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Nuclear factor-κB (NF-κB) is an important transcription factor that induces the expression of antiviral genes and viral genes. NF-κB activation needs the activation of NF-κB upstream molecules, which include receptors, adaptor proteins, NF-κB (IκB) kinases (IKKs), IκBα, and NF-κB dimer p50/p65. To survive, viruses have evolved the capacity to utilize various strategies that inhibit NF-κB activity, including targeting receptors, adaptor proteins, IKKs, IκBα, and p50/p65. To inhibit NF-κB activation, viruses encode several specific NF-κB inhibitors, including NS3/4, 3C and 3C-like proteases, viral deubiquitinating enzymes (DUBs), phosphodegron-like (PDL) motifs, viral protein phosphatase (PPase)-binding proteins, and small hydrophobic (SH) proteins. Finally, we briefly describe the immune evasion mechanism of human immunodeficiency virus 1 (HIV-1) by inhibiting NF-κB activity in productive and latent infections. This paper reviews a viral mechanism of immune evasion that involves the suppression of NF-κB activation to provide new insights into and references for the control and prevention of viral diseases.

Currently, five types of duck hepatitis viruses have been documented, and they are all associated with liver disorders. However, the prevalence of their coinfections involving these viruses remains largely uncertain. Herein, we screened the prevalence of the five types of hepatitis viruses from A to E in 143 samples of diseased duck livers during 2019–2021 in Southwest China. We found the highest infection ratio (86.01%, 123/143) of duck hepatitis B virus (DHBV) among all five types of hepatitis viruses. Importantly, a large portion of DHBV-associated coinfections were identified, with 52.85% (65/123) co-infected with Duck Hepatitis A virus (DHAV), 39.84% (49/123) with tentative Duck Hepatitis D virus (DHDV), and 34.96% (43/123) with Duck Hepatitis E virus (DHEV), respectively. Interestingly, a positive correlation between the DHBV-positive rate and the infection rates of the other co-infected hepatitis viruses was revealed, suggesting the importance of DHBV in duck hepatitis virus co-infection events. To understand the situation of bacterial secondary infection, the prevalence of bacterial infection was simultaneously screened using standard 16S rRNA PCR, and hepatitis virus-associated bacterial infections were observed. Collectively, these findings revealed a high prevalence of DHBV-related coinfections and its association with the coinfection of the other duck hepatitis viruses and bacteria. In the future, it is important to study the impact of DHBV co-infection events on disease severity, thereby evaluating the necessity of vaccine development for DHBV.

Background eIF2α is a regulatory node that controls protein synthesis initiation by its phosphorylation or dephosphorylation. General control nonderepressible-2 (GCN2), protein kinase R-like endoplasmic reticulum kinase (PERK), double-stranded RNA (dsRNA)-dependent protein kinase (PKR) and heme-regulated inhibitor (HRI) are four kinases that regulate eIF2α phosphorylation. Main body In the viral infection process, dsRNA or viral proteins produced by viral proliferation activate different eIF2α kinases, resulting in eIF2α phosphorylation, which hinders ternary tRNA Met -GTP-eIF2 complex formation and inhibits host or viral protein synthesis. The stalled messenger ribonucleoprotein (mRNP) complex aggregates under viral infection stress to form stress granules (SGs), which encapsulate viral RNA and transcription- and translation-related proteins, thereby limiting virus proliferation. However, many viruses have evolved a corresponding escape mechanism to synthesize their own proteins in the event of host protein synthesis shutdown and SG formation caused by eIF2α phosphorylation, and viruses can block the cell replication cycle through the PERK-eIF2α pathway, providing a favorable environment for their own replication. Subsequently, viruses can induce host cell autophagy or apoptosis through the eIF2α-ATF4-CHOP pathway. Conclusions This review summarizes the role of eIF2α in viral infection to provide a reference for studying the interactions between viruses and hosts.

DHAV-1 is a highly infectious pathogen that can cause acute hepatitis in ducklings. MicroRNA (miRNA) plays an essential regulatory role in virus response. We characterized and compared miRNA and mRNA expression profiles in duck embryonic fibroblasts (DEF) and the liver of ducklings infected with DHAV-1. DHAV-1 infected DEF was divided into infection group (D group) and blank group (M group), and DHAV-1 infected duckling group was divided into infection group (H group) and blank group (N group). D vs. M have 130 differentially expressed (DE) miRNA (DEM) and 2204 differentially expressed (DE) mRNA (DEG), H vs. N have 72 DEM and 1976 DEG. By the intersection of D vs. M and H vs. N comparisons, 15 upregulated DEM, 5 downregulated DEM, 340 upregulated DEG and 50 downregulated DEG were found with both in vivo and in vitro DHAV-1 infection. In particular, we identified the same DE miRNA target genes and functional annotations of DE mRNA. We enriched with multiple gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, which may have important roles in viral virulence, host immunity, and metabolism. We selected miR-155, which is co-upregulated, and found that miR-155 targets SOCS1 to inhibit DHVA-1 replication.

The receptor-targeting mechanisms by which λ-like siphophages establish infection in gram-negative bacteria remain poorly characterized. This study demonstrated that the λ-like phage Gifsy-1, which exhibits broad lytic activity in Salmonella enterica , employs two receptor-targeting mechanisms mediated by the side tail fiber Stf and central tail tip J dependent on O-polysaccharide (OPS) production. In rough (OPS-deficient LPS) Salmonella Typhimurium strains, Gifsy-1 employs multiple receptor-targeting: the J protein binds OmpC, OmpX, and BtuB, while the Stf protein targets galactose II (Gal II) of the lipopolysaccharide (LPS) core oligosaccharide. OmpC uniquely serves dual roles as the primary receptor (mediating initial adsorption) and secondary receptor (facilitating DNA ejection), whereas the other three receptors function exclusively as primary receptors to prompt high-efficiency phage adsorption. In contrast, the surface OPS in smooth Salmonella Typhimurium blocks J protein interactions with membrane proteins. Instead, Gifsy-1 utilizes core oligosaccharide Gal II, located between the OPS layer and outer membrane, as its necessary receptor for both adsorption and DNA ejection. This study intriguingly identified a shift in the receptor role of the core oligosaccharide in Gifsy-1 infection, which confers Gifsy-1 adaptation to OPS switching. The adaptability of the two targeting-mechanisms contributes to the understanding of the biological functions of Gifsy-1 and provides a blueprint for engineering phage therapy against multidrug-resistant Salmonella enterica .

Duck hepatitis A virus type 1 (DHAV-1) is one of the most harmful pathogens in the duck industry. The infection of adult ducks with DHAV-1 was previously shown to result in transient cytokine storms in their kidneys. To understand how DHAV-1 infection impacts the host liver, we conducted animal experiments with the virulent CH DHAV-1 strain and the attenuated CH60 commercial vaccine strain. Visual observation and standard hematoxylin and eosin staining were performed to detect pathological damage in the liver, and viral copy numbers and cytokine expression in the liver were evaluated by quantitative PCR. The CH strain (10 8.4 copies/mg) had higher viral titers than the CH60 strain (10 4.9 copies/mg) in the liver and caused ecchymotic hemorrhaging on the liver surface. Additionally, livers from ducklings inoculated with the CH strain were significantly infiltrated by numerous red blood cells, accompanied by severe cytokine storms, but similar signs were not observed in the livers of ducklings inoculated with the CH60 strain. In conclusion, the severe cytokine storm caused by the CH strain apparently induces hemorrhagic lesions in the liver, which might be a key factor in the rapid death of ducklings.

Background The disease caused by Riemerella anatipestifer ( R. anatipestifer , RA) results in large economic losses to the global duck industry every year. Serovar-related genomic variation, such as the O-antigen and capsular polysaccharide (CPS) gene clusters, has been widely used for serotyping in many gram-negative bacteria. RA has been classified into at least 21 serovars based on slide agglutination, but the molecular basis of serotyping is unknown. In this study, we performed a pan-genome-wide association study (Pan-GWAS) to identify the genetic loci associated with RA serovars. Results The results revealed a significant association between the putative CPS synthesis gene locus and the serological phenotype. Further characterization of the CPS gene clusters in 11 representative serovar strains indicated that they were highly diverse and serovar-specific. The CPS gene cluster contained the key genes wzx and wzy , which are involved in the Wzx/Wzy-dependent pathway of CPS synthesis. Similar CPS loci have been found in some other species within the family Weeksellaceae . We have also shown that deletion of the wzy gene in RA results in capsular defects and cross-agglutination. Conclusions This study indicates that the CPS synthesis gene cluster of R. anatipestifer is a serotype-specific genetic locus. Importantly, our finding provides a new perspective for the systematic analysis of the genetic basis of the R anatipestifer serovars and a potential target for establishing a complete molecular serotyping scheme.

Riemerella anatipestifer (R. anatipestifer) is one of the most important pathogens in ducks. The bacteria causes acute or chronic septicemia characterized by fibrinous pericarditis and meningitis. The R. anatipestifer genome encodes multiple iron/hemin-uptake systems that facilitate adaptation to iron-limited host environments. These systems include several TonB-dependent transporters and three TonB proteins responsible for energy transduction. These three tonB genes are present in all the R. anatipestifer genomes sequenced so far. Two of these genes are contained within the exbB-exbD-tonB1 and exbB-exbD-exbD-tonB2 operons. The third, tonB3, forms a monocistronic transcription unit. The inability to recover derivatives deleted for this gene suggests its product is essential for R. anatipestifer growth. Here, we show that deletion of tonB1 had no effect on hemin uptake of R. anatipestifer, though disruption of tonB2 strongly decreases hemin uptake, and disruption of both tonB1 and tonB2 abolishes the transport of exogenously added hemin. The ability of R. anatipestifer to grow on iron-depleted medium is decreased by tonB2 but not tonB1 disruption. When expressed in an E. coli model strain, the TonB1 complex, TonB2 complex, and TonB3 protein from R. anatipestifer cannot energize heterologous hemin transporters. Further, only the TonB1 complex can energize a R. anatipestifer hemin transporter when co-expressed in an E. coli model strain.

Riemerella anatipestifer is a major pathogenic microorganism in poultry causing serositis with significant mortality. Serotype 1 and 2 were most pathogenic, prevalent, and liable over the world. In this study, the intracellular metabolites in R. anatipestifer strains RA-CH-1 (serotype 1) and RA-CH-2 (serotype 2) were identified by gas chromatography-mass spectrometer (GC–MS). The metabolic profiles were performed using hierarchical clustering and partial least squares discriminant analysis (PLS-DA). The results of hierarchical cluster analysis showed that the amounts of the detected metabolites were more abundant in RA-CH-2. RA-CH-1 and RA-CH-2 were separated by the PLS-DA model. 24 potential biomarkers participated in nine metabolisms were contributed predominantly to the separation. Based on the complete genome sequence database and metabolite data, the first large-scale metabolic models of i JL463 (RA-CH-1) and i DZ470 (RA-CH-2) were reconstructed. In addition, we explained the change of purine metabolism combined with the transcriptome and metabolomics data. The study showed that it is possible to detect and differentiate between these two organisms based on their intracellular metabolites using GC–MS. The present research fills a gap in the metabolomics characteristics of R. anatipestifer .