Lipopolysaccharide activation of the TPL-2/MEK/extracellular signal-regulated kinase mitogen-activated protein kinase cascade is regulated by IkappaB kinase-induced proteolysis of NF-kappaB1 p105.

National Institute for Medical Research, Division of Immune Cell Biology, The Ridgeway, Mill Hill, London NW7 1AA, United Kingdom.
Molecular and Cellular Biology (Impact Factor: 5.04). 12/2004; 24(21):9658-67. DOI: 10.1128/MCB.24.21.9658-9667.2004
Source: PubMed

ABSTRACT The MEK kinase TPL-2 (also known as Cot) is required for lipopolysaccharide (LPS) activation of the extracellular signal-regulated kinase (ERK) mitogen-activated protein (MAP) kinase cascade in macrophages and consequent upregulation of genes involved in innate immune responses. In resting cells, TPL-2 forms a stoichiometric complex with NF-kappaB1 p105, which negatively regulates its MEK kinase activity. Here, it is shown that lipopolysaccharide (LPS) stimulation of primary macrophages causes the release of both long and short forms of TPL-2 from p105 and that TPL-2 MEK kinase activity is restricted to this p105-free pool. Activation of TPL-2, MEK, and ERK by LPS is also demonstrated to require proteasome-mediated proteolysis. p105 is known to be proteolysed by the proteasome following stimulus-induced phosphorylation of two serines in its PEST region by the IkappaB kinase (IKK) complex. Expression of a p105 point mutant, which is not susceptible to signal-induced proteolysis, in RAW264.7 macrophages impairs LPS-induced release of TPL-2 from p105 and its subsequent activation of MEK. Furthermore, expression of wild-type but not mutant p105 reconstitutes LPS stimulation of MEK and ERK phosphorylation in primary NF-kappaB1-deficient macrophages. Consistently, pharmacological blockade of IKK inhibits LPS-induced release of TPL-2 from p105 and TPL-2 activation. These data show that IKK-induced p105 proteolysis is essential for LPS activation of TPL-2, thus revealing a novel function of IKK in the regulation of the ERK MAP kinase cascade.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Background Moonlighting proteins perform two or more cellular functions, which are selected based on various contexts including the cell type they are expressed, their oligomerization status, and the binding of different ligands at different sites. To understand overall landscape of their functional diversity, it is important to establish methods that can identify moonlighting proteins in a systematic fashion. Here, we have developed a computational framework to find moonlighting proteins on a genome scale and identified multiple proteomic characteristics of these proteins.ResultsFirst, we analyzed Gene Ontology (GO) annotations of known moonlighting proteins. We found that the GO annotations of moonlighting proteins can be clustered into multiple groups reflecting their diverse functions. Then, by considering the observed GO term separations, we identified 33 novel moonlighting proteins in Escherichia coli and confirmed them by literature review. Next, we analyzed moonlighting proteins in terms of protein-protein interaction, gene expression, phylogenetic profile, and genetic interaction networks. We found that moonlighting proteins physically interact with a higher number of distinct functional classes of proteins than non-moonlighting ones and also found that most of the physically interacting partners of moonlighting proteins share the latter¿s primary functions. Interestingly, we also found that moonlighting proteins tend to interact with other moonlighting proteins. In terms of gene expression and phylogenetically related proteins, a weak trend was observed that moonlighting proteins interact with more functionally diverse proteins. Structural characteristics of moonlighting proteins, i.e. intrinsic disordered regions and ligand binding sites were also investigated.Conclusion Additional functions of moonlighting proteins are difficult to identify by experiments and these proteins also pose a significant challenge for computational function annotation. Our method enables identification of novel moonlighting proteins from current functional annotations in public databases. Moreover, we showed that potential moonlighting proteins without sufficient functional annotations can be identified by analyzing available omics-scale data. Our findings open up new possibilities for investigating the multi-functional nature of proteins at the systems level and for exploring the complex functional interplay of proteins in a cell.ReviewersThis article was reviewed by Michael Galperin, Eugine Koonin, and Nick Grishin.
    Biology Direct 12/2014; 9(1):30. DOI:10.1186/PREACCEPT-2051526116138415 · 4.04 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Cyclic AMP is an important intracellular regulator of microglial cell homeostasis and its negative perturbation through proinflammatory signaling results in microglial cell activation. Though cytokines, TNF-α and IL-1β, decrease intracellular cyclic AMP, the mechanism by which this occurs is poorly understood. The current study examined which signaling pathways are responsible for decreasing cyclic AMP in microglia following TNF-α stimulation and sought to identify the role cyclic AMP plays in regulating these pathways. In EOC2 microglia, TNF-α produced a dramatic reduction in cyclic AMP and increased cyclic AMP-dependent PDE activity that could be antagonized by Rolipram, myristoylated-PKI, PD98059, or JSH-23, implicating a role for PDE4, PKA, MEK, and NF-κB in this regulation. Following TNF-α there were significant increases in iNOS and COX-2 immunoreactivity, phosphorylated ERK1/2 and NF-κB-p65, IκB degradation, and NF-κB p65 nuclear translocation, which were reduced in the presence of high levels of cyclic AMP, indicating that reductions in cyclic AMP during cytokine stimulation are important for removing its inhibitory action on NF-κB activation and subsequent proinflammatory gene expression. Further elucidation of the signaling crosstalk involved in decreasing cyclic AMP in response to inflammatory signals may provide novel therapeutic targets for modulating microglial cell activation during neurological injury and disease.
    BioMed Research International 01/2015; 2015:308461. DOI:10.1155/2015/308461 · 2.71 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Ubiquitylation is a widespread post-translational global regulatory system that is essential for the proper functioning of various cellular events. Recent studies have shown that certain types of Escherichia coli can exploit specific aspects of the ubiquitylation system to influence downstream targets. Despite these findings, examination of the effects pathogenic E. coli have on the overall host ubiquitylation system remain unexplored. To study the impact that pathogenic E. coli have on the ubiquitylation levels of host proteins during infections, we analyzed the entire ubiquitylation system during enteropathogenic E. coli infections of cultured cells. We found that these microbes caused a dramatic decrease in ubiquitylated host proteins during these infections. This occurred with a concomitant reduction in the expression of essential E1 activating enzymes in the host, which are integral for the initiation of the ubiquitylation cascade. Control of host E1 enzyme levels was dependent on the E. coli adherence factor plasmid which acted on host aspartyl proteases within enteropathogenic E. coli. Hijacking of the ubiquitylation system did not require the plasmid-encoded regulator or bundle forming pilus expression, as enteropathogenic E. coli mutated in those factors did not revert the ubiquitylation of host proteins or the abundance of E1 enzyme proteins to uninfected levels. Our work shows that E. coli have developed strategies to usurp post-translational systems by targeting crucial enzymes. The ability of enteropathogenic E. coli to inactivate host protein ubiquitylation could enable more efficient effector protein functionality, providing increased bacterial control of host cells during enteropathogenic E. coli pathogenesis.
    The International Journal of Biochemistry & Cell Biology 12/2012; 44(12):2223-2232. DOI:10.1016/j.biocel.2012.09.005 · 4.24 Impact Factor


1 Download
Available from