ProteoAutoNet: high-throughput co-eluted protein analysis with robotics and machine learning

proteoautonet:-high-throughput-co-eluted-protein-analysis-with-robotics-and-machine-learning
ProteoAutoNet: high-throughput co-eluted protein analysis with robotics and machine learning

Data availability

The proteomics data, the spectral library, and sample information generated in this study have been deposited in PRIDE under the accession number PXD059608. The remaining data are available within the Article, Supplementary Data files or Source Data file. Source data are providd with this paper. Source data are provided with this paper.

Code availability

The computational framework ProteoAutoNet, including R and Python scripts and visualized files, is publicly available at: https://github.com/guomics-lab/ProteoAutoNet. The code and example files that were used in this study are publicly available on Zenodo at https://doi.org/10.5281/zenodo.18217457.

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Acknowledgements

This work is supported by grants from Joint Funds of the National Natural Science Foundation of China (No. U24A20476) to T.G., National Key R&D Program of China (No. 2021YFA1301600) to T.G., National Natural Science Foundation of China (Young Scientist Fund, No. 32401239) to R.S., Zhejiang Provincial Natural Science Foundation of China (LQ24C050002) to R.S., the State Key Laboratory of Medical Proteomics (SKLP-Y202403) to R.S. and Key Technology Research and Development Program of Shandong Province (2022CXGC020510) to X.L. We thank Westlake University Supercomputer Center for assistance in data generation and storage, and the Mass Spectrometry & Metabolomics Core Facility at the Center for Biomedical Research Core Facilities of Westlake University for sample analysis. We thank Prof. Ruedi Aebersold, Dr. Moritz Heusel and Dr. Chen Li for helpful discussions, and Prof. Leonard Foster and Jenny Moon for advice on sample preparation. We also thank Liang Chen for helping with figures.

Author information

Authors and Affiliations

  1. School of Basic Medical Science, Fudan University, Shanghai, China

    Mengge Lyu & Tiannan Guo

  2. Affiliated Hangzhou First People’s Hospital, State Key Laboratory of Medical Proteomics, School of Medicine, Westlake University, Hangzhou, Zhejiang Province, China

    Mengge Lyu, Pingping Hu, Guangmei Zhang, Kunpeng Ma, Xuedong Zhang, Rui Sun, Yi Chen & Tiannan Guo

  3. Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang Province, China

    Mengge Lyu, Pingping Hu, Guangmei Zhang, Kunpeng Ma, Xuedong Zhang, Rui Sun, Yi Chen & Tiannan Guo

  4. Research Center for Industries of the Future, School of Life Sciences, Westlake University, Hangzhou, Zhejiang Province, China

    Mengge Lyu, Pingping Hu, Guangmei Zhang, Kunpeng Ma, Xuedong Zhang, Rui Sun, Yi Chen & Tiannan Guo

  5. Westlake Omics Inc., Hangzhou, Zhejiang Province, China

    Pu Liu

  6. Institute of Automation, Harbin University of Science and Technology, Harbin, China

    Sai Zhang

  7. College of Medical Information and Artificial Intelligence, Shandong First Medical University, Jinan, China

    Xiangqing Li

Authors

  1. Mengge Lyu
  2. Pingping Hu
  3. Guangmei Zhang
  4. Kunpeng Ma
  5. Xuedong Zhang
  6. Pu Liu
  7. Sai Zhang
  8. Xiangqing Li
  9. Rui Sun
  10. Yi Chen
  11. Tiannan Guo

Contributions

T.G., M.L., Y.C., and R.S. conceived and designed the project. M.L., G.Z. and X.Z. performed the cell culture and harvest. M.L., X.L., and S.Z. set up the robotics-assisted platform. M.L., P.H., and K.M. did fractionation and set the robotic platform of CF-MS. M.L., Y.C., and P.L. analyzed the data. M.L. and R.S. created and designed of the figures. M.L., R.S., and T.G. co-wrote the manuscript. M.L., R.S., and T.G. revised the manuscript. T.G. supported the study. All authors reviewed and edited the manuscript.

Corresponding authors

Correspondence to Rui Sun, Yi Chen or Tiannan Guo.

Ethics declarations

Competing interests

T. G. is a shareholder of Westlake Omics Inc. P.L. is a staff of Westlake Omics Inc. The remaining authors declare no competing interests.

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Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

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Supplementary information

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Lyu, M., Hu, P., Zhang, G. et al. ProteoAutoNet: high-throughput co-eluted protein analysis with robotics and machine learning. Nat Commun (2026). https://doi.org/10.1038/s41467-026-68686-9

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  • DOI: https://doi.org/10.1038/s41467-026-68686-9