Subcellular Quantitative Proteomics Reveals Multiple Pathway Cross-Talk That Coordinates Specific Signaling and Transcriptional Regulation for the Early Host Response to LPS

Abstract

Toll-like receptor 4 (TLR4) specifically recognizes lipopolysaccharide (LPS) to initiate signal transduction events that modulate host inflammatory responses. Although increasing numbers of genes have been characterized individually for their involvement in TLR4 signaling, the LPS-induced TLR4-mediated signaling pathway and connected networks are incompletely delineated. Given that most components of signaling pathways are activated at an early phase of the LPS-induced response, we have employed a subcellular, SILAC-based quantitative proteomics approach to identify proteins in LPS-stimulated macrophages showing either cytosolic- or nuclear-specific changes in abundance. Subcellular fractionation not only reduces the spectral complexity for identifying maximum numbers of proteins but also enriches for low-abundance proteins within the compartment in which they function. Following 10 min LPS stimulation, the abundances of 508 proteins were found elevated in the cytosol, while the elevated levels of 678 proteins together with the decreased abundances of another 80 proteins were quantified in nuclei. Coincident with observations that many key proteins involved in signal relays in the MAPK and NF-kappaB cascades were found simultaneously regulated in the cytosol, various transcriptional factors (TFs) such as IRFs were found activated in the nuclei. We also extended links between these intracellular pathways and various biological processes by identifying multiple pathway modules. For the first time, our combined data sets from quantitative proteomics and bioinformatics analyses provide a direct, system-wide insight into how cross-talk between upstream signaling pathways modulates the activities of particular TFs for regulating sets of pro-inflammatory genes.

Phosphoproteome Profiling of the Macrophage Response to Different Toll-Like Receptor Ligands Identifies Differences in Global Phosphorylation Dynamics

“…13 One study investigated changes in the kinase profile when macrophages were infected with Staphylococcus aureus , 14 while another compared the changes in protein expression with mRNA regulation in response to LPS, with the data indicating crosstalk between multiple pathways. 15 Although comparative transcriptome studies of the different TLR pathways have been published, 16−18 there are very few phosphoproteomic studies targeted toward any of the other TLRs 19 and there have been no studies that compared the global phosphoprotein signatures of different TLRs. As bacterial and other microbial pathogens generally trigger a combination of TLRs, 5,20 deciphering the comprehensive signaling pathways of multiple TLRs is a critical step toward characterizing the response of a macrophage to the complex stimuli originating from pathogens during infection.…”

Rapid Temporal Dynamics of Transcription, Protein Synthesis, and Secretion during Macrophage Activation

“…In the most comprehensive proteome-wide quantitative study using SILAC and subcellular fractionation, Du et al revealed signaling and regulatory networks that systematically operate in the early response to LPS (19). Weintz et al and Sharma et al performed quantitative phosphoproteome analyses upon LPS treatment, identifying a highly dynamic phosphorylation pattern in established signaling routes and beyond that could be linked to kinases operating in canonical TLR pathways, but also in the cell cycle (ATM/ATR kinases) and cell growth (mTOR) (13,14).…”

Glutaredoxin Desensitizes Lens to Oxidative Stress by Connecting and Integrating Specific Signaling and Transcriptional Regulation for Antioxidant Response

“…The resulting fractions were then separated via SDS-PAGE, and gel slices were subjected to tryptic digestion and peptide extraction, followed by a LC-MS/MS analysis performed in two replicates ( Fig and 2B). Based on previous criteria and the quality of MS data with a higher signal-to-noise ratio, a threshold of a 20% change in protein abundance [33,34] (a light-to-heavy ratio of >1.2 or <0.8) was used to define whether a protein was differentially expressed. A total of 1,291 DEPs were identified with high confidence based on this threshold.…”