Exploring functional protein covariation across single cells using nPOP

Genome Biology

Research

Nikolai Slavov¹  R. Gray Huffman¹  Andrew Leduc¹  Saad Khan¹  Joshua Cantlon² 

[1]Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, and Barnett Institute, Northeastern University, 02115, Boston, MA, USA

[2]Scienion AG, 85042, Phoenix, AZ, USA

关键词: Single-cell proteomics;    Protein covariation;    Cell division cycle;    Drug resistance;    Single cell;    Sample preparation;   

DOI  :  10.1186/s13059-022-02817-5

 received in 2022-10-14, accepted in 2022-11-18,  发布年份 2022

来源: Springer

【 摘 要 】

BackgroundMany biological processes, such as cell division cycle and drug resistance, are reflected in protein covariation across single cells. This covariation can be quantified and interpreted by single-cell mass spectrometry with sufficiently high throughput and accuracy.ResultsHere, we describe nPOP, a method that enables simultaneous sample preparation of thousands of single cells, including lysing, digesting, and labeling individual cells in volumes of 8–20 nl. nPOP uses piezo acoustic dispensing to isolate individual cells in 300 pl volumes and performs all subsequent sample preparation steps in small droplets on a fluorocarbon-coated glass slide. Protein covariation analysis identifies cell cycle dynamics that are similar and dynamics that differ between cell types, even within subpopulations of melanoma cells delineated by markers for drug resistance priming. Melanoma cells expressing these markers accumulate in the G1 phase of the cell cycle, display distinct protein covariation across the cell cycle, accumulate glycogen, and have lower abundance of glycolytic enzymes. The non-primed melanoma cells exhibit gradients of protein abundance, suggesting transition states. Within this subpopulation, proteins functioning in oxidative phosphorylation covary with each other and inversely with proteins functioning in glycolysis. This protein covariation suggests divergent reliance on energy sources and its association with other biological functions. These results are validated by different mass spectrometry methods.ConclusionsnPOP enables flexible, automated, and highly parallelized sample preparation for single-cell proteomics. This allows for quantifying protein covariation across thousands of single cells and revealing functionally concerted biological differences between closely related cell states. Support for nPOP is available at https://scp.slavovlab.net/nPOP.

【 授权许可】

CC BY   
© The Author(s) 2022

【 图 表 】

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