对离子抑制的强有力的校正.
这种方法在各种分析设置和生物样本中提高了数据可靠性.
工作流有助于发现以前未报告的代谢变化,如卵巢癌研究所示.

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