Quartet metabolite reference materials for inter-laboratory proficiency test and data integration of metabolomics profiling

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2024年1月24日

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Naixin Zhang,
Qiaochu Chen,
Peipei Zhang,
Kejun Zhou,
Yaqing Liu,
Haiyan Wang,
Shumeng Duan,
Yongming Xie,
Wenxiang Yu,
Ziqing Kong,
Luyao Ren,
Wanwan Hou,
Jingcheng Yang,
Xiaoyun Gong,
Lianhua Dong,
Xiang Fang,
Leming Shi,
Ying Yu,
Yuanting Zheng

摘要

Background

Various laboratory-developed metabolomic methods lead to big challenges in inter-laboratory comparability and effective integration of diverse datasets.

Results

As part of the Quartet Project, we establish a publicly available suite of four metabolite reference materials derived from B lymphoblastoid cell lines from a family of parents and monozygotic twin daughters. We generate comprehensive LC–MS-based metabolomic data from the Quartet reference materials using targeted and untargeted strategies in different laboratories. The Quartet multi-sample-based signal-to-noise ratio enables objective assessment of the reliability of intra-batch and cross-batch metabolomics profiling in detecting intrinsic biological differences among the four groups of samples. Significant variations in the reliability of the metabolomics profiling are identified across laboratories. Importantly, ratio-based metabolomics profiling, by scaling the absolute values of a study sample relative to those of a common reference sample, enables cross-laboratory quantitative data integration. Thus, we construct the ratio-based high-confidence reference datasets between two reference samples, providing “ground truth” for inter-laboratory accuracy assessment, which enables objective evaluation of quantitative metabolomics profiling using various instruments and protocols.

Conclusions

Our study provides the community with rich resources and best practices for inter-laboratory proficiency tests and data integration, ensuring reliability of large-scale and longitudinal metabolomic studies.