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Protein Kinase C Signaling in Adenoviral Infection.

ABSTRACT: Activation of protein kinase C (PKC), a serine/threonine protein kinase, ubiquitously influences cellular signal transduction and has been shown to play a role in viral entry. In this study, we explored a role for PKC in human adenovirus type 37 infection of primary human corneal fibroblasts, a major target cell for infection. We sought evidence for an interaction between PKC activation and two potential downstream targets: cSrc kinase, shown previously to play a critical role in adenovirus signaling in these cells, and caveolin-1, reported earlier to be important to entry of adenovirus type 37. Infection of fibroblasts increased PKC? phosphorylation and translocation of PKC? from the cytosol to caveolin-1 containing vesicles. Virus-induced phosphorylation of both cSrc and AKT was abolished in cell lysates pretreated with calphostin C, a chemical inhibitor of PKC. Inhibition of PKC also reduced virus associated phosphorylation of caveolin-1, while inhibition of cSrc by the chemical inhibitor PP2 reduced only caveolin-1 phosphorylation, but not PKC? phosphorylation, in lipid rafts. These results suggest a role for PKC? upstream to both cSrc and caveolin-1. Phosphorylated PKC? was found in the same endosomal fractions as phosphorylated cSrc, and PKC? was present to a greater degree in caveolin-1 pull downs from virus infected than mock infected cell lysates. Calphostin C also reduced early viral gene expression, indicating that PKC? activity may be required for viral entry. PKC? plays a central role in adenovirus infection of corneal fibroblasts and regulation of downstream molecules, including the important lipid raft component caveolin-1.

SUBMITTER: Yousuf MA

PROVIDER: S-EPMC5808905 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Protein Kinase C Signaling in Adenoviral Infection.

Yousuf Mohammad A MA Lee Ji Sun JS Zhou Xiaohong X Ramke Mirja M Lee Jeong Yoon JY Chodosh James J Rajaiya Jaya J

Biochemistry 20161011 42

Activation of protein kinase C (PKC), a serine/threonine protein kinase, ubiquitously influences cellular signal transduction and has been shown to play a role in viral entry. In this study, we explored a role for PKC in human adenovirus type 37 infection of primary human corneal fibroblasts, a major target cell for infection. We sought evidence for an interaction between PKC activation and two potential downstream targets: cSrc kinase, shown previously to play a critical role in adenovirus sign ...[more]

PMID: 27700064

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Project description:Anopheline mosquitoes are the primary vectors of parasites in the genus Plasmodium, the causative agents of malaria. Malaria parasites undergo a series of complex transformations upon ingestion by the mosquito host. During this process, the physical barrier of the midgut epithelium, along with innate immune defenses, functionally restrict parasite development. Although these defenses have been studied for some time, the regulatory factors that control them are poorly understood. The protein kinase C (PKC) gene family consists of serine/threonine kinases that serve as central signaling molecules and regulators of a broad spectrum of cellular processes including epithelial barrier function and immunity. Indeed, PKCs are highly conserved, ranging from 7 isoforms in Drosophila to 16 isoforms in mammals, yet none have been identified in mosquitoes. Despite conservation of the PKC gene family and their potential as targets for transmission-blocking strategies for malaria, no direct connections between PKCs, the mosquito immune response or epithelial barrier integrity are known. Here, we identify and characterize six PKC gene family members--PKCδ, PKCε, PKCζ, PKD, PKN, and an indeterminate conventional PKC--in Anopheles gambiae and Anopheles stephensi. Sequence and phylogenetic analyses of the anopheline PKCs support most subfamily assignments. All six PKCs are expressed in the midgut epithelia of A. gambiae and A. stephensi post-blood feeding, indicating availability for signaling in a tissue that is critical for malaria parasite development. Although inhibition of PKC enzymatic activity decreased NF-κB-regulated anti-microbial peptide expression in mosquito cells in vitro, PKC inhibition had no effect on expression of a panel of immune genes in the midgut epithelium in vivo. PKC inhibition did, however, significantly increase midgut barrier integrity and decrease development of P. falciparum oocysts in A. stephensi, suggesting that PKC-dependent signaling is a negative regulator of epithelial barrier function and a potential new target for transmission-blocking strategies.

Project description:Adenoviruses (AdVs) constitute a diverse family with many pathogenic types that infect a broad range of hosts. Understanding the pathogenesis of adenoviral infections is not only clinically relevant but also important to elucidate the potential use of AdVs as vectors in therapeutic applications. For an adenoviral infection to occur, attachment of the viral ligand to a cellular receptor on the host organism is a prerequisite and, in this sense, it is a criterion to decide whether an adenoviral infection can potentially happen. The interaction between any virus and its corresponding host organism is a specific kind of protein-protein interaction (PPI) and several experimental techniques, including high-throughput methods are being used in exploring such interactions. As a result, there has been accumulating data on virus-host interactions including a significant portion reported at publicly available bioinformatics resources. There is not, however, a computational model to integrate and interpret the existing data to draw out concise decisions, such as whether an infection happens or not. In this study, accepting the cellular entry of AdV as a decisive parameter for infectivity, we have developed a machine learning, more precisely support vector machine (SVM), based methodology to predict whether adenoviral infection can take place in a given host. For this purpose, we used the sequence data of the known receptors of AdVs, we identified sets of adenoviral ligands and their respective host species, and eventually, we have constructed a comprehensive adenovirus-host interaction dataset. Then, we committed interaction predictions through publicly available virus-host PPI tools and constructed an AdV infection predictor model using SVM with RBF kernel, with the overall sensitivity, specificity, and AUC of 0.88 ± 0.011, 0.83 ± 0.064, and 0.86 ± 0.030, respectively. ML-AdVInfect is the first of its kind as an effective predictor to screen the infection capacity along with anticipating any cross-species shifts. We anticipate our approach led to ML-AdVInfect can be adapted in making predictions for other viral infections.

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Protein Kinase C Signaling in Adenoviral Infection.

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Protein Kinase C Signaling in Adenoviral Infection.

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