Volume 13 Issue 5
May  2023
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Congcong Ma, Yanwei Li, Jie Li, Lei Song, Liangyu Chen, Na Zhao, Xueping Li, Ning Chen, Lixia Long, Jin Zhao, Xin Hou, Li Ren, Xubo Yuan. Comprehensive and deep profiling of the plasma proteome with protein corona on zeolite NaY[J]. Journal of Pharmaceutical Analysis, 2023, 13(5): 503-513. doi: 10.1016/j.jpha.2023.04.002
Citation: Congcong Ma, Yanwei Li, Jie Li, Lei Song, Liangyu Chen, Na Zhao, Xueping Li, Ning Chen, Lixia Long, Jin Zhao, Xin Hou, Li Ren, Xubo Yuan. Comprehensive and deep profiling of the plasma proteome with protein corona on zeolite NaY[J]. Journal of Pharmaceutical Analysis, 2023, 13(5): 503-513. doi: 10.1016/j.jpha.2023.04.002

Comprehensive and deep profiling of the plasma proteome with protein corona on zeolite NaY

doi: 10.1016/j.jpha.2023.04.002
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This work was supported by the National Natural Science Foundation of China (Grant No: 51773151).

  • Received Date: Jan. 03, 2023
  • Accepted Date: Apr. 06, 2023
  • Rev Recd Date: Mar. 27, 2023
  • Publish Date: Apr. 12, 2023
  • Proteomic characterization of plasma is critical for the development of novel pharmacodynamic biomarkers. However, the vast dynamic range renders the profiling of proteomes extremely challenging. Here, we synthesized zeolite NaY and developed a simple and rapid method to achieve comprehensive and deep profiling of the plasma proteome using the plasma protein corona formed on zeolite NaY. Specifically, zeolite NaY and plasma were co-incubated to form plasma protein corona on zeolite NaY (NaY-PPC), followed by conventional protein identification using liquid chromatography-tandem mass spectrometry. NaY was able to significantly enhance the detection of low-abundance plasma proteins, minimizing the “masking” effect caused by high-abundance proteins. The relative abundance of middle- and low-abundance proteins increased substantially from 2.54% to 54.41%, and the top 20 high-abundance proteins decreased from 83.63% to 25.77%. Notably, our method can quantify approximately 4000 plasma proteins with sensitivity up to pg/mL, compared to only about 600 proteins identified from untreated plasma samples. A pilot study based on plasma samples from 30 lung adenocarcinoma patients and 15 healthy subjects demonstrated that our method could successfully distinguish between healthy and disease states. In summary, this work provides an advantageous tool for the exploration of plasma proteomics and its translational applications.
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