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Balancing metabolome coverage and reproducibility for untargeted NMR-based metabolic profiling in tissue samples through mixture design methods

  • Hong Zheng
  • Zhitao Ni
  • Aimin Cai
  • Xi Zhang
  • Jiuxia Chen
  • Qi Shu
  • Hongchang Gao
Research Paper
  • 40 Downloads

Abstract

Untargeted metabolomics attempts to acquire a comprehensive and reproducible set of small-molecule metabolites in biological systems. However, metabolite extraction method significantly affects the quality of metabolomics data. In the present study, we calculated the number of peaks (NP) and coefficient of variation (CV) to reflect metabolome coverage and reproducibility in untargeted NMR-based metabolic profiling of tissue samples in rats under different methanol/chloroform/water (MCW) extraction conditions. Different MCW extractions expectedly generated diverse characteristics of metabolome. Moreover, the classic MCW method revealed tissue-specific differences in the NP and CV values. To obtain high-quality metabolomics data, therefore, we used mixture design methods to optimize the MCW extraction strategy by maximizing the NP value and minimizing the CV value in each tissue sample. Results show that the optimal formulations of MCW extraction were 2:2:8 (ml/mg tissue) for brain sample, 2:4:6 (ml/mg tissue) for heart sample, 1.3:2:8.7 (ml/mg tissue) for liver sample, 4:2:6 (ml/mg tissue) for kidney sample, 2:3:7 (ml/mg tissue) for muscle sample, and 2:4:6 (ml/mg tissue) for pancreas sample. Therefore, these findings demonstrate that different tissue samples need a specific optimal extraction condition for balancing metabolome coverage and reproducibility in the untargeted metabolomics study. Mixture design method is an effective tool to optimize metabolite extraction strategy for tissue samples.

Graphical abstract

Keywords

Metabolomics Metabolite extraction Metabolome reproducibility Optimization Tissue-specific 

Notes

Acknowledgments

The Laboratory Animal Center of Wenzhou Medical University is acknowledged for technical services.

Author contributions

HCG and HZ contributed to the experimental design. ZTN, AMC, XZ, JXC, and QX contributed to the sample collection and NMR metabolomics analysis. HZ and HCG contributed to the data analysis, result interpretation, and writing. All authors have read, revised, and approved the final manuscript.

Funding Information

This study was supported by the National Natural Science Foundation of China (Nos. 21605115, 81771386, and 21575105) and the Public Welfare Technology Application Research Foundation of Zhejiang Province (No. 2017C33066).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in this study were in accordance with the Guide for the Care and Use of Laboratory Animals and approved by the Institutional Animal Care and Use Committee of Wenzhou Medical University.

Supplementary material

216_2018_1396_MOESM1_ESM.pdf (2.6 mb)
ESM 1 (PDF 2646 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Hong Zheng
    • 1
  • Zhitao Ni
    • 1
  • Aimin Cai
    • 1
  • Xi Zhang
    • 1
  • Jiuxia Chen
    • 1
  • Qi Shu
    • 1
  • Hongchang Gao
    • 1
  1. 1.Institute of Metabonomics & Medical NMR, School of Pharmaceutical ScienceWenzhou Medical UniversityWenzhouChina

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