High throughput and in-depth single-cell proteomics for plant cells
EMSL Project ID
51688
Abstract
In support of the "Single-cell biology" value stream in EMSD/EMSL DigiPhen Motivation, we propose to develop a high throughput and in-depth single-cell proteomics platform. We aim to reliably quantify > 1500 proteins from single cells at a throughput of >200 single cells per day. The advances will be enabled by two key developments: 1) Reduce the processing volume by an order of magnitude; 2) Establish a boosting-free multiplex labeling method. We will demonstrate the application of the scProteomics to study the regulatory pathways of plants in response to abiotic stress at single-cell resolution and to identify key stress-tolerance genes. The scProteomics platform will significantly enhance both EMSL's functional omics and molecular plant phenotyping capabilities. The new capability will benefit current EMSL users and many prospective users.
Project Details
Start Date
2020-10-26
End Date
2022-04-30
Status
Closed
Released Data Link
Team
Principal Investigator
Team Members
Related Publications
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Charles Ansong, William B. Chrisler, Geremy C. Clair, Song Feng, Ryan T. Kelly, Ronald J. Moore, Ljiljana Paša-Tolić, Richard D. Smith, Chia-Feng Tsai, Sarah M. Williams, Jongmin Woo, Ying Zhu. 2022. "Three-dimensional feature matching improves coverage for single-cell proteomics based on ion mobility filtering." Cell Systems 10.1016/j.cels.2022.02.003
Joshua N. Adkins, Victor Aguilera-Vazquez, Joshua Cantlon-Bruce, Geremy C. Clair, Song Feng, Dehong Hu, Tao Liu, Lye Meng Markillie, Hardeep S. Mehta, Ronald J. Moore, Ljiljana Pasa-Tolic, Richard D. Smith, Ryan L. Sontag, Chia-Feng Tsai, Sarah M. Williams, Jongmin Woo, Ying Zhu. 2021. "High-throughput and high-efficiency sample preparation for single-cell proteomics using a nested nanowell chip." Nature Communications 12 (1) 10.1038/s41467-021-26514-2