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An integrated targeted metabolomic platform for high-throughput metabolite profiling and automated data processing

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Abstract

Multiple reaction monitoring (MRM)-based targeted metabolomics can simultaneously analyze up to hundreds of metabolites with high-throughput, good reproducibility, and wide dynamic range. However, when hundreds or thousands of MRM transitions are measured with tens to hundreds of biological samples, the complexity of MRM dataset acquired is no longer amenable to manual evaluation, and presents a challenge for targeted metabolomics. Here, we developed an R package, namely MRMAnalyzer, to process large set of MRM-based targeted metabolomics data automatically without any manual intervention. To demonstrate our MRMAnalyzer program, we first developed a targeted metabolomic method that simultaneously analyzes 182 metabolites in one 15-min LC run, and demonstrated the data processing procedures using MRMAnalyzer. The data processing steps include “pseudo” accurate m/z transformation, peak detection and alignment, metabolite identification, quality control check and statistical analysis. Finally, a targeted metabolomic assay was designed and integrated with MRMAnalyzer to profile the metabolic changes in Escherichia coli subjected to the protein expression. The generated MRM dataset consisting of more than 8000 MRM transitions were readily processed using MRMAnalyzer within 20 min without any manual intervention. Fourty seven out of 140 detected metabolites, enriched in six metabolic pathways, were found significantly affected in E. coli metabolome. In summary, a targeted metabolomic platform is developed for high-throughput metabolite profiling and automated data processing, and the MRMAnalyzer program is a high efficient informatics tool for large scale targeted metabolomics.

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Acknowledgments

We thank the financial support provided by the startup funding from Interdisciplinary Research Center on Biology and Chemistry (IRCBC), Chinese Academy of Sciences (CAS). Z.-J. Z. is also supported by Thousand Youth Talents Program (The Recruitment Program of Global Youth Experts from Chinese government). The project is also financially supported by Agilent Technologies Thought Leader Award.

Compliance with ethical requirements

All institutional and national guidelines for the care and use of biological samples were followed. The data acquired were in accordance with appropriate ethical requirements.

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There are no conflicts of interest.

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    Authors and Affiliations

    1. Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Ling-Ling Road, Shanghai, 200032, China

      Yuping Cai, Kai Weng, Yuan Guo, Jie Peng & Zheng-Jiang Zhu

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    1. Yuping Cai
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    2. Kai Weng
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    3. Yuan Guo
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    5. Zheng-Jiang Zhu
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    Correspondence to Zheng-Jiang Zhu.

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    Yuping Cai and Kai Weng have contributed equally.

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    Cai, Y., Weng, K., Guo, Y. et al. An integrated targeted metabolomic platform for high-throughput metabolite profiling and automated data processing. Metabolomics 11, 1575–1586 (2015). https://doi.org/10.1007/s11306-015-0809-4

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