Compensatory evolution of net-charge in influenza A virus hemagglutinin

Reduced amino acid alphabet-based encoding and its impact on modeling influenza antigenic evolution

Currently, vaccination is one of the most efficient ways to control and prevent influenza infection. Vaccine production largely relies on the results of laboratory assays, including hemagglutination inhibition and microneutralization assays, which are time-consuming and laborious. Viruses can escape from the immune response that results in the need to revise and update vaccines biannually. The hemagglutination inhibition assay can measure how effectively antibodies against a reference strain bind and block an antigen of the test strain. Various computer-aided models have been developed to optimize candidate vaccine strain selection. A general problem in modeling of antigenic evolution is the representation of genetic sequences for input into the research model. Our motivation stems from the well-known problem of encoding genetic information for modeling antigenic evolution. This paper introduces a two-fold encoding approach based on reduced amino acid alphabet and amino acid index databases called AAindex. We propose to apply a simplified amino acid alphabet in modeling of antigenic evolution. A simplified alphabet, also called a sub-alphabet or reduced amino acid alphabet, implies to use the 20 amino acids being clustered and divided into amino acid groups. The proposed encoding allows to redefine mutations termed for amino acid groups located in reduced alphabets. We investigated 40 reduced amino acid sets and their performance in modeling antigenic evolution. The experimental results indicate that the proposed reduced amino acid alphabets can achieve the performance of the standard alphabet in its accuracy. Moreover, these alphabets provide deeper insight into various aspects of the relationship between mutation and antigenic variation. By checking identified high-impact sites in the Influenza Research Database, we found that not only antigenic sites have a significant influence on antigenicity, but also other amino acids located in close proximity. The results indicate that all selected non-antigenic sites are related to immune responses. According to the Influenza Research Database, these have been experimentally determined to be T-cell epitopes, B-cell epitopes, and MHC-binding epitopes of different classes. This highlighted a caveat: while simulating antigenic evolution, the model should consider not only the genetic information on antigenic sites, but also that of neighboring positions, as they may indirectly impact antigenicity. Additionally, our findings indicate that structural and charge characteristics are the most beneficial in modeling antigenic evolution, which is in agreement with previous studies.

Additional Positive Electric Residues in the Crucial Spike Glycoprotein S Regions of the New SARS-CoV-2 Variants

The change in the formal charge of 34 SARS-CoV-2 lineages from September 2020 to June 2021 was analyzed according to the monthly evidence of the European agency. The reported point mutations and small insertions are electrically neutral (17), positive (12), or negative (3). They had been found in the spike glycoprotein S,  in the RBD and S1/S2 regions, crucial for initiation of viral infection. The most often observed were positive mutations, especially D614G and E484K, located in the region of S1/S2 junction, and in the receptor-binding domain (RBD), respectively. They are related to G and A switching. Positive mutations are stretching equally in both areas, but in the RBD region, they are more dispersed. In the set of analyzed virus variants, the increasing tendency in the number of positively charged residues in spike protein was observed. Furthermore, the well-documented WHO classes show an increase in the COVID-19 percentage case fatality with the positive increase in the spike crucial region’s total charge. The data mining, applying classifier algorithm based on the artificial neuronal network, confirms that the value and the distribution of additional positive charge in S may be important factors enabling virus impact to immunity. This may be promoted by the stronger long-range electrostatic attraction of the virus particle to the host cell, preceding the infection. The estimation of the potential energy for the RBD approaching the angiotensin-converting enzyme (ACE2) was presented.

Exopolysaccharide Produced by Plant-Derived Lactobacillus plantarum SN35N Exhibits Antiviral Activity

A lactic acid bacterial strain, Lactobacillus plantarum SN35N, which has been isolated from the pear, secretes negatively charged acidic exopolysaccharide (EPS) to outside cells. We have previously found that the SN35N-derived acidic EPS inhibits the catalytic activity of hyaluronidase (EC 3.2.1.35) promoting inflammation. The aim of this study is to find other health benefits of EPS. EPS has been found to exhibit an inhibitory effect against the influenza virus (Alphainfluenzavirus Influenza A virus) and feline calicivirus (Vesivirus Feline calicivirus), which is recognized as a model of norovirus. Although more studies on the structure-function relationship of EPSs are needed, SN35N-derived EPS is a promising lead for developing not only anti-inflammatory agents, but also antiviral substances.

The use of negative oxygen ion clusters [O2-(H2O)n] and bicarbonate ions [HCO3-] as the supportive treatment of COVID-19 infections: A possibility

The COVID-19 or novel coronavirus SARS-CoV-2 pandemic is challenging worldwide healthcare system and severely affecting global economy. Furious efforts to end the pandemic including prevention of spread of SARS-CoV-2, use of antiviral drugs, symptomatic treatments and vaccination are underway. But there are no effective treatments available to save the dying patient in stage 2 (pulmonary) and stage 3 (hyperinflammation) of the infection. The detailed genetic and phenotypical analysis of SARS-CoV-2 revealed that the spike protein (S1) has increased positive charges (compared to SARS-CoV) on them and are responsible for attachment to human angiotensin-converting enzyme 2 (ACE2) receptor and infection by the virus. In addition, it was also reported that the inflammation in the tissue rendered the lung environment more acidic supporting the fusion of SARS-CoV-2 with the cells. We hypothesize that the intermittent use of the oxygen ionizer generating negative oxygen ion clusters [O₂^-(H₂O)_n] and sodium bicarbonate nebulizer (generating HCO₃^-); when connected to ventilator inlet or oxygen concentrator will neutralize the spike protein of the virus in respiratory tract and lungs and change the lung environment to neutral/alkaline condition respectively facilitating improved oxygen pressure in blood. These physical changes can effectively reduce the viral burden and help the patient recover from the infection faster.

Structural dynamics of SARS-CoV-2 variants: A health monitoring strategy for anticipating Covid-19 outbreaks

OBJECTIVES

the Covid-19 pandemic has been marked by sudden outbreaks of SARS-CoV-2 variants harboring mutations in both the N-terminal (NTD) and receptor binding (RBD) domains of the spike protein. The goal of this study was to predict the transmissibility of SARS-CoV-2 variants from genomic sequence data.

METHODS

we used a target-based molecular modeling strategy combined with surface potential analysis of the NTD and RBD.

RESULTS

we observed that both domains act synergistically to ensure optimal virus adhesion, which explains why most variants exhibit concomitant mutations in the RBD and in the NTD. Some mutation patterns affect the affinity of the spike protein for ACE-2. However, other patterns increase the electropositive surface of the spike, with determinant effects on the kinetics of virus adhesion to lipid raft gangliosides. Based on this new view of the structural dynamics of SARS-CoV-2 variants, we defined an index of transmissibility (T-index) calculated from kinetic and affinity parameters of coronavirus binding to host cells. The T-index is characteristic of each variant and predictive of its dissemination in animal and human populations.

CONCLUSIONS

the T-index can be used as a health monitoring strategy to anticipate future Covid-19 outbreaks due to the emergence of variants of concern.

Plasmonic/magnetic molybdenum trioxide and graphitic carbon nitride quantum dots-based fluoroimmunosensing system for influenza virus

A novel magnetic/plasmonic-assisted fluoro-immunoassay system is developed for the detection of influenza virus using magnetic-derivatized plasmonic molybdenum trioxide quantum dots (MP-MoO₃ QDs) as the plasmonic/magnetic agent and fluorescent graphitic carbon nitride quantum dots (gCNQDs) as the monitoring probe. Specific antibody against influenza A virus was conjugated onto the surface of MP-MoO₃ QDs and gCNQDs, respectively. In the presence of influenza A virus (as the test virus), a core-satellite immunocomplex is formed between the antibody-conjugated nanomaterials (Ab-MP-MoO₃ QDs and Ab-gCNQDs) and their interaction resulted in the modulation and gradual enhancement of the fluorescence intensity of the detection probe with the influenza virus concentration-dependent increase. In addition, PL change without influenza A virus was not observed. Limits of detection of 0.25 and 0.9 pg/mL were achieved for Influenza virus A/New Caledonia (20/99/IVR/116) (H1N1) detection in deionized water and human serum, respectively. Clinically isolated influenza virus A/Yokohama (110/2009) (H3N2) was detected in the range of 45 - 25,000 PFU/mL, with a limit of detection ca 45 PFU/mL (as opposed to a minimum of 5000 PFU/mL for a commercial test kit). This developed biosensor provides a robust, sensitive as well as a selective platform for influenza virus detection.

Implications of localized charge for human influenza A H1N1 hemagglutinin evolution: Insights from deep mutational scans

Seasonal influenza A viruses of humans evolve rapidly due to strong selection pressures from host immune responses, principally on the hemagglutinin (HA) viral surface protein. Based on mouse transmission experiments, a proposed mechanism for immune evasion consists of increased avidity to host cellular receptors, mediated by electrostatic charge interactions with negatively charged cell surfaces. In support of this, the HA charge of the globally circulating H3N2 has increased over time since its pandemic. However, the same trend was not seen in H1N1 HA sequences. This is counter-intuitive, since immune escape due to increased avidity (due itself to an increase in charge) was determined experimentally. Here, we explore whether patterns of local charge of H1N1 HA can explain this discrepancy and thus further associate electrostatic charge with immune escape and viral evolutionary dynamics. Measures of site-wise functional selection and expected charge computed from deep mutational scan data on an early H1N1 HA yield a striking division of residues into three groups, separated by charge. We then explored evolutionary dynamics of these groups from 1918 to 2008. In particular, one group increases in net charge over time and consists of sites that are evolving the fastest, that are closest to the receptor binding site (RBS), and that are exposed to solvent (i.e., on the surface). By contrast, another group decreases in net charge and consists of sites that are further away from the RBS and evolving slower, but also exposed to solvent. The last group consists of those sites in the HA core, with no change in net charge and that evolve very slowly. Thus, there is a group of residues that follows the same trend as seen for the entire H3N2 HA. It is possible that the H1N1 HA is under other biophysical constraints that result in compensatory decreases in charge elsewhere on the protein. Our results implicate localized charge in HA interactions with host cells, and highlight how deep mutational scan data can inform evolutionary hypotheses.

The hemagglutinin (HA) surface protein of influenza A viruses evolves rapidly to evade host immunity, leading to sizable yearly epidemics in human populations. Previous transmission experiments with H1N1 in mice have tied immune escape to an increase in HA avidity for cellular receptors, mediated by electrostatic charge. Furthermore, retrospective sequence analyses from a previous study confirmed that the HA of circulating global H3N2 has increased in net charge, yet surprisingly, that of H1N1 has not varied significantly. How is a stable net charge related to local patterns of H1N1 HA charge in response to selection? To elucidate the role of local electrostatic charge in host-virus interactions, we investigate characteristics of local charge on the H1N1 HA using functional data from deep mutational scan experiments. Combining measures of functional selection and expected charge at each site on DMS data from a 1933 H1N1 HA yields a striking visual pattern that identifies three groups of sites that have different biophysical properties and that prove to have distinct evolutionary patterns in natural human sequences. Essentially, we find evidence for an increase in charge near the receptor binding site and for compensatory changes elsewhere on the protein. Thus, our findings may reconcile disparate results from transmission experiments and natural sequence analyses, and highlight the importance of local properties of the HA protein. Overall, our findings further support the hypothesis of immune escape due to increased HA avidity to cellular receptors mediated by electrostatic charge. More generally, our work illustrates a novel method of leveraging deep mutational scans in conjunction with natural sequences to shed light on virus-host interactions.

A Study on Host Tropism Determinants of Influenza Virus Using Machine Learning

Background:

The host tropism determinants of influenza virus, which cause changes in the host range and increase the likelihood of interaction with specific hosts, are critical for understanding the infection and propagation of the virus in diverse host species.

Methods:

Six types of protein sequences of influenza viral strains isolated from three classes of hosts (avian, human, and swine) were obtained. Random forest, naïve Bayes classification, and knearest neighbor algorithms were used for host classification. The Java language was used for sequence analysis programming and identifying host-specific position markers.

Results:

A machine learning technique was explored to derive the physicochemical properties of amino acids used in host classification and prediction. HA protein was found to play the most important role in determining host tropism of the influenza virus, and the random forest method yielded the highest accuracy in host prediction. Conserved amino acids that exhibited host-specific differences were also selected and verified, and they were found to be useful position markers for host classification. Finally, ANOVA analysis and post-hoc testing revealed that the physicochemical properties of amino acids, comprising protein sequences combined with position markers, differed significantly among hosts.

Conclusion:

The host tropism determinants and position markers described in this study can be used in related research to classify, identify, and predict the hosts of influenza viruses that are currently susceptible or likely to be infected in the future.

Positive charge of Arg-201 on hemagglutinin is required for the binding of H6N1 avian influenza virus to its target through a two-step process

In our previous study, we produced a monoclonal antibody EB2 that recognized an epitope in the HA1 domain on the hemagglutinin (HA) of H6N1 influenza virus (A/chicken/Taiwan/2838 V/00). The residue Arg-201 (R201) on this epitope was protected by the glycan at Asn-167 (N167) from tryptic digestion; therefore, the infectivity of the virus was retained. R201 was extremely conserved in various subtypes of the influenza virus. To explore the role of R201 and the protecting glycan, we developed a bi-cistronic baculovirus expression system for the production of H6HA1 and H6HA0 (nearly full-length HA), which were glycosylated in insect cells. The expressed H6HA1 was mostly found in the trimeric form, and the H6HA0 protein was only found in the monomeric form. The trimeric H6HA1 was resistant to tryptic digestion; however, it could not bind to fetuin, a glycoprotein containing sialylated N-linked and O-linked glycans. By contrast, the monomeric H6HA0 could bind to fetuin but was sensitive to tryptic digestion. We found that the positive charge on R201 was critical for binding HA to the negatively charged surface of host cells because the mutant R201A of H6HA0 lost its binding capacity substantially. Moreover, this binding capacity was dependent on the pH value and inhibited by free electrically charged amino acids. We propose a two-step model for binding the influenza virus with a host cell. The first step involved the specific recognition of the receptor binding site on HA to the sialylated glycan on the host cell. After the virus is engulfed by the acidic endosome, R201 could bind to the cell surface with stronger interactions and trigger the fusion process.

Inactivation of human and avian influenza viruses by potassium oleate of natural soap component through exothermic interaction

An influenza epidemic is still a problem despite the development of vaccines and anti-influenza drugs. Preventive measures such as handwashing are fundamental and important for counteracting influenza virus infection. In this study, we clarified the anti-influenza virus effects of surfactants, which are the main components of hand soaps for hand washing: potassium oleate (C18:1), sodium laureth sulfate (LES) and sodium lauryl sulfate (SDS). For a human influenza virus strain (H3N2), C18:1 reduced the infectivity by 4 logs or more, whereas LES and SDS reduced the infectivity by 1 log or less. Similar results were obtained when an avian influenza virus strain (H5N3) was used. The interaction between the surfactant and virus was then investigated by isothermal titration calorimetry. The LES-virus system showed a positive value of enthalpy changes (ΔH), meaning an exothermic interaction that indicated a hydrophobic interaction. In contrast, both the C18:1-virus system and the SDS-virus system showed negative values of ΔH, meaning an endothermic interaction that indicated an electrical interaction. The ΔH value of the C18:1-virus system was much higher than that of the SDS-virus system. A mixture of C18:1 and HA proteins similarly showed negative values of ΔH. These results indicate that influenza virus inactivation by a hydrophobic interaction of a surfactant with the viral envelope is insufficient to prevent infection, whereas inactivation by an electrical interaction of a surfactant with HA proteins is sufficient to prevent influenza virus infection.

H3N2 influenza viruses in humans: Viral mechanisms, evolution, and evaluation

Annual seasonal influenza vaccines are composed of two influenza A strains representing the H1N1 and H3N2 subtypes, and two influenza B strains representing the Victoria and Yamagata lineages. Strains from these Influenza A and Influenza B viruses currently co-circulate in humans. Of these, strains associated with the H3N2 subtype are affiliated with severe influenza seasons. H3N2 influenza viruses pre-dominated during 3 of the last 5 quite severe influenza seasons. During the 2016/2017 flu season, the H3N2 component of the influenza vaccine exhibited a poor protective efficacy (∼28-42%) against preventing infection of co-circulating strains. Since their introduction to the human population in 1968, H3N2 Influenza viruses have rapidly evolved both genetically and antigenically in an attempt to escape host immune pressures. As a result, these viruses have added numerous N-linked glycans to the viral hemagglutinin (HA), increased the overall net charge of the HA molecule, changed their preferences in receptor binding, and altered the ability of neuraminidase (NA) to agglutinate red blood cells prior to host entry. Over time, these adaptations have made characterizing these viruses increasingly difficult. This review investigates these recent changes in modern H3N2 influenza viruses and explores the methods that researchers are currently developing in order to study these viruses.

Electrostatic Variation of Haemagglutinin as a Hallmark of the Evolution of Avian Influenza Viruses

Avian influenza virus is a zoonotic agent that significantly impacts public health and the poultry industry. Monitoring viral evolution and spread is crucial for surveillance and tracing programmes, which are currently based on serological or DNA sequencing-phylogenetics analysis. However, virus-host interactions, antigenic drift and spreading of viral clades strongly depend on variation in the surface features of capsid proteins. We report here that in silico comparative structural analysis of haemagglutinin can reveal relevant evolutionary fingerprints, particularly when integrated with sequence-based analyses. Phylogenetic analyses of H9 viral strains from wild birds and poultry, performed with different methods, reliably led to clustering of viruses into five main groups. Subsequent comparison of structural features showed congruence between such clustering and surface electrostatic fingerprints. These latter fingerprints relate group-specific variations in electrostatic charges and isocontours to well-known haemagglutinin sites involved in the modulation of immune escape and host specificity. This work suggests that the integration of structural and sequence comparisons may enhance investigations of trends and relevant mechanisms in viral evolution.

Bacterial ribonuclease binase exerts an intra-cellular anti-viral mode of action targeting viral RNAs in influenza a virus-infected MDCK-II cells

BACKGROUND

Influenza is a severe contagious disease especially in children, elderly and immunocompromised patients. Beside vaccination, the discovery of new anti-viral agents represents an important strategy to encounter seasonal and pandemic influenza A virus (IAV) strains. The bacterial extra-cellular ribonuclease binase is a well-studied RNase from Bacillus pumilus. Treatment with binase was shown to improve survival of laboratory animals infected with different RNA viruses. Although binase reduced IAV titer in vitro and in vivo, the mode of action (MOA) of binase against IAV at the molecular level has yet not been studied in depth and remains elusive.

METHODS

To analyze whether binase impairs virus replication by direct interaction with the viral particle we applied a hemagglutination inhibition assay and monitored the integrity of the viral RNA within the virus particle by RT-PCR. Furthermore, we used Western blot and confocal microscopy analysis to study whether binase can internalize into MDCK-II cells. By primer extension we examined the effect of binase on the integrity of viral RNAs within the cells and using a mini-genome system we explored the effect of binase on the viral expression.

RESULTS

We show that (i) binase does not to attack IAV particle-protected viral RNA, (ii) internalized binase could be detected within the cytosol of MDCK-II cells and that (iii) binase impairs IAV replication by specifically degrading viral RNA species within the infected MDCK-II cells without obvious effect on cellular mRNAs.

CONCLUSION

Our data provide novel evidence suggesting that binase is a potential anti-viral agent with specific intra-cellular MOA.

Charged amino acid variability related to N-glyco -sylation and epitopes in A/H3N2 influenza: Hem -agglutinin and neuraminidase

BACKGROUND

The A/H3N2 influenza viruses circulated in humans have been shown to undergo antigenic drift, a process in which amino acid mutations result from nucleotide substitutions. There are few reports regarding the charged amino acid mutations. The purpose of this paper is to explore the relations between charged amino acids, N-glycosylation and epitopes in hemagglutinin (HA) and neuraminidase (NA).

METHODS

A total of 700 HA genes (691 NA genes) of A/H3N2 viruses were chronologically analyzed for the mutational variants in amino acid features, N-glycosylation sites and epitopes since its emergence in 1968.

RESULTS

It was found that both the number of HA N-glycosylation sites and the electric charge of HA increased gradually up to 2016. The charges of HA and HA1 increased respectively 1.54-fold (+7.0 /+17.8) and 1.08-fold (+8.0/+16.6) and the number of NGS in nearly doubled (7/12). As great diversities occurred in 1990s, involving Epitope A, B and D mutations, the charged amino acids in Epitopes A, B, C and D in HA1 mutated at a high frequency in global circulating strains last decade. The charged amino acid mutations in Epitopes A (T135K) has shown high mutability in strains near years, resulting in a decrease of NGT135-135. Both K158N and K160T not only involved mutations charged in epitope B, but also caused a gain of NYT158-160. Epitope B and its adjacent N-glycosylation site NYT158-160 mutated more frequently, which might be under greater immune pressure than the rest.

CONCLUSIONS

The charged amino acid mutations in A/H3N2 Influenza play a significant role in virus evolution, which might cause an important public health issue. Variability related to both the epitopes (A and B) and N-glycosylation is beneficial for understanding the evolutionary mechanisms, disease pathogenesis and vaccine research.

Enhanced detection of respiratory pathogens with nanotrap particles

The Influenza virus is a leading cause of respiratory disease in the United States each year. While the virus normally causes mild to moderate disease, hospitalization and death can occur in many cases. There are several methodologies that are used for detection; however problems such as decreased sensitivity and high rates of false-negative results may arise. There is a crucial need for an effective sample preparation technology that concentrates viruses at low abundance while excluding resident analytes that may interfere with detection. Nanotrap particles are hydrogel particles that are coupled to chemical dye affinity baits that bind a broad range of proteins and virions. Within minutes (<30 minutes), Nanotrap particles concentrate low abundant proteins and viruses from clinically complex matrices. Nanotrap particles with reactive red baits concentrated numerous respiratory viruses including various strains and subtypes of Influenza virus, Coronavirus, and Respiratory Syncytial Virus from saliva, nasal fluid swab specimens, and nasal aspirates. Detection was enhanced more than 10-fold when coupled to plaque assays and qRT-PCR. Importantly, Nanotrap particle can efficiently capture and concentrate multiple viral pathogens during a coinfection scenario. These results collectively demonstrate that Nanotrap particles are an important tool that can easily be integrated into various detection methodologies.

Selecting vaccine strains for H3N2 human influenza A virus

H3N2 human influenza A virus causes epidemics of influenza mainly in the winter season in temperate regions. Since the antigenicity of this virus evolves rapidly, several attempts have been made to predict the major amino acid sequence of hemagglutinin 1 (HA1) in the target season of vaccination. However, the usefulness of predicted sequence was unclear because its relationship to the antigenicity was unknown. Here the antigenic model for estimating the degree of antigenic difference (antigenic distance) between amino acid sequences of HA1 was integrated into the process of selecting vaccine strains for H3N2 human influenza A virus. When the effectiveness of a potential vaccine strain for a target season was evaluated retrospectively using the average antigenic distance between the strain and the epidemic viruses sampled in the target season, the most effective vaccine strain was identified mostly in the season one year before the target season (pre-target season). Effectiveness of actual vaccines appeared to be lower than that of the strains randomly chosen in the pre-target season on average. It was recommended to replace the vaccine strain for every target season with the strain having the smallest average antigenic distance to the others in the pre-target season. The procedure of selecting vaccine strains for future epidemic seasons described in the present study was implemented in the influenza virus forecasting system (INFLUCAST) (http://www.nsc.nagoya-cu.ac.jp/~yossuzuk/influcast.html).

Predicting host tropism of influenza A virus proteins using random forest

Background

Majority of influenza A viruses reside and circulate among animal populations, seldom infecting humans due to host range restriction. Yet when some avian strains do acquire the ability to overcome species barrier, they might become adapted to humans, replicating efficiently and causing diseases, leading to potential pandemic. With the huge influenza A virus reservoir in wild birds, it is a cause for concern when a new influenza strain emerges with the ability to cross host species barrier, as shown in light of the recent H7N9 outbreak in China. Several influenza proteins have been shown to be major determinants in host tropism. Further understanding and determining host tropism would be important in identifying zoonotic influenza virus strains capable of crossing species barrier and infecting humans.

Results

In this study, computational models for 11 influenza proteins have been constructed using the machine learning algorithm random forest for prediction of host tropism. The prediction models were trained on influenza protein sequences isolated from both avian and human samples, which were transformed into amino acid physicochemical properties feature vectors. The results were highly accurate prediction models (ACC>96.57; AUC>0.980; MCC>0.916) capable of determining host tropism of individual influenza proteins. In addition, features from all 11 proteins were used to construct a combined model to predict host tropism of influenza virus strains. This would help assess a novel influenza strain's host range capability.

Conclusions

From the prediction models constructed, all achieved high prediction performance, indicating clear distinctions in both avian and human proteins. When used together as a host tropism prediction system, zoonotic strains could potentially be identified based on different protein prediction results. Understanding and predicting host tropism of influenza proteins lay an important foundation for future work in constructing computation models capable of directly predicting interspecies transmission of influenza viruses. The models are available for prediction at http://fluleap.bic.nus.edu.sg.

Predictability of antigenic evolution for H3N2 human influenza A virus

Influenza A virus continues to pose a threat to public health. Since this virus can evolve escape mutants rapidly, it is desirable to predict the antigenic evolution for developing effective vaccines. Although empirical methods have been proposed and reported to predict the antigenic evolution more or less accurately, they did not provide much insight into the effects of unobserved mutations and the mechanisms of antigenic evolution. Here a theoretical method was introduced to predict the antigenic evolution of H3N2 human influenza A virus by evaluating de novo mutations through estimating the antigenic distance. The antigenic distance defined with the hemagglutination inhibition (HI) titer was estimated with antigenic models taking into account the volume, isoelectric point, relative solvent accessibility, and distances from receptor-binding sites (RBS) and N-linked glycosylation sites (NGS) for amino acids in hemagglutinin 1 (HA1). When the best model with the optimized parameter values was used to predict the antigenic evolution for the dominant strains, the prediction accuracy was relatively low. However, there appeared to be an overall tendency that the amino acid sites with larger potential net effect on antigenicity were more likely to evolve and the amino acid changes with larger potential effect were more likely to take place, suggesting that natural selection may operate to enhance the antigenic evolution of H3N2 human influenza A virus.

Intracellular nucleic acid delivery by the supercharged dengue virus capsid protein

Supercharged proteins are a recently identified class of proteins that have the ability to efficiently deliver functional macromolecules into mammalian cells. They were first developed as bioengineering products, but were later found in the human proteome. In this work, we show that this class of proteins with unusually high net positive charge is frequently found among viral structural proteins, more specifically among capsid proteins. In particular, the capsid proteins of viruses from the Flaviviridae family have all a very high net charge to molecular weight ratio (> +1.07/kDa), thus qualifying as supercharged proteins. This ubiquity raises the hypothesis that supercharged viral capsid proteins may have biological roles that arise from an intrinsic ability to penetrate cells. Dengue virus capsid protein was selected for a detailed experimental analysis. We showed that this protein is able to deliver functional nucleic acids into mammalian cells. The same result was obtained with two isolated domains of this protein, one of them being able to translocate lipid bilayers independently of endocytic routes. Nucleic acids such as siRNA and plasmids were delivered fully functional into cells. The results raise the possibility that the ability to penetrate cells is part of the native biological functions of some viral capsid proteins.

Antiviral Activity of Binase against the Pandemic Influenza A (H1N1) Virus

The lack of effective antiviral drugs restricts the control of the dangerous RNA-containing influenza A (H1N1) virus. Extracellular ribonuclease of Bacilli (binase) was shown to manifest antiviral activity during single- and multi-cycle viral replication in the range of concentrations non-toxic to epithelial cells and 0.01-0.1 multiplicity of infection. During antiviral treatment for 15-30 min, the concentration of 1 μg/ml binase reduced the amount of focus-forming units of viruses by a factor of 3-10 and suppressed the virus-induced cytopathic effect in A549 human lung cells. The possible mechanisms of interaction between the virus and enzyme are discussed. Positive charges in both binase and viral hemagglutinin cause electrostatic interaction with negatively charged sialic acid on the host cell's surface followed by its penetration into the cell. Capsid elimination and release of viral RNA from endosome to the cytoplasm allows catalytic RNA cleavage by internalized binase. The data obtained confirm that binase is an effective antiviral agent against the pandemic influenza A (H1N1) virus. Certain progress in this field is associated with clarifying the detailed mechanism underlying the antiviral action of binase and development of the most effective way for its practical use.

Triplet entropy analysis of hemagglutinin and neuraminidase sequences measures influenza virus phylodynamics

The influenza virus has been a challenge to science due to its ability to withstand new environmental conditions. Taking into account the development of virus sequence databases, computational approaches can be helpful to understand virus behavior over time. Furthermore, they can suggest new directions to deal with influenza. This work presents triplet entropy analysis as a potential phylodynamic tool to quantify nucleotide organization of viral sequences. The application of this measure to segments of hemagglutinin (HA) and neuraminidase (NA) of H1N1 and H3N2 virus subtypes has shown some variability effects along timeline, inferring about virus evolution. Sequences were divided by year and compared for virus subtype (H1N1 and H3N2). The nonparametric Mann-Whitney test was used for comparison between groups. Results show that differentiation in entropy precedes differentiation in GC content for both groups. Considering the HA fragment, both triplet entropy as well as GC concentration show intersection in 2009, year of the recent pandemic. Some conclusions about possible flu evolutionary lines were drawn.

George K, Webster RG, Air GM. Human H3N2 Influenza Viruses Isolated from 1968 To 2012 Show Varying Preference for Receptor Substructures with No Apparent Consequences for Disease or Spread

It is generally accepted that human influenza viruses bind glycans containing sialic acid linked α2–6 to the next sugar, that avian influenza viruses bind glycans containing the α2–3 linkage, and that mutations that change the binding specificity might change the host tropism. We noted that human H3N2 viruses showed dramatic differences in their binding specificity, and so we embarked on a study of representative human H3N2 influenza viruses, isolated from 1968 to 2012, that had been isolated and minimally passaged only in mammalian cells, never in eggs. The 45 viruses were grown in MDCK cells, purified, fluorescently labeled and screened on the Consortium for Functional Glycomics Glycan Array. Viruses isolated in the same season have similar binding specificity profiles but the profiles show marked year-to-year variation. None of the 610 glycans on the array (166 sialylated glycans) bound to all viruses; the closest was Neu5Acα2–6(Galβ1–4GlcNAc)₃ in either a linear or biantennary form, that bound 42 of the 45 viruses. The earliest human H3N2 viruses preferentially bound short, branched sialylated glycans while recent viruses bind better to long polylactosamine chains terminating in sialic acid. Viruses isolated in 1996, 2006, 2010 and 2012 bind glycans with α2–3 linked sialic acid; for 2006, 2010 and 2012 viruses this binding was inhibited by oseltamivir, indicating binding of α2–3 sialylated glycans by neuraminidase. More significantly, oseltamivir inhibited virus entry of 2010 and 2012 viruses into MDCK cells. All of these viruses were representative of epidemic strains that spread around the world, so all could infect and transmit between humans with high efficiency. We conclude that the year-to-year variation in receptor binding specificity is a consequence of amino acid sequence changes driven by antigenic drift, and that viruses with quite different binding specificity and avidity are equally fit to infect and transmit in the human population.

The evolutionary dynamics of receptor binding avidity in influenza A: a mathematical model for a new antigenic drift hypothesis

The most salient feature of influenza evolution in humans is its antigenic drift. This process is characterized by structural changes in the virus's B-cell epitopes and ultimately results in the ability of the virus to evade immune recognition and thereby reinfect previously infected hosts. Until recently, amino acid substitutions in epitope regions of the viral haemagglutinin were thought to be positively selected for their ability to reduce antibody binding and therefore were thought to be responsible for driving antigenic drift. However, a recent hypothesis put forward by Hensley and co-workers posits that cellular receptor binding avidity is the dominant phenotype under selection, with antigenic drift being a side effect of these binding avidity changes. Here, we present a mathematical formulation of this new antigenic drift model and use it to show how rates of antigenic drift depend on epidemiological parameters. We further use the model to evaluate how two different vaccination strategies can impact antigenic drift rates and ultimately disease incidence levels. Finally, we discuss the assumptions present in the model formulation, predictions of the model, and future work that needs to be done to determine the consistency of this hypothesis with known patterns of influenza's genetic and antigenic evolution.

Mapping the phosphoproteome of influenza A and B viruses by mass spectrometry

Protein phosphorylation is a common post-translational modification in eukaryotic cells and has a wide range of functional effects. Here, we used mass spectrometry to search for phosphorylated residues in all the proteins of influenza A and B viruses--to the best of our knowledge, the first time such a comprehensive approach has been applied to a virus. We identified 36 novel phosphorylation sites, as well as confirming 3 previously-identified sites. N-terminal processing and ubiquitination of viral proteins was also detected. Phosphorylation was detected in the polymerase proteins (PB2, PB1 and PA), glycoproteins (HA and NA), nucleoprotein (NP), matrix protein (M1), ion channel (M2), non-structural protein (NS1) and nuclear export protein (NEP). Many of the phosphorylation sites detected were conserved between influenza virus genera, indicating the fundamental importance of phosphorylation for all influenza viruses. Their structural context indicates roles for phosphorylation in regulating viral entry and exit (HA and NA); nuclear localisation (PB2, M1, NP, NS1 and, through NP and NEP, of the viral RNA genome); and protein multimerisation (NS1 dimers, M2 tetramers and NP oligomers). Using reverse genetics we show that for NP of influenza A viruses phosphorylation sites in the N-terminal NLS are important for viral growth, whereas mutating sites in the C-terminus has little or no effect. Mutating phosphorylation sites in the oligomerisation domains of NP inhibits viral growth and in some cases transcription and replication of the viral RNA genome. However, constitutive phosphorylation of these sites is not optimal. Taken together, the conservation, structural context and functional significance of phosphorylation sites implies a key role for phosphorylation in influenza biology. By identifying phosphorylation sites throughout the proteomes of influenza A and B viruses we provide a framework for further study of phosphorylation events in the viral life cycle and suggest a range of potential antiviral targets.