Predicting Antigenicity of Influenza A Viruses Using biophysical ideas

Sequence-based detection of emerging antigenically novel influenza A viruses

The detection of evolutionary transitions in influenza A (H3N2) viruses' antigenicity is a major obstacle to effective vaccine design and development. In this study, we describe Novel Influenza Virus A Detector (NIAViD), an unsupervised machine learning tool, adept at identifying these transitions, using the HA1 sequence and associated physico-chemical properties. NIAViD performed with 88.9% (95% CI, 56.5-98.0%) and 72.7% (95% CI, 43.4-90.3%) sensitivity in training and validation, respectively, outperforming the uncalibrated null model-33.3% (95% CI, 12.1-64.6%) and does not require potentially biased, time-consuming and costly laboratory assays. The pivotal role of the Boman's index, indicative of the virus's cell surface binding potential, is underscored, enhancing the precision of detecting antigenic transitions. NIAViD's efficacy is not only in identifying influenza isolates that belong to novel antigenic clusters, but also in pinpointing potential sites driving significant antigenic changes, without the reliance on explicit modelling of haemagglutinin inhibition titres. We believe this approach holds promise to augment existing surveillance networks, offering timely insights for the development of updated, effective influenza vaccines. Consequently, NIAViD, in conjunction with other resources, could be used to support surveillance efforts and inform the development of updated influenza vaccines.

CAvant® WO-60 as an Effective Immunological Adjuvant for Avian Influenza and Newcastle Disease Vaccine

Despite the immunogenicity of vaccines currently used in poultry, several pathogens, including avian influenza virus (AIV) and Newcastle disease virus (NDV), cause enormous economic losses to the global poultry industry. The efficacy of vaccines can be improved by the introduction of effective adjuvants. This study evaluated a novel water-in-oil emulsion adjuvant, CAvant® WO-60, which effectively enhanced both the immunogenicity of conserved influenza antigen sM2HA2 and inactivated whole H9N2 antigen (iH9N2). CAvant® WO-60 induced both humoral and cell-mediated immunity in mice and provided 100% protection from challenge with 10 LD50 of A/Aquatic bird/Korea/W81/2005 (H5N2) and A/Chicken/Korea/116/2004 (H9N2) AIV. Importantly, immunization of chickens with iH9N2 plus inactivated NDV LaSota (iNDV) bivalent inactivated vaccine emulsified in CAvant® WO-60 induced seroprotective levels of antigen-specific antibody responses. Taken together, these results suggested that CAvant® WO-60 is a promising adjuvant for poultry vaccines.

A Herbal Mixture Formula of OCD20015-V009 Prophylactic Administration to Enhance Interferon-Mediated Antiviral Activity Against Influenza A Virus

OCD20015-V009 is an herbal mix of water-extracted Ginseng Radix, Poria (Hoelen), Rehmanniae Radix, Adenophorae Radix, Platycodi Radix, Crataegii Fructus, and Astragali Radix. In this study, its in vitro and in vivo antiviral activity and mechanisms against the influenza A virus were evaluated using a GFP-tagged influenza A virus (A/PR/8/34-GFP) to infect murine macrophages. We found that OCD20015-V009 pre-treatment substantially reduced A/PR/8/34-GFP replication. Also, OCD20015-V009 pre-treatment increased the phosphorylation of type-I IFN-related proteins TBK-1 and STAT1 and the secretion of pro-inflammatory cytokines TNF-α and IL-6 by murine macrophages. Moreover, OCD20015-V009 prophylactic administration increased IFN-stimulated genes-related 15, 20, and 56 and IFN-β mRNA in vitro. Thus, OCD20015-V009 likely modulates murine innate immune response via macrophages. This finding is potentially useful for developing prophylactics or therapeutics against the influenza A virus. Furthermore, pre-treatment with OCD20015-V009 decreased the mortality of the mice exposed to A/PR/8/34-GFP by 20% compared to that in the untreated animals. Thus, OCD20015-V009 stimulates the antiviral response in murine macrophages and mice to viral infections. Additionally, we identified chlorogenic acid and ginsenoside Rd as the antiviral components in OCD20015-V009. Further investigations are needed to elucidate the protective effects of active components of OCD20015-V009 against influenza A viruses.

A statistical analysis of antigenic similarity among influenza A (H3N2) viruses

An accurate assessment of antigenic similarity between influenza viruses is important for vaccine strain recommendations and influenza surveillance. Due to the mechanisms that result in frequent changes in the antigenicities of strains, it is desirable to obtain an antigenic similarity measure that accounts for specific changes in strains that are of epidemiological importance in influenza. Empirically grounded statistical models best achieve this. In this study, an interpretable machine-learning model was developed using distinguishing features of antigenic variants to analyze antigenic similarity. The features comprised of cluster information, amino acid sequences located in known antigenic and receptor-binding sites of influenza A (H3N2). In order to assess validity of parameters, accuracy and relevance of model to vaccine effectiveness, the model was applied to influenza A (H3N2) viruses due to their abundant genetic data and epidemiological relevance to influenza surveillance. An application of the model revealed that all model parameters were statistically significant to determining antigenic similarity between strains. Furthermore, upon evaluating the model for predicting antigenic similarity between strains, it achieved 95% area under Receiver Operating Characteristic curve (AUC), 94% accuracy, 76% precision, 97% specificity, 68% sensitivity and a diagnostic odds ratio (DOR) of 83.19. Above all, the model was found to be strongly related to influenza vaccine effectiveness to indicate the correlation between vaccine effectiveness and antigenic similarity between vaccine and circulating strains in an epidemic. The study predicts probabilities of antigenic similarity and estimates changes in strains that lead to antigenic variants. A successful application of the methods presented in this study would complement the global efforts in influenza surveillance.

Influenza Anti-Stalk Antibodies: Development of a New Method for the Evaluation of the Immune Responses to Universal Vaccine

Growing interest in universal influenza vaccines and novel administration routes has led to the development of alternative serological assays that are able to detect antibodies against conserved epitopes. We present a competitive ELISA method that is able to accurately determine the ratio of serum immunoglobulin G directed against the different domains of the hemagglutinin, the head and the stalk. Human serum samples were treated with two variants of the hemagglutinin protein from the A/California/7/2009 influenza virus. The signals detected were assigned to different groups of antibodies and presented as a ratio between head and stalk domains. A subset of selected sera was also tested by hemagglutination inhibition, single radial hemolysis, microneutralization, and enzyme-linked lectin assays. Pre-vaccination samples from adults showed a quite high presence of anti-stalk antibodies, and the results were substantially in line with those of the classical serological assays. By contrast, pre-vaccination samples from children did not present anti-stalk antibodies, and the majority of the anti-hemagglutinin antibodies that were detected after vaccination were directed against the head domain. The presented approach, when supported by further assays, can be used to assess the presence of specific anti-stalk antibodies and the potential boost of broadly protective antibodies, especially in the case of novel universal influenza vaccine approaches.