» Articles » PMID: 20467045

Synthetic Peptide Arrays for Pathway-level Protein Monitoring by Liquid Chromatography-tandem Mass Spectrometry

Abstract

Effective methods to detect and quantify functionally linked regulatory proteins in complex biological samples are essential for investigating mammalian signaling pathways. Traditional immunoassays depend on proprietary reagents that are difficult to generate and multiplex, whereas global proteomic profiling can be tedious and can miss low abundance proteins. Here, we report a target-driven liquid chromatography-tandem mass spectrometry (LC-MS/MS) strategy for selectively examining the levels of multiple low abundance components of signaling pathways which are refractory to standard shotgun screening procedures and hence appear limited in current MS/MS repositories. Our stepwise approach consists of: (i) synthesizing microscale peptide arrays, including heavy isotope-labeled internal standards, for use as high quality references to (ii) build empirically validated high density LC-MS/MS detection assays with a retention time scheduling system that can be used to (iii) identify and quantify endogenous low abundance protein targets in complex biological mixtures with high accuracy by correlation to a spectral database using new software tools. The method offers a flexible, rapid, and cost-effective means for routine proteomic exploration of biological systems including "label-free" quantification, while minimizing spurious interferences. As proof-of-concept, we have examined the abundance of transcription factors and protein kinases mediating pluripotency and self-renewal in embryonic stem cell populations.

Citing Articles

Quantitative Cell Proteomic Atlas: Pathway-Scale Targeted Mass Spectrometry for High-Resolution Functional Profiling of Cell Signaling.

Cifani P, Kentsis A J Proteome Res. 2022; 21(10):2535-2544.

PMID: 36154077 PMC: 10494574. DOI: 10.1021/acs.jproteome.2c00223.


Cand1 promotes assembly of new SCF complexes through dynamic exchange of F box proteins.

Pierce N, Lee J, Liu X, Sweredoski M, Graham R, Larimore E Cell. 2013; 153(1):206-15.

PMID: 23453757 PMC: 3656483. DOI: 10.1016/j.cell.2013.02.024.


A systematic model of the LC-MS proteomics pipeline.

Sun Y, Braga-Neto U, Dougherty E BMC Genomics. 2012; 13 Suppl 6:S2.

PMID: 23134670 PMC: 3481448. DOI: 10.1186/1471-2164-13-S6-S2.


Selected reaction monitoring-based proteomics: workflows, potential, pitfalls and future directions.

Picotti P, Aebersold R Nat Methods. 2012; 9(6):555-66.

PMID: 22669653 DOI: 10.1038/nmeth.2015.

References
1.
Kislinger T, Gramolini A, MacLennan D, Emili A . Multidimensional protein identification technology (MudPIT): technical overview of a profiling method optimized for the comprehensive proteomic investigation of normal and diseased heart tissue. J Am Soc Mass Spectrom. 2005; 16(8):1207-20. DOI: 10.1016/j.jasms.2005.02.015. View

2.
Anderson N, Anderson N, Pearson T, Borchers C, Paulovich A, Patterson S . A human proteome detection and quantitation project. Mol Cell Proteomics. 2009; 8(5):883-6. PMC: 2689772. DOI: 10.1074/mcp.R800015-MCP200. View

3.
Kiebel G, Auberry K, Jaitly N, Clark D, Monroe M, Peterson E . PRISM: a data management system for high-throughput proteomics. Proteomics. 2006; 6(6):1783-90. DOI: 10.1002/pmic.200500500. View

4.
Takahashi K, Yamanaka S . Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell. 2006; 126(4):663-76. DOI: 10.1016/j.cell.2006.07.024. View

5.
Lange V, Picotti P, Domon B, Aebersold R . Selected reaction monitoring for quantitative proteomics: a tutorial. Mol Syst Biol. 2008; 4:222. PMC: 2583086. DOI: 10.1038/msb.2008.61. View