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Yoshii, K.

Publications and source records attributed to Yoshii, K..

2 recordsLinked to original sources

West Nile virus capsid protein promotes viral replication and pathogenesis through PKCα-dependent lamin phosphorylation and nuclear deformation

The genus Orthoflavivirus comprises several medically important pathogens such as the West Nile virus (WNV), which causes encephalitis in humans. Although viral replication occurs in the cytoplasm, the capsid (C) protein of the orthoflavivirus is localized to both the cytoplasm and nucleus. Nuclear C protein contributes to viral replication and disease progression. However, the underlying mechanisms remain unclear. Here, we investigated whether the WNV C protein induces nuclear deformation and examined the underlying mechanism. We also assessed the contribution of this deformation to viral replication and pathogenesis. WNV infection and C protein expression induced morphological alterations in the nuclear lamina, leading to nuclear deformation. C protein expression enhanced lamin phosphorylation and the disassembly of the polymerized lamin network. In addition, C protein interacted with protein kinase C alpha (PKC) and localized PKC near the nuclear lamina. Downregulation of PKC expression inhibited C protein-induced lamin phosphorylation and nuclear deformation. In addition, both the downregulation of PKC expression and pharmacological inhibition of PKC reduced WNV replication. In contrast, the expression of phosphorylation-deficient lamin mutants attenuated the inhibitory effect of downregulated PKC expression on WNV replication. Furthermore, the pharmacological inhibition of PKC increased the survival rate of WNV-infected mice and suppressed both viral replication and nuclear deformation in the brain. Collectively, these results demonstrate that C protein remodels the nuclear lamina architecture through the PKC-lamin pathway, and that virus-induced nuclear deformation contributes to WNV replication and pathogenesis. Author summaryThe West Nile virus (WNV), a neurotropic orthoflavivirus, causes severe neurological diseases in humans. In host cells, orthoflaviviruses exclusively replicate in the cytoplasm. However, their capsid (C) proteins are localized to both the nucleus and cytoplasm. Although the nuclear C protein has been implicated in viral replication and disease progression, its underlying mechanisms remain unclear. Here, we demonstrate that the WNV C protein induces nuclear deformation, accompanied by the phosphorylation of lamin and disassembly of the nuclear lamina, a structural scaffold that maintains the nuclear shape. The C protein promotes the localization of PKC, a host kinase protein, near the nuclear lamina. Suppression of PKC expression or activity reduces lamin phosphorylation, nuclear deformation, and WNV replication. Importantly, pharmacological inhibition of PKC in WNV-infected mice reduced nuclear deformation and viral replication in the brain and improved survival rates. Collectively, our findings identify the host nucleus as an important site of WNV-host interaction and provide a new perspective that WNV, despite replicating in the cytoplasm, remodels host nuclear architecture to promote viral replication and pathogenesis.

microbiology↗

Peak identification and quantification by proteomic mass spectrogram decomposition

Recent advances in liquid chromatography/mass spectrometry (LC/MS) technology have notably improved the sensitivity, resolution, and speed of proteome analysis, resulting in increasing demand for more sophisticated algorithms to interpret complex mass spectrograms. Here, we propose a novel statistical method that we call proteomic mass spectrogram decomposition (ProtMSD) for joint identification and quantification of peptides and proteins. Given the proteomic mass spectrogram and the reference mass spectra of all possible peptide ions associated with proteins as a dictionary, our method directly estimates the temporal intensity curves of those peptide ions, i.e., the chromatograms, under a group sparsity constraint without using the conventional careful pre-processing (e.g., thresholding and peak picking). We show that the accuracy of protein identification was significantly improved by using the protein-peptide hierarchical relationships, the isotopic distribution profiles and predicted retention times of peptide ions and the pre-learned mass spectra of noise. In the analysis of E. coli cell lysate, our ProtMSD showed excellent agreement (3277 peptide ions (94.79%) and 493 proteins (98.21%)) with the conventional cascading approach to identification and quantification based on Mascot and Skyline. This is the first attempt to use a matrix decomposition technique as a tool for LC/MS-based joint proteome identification and quantification.

bioinformatics↗