Continual Antigenic Diversification in China Leads to Global Antigenic Complexity of Avian Influenza H5N1 Viruses

Surveillance of avian influenza viruses in live bird markets of Shandong province from 2013 to 2019

Avian influenza viruses (AIVs) seriously affect the poultry industry and pose a great threat to humans. Timely surveillance of AIVs is the basis for preparedness of the virus. This study reported the long-term surveillance of AIVs in the live bird market (LBM) of 16 cities in Shandong province from 2013 to 2019. A total of 29,895 samples were obtained and the overall positive rate of AIVs was 9.7%. The H9 was found to be the most predominant subtype in most of the time and contributed most to the monthly positve rate of AIVs as supported by the univariate and multivariate analysis, while H5 and H7 only circulated in some short periods. Then, the whole-genome sequences of 62 representative H9N2 viruses including one human isolate from a 7-year-old boy in were determined and they were genetically similar to each other with the median pairwise sequence identities ranging from 0.96 to 0.98 for all segments. The newly sequenced viruses were most similar to viruses isolated in chickens in mainland China, especially the provinces in Eastern China. Phylogenetic analysis showed that these newly sequenced H9N2 viruses belonged to the same clade for all segments except PB1. Nearly all of these viruses belonged to the G57 genotype which has dominated in China since 2010. Finally, several molecular markers associated with human adaptation, mammalian virulence, and drug resistance were identified in the newly sequenced H9N2 viruses. Overall, the study deepens our understanding of the epidemic and evolution of AIVs and provides a basis for effective control of AIVs in China.

Inhibition of Influenza Virus Polymerase by Interfering with Its Protein-Protein Interactions

Influenza (flu) virus is a serious threat to global health with the potential to generate devastating pandemics. The availability of broad spectrum antiviral drugs is an unequaled weapon during pandemic events, especially when a vaccine is still not available. One of the most promising targets for the development of new antiflu therapeutics is the viral RNA-dependent RNA polymerase (RdRP). The assembly of the flu RdRP heterotrimeric complex from the individual polymerase acidic protein (PA), polymerase basic protein 1 (PB1), and polymerase basic protein 2 (PB2) subunits is a prerequisite for RdRP functions, such as mRNA synthesis and genome replication. In this Review, we report the known protein-protein interactions (PPIs) occurring by RdRP that could be disrupted by small molecules and analyze their benefits and drawbacks as drug targets. An overview of small molecules able to interfere with flu RdRP functions exploiting the PPI inhibition approach is described. In particular, an update on the most recent inhibitors targeting the well-consolidated RdRP PA-PB1 subunit heterodimerization is mainly reported, together with pioneer inhibitors targeting other virus-virus or virus-host interactions involving RdRP subunits. As demonstrated by the PA-PB1 interaction inhibitors discussed herein, the inhibition of flu RdRP functions by PPI disrupters clearly represents a valid means to identify compounds endowed with a broad spectrum of action and a reduced propensity to develop drug resistance, which are the main issues of antiviral drugs.

Time series computational prediction of vaccines for influenza A H3N2 with recurrent neural networks

Influenza viruses are persistently threatening public health, causing annual epidemics and sporadic pandemics due to rapid viral evolution. Vaccines are used to prevent influenza infections but the composition of the influenza vaccines have to be updated regularly to ensure its efficacy. Computational tools and analyses have become increasingly important in guiding the process of vaccine selection. By constructing time-series training samples with splittings and embeddings, we develop a computational method for predicting suitable strains as the recommendation of the influenza vaccines using recurrent neural networks (RNNs). The Encoder-decoder architecture of RNN model enables us to perform sequence-to-sequence prediction. We employ this model to predict the prevalent sequence of the H3N2 viruses sampled from 2006 to 2017. The identity between our predicted sequence and recommended vaccines is greater than 98% and the Pepitope<0.2 indicates their antigenic similarity. The multi-step vaccine prediction further demonstrates the robustness of our method which achieves comparable results in contrast to single step prediction. The results show significant matches of the recommended vaccine strains to the circulating strains. We believe it would facilitate the process of vaccine selection and surveillance of seasonal influenza epidemics.

Efficacy of two vaccines against recent emergent antigenic variants of clade 2.3.2.1a highly pathogenic avian influenza viruses in Bangladesh

H5N1 highly pathogenic avian influenza viruses (HPAIVs) have caused outbreaks in poultry in Bangladesh since 2007. While clade 2.2.2 and 2.3.4.2 HPAIVs have not been detected since 2012, clade 2.3.2.1a viruses have caused continuous outbreaks since 2012 despite the use of vaccines. In this study, we evaluated the efficacy of two H5 vaccines licensed in Bangladesh, RE-6 inactivated vaccine, and a recombinant herpesvirus of turkeys vaccine with an H5 insert (rHVT-H5), for protection against recent field viruses in chickens. We selected three viruses for efficacy tests (A/chicken/Bangladesh/NRL-AI-3237/2017, A/crow/Bangladesh/NRL-AI-8471/2017 and A/chicken/Bangladesh/NRL-AI-8323/2017) from 36 H5 viruses isolated from Bangladesh between 2016 and 2018 by comparing the amino acid sequences at five antigenic sites (A-E) and analyzing hemagglutination inhibition (HI) titers with reference antisera. The RE-6 and rHVT-H5 vaccines both conferred 80-100% clinical protection (i.e. reduced morbidity and mortality) against the three challenge viruses with no significant differences in protection. In addition, both vaccines significantly decreased viral shedding from infected chickens as compared to challenge control chickens. Based on these metrics, the current licensed H5 vaccines protected chickens against the recent field viruses. However, the A/crow/Bangladesh/NRL-AI-8471/2017 virus exhibited antigenic divergence including: several unique amino acid changes in antigenic epitope sites A and B and was a serological outlier in cross HI tests as visualized on the antigenic map. The continuing emergence of such antigenic variants which could alter the dominant antigenicity of field viruses should be continuously monitored and vaccines should be updated if field efficacy declines.

Identification of a universal antigen epitope of influenza A virus using peptide microarray

Background

Hemagglutinin is a major surface protein in influenza A virus (IAV), and HA2 is relative conserved among different IAVs. It will be meaningful to identify broad-spectrum epitopes based on the HA2 protein.

Results

Overlapping peptides of the HA2 protein of the H5N1 IAV A/Mallard/Huadong/S/2005 were synthesized and loaded on modified silica gel film to form a microarray, and antisera against different subtypes of IAVs were used to screen universal epitopes. The selected epitope was further confirmed by western blotting using anti-peptide immune serum and viruses rescued with amino acid substitution. The results showed that 485-FYHKCDNECME-495 of the H5 14th peptide in HA2 had broad-spectrum binding activity with antisera against H1, H3, H4, H5, H6, H7, H8, H9, and H10 subtype IAV. Substitution of amino acids (K or D) in rescued viruses resulted in decreased serum binding, indicating that they were critical residues for serum binding activity. In Immune Epitope Database, some epitopes containing 14–4 peptide were confirmed as MHC-II-restricted CD4 T cell epitope and had effects on releasing IL-2 or IFN.

Conclusion

The identified epitope should be a novel universal target for detection and vaccine design and its ability to generate immune protection needs further exploration.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12917-020-02725-5.

Tempel: time-series mutation prediction of influenza A viruses via attention-based recurrent neural networks

Motivation

Influenza viruses are persistently threatening public health, causing annual epidemics and sporadic pandemics. The evolution of influenza viruses remains to be the main obstacle in the effectiveness of antiviral treatments due to rapid mutations. The goal of this work is to predict whether mutations are likely to occur in the next flu season using historical glycoprotein hemagglutinin sequence data. One of the major challenges is to model the temporality and dimensionality of sequential influenza strains and to interpret the prediction results.

Results

In this article, we propose an efficient and robust time-series mutation prediction model (Tempel) for the mutation prediction of influenza A viruses. We first construct the sequential training samples with splittings and embeddings. By employing recurrent neural networks with attention mechanisms, Tempel is capable of considering the historical residue information. Attention mechanisms are being increasingly used to improve the performance of mutation prediction by selectively focusing on the parts of the residues. A framework is established based on Tempel that enables us to predict the mutations at any specific residue site. Experimental results on three influenza datasets show that Tempel can significantly enhance the predictive performance compared with widely used approaches and provide novel insights into the dynamics of viral mutation and evolution.

Availability and implementation

The datasets, source code and supplementary documents are available at: https://drive.google.com/drive/folders/15WULR5__6k47iRotRPl3H7ghi3RpeNXH.

Supplementary information

Supplementary data are available at Bioinformatics online.

Detecting influenza and emerging avian influenza virus by influenza and pneumonia surveillance systems in a large city in China, 2005 to 2016

Background

Detecting avian influenza virus has become an important public health strategy for controlling the emerging infectious disease.

Methods

The HIS (hospital information system) modified influenza surveillance system (ISS) and a newly built pneumonia surveillance system (PSS) were used to monitor the influenza viruses in Changsha City, China. The ISS was used to monitor outpatients in two sentinel hospitals and to detect mild influenza and avian influenza cases, and PSS was used to monitor inpatients in 49 hospitals and to detect severe and death influenza cases.

Results

From 2005 to 2016, there were 3,551,917 outpatients monitored by the ISS system, among whom 126,076 were influenza-like illness (ILI) cases, with the ILI proportion (ILI%) of 3.55%. After the HIS was used, the reported incident cases of ILI and ILI% were increased significantly. From March, 2009 to September, 2016, there were 5,491,560 inpatient cases monitored by the PSS system, among which 362,743 were pneumonia cases, with a proportion of 6.61%. Among pneumonia cases, about 10.55% (38,260/362,743) of cases were severe or death cases. The pneumonia incidence increased each year in the city. Among 15 avian influenza cases reported from January, 2005 to September, 2016, there were 26.7% (4/15) mild cases detected by the HIS-modified ISS system, while 60.0% (9/15) were severe or death cases detected by the PSS system. Two H5N1 severe cases were missed by the ISS system in January, 2009 when the PSS system was not available.

Conclusions

The HIS was able to improve the efficiency of the ISS for monitoring ILI and emerging avian influenza virus. However, the efficiency of the system needs to be verified in a wider area for a longer time span in China.

Regulation of Early Host Immune Responses Shapes the Pathogenicity of Avian Influenza A Virus

Avian influenza A viruses (IAV) can cross the species barrier and cause disease in humans. Understanding the pathogenesis of avian IAV remains a challenge. Interferon-mediated antiviral responses and multiple cytokines production are important host cellular antiviral immunity against IAV infection. To elucidate the pathogenicity of avian IAV, a system approach was adopted to investigate dysregulation of the two host cellular antiviral immune responses in contrast with human IAV. As a result, we revealed that avian IAV not only disrupted normal early host cellular interferon-mediated antiviral responses, but also caused abnormal cytokines production through different pathways. For avian IAV infection, dysregulation of STAT2 was mainly responsible for abnormal cellular interferon-mediated antiviral responses, and IRF5 and NFKB1 played crucial roles in unusual cytokines production. In contrast, for human IAV infection, IRF1, IRF7, and STAT1 contributed to cellular cytokines production. Furthermore, differential activation of pattern recognition receptors (PRRs) likely led to avian IAV-related abnormal early host cellular antiviral immunity, where TLR7 and RIG-I were activated by avian and human IAV, respectively. Finally, a pathogenesis model was proposed that combined of early host cellular interferon-mediated antiviral responses with cytokines production could partly explain the pathogenicity of avian IAV. In conclusion, our study provides a new perspective of the pathogenesis of avian IAV, which will be helpful in preventing their infections in the future.

Positive selection pressure on E2 protein of classical swine fever virus drives variations in virulence, pathogenesis and antigenicity: Implication for epidemiological surveillance in endemic areas

Classical swine fever (CSF), caused by CSF virus (CSFV), is considered one of the most important infectious diseases with devasting consequences for the pig industry. Recent reports describe the emergence of new CSFV strains resulting from the action of positive selection pressure, due mainly to the bottleneck effect generated by ineffective vaccination. Even though a decrease in the genetic diversity of the positively selected CSFV strains has been observed by several research groups, there is little information about the effect of this selective force on the virulence degree, antigenicity and pathogenicity of this type of strains. Hence, the aim of the current study was to determine the effect of the positive selection pressure on these three parameters of CSFV strains, emerged as result of the bottleneck effects induced by improper vaccination in a CSF-endemic area. Moreover, the effect of the positively selected strains on the epidemiological surveillance system was assessed. By the combination of in vitro, in vivo and immunoinformatic approaches, we revealed that the action of the positive selection pressure induces a decrease in virulence and alteration in pathogenicity and antigenicity. However, we also noted that the evolutionary process of CSFV, especially in segregated microenvironments, could contribute to the gain-fitness event, restoring the highly virulent pattern of the circulating strains. Besides, we denoted that the presence of low virulent strains selected by bottleneck effect after inefficient vaccination can lead to a relevant challenge for the epidemiological surveillance of CSF, contributing to under-reports of the disease, favouring the perpetuation of the virus in the field. In this study, B-cell and CTL epitopes on the E2 3D-structure model were also identified. Thus, the current study provides novel and significant insights into variation in virulence, pathogenesis and antigenicity experienced by CSFV strains after the positive selection pressure effect.

Geographical and Historical Patterns in the Emergences of Novel Highly Pathogenic Avian Influenza (HPAI) H5 and H7 Viruses in Poultry

Over the years, the emergence of novel H5 and H7 highly pathogenic avian influenza viruses (HPAI) has been taking place through two main mechanisms: first, the conversion of a low pathogenic into a highly pathogenic virus, and second, the reassortment between different genetic segments of low and highly pathogenic viruses already in circulation. We investigated and summarized the literature on emerging HPAI H5 and H7 viruses with the aim of building a spatio-temporal database of all these recorded conversions and reassortments events. We subsequently mapped the spatio-temporal distribution of known emergence events, as well as the species and production systems that they were associated with, the aim being to establish their main characteristics. From 1959 onwards, we identified a total of 39 independent H7 and H5 LPAI to HPAI conversion events. All but two of these events were reported in commercial poultry production systems, and a majority of these events took place in high-income countries. In contrast, a total of 127 reassortments have been reported from 1983 to 2015, which predominantly took place in countries with poultry production systems transitioning from backyard to intensive production systems. Those systems are characterized by several co-circulating viruses, multiple host species, regular contact points in live bird markets, limited biosecurity within value chains, and frequent vaccination campaigns that impose selection pressures for emergence of novel reassortants. We conclude that novel HPAI emergences by these two mechanisms occur in different ecological niches, with different viral, environmental and host associated factors, which has implications in early detection and management and mitigation of the risk of emergence of novel HPAI viruses.

Antiviral effects of Shuanghuanglian injection powder against influenza A virus H5N1 in vitro and in vivo

The current study was to identify a protective role of Shuanghuanglian (SHL) injection powder in vitro and in vivo after H5N1 viral infection. Immunofluorescent staining was used to determine the susceptibility of rat intestinal mucosa microvascular endothelial cells (RIM-MVECs) to the H5N1 virus. Viral replication of RIM-MVECs was measured by transmission electron microscopy (TEM) a hemagglutination assay and real-time quantitative PCR. H5N1 virally infected RIM-MVECs, and BALB/c mice were treated with SHL to investigate its therapeutic effect. Animal survival and the weight of H5N1 virally infected BALB/c mice after SHL treatment was noted, and histology and real-time PCR applied to mouse lungs were used to confirm the anti-H5N1 viral effects of SHL. RIM-MVECs supported replication of the H5N1 virus in vitro. SHL treatment reduced viral titers in H5N1 virally infected RIM-MVECs and mouse lungs. SHL -treated mice survived compared to controls. Mild pathological changes, reduced inflammatory cell infiltration and fewer viral antigens were observed in the lungs of SHL-treated mice at days 3 and 6 post-infection. In conclusion, SHL may have the antiviral activity against the H5N1 virus infection by inhibiting viral replication and alleviating lung injury.

In Silico Vaccine Strain Prediction for Human Influenza Viruses

Vaccines preventing seasonal influenza infections save many lives every year; however, due to rapid viral evolution, they have to be updated frequently to remain effective. To identify appropriate vaccine strains, the World Health Organization (WHO) operates a global program that continually generates and interprets surveillance data. Over the past decade, sophisticated computational techniques, drawing from multiple theoretical disciplines, have been developed that predict viral lineages rising to predominance, assess their suitability as vaccine strains, link genetic to antigenic alterations, as well as integrate and visualize genetic, epidemiological, structural, and antigenic data. These could form the basis of an objective and reproducible vaccine strain-selection procedure utilizing the complex, large-scale data types from surveillance. To this end, computational techniques should already be incorporated into the vaccine-selection process in an independent, parallel track, and their performance continuously evaluated.

Evolution of Influenza A Virus by Mutation and Re-Assortment

Influenza A virus (IAV), a highly infectious respiratory pathogen, has continued to be a significant threat to global public health. To complete their life cycle, influenza viruses have evolved multiple strategies to interact with a host. A large number of studies have revealed that the evolution of influenza A virus is mainly mediated through the mutation of the virus itself and the re-assortment of viral genomes derived from various strains. The evolution of influenza A virus through these mechanisms causes worldwide annual epidemics and occasional pandemics. Importantly, influenza A virus can evolve from an animal infected pathogen to a human infected pathogen. The highly pathogenic influenza virus has resulted in stupendous economic losses due to its morbidity and mortality both in human and animals. Influenza viruses fall into a category of viruses that can cause zoonotic infection with stable adaptation to human, leading to sustained horizontal transmission. The rapid mutations of influenza A virus result in the loss of vaccine optimal efficacy, and challenge the complete eradication of the virus. In this review, we highlight the current understanding of influenza A virus evolution caused by the mutation and re-assortment of viral genomes. In addition, we discuss the specific mechanisms by which the virus evolves.