Deep Profiling of Oocyte Aging Enabled by Simple One-Step Vial-Based Pretreatment and Single-Cell Proteomics

Single-cell proteomics is a pivotal technology for studying cellular phenotypes, offering unparalleled insights into cellular heterogeneity and dynamic functions. Technical improvement in mass spectrometry instruments and sample preparation has made proteomics profiling of single mouse oocytes or early embryos feasible in recent years. Yet, developing a simple and robust sample preparation method to enable deep proteomics profiling of single germline cells remains a significant challenge. Herein, we developed a simple one-step vial-based pretreatment (SOViP) for deep label-free single-cell proteomics of germline cells. SOViP integrates all sample preparation procedures into a single step in autosampler vials, yet it is highly efficient and high-throughput in comparison to reported multistep methods. SOViP can be finished within ∼2 h with hands-on time limited to merely a few minutes. On average, over 6500 protein groups can be quantified from a single mouse oocyte using SOViP. In total, 6983 protein groups were identified from single mouse oocytes across an entire reproductive lifespan, offering a valuable proteomics resource for oocyte aging. Unique molecular characteristics of oocytes at different ages were revealed, and a classifier consisting of ten proteins demonstrated accurate age-group classification and fertility-level prediction. Although demonstrated using mouse oocytes in this study, SOViP is adaptable to rare cell samples and other large cells including follicles and preimplantation embryo cells, among others.

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Publication Details

Journal
JACS Au
Published
2025-05-01
DOI
https://doi.org/10.1021/jacsau.5c00244
Citations
4
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
3.22

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article

Deep Profiling of Oocyte Aging Enabled by Simple One-Step Vial-Based Pretreatment and Single-Cell Proteomics

Jing Yang, Hailu Zhang, Yun Yang, Qing Zeng et al.
4 citations
JACS Au
Single-cell and spatial transcriptomics
3.22
article

Deep Profiling of Oocyte Aging Enabled by Simple One-Step Vial-Based Pretreatment and Single-Cell Proteomics

Jing Yang, Hailu Zhang, Yun Yang, Qing Zeng, Chuanxi Huang, Chunyan Tian, Hui Zhang, Fu-Chu He
article en
4 citations

Abstract

Single-cell proteomics is a pivotal technology for studying cellular phenotypes, offering unparalleled insights into cellular heterogeneity and dynamic functions. Technical improvement in mass spectrometry instruments and sample preparation has made proteomics profiling of single mouse oocytes or early embryos feasible in recent years. Yet, developing a simple and robust sample preparation method to enable deep proteomics profiling of single germline cells remains a significant challenge. Herein, we developed a simple one-step vial-based pretreatment (SOViP) for deep label-free single-cell proteomics of germline cells. SOViP integrates all sample preparation procedures into a single step in autosampler vials, yet it is highly efficient and high-throughput in comparison to reported multistep methods. SOViP can be finished within ∼2 h with hands-on time limited to merely a few minutes. On average, over 6500 protein groups can be quantified from a single mouse oocyte using SOViP. In total, 6983 protein groups were identified from single mouse oocytes across an entire reproductive lifespan, offering a valuable proteomics resource for oocyte aging. Unique molecular characteristics of oocytes at different ages were revealed, and a classifier consisting of ten proteins demonstrated accurate age-group classification and fertility-level prediction. Although demonstrated using mouse oocytes in this study, SOViP is adaptable to rare cell samples and other large cells including follicles and preimplantation embryo cells, among others.

JACS AuVol. 5(5)
Target (United States) (US), Southern University of Science and Technology (CN), Guangzhou Experimental Station (CN), Beijing Proteome Research Center (CN), State Key Laboratory of Respiratory Disease (CN), Guangzhou Medical University (CN)
Ministry of Science and Technology of the People's Republic of China
Zero hunger
Openalex Percentile: Top 9%
Single-cell and spatial transcriptomics
3.22
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