Virologica Sinica

The 2019-nCoV is reported to share the same entry (ACE2) as SARS-CoV according to the updated findings. Analyzing the distribution and expression level of the route of coronavirus may help reveal underlying mechanisms of viral susceptibility and post-infection modulation. In this study, we found that the expression of ACE2 in healthy populations and patients with underlying diseases was not significantly different, suggesting relatively similar susceptibility. Besides, based on the expression of ACE2 in smoking individuals, we inferred that long-term smoking might be a risk factor for 2019-nCoV. Analyzing the ACE2 in SARS-CoV infected cells suggested that ACE2 was more than just a receptor but also participated in post-infection regulation, including immune response, cytokine secretion, and viral genome replication. Moreover, we also constructed Protein-protein interaction (PPI) networks and identified hub genes in viral activity and cytokine secretion. Our findings may explain the clinical symptoms so far and help clinicians and researchers understand the pathogenesis and design therapeutic strategies for 2019-nCoV.

Clear cell renal cell carcinoma (ccRCC) accounts for the highest number of renal malignancies and 3% of all adult cancers. The incidence of ccRCC is increasing worldwide, and its prognosis is poor. Approximately 30% of the patients are diagnosed at a late stage and are frequently asymptomatic. Cuproptosis is a new type of cell death that is regulated by Cu ions. As cuproptosis is associated with cancer development, we hypothesized that changes in the expression of cuproptosis-related genes (CRGs) are associated with the prognosis of ccRCC, and that CRGs can serve as biomarkers for the diagnosis and prognosis of ccRCC. In the present study, we explored the correlation between CRGs and ccRCC prognosis by analyzing publicly available data. We analyzed the clinical information and RNA-sequencing data in The Cancer Genome Atlas using bioinformatics tools. Dihydrolipoamide S-succinyltransferase (DLST) was identified as a novel gene with predictive and diagnostic potential. CRGs were under-expressed in ccRCC samples, and downregulation of DLST was highly associated with poor prognosis. Cox univariate and multivariate regression analyses revealed that DLST could serve as an independent prognostic factor for ccRCC. Further, functional enrichment analysis indicated that low expression of DLST may affect immune function. Our results strongly indicate that DLST plays an important role in ccRCC progression and may serve as an independent diagnostic and prognostic biomarker for ccRCC. Therefore, DLST is a potential therapeutic target for patients with ccRCC.

Papillary thyroid cancer (PTC) is the most common thyroid malignancy. Although PTC usually has a favorable prognosis, some aggressive PTC subtypes and lymph node (LN) metastasis contribute to high rates of recurrence and poor clinical outcomes. We analyzed single-cell RNA sequencing (scRNA-seq) data from 15 samples, including primary tumors of PTC, metastatic LNs, and paracancerous tissues. After quality filtering, 28,205 cells were detected. Of these, 13,390 cells originated from 7 tumor tissues, 2,869 cells from 2 metastatic LNs, and 11,945 cells from 6 paracancerous tissues. The increase in the proportion of CD4+ Tregs may be a key factor responsible for the immunosuppressive property of PTC. A novel cell type was identified, named Protective EGR1+CD4+ T cell, which might be antagonistic to the CD4+ Tregs and inhibit the formation of the immunosuppressive microenvironment and tumor immune evasion. Inhibitory checkpoints TIGIT and CD96 were found to be better targets than PD-1 for immune therapy in PTC patients with LN metastasis. For PTC patients without LN metastasis, however, PD-1, TIGIT, and CD96 could be suitable targets of immunotherapy. These findings would contribute to the further understanding of molecular mechanisms resulting in occurrence and development of PTC, and provide a theoretical rationale for targeted therapy and immunotherapy.

COVID-19 is a highly contagious disease caused by a novel coronavirus SARS-CoV-2. The interaction between SARS-CoV-2 spike protein and the host cell surface receptor ACE2 is responsible for mediating SARS-CoV-2 infection. By analyzing the spike-hACE2 interacting surface, we predicted many hot spot residues that make major contributions to the binding affinity. Mutations on most of these residues are likely to be deleterious, leading to less infectious virus strains that may suffer from negative selection. Meanwhile, several residues with mostly advantageous mutations have been predicted. It is more probable that mutations on these residues increase the transmission ability of the virus by enhancing spike-hACE2 interaction. So far, only a limited number of mutations has been reported in this region. However, the list of hot spot residues with predicted downstream effects from this study can still serve as a tracking list for SARS-CoV-2 evolution studies. Coincidentally, one advantageous mutation, p.476G>S, started to surge in the last couple of weeks based on the data submitted to the public domain, indicating that virus strains with increased transmission ability may have already spread.

BackgroundThe classic infantile-onset Pompe disease (IOPD) is characterized by cardiac hypertrophy, respiratory insufficiency, and rapidly progressive muscle weakness due to the acid alpha-glucosidase (GAA) deficiency. Enzyme replacement therapy (ERT) is the current approach for IOPD, but it entails several limitations. Aiming to overcome the limited efficiency of ERT, we developed adeno-associated virus (AAV) gene therapy for IOPD patients. MethodOne IOPD patient received a single intravenous dose of GC301, a recombinant adeno-associated virus 9 (rAAV9) expressing the human GAA (rAAV-hGAA). During the follow-up, safety was accessed by the physical examinations, cardiac and laboratory evaluations. GAA activity, the titers of serum antibodies to AAV9 and GAA, and motor development were monitored regularly. ResultThe infant showed significant improvements in motor milestones. The GAA enzyme activity increased to the normal range. The cardiac function improved notably. ConclusionIn patient with IOPD, a single intravenous AAV9-hGAA gene therapy improved the clinical outcomes remarkably. The trial is still ongoing, the safety of this gene therapy and the long-term clinical benefit remain to be monitored for months and years to come.

Coronaviruses remodel intracellular membranes to form specialized viral replication compartments, such as double-membrane vesicles where viral RNA genome replication takes place. Understanding the factors affecting host response is instrumental to design of therapeutics to prevent or ameliorate the course of infection. As part of explorative tests in hospitalized patients with confirmed COVID-19 infection participating in ODYSSEY trial, we obtained samples for whole genome sequencing analysis as well as for viral genome sequencing. Based on our data, we confirm one of the strongest severity susceptibility locus thus far reported in association with severe COVID-19: 3p21.31 locus with lead variant rs73064425. We further examine the associated region. Interestingly based on LD analysis we report 3 coding mutations within one gene in the region of FYVE and Coiled-Coil Domain Autophagy Adaptor 1 (FYCO1). We specifically focus on the role of FYCO1 modifiers and gain-of-function variants. We report the associations between the region and clinical characteristics in this severe set of COVID-19 patients. We next analyzed expression profiles of FYCO1 across all 466 compounds tested. We selected only those results that showed a significant reduction of expression of FYCO1. The most significant candidate was indomethacin - an anti-inflammatory that could potentially downregulate FYCO1. We hypothesize that via its direct effects on efficiency of viral egress, it may serve as a potent therapeutic decreasing the replication and infectivity of the virus. Clinical studies will be needed to examine the therapeutic utility of indomethacin and other compounds downregulating FYCO1 in COVID-19 infection and other strains of betacoronaviruses.

This study investigated the human papillomavirus (HPV) infection status, genotype distribution, and associated risk factors among women in Suzhou to provide a theoretical basis for controlling cervical cancer and guiding vaccine development. From November 2022 to April 2023, 566 qualified participants undergoing health examinations at Suzhou Municipal Hospital were enrolled. Cervical exfoliated cells were tested for 21 HPV genotypes using fluorescence quantitative PCR, and data on general information, lifestyle, and clinical history were collected via questionnaire. The overall HPV infection rate was 11.31% (64/566). The most prevalent genotypes were HPV16, HPV52, and HPV58, each with an infection rate of 1.77%. Single infections predominated (8.83%, 50/566), with HPV16 (18%), HPV58 (14%), HPV51 (12%), and HPV81 (12%) being the most common. Multiple infections accounted for 2.47%, primarily dual infections (78.57%). Infection rates varied significantly by age, with the highest prevalence in women aged [&ge;]50 years (24.37%), followed by those aged 40-49 (8.42%) and [&le;]39 (7.35%). Significant risk factors for HPV infection included older age (OR=1.075, P<0.01), secondhand smoke exposure (OR=2.126, P<0.05), a history of underlying diseases, and a history of cervical surgery. In conclusion, the HPV infection rate in Suzhou remains considerable, with genotypes 16, 52, and 58 being predominant and single infections most common. Older age, secondhand smoke exposure, underlying diseases, and cervical surgery history are key risk factors, highlighting the need for targeted prevention and comprehensive control strategies.

Sporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened. Pathway and GO enrichment analyses of DEGs were performed. Furthermore, the protein-protein interaction (PPI) network was predicted using the IntAct Molecular Interaction Database and visualized with Cytoscape software. In addition, hub genes and important modules were selected based on the network. Finally, we constructed target genes - miRNA regulatory network and target genes - TF regulatory network. Hub genes were validated. A total of 891 DEGs 448 of these DEGs presented significant up regulated, and the remaining 443 down regulated were obtained. Pathway enrichment analysis indicated that up regulated genes were mainly linked with glutamine degradation/glutamate biosynthesis, while the down regulated genes were involved in melatonin degradation. GO enrichment analyses indicated that up regulated genes were mainly linked with chemical synaptic transmission, while the down regulated genes were involved in regulation of immune system process. hub and target genes were selected from the PPI network, modules, and target genes - miRNA regulatory network and target genes - TF regulatory network namely YWHAZ, GABARAPL1, EZR, CEBPA, HSPB8, TUBB2A and CDK14. The current study sheds light on the molecular mechanisms of sCJD and may provide molecular targets and diagnostic biomarkers for sCJD.

Chronic Hepatitis B virus (HBV) infection poses a global public health challenge, for which an effective cure remains elusive. A substantial amount of data has shown that single nucleotide polymorphisms (SNPs) within host genes can affect the regulation and expression of proteins, thereby influencing the susceptibility to HBV infection as well as disease progression and response to treatment. HBV-related SNPs have been identified in the population of Saudi Arabia, however, there is a lack of in-depth characterization of the translational and functional impact of these SNPs. This article aims to analyze the SNPs significantly associated with HBV-associated complications in the Saudi population, predict their functional impact using bioinformatic tools and propose future projections for HBV research in Saudi Arabia. The findings of these genetic studies are likely to pave the way for developing more effective preventive and therapeutic interventions by personalizing the management of HBV infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic. Understanding the influence of mutations in the SARS-CoV-2 gene on clinical outcomes and related factors is critical for treatment and prevention. Here, we analyzed 209,551 high-coverage complete virus sequences and 321 RNA-seq samples to mine the mutations associated with clinical outcome in the SARS-CoV-2 genome. Several important hotspot variants were found to be associated with severe clinical outcomes. Q57H variant in ORF3a protein were found to be associated with higher mortality rate, and was high proportion in severe cases (39.36%) and 501Y.V2 strains (100%) but poorly proportional to asymptomatic cases (10.04%). T265I could change nsp2 structure and mitochondrial permeability, and evidently higher in severe cases (20.12%) and 501Y.V2 strains (100%) but lower in asymptomatic cases (1.43%). Additionally, R203K and G204R could decrease the flexibility and immunogenic property of N protein with high frequency among severe cases, VUI 202012/01 and 484K.V2 strains. Interestingly, the SARS-CoV-2 genome was more susceptible to mutation because of the high frequency of nt14408 mutation (which located in RNA polymerase) and the high expression levels of ADAR and APOBEC in severe clinical outcomes. In conclusion, several important mutation hotspots in the SARS-CoV-2 genome associated with clinical outcomes was found in our study, and that might correlate with different SARS-CoV-2 mortality rates.

nCOVID-19 virus makes cellular entry using its spike protein protruding out on its surface. Angiotensin converting enzyme 2 receptor has been identified as a receptor that mediates the viral entry by binding with the receptor binding motif of spike protein. In the present study, we elucidate the significance of N-terminal domain of spike protein in spike-receptor interactions. Recent clinical reports indicate a link between nCOVID-19 infections with patient comorbidities. The underlying reason behind this relationship is not clear. Using molecular docking, we study the affinity of the nCOVID-19 spike protein with cell receptors overexpressed under disease conditions. Our results suggest that certain cell receptors such as DC/L-SIGN, DPP4, IL22R and ephrin receptors could act as potential receptors for the spike protein. The receptor binding domain of nCOVID-19 is more flexible than that of SARS-COV and has a high propensity to undergo phase separation. Higher flexibility of nCOVID-19 receptor binding domain might enable it to bind multiple receptor partners. Further experimental work on the association of these receptors with spike protein may help us to explain the severity of nCOVID-19 infection in patients with comorbidities.

Since the first case of Novel Coronavirus (2019-nCov) was identified in December 2019 in Wuhan City, China, the number of cases continues to grow across China and multiple cases have been exported to other countries. The cumulative number of reported deaths is at 637 as of February 7, 2020. Here we statistically estimated the time-delay adjusted death risk for Wuhan as well as for China excluding Wuhan to interpret the current severity of the epidemic in China. We found that the latest estimates of the death risk in Wuhan could be as high as 20% in the epicenter of the epidemic whereas we estimate it [~]1% in the relatively mildly-affected areas. Because the elevated death risk estimates are likely associated with a breakdown of the medical/health system, enhanced public health interventions including social distancing and movement restrictions should be effectively implemented to bring the epidemic under control.

We investigated clinical outcome of asymptomatic coronavirus disease 2019 (COVID-19) and identified risk factors associated with high patient mortality using Korean nationwide public database of 5,621 hospitalized patients. The mortality rate and admission rate to intensive care unit were compared between asymptomatic and symptomatic patients. The prediction model for patient mortality was developed through risk factor analysis among asymptomatic patients. The prevalence of asymptomatic COVID-19 infection was 25.8%. The mortality rates were not different between groups (3.3% vs. 4.5%, p=0.17). However, symptomatic patients were more likely to receive ICU care compared to asymptomatic patients (4.1% vs. 1.0%, p<0.0001). The age-adjusted Charlson comorbidity index score (CCIS) was the most potent predictor for patient mortality in asymptomatic patients. The clinicians should predict the risk of death by evaluating age and comorbidities but not the presence of symptoms. Article Summary LineSince asymptomatic patients have similar mortality rate with symptomatic patients, the clinicians should not classify clinical severity according to initial presence of symptom.

Hepatoblastoma is the childhood liver cancer. Profound efforts have been made to illuminate the pathology, but the molecular mechanisms of hepatoblastoma are still not well understood. To identify the candidate genes in the carcinogenesis and progression of hepatoblastoma, microarray dataset GSE131329 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and pathway and Gene Ontology (GO) enrichment analysis were performed. The protein-protein interaction network (PPI), module analysis, target gene - miRNA regulatory network and target gene - TF regulatory network were constructed and analyzed. A total of 996 DEGs were identified, consisting of 499 up regulated genes and 497 down regulated genes. The pathway and Gene Ontology (GO) enrichment analysis of the DEGs include proline biosynthesis, superpathway of tryptophan utilization, chromosome organization and organic acid metabolic process. Twenty-four hub genes were identified and biological process analysis revealed that these genes were mainly enriched in cell cycle, chromosome organization, lipid metabolic process and oxidation-reduction process. Validation of hub genes showed that TP53, PLK1, AURKA, CDK1, ANLN, ESR1, FGB, ACAT1, GOT1 and ALAS1 may be involved in the carcinogenesis, invasion or recurrence of hepatoblastoma. In conclusion, DEGs and hub genes identified in the present study help us understand the molecular mechanisms underlying the carcinogenesis and progression of hepatoblastoma, and provide candidate targets for diagnosis and treatment of hepatoblastoma.

The current investigation aimed to mine therapeutic molecular targets that play an key part in the advancement of pancreatic ductal adenocarcinoma (PDAC). The expression profiling by high throughput sequencing dataset profile GSE133684 dataset was downloaded from the Gene Expression Omnibus (GEO) database. Limma package of R was used to identify differentially expressed genes (DEGs). Functional enrichment analysis of DEGs were performed. Protein-protein interaction (PPI) networks of the DEGs were constructed. An integrated gene regulatory network was built including DEGs, microRNAs (miRNAs), and transcription factors. Furthermore, consistent hub genes were further validated. Molecular docking experiment was conducted. A total of 463 DEGs (232 up regulated and 231 down regulated genes) were identified between very early PDAC and normal control samples. The results of Functional enrichment analysis revealed that the DEGs were significantly enriched in vesicle organization, secretory vesicle, protein dimerization activity, lymphocyte activation, cell surface, transferase activity, transferring phosphorus-containing groups, hemostasis and adaptive immune system. The PPI network and gene regulatory network of up regulated genes and down regulated genes were established, and hub genes were identified. The expression of hub genes (CCNB1, FHL2, HLA-DPA1 and TUBB1) were also validated to be differentially expressed among PDAC and normal control samples. Molecular docking experiment predicted the novel inhibitory molecules for CCNB1 and FHL2. The identification of hub genes in PDAC enhances our understanding of the molecular mechanisms underlying the progression of this disease. These genes may be potential diagnostic biomarkers and/or therapeutic molecular targets in patients with PDAC.

Human (h) coronaviruses (CoVs) 229E, NL63, OC43, and HKU1 are less virulent and cause mild, self-limiting respiratory tract infections, while SARS-CoV, MERS-CoV, and SARS-CoV-2, are more virulent and have caused severe outbreaks. The CoV envelope (E) protein, an important contributor to the pathogenesis of severe hCoVs infections, may provide insight into this disparate severity of the disease. Topology prediction programs and 3D modelling software was used to predict and visualize structural aspects of the hCoV E protein related to its functions. All seven hCoV E proteins largely adopted different topologies, with some distinction between the more virulent and less virulent ones. The 3D models refined this distinction, showing the PDZ-binding motif (PBM) of SARS-CoV, MERS-CoV, and SARS-CoV-2 to be more flexible than the PBM of hCoVs 229E, NL63, OC43, and HKU1. We speculate that the increased flexibility of the PBM may provide the more virulent hCoVs with a greater degree of freedom, which can allow them to bind to different host proteins and can contribute to a more severe form of the disease. This is the first paper to predict the topologies and model 3D structures of all seven hCoVs E proteins, providing novel insights for possible drug and/or vaccine development.

African swine fever virus (ASFV) is a large and complex double-stranded DNA virus that poses serious threats to the pig industry. It is well-accepted that the multigene family (MGF) proteins are extensively distributed in ASFVs and are generally classified into five families, including MGF-100, MGF-110, MGF-300, MGF-360 and MGF-505. Most MGF proteins, however, have not been well characterized and classified within each family. To bridge this gap, this study first classified the MGF proteins into 35 groups based on protein sequence homology. A web server for classifying the MGF proteins was then established and available for free at http://www.computationalbiology.cn/MGF/home.html. Results showed that the genetic diversity of the MGF groups varied widely, mainly due to the occurrence of indels. In addition, the MGF proteins were predicted to have large structural and functional diversity, and the MGF proteins of the same MGF family tended to have similar structure, location and function. Evolutionary analysis revealed the dynamic changes of the MGF proteins in the ASFV genomes, and more than half of MGF groups were presented in all ASFV genomes, which indicated the important role of MGF proteins in ASFVs. Overall, it is expected that the work would not only provide a detailed classification for MGF proteins, but also facilitate further research on MGF proteins.

An outbreak of new SARS-like viral in Wuhan, China has been named 2019-nCoV. The current state of the epidemic is increasingly serious, and there has been the urgent necessity to develop an effective new drug. In previous studies, it was found that the conformation change in CTD1 was the region where SARS-CoV bound to human ACE2. Although there are mutations of the 2019-nCoV, the binding energy of ACE2 remains high. The surface glycoprotein of 2019-nCoV was coincident with the CTD1 region of the S-protein by comparing the I-TASSER prediction model with the actual SARS model, which suggests that 2019-nCoV may bind to the ACE2 receptor through conformational changes. Furthermore, site prediction on the surface glycoprotein of 2019-nCoV suggests some core amino acid area may be a novel drug target against 2019-nCoV.

Coronavirus disease 2019 (COVID-19) is a new emerging human infectious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2, also previously known as 2019-nCoV), originated in Wuhan seafood and animal market, China. Since December 2019, more than 69,000 cases of COVID-19 have been confirmed in China and quickly spreads to other counties. Currently, researchers put their best efforts to identify effective drugs for COVID-19. The neutralizing antibody, which binds to viral capsid in a manner that inhibits cellular entry of virus and uncoating of the genome, is the specific defense against viral invaders. In this study, we investigate to identify neutralizing antibodies that can bind to SARS-CoV-2 Sipke (S) protein and interfere with the interaction between viral S protein and a host receptor by bioinformatic methods. The sequence analysis of S protein showed two major differences in the RBD region of the SARS-CoV-2 S protein compared to SARS-CoV and SARS-CoV related bat viruses (btSARS-CoV). The insertion regions were close to interacting residues with the human ACE2 receptor. Epitope analysis of neutralizing antibodies revealed that SARS-CoV neutralizing antibodies used conformational epitopes, whereas MERS-CoV neutralizing antibodies used a common linear epitope region, which contributes to form the {beta}-sheet structure in MERS-CoV S protein and deleted in SARS-CoV-2 S protein. To identify effective neutralizing antibodies for SARS-CoV-2, the binding affinities of neutralizing antibodies with SARS-CoV-2 S protein were predicted and compared by antibody-antigen docking simulation. The result showed that CR3022 neutralizing antibody from human may have higher binding affinity with SARS-CoV-2 S protein than SARS-CoV S protein. We also found that F26G19 and D12 mouse antibodies could bind to SARS-CoV S protein with high affinity. Our findings provide crucial clues towards the development of antigen diagnosis, therapeutic antibody, and the vaccine against SARS-CoV-2.

Leucine rich repeat and fibronectin type III domain containing 4(LRFN4) has been reported to be upregulated in multiple tumors and related to prognosis and survival of patients. However, the function of LRFN4 in LUAD is still unclear. Herein, bioinformatic approach was used for the first time to elucidate the relationship between LRFN4 and LUAD. In LUAD tissues, we discovered that LRFN4 mRNA expression was considerably higher. Higher LRFN4 expression was associated with poorer prognosis and higher clinical stage of LUAD patients. Paraffin pathology sections (12 samples including LUAD tissues and paired normal tissues from the Second Affiliated Hospital of Chongqing Medical University) were used to verify the expression of LRFN4 at the protein level by immunohistochemical staining. On the other hand, we identified that LRFN4 expression was related to multiple immune cells that constitute tumor immune microenvironment. Pathway enrichment analysis also suggested the enrichment of several tumor- and immune-related pathways, such as: Hippo pathway, NOD-like pathway, TNF pathway and P53 pathway. Finally, we constructed an 8-gene prognostic risk signature based on 35 LRFN4-related immunomodulators using the Cox regression model, and obtained reasonably good accuracy through Receiver Operating Characteristic curve (ROC curve) validation. The risk signature was further identified as an independent risk factor - was linked with worse survival of LUAD patients. Furthermore, a prognostic risk profile based on LRFN4-related immunomodulators was constructed. Meanwhile, other clinical features were integrated together as prognostic markers to construct a nomogram to predict the long-term survival probability of LUAD patients, and fairly high credibility was obtained by validation of calibration curves.