Automated Microvolume Secretome Proteomics Enables Sensitive and Deep Profiling and Noninvasive Single-Embryo Analysis
Cells continuously deliver proteins into the extracellular space, forming the secretome, which provides a dynamic, biologically informative, and noninvasive readout of cellular functional states. However, conventional secretome proteomics typically requires large sample volumes greater than 2 mL, delivers limited proteome depth, and supports low processing throughput of less than 30 samples a day. Here, we developed an automated microvolume secretome profiling workflow that integrates optimized sample pretreatment and magnetic bead-based proteome sample preparation. This workflow enables efficient secretome profiling from less than 20 μL of conditioned medium, achieving deep proteome coverage of over 3000 proteins with a sample processing throughput exceeding 96 samples per day. Using this workflow, we achieved high-depth, time-resolved secretome profiling from microscale culture medium, capturing temporal changes of secretome. We further applied the method to single mouse embryo culture medium and consistently identified more than 200 secretome proteins per embryo. Notably, Sdc4 and Ooep were consistently observed across developmental stages, highlighting the potential for noninvasive secretome profiling at the single-embryo level. Together, this work establishes a robust and scalable framework for high-depth secretome profiling from ultralow-input samples, broadening the scope of LC-MS-based analysis to microscale and longitudinal biological applications.
Authors
- Zilu Ye (ORCID: https://orcid.org/0000-0001-8829-6579)
- Haitao Zhang (ORCID: https://orcid.org/0000-0002-1639-4089)
- Jiwei Wang (ORCID: https://orcid.org/0000-0002-6202-4652)
- Jingsheng Xie
- Yuhe Ge
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking Union Medical College Hospital (CN)
- Soochow University (CN)
- Seattle Reproductive Medicine (US)
- Second Affiliated Hospital of Soochow University (CN)
- Suzhou Research Institute (CN)
Publication Details
- Journal
- Journal of Proteome Research
- Published
- 2026-05-27
- DOI
- https://doi.org/10.1021/acs.jproteome.6c00284
- Primary Topic
- Advanced Proteomics Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Jiangsu Province
- Chinese Academy of Medical Sciences
- National Key Research and Development Program of China