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Identification of Kinase-substrate Pairs Using High Throughput Screening
Published on: August 29, 2015
Identification of direct tyrosine kinase substrates based on protein kinase assay-linked phosphoproteomics
Liang Xue1, Robert L Geahlen, W Andy Tao
1Department of Biochemistry.
Abstract:
Protein kinases are implicated in multiple diseases such as cancer, diabetes, cardiovascular diseases, and central nervous system disorders. Identification of kinase substrates is critical to dissecting signaling pathways and to understanding disease pathologies. However, methods and techniques used to identify bona fide kinase substrates have remained elusive. Here we describe a proteomic strategy suitable for identifying kinase specificity and direct substrates in high throughput. This approach includes an in vitro kinase assay-based substrate screening and an endogenous kinase dependent phosphorylation profiling. In the in vitro kinase reaction route, a pool of formerly phosphorylated proteins is directly extracted from whole cell extracts, dephosphorylated by phosphatase treatment, after which the kinase of interest is added. Quantitative proteomics identifies the rephosphorylated proteins as direct substrates in vitro. In parallel, the in vivo quantitative phosphoproteomics is performed in which cells are treated with or without the kinase inhibitor. Together, proteins phosphorylated in vitro overlapping with the kinase-dependent phosphoproteome in vivo represents the physiological direct substrates in high confidence. The protein kinase assay-linked phosphoproteomics was applied to identify 25 candidate substrates of the protein-tyrosine kinase SYK, including a number of known substrates and many novel substrates in human B cells. These shed light on possible new roles for SYK in multiple important signaling pathways. The results demonstrate that this integrated proteomic approach can provide an efficient strategy to screen direct substrates for protein tyrosine kinases.
Insights
Identifying kinase substrates is crucial for understanding diseases. This study presents a novel proteomic strategy to efficiently discover direct kinase substrates and their roles in signaling pathways.
Area of Science:
- Biochemistry
- Proteomics
- Molecular Biology
Background:
- Protein kinases play vital roles in cellular signaling and are implicated in various diseases, including cancer and diabetes.
- Identifying direct kinase substrates is essential for dissecting signaling pathways and understanding disease mechanisms.
- Current methods for identifying kinase substrates are often limited in throughput and confidence.
Purpose of the Study:
- To develop and validate a high-throughput proteomic strategy for identifying kinase specificity and direct substrates.
- To discover novel substrates of protein-tyrosine kinase SYK in human B cells.
- To elucidate the role of SYK in cellular signaling pathways.
Main Methods:
- An integrated proteomic approach combining in vitro kinase assay-based substrate screening and in vivo quantitative phosphoproteomics.
- In vitro screening involves dephosphorylating cell extracts, incubating with the kinase of interest, and identifying rephosphorylated proteins via quantitative proteomics.
- In vivo profiling uses quantitative phosphoproteomics with and without kinase inhibitors to identify kinase-dependent phosphorylation events.
Main Results:
- The integrated approach successfully identified 25 candidate substrates for the protein-tyrosine kinase SYK in human B cells.
- The identified substrates include both known and novel targets of SYK.
- The findings suggest new roles for SYK in multiple important signaling pathways.
Conclusions:
- The developed integrated proteomic strategy provides an efficient and high-confidence method for screening direct substrates of protein tyrosine kinases.
- This approach facilitates the discovery of novel kinase substrates, advancing our understanding of kinase function in health and disease.
- The identification of SYK substrates offers insights into SYK's involvement in B cell signaling and potential disease pathologies.
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