SummaryThe genomic RNA of hepatitis C virus (HCV) encodes the viral polyprotein precursor that undergoes proteolytic cleavage into structural and nonstructural proteins by cellular and the viral NS3 and NS2-3 proteases. Nonstructural protein 4A (NS4A) is a cofactor of the NS3 serine protease and has been demonstrated to inhibit protein synthesis. In this study, GST pull-down assay was performed to examine potential cellular factors that interact with the NS4A protein and are involved in the pathogenesis of HCV. A trypsin digestion followed by LC-MS/MS analysis revealed that one of the GST-NS4A-interacting proteins to be eukaryotic elongation factor 1A (eEF1A). Both the N-terminal domain of NS4A from amino acid residues 1-20, and the central domain from residues 21-34 interacted with eEF1A, but the central domain was the key player involved in the NS4A-mediated translation inhibition. NS4A(21-34) diminished both cap-dependent and HCV IRES-mediated translation in a dose-dependent manner. The translation inhibitory effect of NS4A(21-34) was relieved by the addition of purified recombinant eEF1A in an in vitro translation system. Taken together, NS4A inhibits host and viral translation through interacting with eEF1A, implying a possible mechanism by which NS4A is involved in the pathogenesis and chronic infection of HCV.

The Allium genus is cultivated globally as vegetables, condiments, or medicinal plants and is characterized by large genomes and strong pungency. However, the genome evolution and genomic basis underlying their unique flavor formation remain poorly understood. Herein, we report an 11.27-Gb chromosome-scale genome assembly for bunching onion (A. fistulosum). The uneven bursts of long-terminal repeats contribute to diversity in genome constituents, and dispersed duplication events largely account for gene expansion in Allium genomes. The extensive duplication and differentiation of alliinase and lachrymatory factor synthase manifest as important evolutionary events during flavor formation in Allium crops. Furthermore, differential selective preference for flavor-related genes likely lead to the variations in isoalliin content in bunching onions. Moreover, we reveal that China is the origin and domestication center for bunching onions. Our findings provide insights into Allium genome evolution, flavor formation and domestication history and enable future genome-assisted breeding of important traits in these crops.

Chronic hepatitis B (CHB) is a major global health issue. The role of rare genetic variants in CHB has not been elucidated. We aimed to identify rare allelic variants predisposing to CHB. We performed exome sequencing in 50 CHB patients who had no identifiable risk factors for CHB and 40 controls who were healthy and hepatitis B surface antibody-positive, but had never received hepatitis B vaccination. We selected six rare variant alleles and followed up their association with disease status by Sanger sequencing in a case-control study comprising 1,728 CHB patients and 1,636 healthy controls. The latter had either not been immunized with hepatitis B vaccine or had uncertain vaccination status. Our results showed that transmembrane protein 2 p.Ser1254Asn, interferon alpha 2 p.Ala120Thr, its regulator NLR family member X1 p.Arg707Cys, and complement component 2 p.Glu318Asp were associated with CHB, with P values of <1.0 3 10 27 , 2.76 3 10 25 , 5.08 3 10 25 , 2.78 3 10 24 and odds ratios (ORs) of 2.45, 4.08, 2.34, and 1.97, respectively. The combined P value was <2.0 3 10 216 . As there has been no indication of immunological functions for the associated gene, transmembrane protein 2, we further studied its expression by immunohistochemistry, real-time polymerase chain reaction, and western blotting. Our results showed that it was strongly expressed by healthy hepatocytes, but its expression was reduced in liver tissues with CHB, hepatitis B viral (HBV) genomecontaining HepG2.2.15 cells, as compared with healthy liver tissues and non-HBV genome-containing HepG2 cells (P 5 0.022 and 0.0036, respectively). Conclusion: We identified four missense mutations associated with CHB, our results providing evidence for rare inborn genetic defects that contribute to increased host susceptibility to

Background To illustrate the molecular mechanism of mycoheterotrophic interactions between orchids and fungi, we assembled chromosome-level reference genome of Gastrodia menghaiensis (Orchidaceae) and analyzed the genomes of two species of Gastrodia. Results Our analyses indicated that the genomes of Gastrodia are globally diminished in comparison to autotrophic orchids, even compared to Cuscuta (a plant parasite). Genes involved in arbuscular mycorrhizae colonization were found in genomes of Gastrodia, and many of the genes involved biological interaction between Gatrodia and symbiotic microbionts are more numerous than in photosynthetic orchids. The highly expressed genes for fatty acid and ammonium root transporters suggest that fungi receive material from orchids, although most raw materials flow from the fungi. Many nuclear genes (e.g. biosynthesis of aromatic amino acid L-tryptophan) supporting plastid functions are expanded compared to photosynthetic orchids, an indication of the importance of plastids even in totally mycoheterotrophic species. Conclusion Gastrodia menghaiensis has the smallest proteome thus far among angiosperms. Many of the genes involved biological interaction between Gatrodia and symbiotic microbionts are more numerous than in photosynthetic orchids.

Most life activities in organisms are regulated through protein complexes, which are mainly controlled via Protein–Protein Interactions (PPIs). Discovering new interactions between proteins and revealing their biological functions are of great significance for understanding the molecular mechanisms of biological processes and identifying the potential targets in drug discovery. Current experimental methods only capture stable protein interactions, which lead to limited coverage. In addition, expensive cost and time consuming are also the obvious shortcomings. In recent years, various computational methods have been successfully developed for predicting PPIs based only on protein homology, primary sequences of protein or gene ontology information. Computational efficiency and data complexity are still the main bottlenecks for the algorithm generalization. In this study, we proposed a novel computational framework, HNSPPI, to predict PPIs. As a hybrid supervised learning model, HNSPPI comprehensively characterizes the intrinsic relationship between two proteins by integrating amino acid sequence information and connection properties of PPI network. The experimental results show that HNSPPI works very well on six benchmark datasets. Moreover, the comparison analysis proved that our model significantly outperforms other five existing algorithms. Finally, we used the HNSPPI model to explore the SARS-CoV-2-Human interaction system and found several potential regulations. In summary, HNSPPI is a promising model for predicting new protein interactions from known PPI data.