Toxalim (Research Centre in Food Toxicology), Toulouse University, INRAE UMR 1331, ENVT, INP-Purpan, UPS, MetaToul-AXIOM Platform, National Infrastructure of Metabolomics and Fluxomics: MetaboHUB, INRAE, 31027, Toulouse, France.
INRAE, Univ. Bordeaux, Biologie du Fruit et Pathologie, UMR1332, Bordeaux Metabolome - MetaboHUB, Centre INRAE de Nouvelle-Aquitaine Bordeaux, 33140, Villenave d'Ornon, France.
Metabolomics. 2023 Jul 7;19(7):65. doi: 10.1007/s11306-023-02028-4.
Absolute quantification of individual metabolites in complex biological samples is crucial in targeted metabolomic profiling.
An inter-laboratory test was performed to evaluate the impact of the NMR software, peak-area determination method (integration vs. deconvolution) and operator on quantification trueness and precision.
A synthetic urine containing 32 compounds was prepared. One site prepared the urine and calibration samples, and performed NMR acquisition. NMR spectra were acquired with two pulse sequences including water suppression used in routine analyses. The pre-processed spectra were sent to the other sites where each operator quantified the metabolites using internal referencing or external calibration, and his/her favourite in-house, open-access or commercial NMR tool.
For 1D NMR measurements with solvent presaturation during the recovery delay (zgpr), 20 metabolites were successfully quantified by all processing strategies. Some metabolites could not be quantified by some methods. For internal referencing with TSP, only one half of the metabolites were quantified with a trueness below 5%. With peak integration and external calibration, about 90% of the metabolites were quantified with a trueness below 5%. The NMRProcFlow integration module allowed the quantification of several additional metabolites. The number of quantified metabolites and quantification trueness improved for some metabolites with deconvolution tools. Trueness and precision were not significantly different between zgpr- and NOESYpr-based spectra for about 70% of the variables.
External calibration performed better than TSP internal referencing. Inter-laboratory tests are useful when choosing to better rationalize the choice of quantification tools for NMR-based metabolomic profiling and confirm the value of spectra deconvolution tools.
在靶向代谢组学分析中,对复杂生物样本中个体代谢物进行绝对定量至关重要。
进行了一项实验室间测试,以评估 NMR 软件、峰面积测定方法(积分与解卷积)和操作人员对定量准确性和精密度的影响。
制备了一种含有 32 种化合物的合成尿液。一个站点负责尿液和校准样品的制备,并进行 NMR 采集。使用两种包括在常规分析中使用的水抑制脉冲序列采集 NMR 谱。预处理后的谱图被发送到其他站点,每个操作人员使用内部参考或外部校准以及他/她喜欢的内部、开放获取或商业 NMR 工具对代谢物进行定量。
对于在恢复延迟期间使用溶剂饱和的 1D NMR 测量(zgpr),所有处理策略都成功定量了 20 种代谢物。有些代谢物无法用某些方法定量。对于 TSP 的内部参考,只有一半的代谢物的准确性低于 5%。使用峰积分和外部校准,约 90%的代谢物的准确性低于 5%。NMRProcFlow 积分模块允许对几个额外的代谢物进行定量。使用解卷积工具,一些代谢物的定量数量和准确性有所提高。对于约 70%的变量, zgpr 和 NOESYpr 基谱的准确性和精密度没有显著差异。
外部校准比 TSP 内部参考表现更好。当选择更好地合理化基于 NMR 的代谢组学分析中定量工具的选择并确认光谱解卷积工具的价值时,实验室间测试是有用的。