Phosphoproteomic profiling of mouse primary HSPCs reveals new regulators of HSPC mobilization.
Leo David WangScott B FicarroJohn N HutchinsonRoland Csepanyi-KomiPhi T NguyenEva WisniewskiJessica SullivanOliver HofmannErzsébet LigetiJarrod A MartoAmy J WagersPublished in: Blood (2016)
Protein phosphorylation is a central mechanism of signal transduction that both positively and negatively regulates protein function. Large-scale studies of the dynamic phosphorylation states of cell signaling systems have been applied extensively in cell lines and whole tissues to reveal critical regulatory networks, and candidate-based evaluations of phosphorylation in rare cell populations have also been informative. However, application of comprehensive profiling technologies to adult stem cell and progenitor populations has been challenging, due in large part to the scarcity of such cells in adult tissues. Here, we combine multicolor flow cytometry with highly efficient 3-dimensional high performance liquid chromatography/mass spectrometry to enable quantitative phosphoproteomic analysis from 200 000 highly purified primary mouse hematopoietic stem and progenitor cells (HSPCs). Using this platform, we identify ARHGAP25 as a novel regulator of HSPC mobilization and demonstrate that ARHGAP25 phosphorylation at serine 363 is an important modulator of its function. Our approach provides a robust platform for large-scale phosphoproteomic analyses performed with limited numbers of rare progenitor cells. Data from our study comprises a new resource for understanding the molecular signaling networks that underlie hematopoietic stem cell mobilization.
Keyphrases
- single cell
- high performance liquid chromatography
- flow cytometry
- mass spectrometry
- protein kinase
- highly efficient
- stem cells
- high throughput
- transcription factor
- hematopoietic stem cell
- cell therapy
- tandem mass spectrometry
- gene expression
- induced apoptosis
- liquid chromatography
- solid phase extraction
- amino acid
- protein protein
- multidrug resistant
- machine learning
- mesenchymal stem cells
- cell proliferation
- big data
- young adults
- cell cycle arrest
- oxidative stress
- electronic health record
- gas chromatography
- cell death
- capillary electrophoresis
- data analysis
- endoplasmic reticulum stress