Pre-pandemic Virus Research Articles

Intranasal administration of octavalent next-generation influenza vaccine elicits protective immune responses against seasonal and pre-pandemic viruses.

Influenza is a respiratory virus which infects around a billion people globally every year, with millions experiencing severe illness. Commercial vaccine efficacy varies year to year and can be low due to mismatch of circulating virus strains. Thus, the formulation of current vaccines has to be adapted accordingly every year. The development of a broadly reactive influenza vaccine would lessen the global economic and public health burden caused by the different types of influenza viruses. The significance of our research is producing a promising universal vaccine candidate which provides protection against a wider range of virus strains over a wider range of time.

Multivalent next generation influenza virus vaccines protect against seasonal and pre-pandemic viruses

Each year, new influenza virus vaccine formulations are generated to keep up with continuously circulating and mutating viral variants. A next-generation influenza virus vaccine would provide long-lasting, broadly-reactive immune protection against current and future influenza virus strains for both seasonal and pre-pandemic viruses. Next generation immunogens were designed using computationally optimized broadly reactive antigen (COBRA) methodology to protect against a broad range of strains over numerous seasons. Novel HA and NA amino acid sequences were derived from multilayered consensus sequence alignment for multiple subtypes of influenza. This multivalent formulation was hypothesized to elicit broadly protective immune responses against both seasonal and pre-pandemic influenza viruses. Mice were vaccinated with multivalent mixtures of HA and NA (H1, H2, H3, H5, H7, N1, N2) proteins. Multivalent COBRA vaccinations elicited antibodies that recognized a broad panel of strains and vaccinated mice were protected against viruses representing multiple subtypes. This is a promising candidate for a universal influenza vaccine that elicits protective immune responses against seasonal and pre-pandemic strains over multiple seasons.

Evaluation of Pre-Pandemic Trivalent COBRA HA Vaccine in Mice Pre-Immune to Historical H1N1 and H3N2 Influenza Viruses.

Initial exposure to influenza virus(es) during early childhood produces protective antibodies that may be recalled following future exposure to subsequent viral infections or vaccinations. Most influenza vaccine research studies use immunologically naïve animal models to assess vaccine effectiveness. However, most people have an extensive influenza immune history, with memory cells produced by viruses or vaccines representing multiple influenza viruses. In this study, we explored the effect influenza seasonal virus-induced immunity has on pre-pandemic influenza virus vaccination. The mice that were pre-immune to historical H1N1 and H3N2 seasonal influenza viruses were vaccinated with adjuvanted pre-pandemic (H2, H5, and H7) HA-based computationally optimized broadly reactive antigen (COBRA) vaccines, and were fully protected from lethal challenge, whereas the mock-vaccinated mice, with or without pre-immunity, were not protected from morbidity or mortality. Detectable antibody titers were present in the pre-immune mice vaccinated with a single dose of vaccine, but not in the immunologically naïve mice. The mice vaccinated twice with the trivalent COBRA HA vaccine had similar antibody titers regardless of their pre-immune status. Overall, seasonal pre-immunity did not interfere with the immune responses elicited by pre-pandemic COBRA HA vaccines or the protection against pre-pandemic viruses.

An evolution-based high-fidelity method of epistasis measurement: Theory and application to influenza.

Linkage effects in a multi-locus population strongly influence its evolution. The models based on the traveling wave approach enable us to predict the average speed of evolution and the statistics of phylogeny. However, predicting statistically the evolution of specific sites and pairs of sites in the multi-locus context remains a mathematical challenge. In particular, the effects of epistasis, the interaction of gene regions contributing to phenotype, is difficult to predict theoretically and detect experimentally in sequence data. A large number of false-positive interactions arises from stochastic linkage effects and indirect interactions, which mask true epistatic interactions. Here we develop a proof-of-principle method to filter out false-positive interactions. We start by demonstrating that the averaging of haplotype frequencies over multiple independent populations is necessary but not sufficient for epistatic detection, because it still leaves high numbers of false-positive interactions. To compensate for the residual stochastic noise, we develop a three-way haplotype method isolating true interactions. The fidelity of the method is confirmed analytically and on simulated genetic sequences evolved with a known epistatic network. The method is then applied to a large sequence database of neurominidase protein of influenza A H1N1 obtained from various geographic locations to infer the epistatic network responsible for the difference between the pre-pandemic virus and the pandemic strain of 2009. These results present a simple and reliable technique to measure epistatic interactions of any sign from sequence data.

Controlling Avian Influenza Virus in Bangladesh: Challenges and Recommendations.

Avian influenza virus (AIV) remains a huge challenge for poultry production with negative repercussions for micro- and macro-economy and public health in Bangladesh. High (HP) H5N1 and low pathogenicity (LP) H9N2 AIV are currently endemic in poultry, and both have been reported to infect humans sporadically. Multiple virus introductions of different clades of HPAIV H5N1, reassorted genotypes, and on-going diversification of LPAIV H9N2 create a highly volatile virological environment which potentially implicates increased virulence, adaptation to new host species, and subsequent zoonotic transmission. Allotropy of poultry rearing systems and supply chains further increase the risk of virus spreading, which leads to human exposure and fosters the emergence of new potentially pre-pandemic virus strains. Here, we review the epidemiology, focusing on (i) risk factors for virus spreading, (ii) viral genetic evolution, and (iii) options for AIV control in Bangladesh. It is concluded that improved control strategies would profit from the integration of various intervention tools, including effective vaccination, enhanced biosecurity practice, and improved awareness of producers and traders, although widespread household poultry rearing significantly interferes with any such strategies. Nevertheless, continuous surveillance associated with rapid diagnosis and thorough virus characterization is the basis of such strategies.

Three Levels of the Predicting of the Influenza Vaccine Strains

Relevance. The influenza vaccine can reduce the incidence and mortality from influenza if that are antigenically the same or related to the viruses. There are at least 3 levels of prediction: vaccine strains for the upcoming epidemic season; the trend of influenza viruses for 2–3 years ahead, the emergence of pre-pandemic virus strains. The aim of the work was to analyze the potential of bioinformatics to implement prediction at these 3 levels for subtypes H1N1 and H3N2. Materials and methods. For the computer analysis, the database of the hemagglutinin (HA) primary structures of the H1N1 and H3N2 strains isolated in the influenza epidemiological season 2016–2017 – 2018–2019 was used from the Internet. At the first prediction level, an adapted hidden Markov model was used, at the second, invariants were searched for НА H1N1 and its antigenic sites, and at the third level, prediction was based on identifying invariants in structural proteins of pandemic strains. Results. The circulation of several dominant strains in the epidemiological season 2018–2019 was predicted, the existence of invariants in НА Н1 and its antigenic sites НА H1N1 was shown, and it was concluded that the threat of an influenza pandemic caused by avian influenza viruses was unlikely. Conclusion The bioinformatics approach can be considered as a valuable tool in predicting, at different levels of circulation, certain strains of the influenza virus in the epidemic season.

Pandemic preparedness and the Influenza Risk Assessment Tool (IRAT).

Influenza infections have resulted in millions of deaths and untold millions of illnesses throughout history. Influenza vaccines are the cornerstone of influenza prevention and control. Recommendations are made by the World Health Organization (WHO) 6-9 months in advance of the influenza season regarding what changes, if any, should be made in the formulation of seasonal influenza vaccines. This allows time to manufacture, test, distribute, and administer vaccine prior to the beginning of the influenza season. At the same time experts also consider which viruses not currently circulating in the human population, but with pandemic potential, pose the greatest risk to public health. Experts may conclude that one or more of these viruses are of enough concern to warrant development of a high-growth reassortant candidate vaccine virus. Subsequently, national authorities may determine that a vaccine should be manufactured, tested in clinical trials, and even stockpiled in some circumstances. The Influenza Risk Assessment Tool (IRAT) was created in an effort to develop a standardized set of elements that could be applied for decision making when evaluating pre-pandemic viruses. The tool is a simple, additive model, based on multi-attribute decision analysis . The ultimate goal is to identify an appropriate candidate vaccine virus and prepare a human vaccine before the virus adapts to infect and efficiently transmit in susceptible human populations. This pre-pandemic preparation allows production of vaccine-a strategy that could save lives and mitigate illness during a pandemic.

Molecular determinants of influenza virus pathogenesis in mice.

Mice are widely used for studying influenza virus pathogenesis and immunology because of their low cost, the wide availability of mouse-specific reagents, and the large number of mouse strains available, including knockout and transgenic strains. However, mice do not fully recapitulate the signs of influenza infection of humans: transmission of influenza between mice is much less efficient than in humans, and influenza viruses often require adaptation before they are able to efficiently replicate in mice. In the process of mouse adaptation, influenza viruses acquire mutations that enhance their ability to attach to mouse cells, replicate within the cells, and suppress immunity, among other functions. Many such mouse-adaptive mutations have been identified, covering all 8 genomic segments of the virus. Identification and analysis of these mutations have provided insight into the molecular determinants of influenza virulence and pathogenesis, not only in mice but also in humans and other species. In particular, several mouse-adaptive mutations of avian influenza viruses have proved to be general mammalian-adaptive changes that are potential markers of pre-pandemic viruses. As well as evaluating influenza pathogenesis, mice have also been used as models for evaluation of novel vaccines and anti-viral therapies. Mice can be a useful animal model for studying influenza biology as long as differences between human and mice infections are taken into account.

Assessment of viral replication in eggs and HA protein yield of pre-pandemic H5N1 candidate vaccine viruses

H5N1 infection and the potential for spread from human to human continue to pose a severe public health concern. Since vaccination remains the most effective way to prevent a potential H5N1 pandemic, the World Health Organization (WHO) Collaborating Centers (CCs) and Essential Regulatory Laboratories (ERLs) engineered and developed a panel of H5N1 pre-pandemic vaccine viruses for pandemic vaccine preparedness as well as production of antigen potency testing reagents (reference antigen and reference anti-serum) for vaccine standardization. To develop a strategy utilizing a number of biochemical methods for the characterization of the viral growth properties and protein yield in eggs, we have selected eight H5N1 pre-pandemic viruses and determined the viral Egg Infectious Dose 50 (EID50), total protein yield, hemagglutinin (HA) to nucleoprotein (NP) ratios (HA:NP), and HA1 content of each virus. Our results showed that all the tested H5N1 vaccine viruses grew to high titers in eggs. The total viral protein yield varies within a narrow range, whereas there were greater differences in the HA:NP protein ratios among the eight viruses. The RP-HPLC based HA1 content analysis demonstrated that the viruses A/Anhui/1/2010, A/Hubei/1/2005, and A/goose/Guiyang/337/2006 contained higher HA contents than other five viruses including A/Vietnam/1203/2003. Our approach for analyzing virus growth and protein yield will allow us identify optimal vaccine virus in a timely manner. In addition, we successfully purified the HA proteins of H5N1 vaccine viruses by optimizing bromelain cleavage conditions. Our studies on the HA protein purification may improve the quality control of the production of influenza vaccine test reagent.

Development of an Influenza Virologic Risk Assessment Tool

Influenza pandemics pose a continuous risk to human and animal health and may engender food security issues worldwide. As novel influenza A virus infections in humans are identified, pandemic preparedness strategies necessarily involve decisions regarding which viruses should be included for further studies and mitigation efforts. Resource and time limitations dictate that viruses determined to pose the greatest risk to public or animal health should be selected for further research to fill information gaps and, potentially, for development of vaccine candidates that could be put in libraries, manufactured and stockpiled, or even administered to protect susceptible populations of animals or people. A need exists to apply an objective, science-based risk assessment to the process of evaluating influenza viruses. During the past year, the Centers for Disease Control and Prevention began developing a tool to evaluate influenza A viruses that are not circulating in the human population but pose a pandemic risk. The objective is to offer a standardized set of considerations to be applied when evaluating prepandemic viruses. The tool under consideration is a simple, additive model, based on multiattribute decision analysis. The model includes elements that address the properties of the virus itself and population attributes, considers both veterinary and human findings, and integrates both laboratory and field observations. Additionally, each element is assigned a weight such that all elements are not considered of equal importance within the model.