A methodology for comprehensive analysis of toll-like receptor signaling in macrophages

3Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.
Get full text

Abstract

A combination of high-throughput, multiplexed, quantitative methods with computational modeling and statistical approaches is required to obtain system-level understanding of biological function. Mass spectrometry (MS)-based proteomics has emerged as a preferred tool for the analysis of changes in protein abundance and their post-translational modification (PTM) levels at a global scale, comparable with genomic experiments and generating data suitable for use in mathematical modeling of signaling pathways. Here we describe a set of parallel bottom-up proteomic approaches to detect and quantify the global protein changes in total intracellular proteins, their phosphorylation, and the proteins released by active and passive secretion or shedding mechanisms (referred to as the secretome as reviewed in Makridakis and Vlahou, J Proteome 73:2291–2305, 2010) in response to the stimulation of Toll-like receptors (TLRs) with specific ligands in cultured macrophages. The method includes protocols for metabolic labeling of cells (SILAC: stable isotope labeling by amino acids in cell culture; Ong et al., Mol Cell Proteomics 1:376–386, 2002), ligand stimulation, cell lysis and media collection, in-gel and in-solution modification and digestion of proteins, phosphopeptide enrichment for phosphoproteomics, and LC-MS/MS analysis. With these methods, we can not only reliably quantify the relative changes in the TLR signaling components (Sjoelund et al., J Proteome Res 13:5185–5197, 2014) but also use the data as constraints for mathematical modeling.

Cite

CITATION STYLE

APA

Koppenol-Raab, M., & Nita-Lazar, A. (2017). A methodology for comprehensive analysis of toll-like receptor signaling in macrophages. In Methods in Molecular Biology (Vol. 1636, pp. 301–312). Humana Press Inc. https://doi.org/10.1007/978-1-4939-7154-1_19

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free