Classical swine fever virus NS5A protein activates autophagy via the PP2A-DAPK3-Beclin 1 axis.

IMPORTANCE: Autophagy is a conserved degradation process that maintains cellular homeostasis and regulates native and adaptive immunity. Viruses have evolved diverse strategies to inhibit or activate autophagy for their benefit. The paper reveals that CSFV NS5A mediates the dissociation of PP2A from Beclin 1 and the association of PP2A with DAPK3 by interaction with PPP2R1A and DAPK3, PP2A dephosphorylates DAPK3 to activate its protein kinase activity, and activated DAPK3 phosphorylates Beclin 1 to trigger autophagy, indicating that NS5A activates autophagy via the PP2A-DAPK3-Beclin 1 axis. These data highlight a novel mechanism by which CSFV activates autophagy to favor its replication, thereby contributing to the development of antiviral strategies.

Classical swine fever virus NS5A protein antagonizes innate immune response by inhibiting the NF-κB signaling.

The NS5A non-structural protein of classical swine fever virus (CSFV) is a multifunctional protein involved in viral genomic replication, protein translation, assembly of infectious virus particles, and regulation of cellular signaling pathways. Previous report showed that NS5A inhibited nuclear factor kappa B (NF-κB) signaling induced by poly(I:C); however, the mechanism involved has not been elucidated. Here, we reported that NS5A directly interacted with NF-κB essential modulator (NEMO), a regulatory subunit of the IκB kinase (IKK) complex, to inhibit the NF-κB signaling pathway. Further investigations showed that the zinc finger domain of NEMO and the aa 126-250 segment of NS5A are essential for the interaction between NEMO and NS5A. Mechanistic analysis revealed that NS5A mediated the proteasomal degradation of NEMO. Ubiquitination assay showed that NS5A induced the K27-linked but not the K48-linked polyubiquitination of NEMO for proteasomal degradation. In addition, NS5A blocked the K63-linked polyubiquitination of NEMO, thus inhibiting IKK phosphorylation, IκBα degradation, and NF-κB activation. These findings revealed a novel mechanism by which CSFV inhibits host innate immunity, which might guide the drug design against CSFV in the future.

A deep learning-based drug repurposing screening and validation for anti-SARS-CoV-2 compounds by targeting the cell entry mechanism.

The recent outbreak of Corona Virus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a severe threat to the global public health and economy, however, effective drugs to treat COVID-19 are still lacking. Here, we employ a deep learning-based drug repositioning strategy to systematically screen potential anti-SARS-CoV-2 drug candidates that target the cell entry mechanism of SARS-CoV-2 virus from 2635 FDA-approved drugs and 1062 active ingredients from Traditional Chinese Medicine herbs. In silico molecular docking analysis validates the interactions between the top compounds and host receptors or viral spike proteins. Using a SARS-CoV-2 pseudovirus system, we further identify several drug candidates including Fostamatinib, Linagliptin, Lysergol and Sophoridine that can effectively block the cell entry of SARS-CoV-2 variants into human lung cells even at a nanomolar scale. These efforts not only illuminate the feasibility of applying deep learning-based drug repositioning for antiviral agents by targeting a specified mechanism, but also provide a valuable resource of promising drug candidates or lead compounds to treat COVID-19.

Synthesis of Abscisic Acid in Neopyropia yezoensis and Its Regulation of Antioxidase Genes Expressions Under Hypersaline Stress.

Abscisic acid (ABA) is regarded as crucial for plant adaptation to water-limited conditions and it functions evolutionarily conserved. Thus, insights into the synthesis of ABA and its regulation on downstream stress-responsive genes in Neopyropia yezoensis, a typical Archaeplastida distributed in intertidal zone, will improve the knowledge about how ABA signaling evolved in plants. Here, the variations in ABA contents, antioxidant enzyme activities and expression of the target genes were determined under the presence of exogenous ABA and two specific inhibitors of the ABA precursor synthesis. ABA content was down-regulated under the treatments of each or the combination of the two inhibitors. Antioxidant enzyme activities like SOD, CAT and APX were decreased slightly with inhibitors, but up-regulated when the addition of exogenous ABA. The quantitative assays using real-time PCR (qRT-PCR) results were consistent with the enzyme activities. All the results suggested that ABA can also alleviate oxidative stress in N. yezoensis as it in terrestrial plant. Combined with the transcriptome assay, it was hypothesized that ABA is synthesized in N. yezoensis via a pathway that is similar to the carotenoid pathway in higher plants, and both the MVA and that the MEP pathways for isoprenyl pyrophosphate (IPP) synthesis likely exist simultaneously. The ABA signaling pathway in N. yezoensis was also analyzed from an evolutionary standpoint and it was illustrated that the emergence of the ABA signaling pathway in this alga is an ancestral one. In addition, the presence of the ABRE motif in the promoter region of antioxidase genes suggested that the antioxidase system is regulated by the ABA signaling pathway.

An Optimal Resonant Frequency Band Feature Extraction Method Based on Empirical Wavelet Transform.

The Empirical Wavelet Transform (EWT), which has a reliable mathematical derivation process and can adaptively decompose signals, has been widely used in mechanical applications, EEG, seismic detection and other fields. However, the EWT still faces the problem of how to optimally divide the Fourier spectrum during the application process. When there is noise interference in the analyzed signal, the parameterless scale-space histogram method will divide the spectrum into a variety of narrow bands, which will weaken or even fail to extract the fault modulation information. To accurately determine the optimal resonant demodulation frequency band, this paper proposes a method for applying Adaptive Average Spectral Negentropy (AASN) to EWT analysis (AEWT): Firstly, the spectrum is segmented by the parameterless clustering scale-space histogram method to obtain the corresponding empirical mode. Then, by comprehensively considering the Average Spectral Negentropy (ASN) index and correlation coefficient index on each mode, the correlation coefficient is used to adjust the ASN value of each mode, and the IMF with the highest value is used as the center frequency band of the fault information. Finally, a new resonant frequency band is reconstructed for the envelope demodulation analysis. The experimental results of different background noise intensities show that the proposed method can effectively detect the repetitive transients in the signal.