CIMR-Shiyu Liu

Research Group

Shiyu Liu

shiyu.liu(at)cimrbj.ac.cn

Assistant Investigator

Metabolic Flux Analysis, Computational Metabolic Physiology,

Stable Isotope Tracing, Metabolic Diseases, Multi-omics Integration

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shiyu.liu(at)cimrbj.ac.cn

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B.S. in Biology, Peking University, China

Ph.D. in Computational Biology and Bioinformatics, Duke University, USA

Work Experience

2025.1-Present

Assistant Investigator, Chinese Institute for Medical Physiology, Chinese Institutes for Medical Research, Beijing, China

2021.12-2025.1

Postdoctoral Fellow, Department of Pharmacology and Cancer Biology, Duke University School of Medicine, USA

Research Interests

The Liu Laboratory at CIMR centers on metabolic flux analysis as its core technology, integrating it with advanced physiological, multi-omics, computational, and genetic approaches. We aim to quantitatively uncover the fundamental principles that govern metabolic networks in living systems, and to translate these insights into innovative therapeutic strategies for a broad spectrum of metabolic diseases. Our current directions include:

1. Developing and optimizing the algorithms, software, and standardized experimental pipelines of metabolic flux analysis, to make metabolic research more efficient, accurate, and accessible.
2. Applying metabolic flux analysis to whole-body metabolic networks to quantitatively characterize metabolic physiology in animals and humans, with a focus on metabolic diseases such as obesity and gout.
3. Combining metabolic flux analysis with spatial metabolomics and single-cell metabolic networks to investigate metabolic heterogeneity among cells within organs and its links to organ physiology and pathology.
4. Integrating metabolic network models with multi-omics data to infer multi-organ metabolic interactions within living organisms.

Major Contributions

1. Constructed a multi-tissue metabolic network to quantify the contributions of glucose and lactate to the TCA cycle in various mouse organs (Cell Metabolism, 2020).

2. Analyzed energy fluxes in Drosophila to uncover how a methionine-restricted diet impacts longevity and fertility (Nature Aging, 2024, second author).

3. Developed a novel methodology to evaluate the accuracy of flux analysis results and designed an improved pipeline to enhance its precision and robustness (Nature Metabolism, 2024).

Representative Publications *：Co-first author; #：Co-corresponding author

Liu S, Liu X & Locasale JW. Quantification of metabolic activity from isotope tracing data using automated methodology. Nature Metabolism, 2024, 6: 2207–2209. DOI: 10.1038/s42255-024-01144-2

Wei F, Liu S, Liu J, Sun Y, Allen A, Reid MA & Locasale JW. Separation of reproductive decline from lifespan extension. Nature Aging, 2024, 4: 1089-1101. DOI: 10.1038/s43587-024-00674-4

Liu S & Locasale JW. Delineating a role for methionine metabolism in colorectal cancer. Cancer Research, 2023, 83: 3833–3834. DOI: 10.1158/0008-5472.CAN-23-3169

Liu S, Dai Z, Cooper DE, Kirsch DG & Locasale JW. Quantitative Analysis of the Physiological Contributions of Glucose to the TCA Cycle. Cell Metabolism, 2020, 32: 619-628.e21. DOI: 10.1016/j.cmet.2020.09.005