Improving pandemic influenza risk assessment

Regulatory role of miRNAs in the human immune and inflammatory response during the infection of SARS-CoV-2 and other respiratory viruses: A comprehensive review

miRNAs are single-stranded ncRNAs that act as regulators of different human body processes. Several miRNAs have been noted to control the human immune and inflammatory response during severe acute respiratory infection syndrome (SARS-CoV-2) infection. Similarly, many miRNAs were upregulated and downregulated during different respiratory virus infections. Here, an attempt has been made to capture the regulatory role of miRNAs in the human immune and inflammatory response during the infection of SARS-CoV-2 and other respiratory viruses. Firstly, the role of miRNAs has been depicted in the human immune and inflammatory response during the infection of SARS-CoV-2. In this direction, several significant points have been discussed about SARS-CoV-2 infection, such as the role of miRNAs in human innate immune response; miRNAs and its regulation of granulocytes; the role of miRNAs in macrophage activation and polarisation; miRNAs and neutrophil extracellular trap formation; miRNA-related inflammatory response; and miRNAs association in adaptive immunity. Secondly, the miRNAs landscape has been depicted during human respiratory virus infections such as human coronavirus, respiratory syncytial virus, influenza virus, rhinovirus, and human metapneumovirus. The article will provide more understanding of the miRNA-controlled mechanism of the immune and inflammatory response during COVID-19, which will help more therapeutics discoveries to fight against the future pandemic.

Genetic Characterization and Pathogenesis of Avian Influenza Virus H3N8 Isolated from Chinese pond heron in China in 2021

In October 2021, a wild bird-origin H3N8 influenza virus-A/Chinese pond heron/Jiangxi 5-1/2021 (H3N8)-was isolated from Chinese pond heron in China. Phylogenetic and molecular analyses were performed to characterize the genetic origin of the H3N8 strain. Phylogenetic analysis revealed that eight gene segments of this avian influenza virus H3N8 belong to Eurasian lineages. HA gene clustered with avian influenza viruses is circulating in poultry in southern China. The NA gene possibly originated from wild ducks in South Korea and has the highest homology (99.3%) with A/Wild duck/South Korea/KNU2020-104/2020 (H3N8), while other internal genes have a complex and wide range of origins. The HA cleavage site is PEKQTR↓GLF with one basic amino acid, Q226 and T228 at HA preferentially bind to the alpha-2,3-linked sialic acid receptor, non-deletion of the stalk region in the NA gene and no mutations at E627K and D701N of the PB2 protein, indicating that isolate A/Chinese pond heron/Jiangxi 5-1/2021 (H3N8) was a typical avian influenza with low pathogenicity. However, there are some mutations that may increase pathogenicity and transmission in mammals, such as N30D, T215A of M1 protein, and P42S of NS1 protein. In animal studies, A/Chinese pond heron/Jiangxi 5-1/2021 (H3N8) replicates inefficiently in the mouse lung and does not adapt well to the mammalian host. Overall, A/Chinese pond heron/Jiangxi 5-1/2021 (H3N8) is a novel wild bird-origin H3N8 influenza virus reassortant from influenza viruses of poultry and wild birds. This wild bird-origin avian influenza virus is associated with wild birds along the East Asian-Australasian flyway. Therefore, surveillance of avian influenza viruses in wild birds should be strengthened to assess their mutation and pandemic risk in advance.

Assess transmissibility of different influenza subtypes: Based on a SEIABR model

OBJECTIVE

Influenza is a worldwide public health problem which causes a serious economic and health burden. In order to provide a scientific basis for improving the prevention and control level of influenza, using dynamic model to evaluate the infection rates of influenza different subtypes from 2010 to 2019 in China.

METHODS

This article established SEIABR model based on influenza cases reported by China National Influenza Center from 2010 to 2019. And calculated the transmission rate and R_e by combined the natural birth rate, natural death rate, infectious rate, proportion of asymptomatic patients, proportion of untreated patients, recovery rate and fatality rate.

RESULTS

The average infection rate of influenza was (2.38 ± 0.59) × 10^-10, and influenza A was (2.24 ± 0.51) × 10^-10, influenza B was (2.21 ± 0.68) × 10^-10. And average R_e were 1.60, 1.51, 1.49. In addition, the infection rates of A /H1N1, A/H3N2, B/Yamagata and B/Victoria were (2.47 ± 0.51) × 10^-10, (2.25 ± 0.48) × 10^-10, (2.15 ± 0.61) × 10^-10, and (2.30 ± 0.66) × 10^-10 and average R_e were 1.67, 1.52, 1.44, 1.56.

CONCLUSION

Between each year, flu transmission capacity had fluctuation. Influenza A was more transmissible than influenza B, and during the major subtypes, influenza A/H1N1 was the most transmissible.

The development trend of influenza in China from 2010 to 2019

In this study, we quantify and evaluate the transmission capacity of different types of influenza, and evaluate the flu vaccination effect. Taking the influenza cases reported by the National Influenza Center of China from 2010 to 2019 as the research object (http://www.chinaivdc.cn/cnic), we established the SEIABR model to calculate the influenza infection rate and R₀ for each year from 2010 to 2019, and calculate the influenza A and B influenza infection rates. We further added vaccination measures to the SEIABR model, and analysis the impact of different vaccination rates on the spread of influenza. We find that the range of β(infection rate) is 6.03×10−10 to 9.66×10−10, and the average is 7.95±1.27×10−10, the range of R₀ is .98 to 1.47, and the average is 1.21. Simulation result suggest that vaccine coverage needed to reach 60%-80% to control the spread of influenza virus in China when the vaccine effectiveness was 20%-40%. When the vaccine effectiveness is 40%-60%, vaccine coverage needs to reach 40%-60% to control the spread of influenza virus in China. In China, the infection rate of influenza A is higher than influenza B, to better control the spread of the flu virus, we suggest that we also need to increase the number of people vaccinated or improve the efficiency of vaccines(the current vaccination coverage is probably less than 20%).

Classification of Influenza Hemagglutinin Protein Sequences using Convolutional Neural Networks

The Influenza virus can be considered as one of the most severe viruses that can infect multiple species with often fatal consequences to the hosts. The Hemagglutinin (HA) gene of the virus can be a target for antiviral drug development realised through accurate identification of its sub-types and possible the targeted hosts. This paper focuses on accurately predicting if an Influenza type A virus can infect specific hosts, and more specifically, Human, Avian and Swine hosts, using only the protein sequence of the HA gene. In more detail, we propose encoding the protein sequences into numerical signals using the Hydrophobicity Index and subsequently utilising a Convolutional Neural Network-based predictive model. The Influenza HA protein sequences used in the proposed work are obtained from the Influenza Research Database (IRD). Specifically, complete and unique HA protein sequences were used for avian, human and swine hosts. The data obtained for this work was 17999 human-host proteins, 17667 avian-host proteins and 9278 swine-host proteins. Given this set of collected proteins, the proposed method yields as much as 10% higher accuracy for an individual class (namely, Avian) and 5% higher overall accuracy than in an earlier study. It is also observed that the accuracy for each class in this work is more balanced than what was presented in this earlier study. As the results show, the proposed model can distinguish HA protein sequences with high accuracy whenever the virus under investigation can infect Human, Avian or Swine hosts.

Drivers and Distribution of Henipavirus-Induced Syncytia: What Do We Know?

Syncytium formation, i.e., cell-cell fusion resulting in the formation of multinucleated cells, is a hallmark of infection by paramyxoviruses and other pathogenic viruses. This natural mechanism has historically been a diagnostic marker for paramyxovirus infection in vivo and is now widely used for the study of virus-induced membrane fusion in vitro. However, the role of syncytium formation in within-host dissemination and pathogenicity of viruses remains poorly understood. The diversity of henipaviruses and their wide host range and tissue tropism make them particularly appropriate models with which to characterize the drivers of syncytium formation and the implications for virus fitness and pathogenicity. Based on the henipavirus literature, we summarized current knowledge on the mechanisms driving syncytium formation, mostly acquired from in vitro studies, and on the in vivo distribution of syncytia. While these data suggest that syncytium formation widely occurs across henipaviruses, hosts, and tissues, we identified important data gaps that undermined our understanding of the role of syncytium formation in virus pathogenesis. Based on these observations, we propose solutions of varying complexity to fill these data gaps, from better practices in data archiving and publication for in vivo studies, to experimental approaches in vitro.

From Protein to Pandemic: The Transdisciplinary Approach Needed to Prevent Spillover and the Next Pandemic

Pandemics are a consequence of a series of processes that span scales from viral biology at 10-9 m to global transmission at 106 m. The pathogen passes from one host species to another through a sequence of events that starts with an infected reservoir host and entails interspecific contact, innate immune responses, receptor protein structure within the potential host, and the global spread of the novel pathogen through the naive host population. Each event presents a potential barrier to the onward passage of the virus and should be characterized with an integrated transdisciplinary approach. Epidemic control is based on the prevention of exposure, infection, and disease. However, the ultimate pandemic prevention is prevention of the spillover event itself. Here, we focus on the potential for preventing the spillover of henipaviruses, a group of viruses derived from bats that frequently cross species barriers, incur high human mortality, and are transmitted among humans via stuttering chains. We outline the transdisciplinary approach needed to prevent the spillover process and, therefore, future pandemics.

Cross-scale dynamics and the evolutionary emergence of infectious diseases

When emerging pathogens encounter new host species for which they are poorly adapted, they must evolve to escape extinction. Pathogens experience selection on traits at multiple scales, including replication rates within host individuals and transmissibility between hosts. We analyze a stochastic model linking pathogen growth and competition within individuals to transmission between individuals. Our analysis reveals a new factor, the cross-scale reproductive number of a mutant virion, that quantifies how quickly mutant strains increase in frequency when they initially appear in the infected host population. This cross-scale reproductive number combines with viral mutation rates, single-strain reproductive numbers, and transmission bottleneck width to determine the likelihood of evolutionary emergence, and whether evolution occurs swiftly or gradually within chains of transmission. We find that wider transmission bottlenecks facilitate emergence of pathogens with short-term infections, but hinder emergence of pathogens exhibiting cross-scale selective conflict and long-term infections. Our results provide a framework to advance the integration of laboratory, clinical, and field data in the context of evolutionary theory, laying the foundation for a new generation of evidence-based risk assessment of emergence threats.

Comparative Review of SARS-CoV-2, SARS-CoV, MERS-CoV, and Influenza A Respiratory Viruses

The 2019 novel coronavirus (SARS-CoV-2) pandemic has caused a global health emergency. The outbreak of this virus has raised a number of questions: What is SARS-CoV-2? How transmissible is SARS-CoV-2? How severely affected are patients infected with SARS-CoV-2? What are the risk factors for viral infection? What are the differences between this novel coronavirus and other coronaviruses? To answer these questions, we performed a comparative study of four pathogenic viruses that primarily attack the respiratory system and may cause death, namely, SARS-CoV-2, severe acute respiratory syndrome (SARS-CoV), Middle East respiratory syndrome (MERS-CoV), and influenza A viruses (H1N1 and H3N2 strains). This comparative study provides a critical evaluation of the origin, genomic features, transmission, and pathogenicity of these viruses. Because the coronavirus disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 is ongoing, this evaluation may inform public health administrators and medical experts to aid in curbing the pandemic's progression.

Deep Mutational Scanning of SARS-CoV-2 Receptor Binding Domain Reveals Constraints on Folding and ACE2 Binding

The receptor binding domain (RBD) of the SARS-CoV-2 spike glycoprotein mediates viral attachment to ACE2 receptor and is a major determinant of host range and a dominant target of neutralizing antibodies. Here, we experimentally measure how all amino acid mutations to the RBD affect expression of folded protein and its affinity for ACE2. Most mutations are deleterious for RBD expression and ACE2 binding, and we identify constrained regions on the RBD's surface that may be desirable targets for vaccines and antibody-based therapeutics. But a substantial number of mutations are well tolerated or even enhance ACE2 binding, including at ACE2 interface residues that vary across SARS-related coronaviruses. However, we find no evidence that these ACE2-affinity-enhancing mutations have been selected in current SARS-CoV-2 pandemic isolates. We present an interactive visualization and open analysis pipeline to facilitate use of our dataset for vaccine design and functional annotation of mutations observed during viral surveillance.

Deep mutational scanning of SARS-CoV-2 receptor binding domain reveals constraints on folding and ACE2 binding

The receptor binding domain (RBD) of the SARS-CoV-2 spike glycoprotein mediates viral attachment to ACE2 receptor, and is a major determinant of host range and a dominant target of neutralizing antibodies. Here we experimentally measure how all amino-acid mutations to the RBD affect expression of folded protein and its affinity for ACE2. Most mutations are deleterious for RBD expression and ACE2 binding, and we identify constrained regions on the RBD's surface that may be desirable targets for vaccines and antibody-based therapeutics. But a substantial number of mutations are well tolerated or even enhance ACE2 binding, including at ACE2 interface residues that vary across SARS-related coronaviruses. However, we find no evidence that these ACE2-affinity enhancing mutations have been selected in current SARS-CoV-2 pandemic isolates. We present an interactive visualization and open analysis pipeline to facilitate use of our dataset for vaccine design and functional annotation of mutations observed during viral surveillance.

Performance of the Public Health System During a Full-Scale Yellow Fever Simulation Exercise in Lagos State, Nigeria, in 2018: How Prepared Are We for the Next Outbreak?

Recurring outbreaks of infectious diseases have characterized the West African region in the past 4 decades. There is a moderate to high risk of yellow fever in countries in the region, and the disease has reemerged in Nigeria after 21 years. A full-scale simulation exercise of the outbreak of yellow fever was conducted to assess preparedness and response in the event of a full-scale outbreak. The exercise was a multi-agency exercise conducted in Lagos, and it involved health facilities, points of entry, state and national public health emergency operation centers, and laboratories. An evaluation of the exercise assessed the capability of the system to identify, respond to, and recover from the emergency using adapted WHO tools. The majority of participants, observers, and evaluators agreed that the exercise was well-structured and organized. Participants also strongly agreed that the exercise helped them to identify strengths and gaps in their understanding of the emergency response systems and plans. Overall, the exercise identified existing gaps in the current capabilities of several thematic areas involved in a yellow fever response. The evaluation presented an opportunity to assess the response capabilities of multisectoral collaborations in the national public health system. It also demonstrated the usefulness of the exercise in understanding public health officials' roles and responsibilities; enabling knowledge transfer among these individuals and organizations; and identifying specific public health systems-level strengths, weaknesses, and challenges.

Epidemiological and Immunological Features of Influenza Viruses in Hospitalized Children with Influenza Illness in Hangzhou

Objectives: We evaluated the epidemiological features and various inflammatory markers in hospitalized children with influenza virus infection in China. Methods: The real-time RT-PCR assay was performed for detection and genotyping of influenza A and B virus. Th1/Th2 cytokines, WBC, and CRP were determined in influenza virus positive children. Results: H1N1 and Yamagata were the prevalent genotypes of influenza A and B virus in Hangzhou, respectively. IL-2, IL-10, and CRP were significantly increased and IFN-γ was decreased in children with severe Influenza A virus infection, and TNF-α and IFN-γ levels were found to be significantly lower in children with severe Influenza B virus infection. Conclusion: Increased IL-2, IL-10, and CRP with decreased IFN-γ may indicate a severe influenza A virus infection, and decreased TNF-α and IFN-γ may indicate a severe influenza B virus infection in children.

Host microRNAs and exosomes that modulate influenza virus infection

MicroRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally regulate over half of human protein-coding genes and play a vital role in cellular development, proliferation, metabolism, and homeostasis. Exosomes are rounded or cup-like extracellular vesicles that carry proteins, mRNAs, miRNAs, and lipids for release and exchange messages between cells involved in various cellular processes. Influenza virus is a substantial public health challenge. The expression of host miRNAs is altered in response to stimulation by influenza virus. These dysregulated miRNAs directly or indirectly target viral genes to regulate viral replication and stimulate or suppress innate immune responses and cell apoptosis during viral infection. Exosomes released by infected cells are associated with the transfer of antigens and key molecules that activate and modulate immune function. Dysregulation of miRNAs and secretion of exosomes are associated with pathogenicity and immune regulation during influenza infection. This review provides a comprehensive summary of the information available regarding host miRNAs and exosomes that are involved in the modulation of influenza virus infection and will facilitate the development of preventative or therapeutic strategies against influenza virus.

Artificial Light at Night (ALAN): A Potential Anthropogenic Component for the COVID-19 and HCoVs Outbreak

The origin of the coronavirus disease 2019 (COVID-19) pandemic is zoonotic. The circadian day-night is the rhythmic clue to organisms for their synchronized body functions. The "development for mankind" escalated the use of artificial light at night (ALAN). In this article, we tried to focus on the possible influence of this anthropogenic factor in human coronavirus (HCoV) outbreak. The relationship between the occurrences of coronavirus and the ascending curve of the night-light has also been delivered. The ALAN influences the physiology and behavior of bat, a known nocturnal natural reservoir of many Coronaviridae. The "threatened" and "endangered" status of the majority of bat species is mainly because of the destruction of their proper habit and habitat predominantly through artificial illumination. The stress exerted by ALAN leads to the impaired body functions, especially endocrine, immune, genomic integration, and overall rhythm features of different physiological variables and behaviors in nocturnal animals. Night-light disturbs "virus-host" synchronization and may lead to mutation in the genomic part of the virus and excessive virus shedding. We also proposed some future strategies to mitigate the repercussions of ALAN and for the protection of the living system in the earth as well.

Pathogen Genomics in Public Health

Rapid advances in DNA sequencing technology ("next-generation sequencing") have inspired optimism about the potential of human genomics for "precision medicine." Meanwhile, pathogen genomics is already delivering "precision public health" through more effective investigations of outbreaks of foodborne illnesses, better-targeted tuberculosis control, and more timely and granular influenza surveillance to inform the selection of vaccine strains. In this article, we describe how public health agencies have been adopting pathogen genomics to improve their effectiveness in almost all domains of infectious disease. This momentum is likely to continue, given the ongoing development in sequencing and sequencing-related technologies.

Influenza A Hemagglutinin Passage Bias Sites and Host Specificity Mutations

Animal studies aimed at understanding influenza virus mutations that change host specificity to adapt to replication in mammalian hosts are necessarily limited in sample numbers due to high cost and safety requirements. As a safe, higher-throughput alternative, we explore the possibility of using readily available passage bias data obtained mostly from seasonal H1 and H3 influenza strains that were differentially grown in mammalian (MDCK) and avian cells (eggs). Using a statistical approach over 80,000 influenza hemagglutinin sequences with passage information, we found that passage bias sites are most commonly found in three regions: (i) the globular head domain around the receptor binding site, (ii) the region that undergoes pH-dependent structural changes and (iii) the unstructured N-terminal region harbouring the signal peptide. Passage bias sites were consistent among different passage cell types as well as between influenza A subtypes. We also find epistatic interactions of site pairs supporting the notion of host-specific dependency of mutations on virus genomic background. The sites identified from our large-scale sequence analysis substantially overlap with known host adaptation sites in the WHO H5N1 genetic changes inventory suggesting information from passage bias can provide candidate sites for host specificity changes to aid in risk assessment for emerging strains.

Advances in Visualization Tools for Phylogenomic and Phylodynamic Studies of Viral Diseases

Genomic and epidemiological monitoring have become an integral part of our response to emerging and ongoing epidemics of viral infectious diseases. Advances in high-throughput sequencing, including portable genomic sequencing at reduced costs and turnaround time, are paralleled by continuing developments in methodology to infer evolutionary histories (dynamics/patterns) and to identify factors driving viral spread in space and time. The traditionally static nature of visualizing phylogenetic trees that represent these evolutionary relationships/processes has also evolved, albeit perhaps at a slower rate. Advanced visualization tools with increased resolution assist in drawing conclusions from phylogenetic estimates and may even have potential to better inform public health and treatment decisions, but the design (and choice of what analyses are shown) is hindered by the complexity of information embedded within current phylogenetic models and the integration of available meta-data. In this review, we discuss visualization challenges for the interpretation and exploration of reconstructed histories of viral epidemics that arose from increasing volumes of sequence data and the wealth of additional data layers that can be integrated. We focus on solutions that address joint temporal and spatial visualization but also consider what the future may bring in terms of visualization and how this may become of value for the coming era of real-time digital pathogen surveillance, where actionable results and adequate intervention strategies need to be obtained within days.

Comprehensive mapping of adaptation of the avian influenza polymerase protein PB2 to humans

Viruses like influenza are infamous for their ability to adapt to new hosts. Retrospective studies of natural zoonoses and passaging in the lab have identified a modest number of host-adaptive mutations. However, it is unclear if these mutations represent all ways that influenza can adapt to a new host. Here we take a prospective approach to this question by completely mapping amino-acid mutations to the avian influenza virus polymerase protein PB2 that enhance growth in human cells. We identify numerous previously uncharacterized human-adaptive mutations. These mutations cluster on PB2’s surface, highlighting potential interfaces with host factors. Some previously uncharacterized adaptive mutations occur in avian-to-human transmission of H7N9 influenza, showing their importance for natural virus evolution. But other adaptive mutations do not occur in nature because they are inaccessible via single-nucleotide mutations. Overall, our work shows how selection at key molecular surfaces combines with evolutionary accessibility to shape viral host adaptation.

Viruses copy themselves by hijacking the cells of an infected host, but this comes with some limitations. Cells from different species have different molecular machinery and so viruses often have to specialize to a narrow group of species. This specialization consists largely of fine-tuning the way that viral proteins interact with host proteins.

For instance, in bird flu viruses, a protein known as PB2 does not interact well with the machinery in human cells. Because PB2 proteins form part of the viral polymerase (the structure that copies the viral genome), this prevents bird flu viruses from replicating efficiently in humans. Sometimes however, changes in the PB2 protein allow bird flu viruses to better replicate in humans, potentially leading to deadly flu pandemics.

To understand exactly how this happens, researchers have previously used two approaches: examining the changes that have happened in past flu viruses, and monitoring the evolution of bird flu viruses grown in human cells in the lab. However, these approaches can only look at a small number of the many possible genetic changes to the virus. This makes it hard to anticipate the new ways that flu might adapt to human cells in the future.

To overcome this problem, Soh et al. systematically created all of the single changes to the bird flu PB2, altering every element of the protein sequence one-by-one. They then tested which of the changes to PB2 helped the virus grow better in human cells. The modifications that made the viruses thrive were on the surface of the protein, suggesting that they might improve interaction with the cell machinery of the host. Some changes have been found in bird flu viruses that have recently jumped into humans in nature, although fortunately none of these viruses have yet spread widely to cause a pandemic.

Many factors affect the evolution of viruses, and their ability to infect new species. Understanding which changes in proteins help these microbes adapt to new hosts is an important element that scientists could consider to assess future risks of pandemics.

Fogarty International Center collaborative networks in infectious disease modeling: Lessons learnt in research and capacity building

Due to a combination of ecological, political, and demographic factors, the emergence of novel pathogens has been increasingly observed in animals and humans in recent decades. Enhancing global capacity to study and interpret infectious disease surveillance data, and to develop data-driven computational models to guide policy, represents one of the most cost-effective, and yet overlooked, ways to prepare for the next pandemic. Epidemiological and behavioral data from recent pandemics and historic scourges have provided rich opportunities for validation of computational models, while new sequencing technologies and the 'big data' revolution present new tools for studying the epidemiology of outbreaks in real time. For the past two decades, the Division of International Epidemiology and Population Studies (DIEPS) of the NIH Fogarty International Center has spearheaded two synergistic programs to better understand and devise control strategies for global infectious disease threats. The Multinational Influenza Seasonal Mortality Study (MISMS) has strengthened global capacity to study the epidemiology and evolutionary dynamics of influenza viruses in 80 countries by organizing international research activities and training workshops. The Research and Policy in Infectious Disease Dynamics (RAPIDD) program and its precursor activities has established a network of global experts in infectious disease modeling operating at the research-policy interface, with collaborators in 78 countries. These activities have provided evidence-based recommendations for disease control, including during large-scale outbreaks of pandemic influenza, Ebola and Zika virus. Together, these programs have coordinated international collaborative networks to advance the study of emerging disease threats and the field of computational epidemic modeling. A global community of researchers and policy-makers have used the tools and trainings developed by these programs to interpret infectious disease patterns in their countries, understand modeling concepts, and inform control policies. Here we reflect on the scientific achievements and lessons learnt from these programs (h-index = 106 for RAPIDD and 79 for MISMS), including the identification of outstanding researchers and fellows; funding flexibility for timely research workshops and working groups (particularly relative to more traditional investigator-based grant programs); emphasis on group activities such as large-scale modeling reviews, model comparisons, forecasting challenges and special journal issues; strong quality control with a light touch on outputs; and prominence of training, data-sharing, and joint publications.

Current and future influenza vaccines

Although antiviral drugs and vaccines have reduced the economic and healthcare burdens of influenza, influenza epidemics continue to take a toll. Over the past decade, research on influenza viruses has revealed a potential path to improvement. The clues have come from accumulated discoveries from basic and clinical studies. Now, virus surveillance allows researchers to monitor influenza virus epidemic trends and to accumulate virus sequences in public databases, which leads to better selection of candidate viruses for vaccines and early detection of drug-resistant viruses. Here we provide an overview of current vaccine options and describe efforts directed toward the development of next-generation vaccines. Finally, we propose a plan for the development of an optimal influenza vaccine.

The Geographic Variation of Surveillance and Zoonotic Spillover Potential of Influenza Viruses in Domestic Poultry and Swine

Background

Avian and swine influenza viruses circulate worldwide and pose threats to both animal and human health. The design of global surveillance strategies is hindered by information gaps on the geospatial variation in virus emergence potential and existing surveillance efforts.

Methods

We developed a spatial framework to quantify the geographic variation in outbreak emergence potential based on indices of potential for animal-to-human and secondary human-to-human transmission. We then compared our resultant raster model of variation in emergence potential with the global distribution of recent surveillance efforts from 359105 reports of surveillance activities.

Results

Our framework identified regions of Southeast Asia, Eastern Europe, Central America, and sub-Saharan Africa with high potential for influenza virus spillover. In the last 15 years, however, we found that 78.43% and 49.01% of high-risk areas lacked evidence of influenza virus surveillance in swine and domestic poultry, respectively.

Conclusions

Our work highlights priority areas where improved surveillance and outbreak mitigation could enhance pandemic preparedness strategies.

Respiratory Mononuclear Phagocytes in Human Influenza A Virus Infection: Their Role in Immune Protection and As Targets of the Virus

Emerging viruses have become increasingly important with recurrent epidemics. Influenza A virus (IAV), a respiratory virus displaying continuous re-emergence, contributes significantly to global morbidity and mortality, especially in young children, immunocompromised, and elderly people. IAV infection is typically confined to the airways and the virus replicates in respiratory epithelial cells but can also infect resident immune cells. Clearance of infection requires virus-specific adaptive immune responses that depend on early and efficient innate immune responses against IAV. Mononuclear phagocytes (MNPs), comprising monocytes, dendritic cells, and macrophages, have common but also unique features. In addition to being professional antigen-presenting cells, MNPs mediate leukocyte recruitment, sense and phagocytose pathogens, regulate inflammation, and shape immune responses. The immune protection mediated by MNPs can be compromised during IAV infection when the cells are also targeted by the virus, leading to impaired cytokine responses and altered interactions with other immune cells. Furthermore, it is becoming increasingly clear that immune cells differ depending on their anatomical location and that it is important to study them where they are expected to exert their function. Defining tissue-resident MNP distribution, phenotype, and function during acute and convalescent human IAV infection can offer valuable insights into understanding how MNPs maintain the fine balance required to protect against infections that the cells are themselves susceptible to. In this review, we delineate the role of MNPs in the human respiratory tract during IAV infection both in mediating immune protection and as targets of the virus.

Cholesterol enhances influenza binding avidity by controlling nanoscale receptor clustering

Influenza virus infects cells by binding to sialylated glycans on the cell surface. While the chemical structure of these glycans determines hemagglutinin-glycan binding affinity, bimolecular affinities are weak, so binding is avidity-dominated and driven by multivalent interactions. Here, we show that membrane spatial organization can control viral binding. Using single-virus fluorescence microscopy, we demonstrate that the sterol composition of the target membrane enhances viral binding avidity in a dose-dependent manner. Binding shows a cooperative dependence on concentration of receptors for influenza virus, as would be expected for a multivalent interaction. Surprisingly, the ability of sterols to promote viral binding is independent of their ability to support liquid-liquid phase separation in model systems. We develop a molecular explanation for this observation via molecular dynamics simulations, where we find that cholesterol promotes small-scale clusters of glycosphingolipid receptors. We propose a model whereby cholesterol orders the monomeric state of glycosphingolipid receptors, reducing the entropic penalty of receptor association and thus favoring multimeric complexes without phase separation. This model explains how cholesterol and other sterols control the spatial organization of membrane receptors for influenza and increase viral binding avidity. A natural consequence of this finding is that local cholesterol concentration in the plasma membrane of cells may alter the binding avidity of influenza virions. Furthermore, our results demonstrate a form of cholesterol-dependent membrane organization that does not involve lipid rafts, suggesting that cholesterol's effect on cell membrane heterogeneity is likely the interplay of several different factors.

Why Do Exceptionally Dangerous Gain-of-Function Experiments in Influenza?

This chapter makes the case against performing exceptionally dangerous gain-of-function experiments that are designed to create potentially pandemic and novel strains of influenza, for example, by enhancing the airborne transmissibility in mammals of highly virulent avian influenza strains. This is a question of intense debate over the last 5 years, though the history of such experiments goes back at least to the synthesis of viable influenza A H1N1 (1918) based on material preserved from the 1918 pandemic. This chapter makes the case that experiments to create potential pandemic pathogens (PPPs) are nearly unique in that they present biosafety risks that extend well beyond the experimenter or laboratory performing them; an accidental release could, as the name suggests, lead to global spread of a virulent virus, a biosafety incident on a scale never before seen. In such cases, biosafety considerations should be uppermost in the consideration of alternative approaches to experimental objectives and design, rather than being settled after the fact, as is appropriately done for most research involving pathogens. The extensive recent discussion of the magnitude of risks from such experiments is briefly reviewed. The chapter argues that, while there are indisputably certain questions that can be answered only by gain-of-function experiments in highly pathogenic strains, these questions are narrow and unlikely to meaningfully advance public health goals such as vaccine production and pandemic prediction. Alternative approaches to experimental influenza virology and characterization of existing strains are in general completely safe, higher throughput, more generalizable, and less costly than creation of PPP in the laboratory and can thereby better inform public health. Indeed, virtually every finding of recent PPP experiments that has been cited for its public health value was predated by similar findings using safe methodologies. The chapter concludes that the unique scientific and public health value of PPP experiments is inadequate to justify the unique risks they entail and that researchers would be well-advised to turn their talents to other methodologies that will be safe and more rewarding scientifically.

Local, national, and regional viral haemorrhagic fever pandemic potential in Africa: a multistage analysis

BACKGROUND

Predicting when and where pathogens will emerge is difficult, yet, as shown by the recent Ebola and Zika epidemics, effective and timely responses are key. It is therefore crucial to transition from reactive to proactive responses for these pathogens. To better identify priorities for outbreak mitigation and prevention, we developed a cohesive framework combining disparate methods and data sources, and assessed subnational pandemic potential for four viral haemorrhagic fevers in Africa, Crimean-Congo haemorrhagic fever, Ebola virus disease, Lassa fever, and Marburg virus disease.

METHODS

In this multistage analysis, we quantified three stages underlying the potential of widespread viral haemorrhagic fever epidemics. Environmental suitability maps were used to define stage 1, index-case potential, which assesses populations at risk of infection due to spillover from zoonotic hosts or vectors, identifying where index cases could present. Stage 2, outbreak potential, iterates upon an existing framework, the Index for Risk Management, to measure potential for secondary spread in people within specific communities. For stage 3, epidemic potential, we combined local and international scale connectivity assessments with stage 2 to evaluate possible spread of local outbreaks nationally, regionally, and internationally.

FINDINGS

We found epidemic potential to vary within Africa, with regions where viral haemorrhagic fever outbreaks have previously occurred (eg, western Africa) and areas currently considered non-endemic (eg, Cameroon and Ethiopia) both ranking highly. Tracking transitions between stages showed how an index case can escalate into a widespread epidemic in the absence of intervention (eg, Nigeria and Guinea). Our analysis showed Chad, Somalia, and South Sudan to be highly susceptible to any outbreak at subnational levels.

INTERPRETATION

Our analysis provides a unified assessment of potential epidemic trajectories, with the aim of allowing national and international agencies to pre-emptively evaluate needs and target resources. Within each country, our framework identifies at-risk subnational locations in which to improve surveillance, diagnostic capabilities, and health systems in parallel with the design of policies for optimal responses at each stage. In conjunction with pandemic preparedness activities, assessments such as ours can identify regions where needs and provisions do not align, and thus should be targeted for future strengthening and support.

FUNDING

Paul G Allen Family Foundation, Bill & Melinda Gates Foundation, Wellcome Trust, UK Department for International Development.

Seasonality in risk of pandemic influenza emergence

Influenza pandemics can emerge unexpectedly and wreak global devastation. However, each of the six pandemics since 1889 emerged in the Northern Hemisphere just after the flu season, suggesting that pandemic timing may be predictable. Using a stochastic model fit to seasonal flu surveillance data from the United States, we find that seasonal flu leaves a transient wake of heterosubtypic immunity that impedes the emergence of novel flu viruses. This refractory period provides a simple explanation for not only the spring-summer timing of historical pandemics, but also early increases in pandemic severity and multiple waves of transmission. Thus, pandemic risk may be seasonal and predictable, with the accuracy of pre-pandemic and real-time risk assessments hinging on reliable seasonal influenza surveillance and precise estimates of the breadth and duration of heterosubtypic immunity.

Predicting Zoonotic Risk of Influenza A Viruses from Host Tropism Protein Signature Using Random Forest

Influenza A viruses remain a significant health problem, especially when a novel subtype emerges from the avian population to cause severe outbreaks in humans. Zoonotic viruses arise from the animal population as a result of mutations and reassortments, giving rise to novel strains with the capability to evade the host species barrier and cause human infections. Despite progress in understanding interspecies transmission of influenza viruses, we are no closer to predicting zoonotic strains that can lead to an outbreak. We have previously discovered distinct host tropism protein signatures of avian, human and zoonotic influenza strains obtained from host tropism predictions on individual protein sequences. Here, we apply machine learning approaches on the signatures to build a computational model capable of predicting zoonotic strains. The zoonotic strain prediction model can classify avian, human or zoonotic strains with high accuracy, as well as providing an estimated zoonotic risk. This would therefore allow us to quickly determine if an influenza virus strain has the potential to be zoonotic using only protein sequences. The swift identification of potential zoonotic strains in the animal population using the zoonotic strain prediction model could provide us with an early indication of an imminent influenza outbreak.

Evidence for history-dependence of influenza pandemic emergence

Influenza A viruses have caused a number of global pandemics, with considerable mortality in humans. Here, we analyse the time periods between influenza pandemics since 1700 under different assumptions to determine whether the emergence of new pandemic strains is a memoryless or history-dependent process. Bayesian model selection between exponential and gamma distributions for these time periods gives support to the hypothesis of history-dependence under eight out of nine sets of modelling assumptions. Using the fitted parameters to make predictions shows a high level of variability in the modelled number of pandemics from 2010–2110. The approach we take here relies on limited data, so is uncertain, but it provides cheap, safe and direct evidence relating to pandemic emergence, a field where indirect measurements are often made at great risk and cost.

Viral factors in influenza pandemic risk assessment

The threat of an influenza A virus pandemic stems from continual virus spillovers from reservoir species, a tiny fraction of which spark sustained transmission in humans. To date, no pandemic emergence of a new influenza strain has been preceded by detection of a closely related precursor in an animal or human. Nonetheless, influenza surveillance efforts are expanding, prompting a need for tools to assess the pandemic risk posed by a detected virus. The goal would be to use genetic sequence and/or biological assays of viral traits to identify those non-human influenza viruses with the greatest risk of evolving into pandemic threats, and/or to understand drivers of such evolution, to prioritize pandemic prevention or response measures. We describe such efforts, identify progress and ongoing challenges, and discuss three specific traits of influenza viruses (hemagglutinin receptor binding specificity, hemagglutinin pH of activation, and polymerase complex efficiency) that contribute to pandemic risk.

Role of the B Allele of Influenza A Virus Segment 8 in Setting Mammalian Host Range and Pathogenicity

Two alleles of segment 8 (NS) circulate in nonchiropteran influenza A viruses. The A allele is found in avian and mammalian viruses, but the B allele is viewed as being almost exclusively found in avian viruses. This might reflect the fact that one or both of its encoded proteins (NS1 and NEP) are maladapted for replication in mammalian hosts. To test this, a number of clade A and B avian virus-derived NS segments were introduced into human H1N1 and H3N2 viruses. In no case was the peak virus titer substantially reduced following infection of various mammalian cell types. Exemplar reassortant viruses also replicated to similar titers in mice, although mice infected with viruses with the avian virus-derived segment 8s had reduced weight loss compared to that achieved in mice infected with the A/Puerto Rico/8/1934 (H1N1) parent. In vitro, the viruses coped similarly with type I interferons. Temporal proteomics analysis of cellular responses to infection showed that the avian virus-derived NS segments provoked lower levels of expression of interferon-stimulated genes in cells than wild type-derived NS segments. Thus, neither the A nor the B allele of avian virus-derived NS segments necessarily attenuates virus replication in a mammalian host, although the alleles can attenuate disease. Phylogenetic analyses identified 32 independent incursions of an avian virus-derived A allele into mammals, whereas 6 introductions of a B allele were identified. However, A-allele isolates from birds outnumbered B-allele isolates, and the relative rates of Aves-to-Mammalia transmission were not significantly different. We conclude that while the introduction of an avian virus segment 8 into mammals is a relatively rare event, the dogma of the B allele being especially restricted is misleading, with implications in the assessment of the pandemic potential of avian influenza viruses.

IMPORTANCE

Influenza A virus (IAV) can adapt to poultry and mammalian species, inflicting a great socioeconomic burden on farming and health care sectors. Host adaptation likely involves multiple viral factors. Here, we investigated the role of IAV segment 8. Segment 8 has evolved into two distinct clades: the A and B alleles. The B-allele genes have previously been suggested to be restricted to avian virus species. We introduced a selection of avian virus A- and B-allele segment 8s into human H1N1 and H3N2 virus backgrounds and found that these reassortant viruses were fully competent in mammalian host systems. We also analyzed the currently available public data on the segment 8 gene distribution and found surprisingly little evidence for specific avian host restriction of the B-clade segment. We conclude that B-allele segment 8 genes are, in fact, capable of supporting infection in mammals and that they should be considered during the assessment of the pandemic risk of zoonotic influenza A viruses.

Mapping the Resistance Potential of Influenza's H+ Channel against an Antiviral Blocker

The development of drug resistance has long plagued our efforts to curtail viral infections in general and influenza in particular. The problem is particularly challenging since the exact mode of resistance may be difficult to predict, without waiting for untreatable strains to evolve. Herein, a different approach is taken. Using a novel genetic screen, we map the resistance options of influenza's M2 channel against its aminoadamantane antiviral inhibitors. In the process, we could identify clinically known resistant mutations in a completely unbiased manner. Additionally, novel mutations were obtained, which, while known to exist in circulating viruses, were not previously classified as drug resistant. Finally, we demonstrated the approach against an anti-influenza drug that has not seen clinical use, identifying several resistance mutations in the process. In conclusion, we present and employ a method to predict the resistance options of influenza's M2 channel to antiviral agents ahead of clinical use and without medical hazard.

Complexities in Ferret Influenza Virus Pathogenesis and Transmission Models

Ferrets are widely employed to study the pathogenicity, transmissibility, and tropism of influenza viruses. However, inherent variations in inoculation methods, sampling schemes, and experimental designs are often overlooked when contextualizing or aggregating data between laboratories, leading to potential confusion or misinterpretation of results. Here, we provide a comprehensive overview of parameters to consider when planning an experiment using ferrets, collecting data from the experiment, and placing results in context with previously performed studies. This review offers information that is of particular importance for researchers in the field who rely on ferret data but do not perform the experiments themselves. Furthermore, this review highlights the breadth of experimental designs and techniques currently available to study influenza viruses in this model, underscoring the wide heterogeneity of protocols currently used for ferret studies while demonstrating the wealth of information which can benefit risk assessments of emerging influenza viruses.

Virological factors that increase the transmissibility of emerging human viruses

The early detection of pathogens with epidemic potential is of major importance to public health. Most emerging infections result in dead-end "spillover" events in which a pathogen is transmitted from an animal reservoir to a human but is unable to achieve the sustained human-to-human transmission necessary for a full-blown epidemic. It is therefore critical to determine why only some virus infections are efficiently transmitted among humans whereas others are not. We sought to determine which biological features best characterized those viruses that have achieved sustained human transmission. Accordingly, we compiled a database of 203 RNA and DNA human viruses and used an information theoretic approach to assess which of a set of key biological variables were the best predictors of human-to-human transmission. The variables analyzed were as follows: taxonomic classification; genome length, type, and segmentation; the presence or absence of an outer envelope; recombination frequency; duration of infection; host mortality; and whether or not a virus exhibits vector-borne transmission. This comparative analysis revealed multiple strong associations. In particular, we determined that viruses with low host mortality, that establish long-term chronic infections, and that are nonsegmented, nonenveloped, and, most importantly, not transmitted by vectors were more likely to be transmissible among humans. In contrast, variables including genome length, genome type, and recombination frequency had little predictive power. In sum, we have identified multiple biological features that seemingly determine the likelihood of interhuman viral transmissibility, in turn enabling general predictions of whether viruses of a particular type will successfully emerge in human populations.

What next for gain-of-function research in Europe?

A working group on gain-of-function research set up by the European Academies Science Advisory Council (EASAC) has emphasised the importance of ensuring that the necessary safeguards and policies are in place

European Academies Advise on Gain-of-Function Studies in Influenza Virus Research

Gain-of-function (GoF) studies to understand factors affecting transmissibility of potentially pandemic pathogens are controversial. The European Academies Science Advisory Council (EASAC) recently published consensus recommendations relating to GoF research review and management on self-regulation and harmonization; bioethical considerations; benefit-risk assessment; biosafety, and biosecurity advisory options; and publication of sensitive information. A layered approach to integration of responsibilities must include conforming to the stringent rules and guidance already existing. Further commitment is essential to extend the debate on issues worldwide.

Gain-of-Function Research and the Relevance to Clinical Practice

The ongoing moratorium on gain-of-function (GOF) research with highly pathogenic avian influenza virus, severe acute respiratory syndrome coronavirus, and Middle East respiratory syndrome coronavirus has drawn attention to the current debate on these research practices and the potential benefits and risks they present. While much of the discussion has been steered by members of the microbiology and policy communities, additional input from medical practitioners will be highly valuable toward developing a broadly inclusive policy that considers the relative value and harm of GOF research. This review attempts to serve as a primer on the topic for the clinical community by providing a historical context for GOF research, summarizing concerns about its risks, and surveying the medical products that it has yielded.

Mapping influenza transmission in the ferret model to transmission in humans

The controversy surrounding 'gain-of-function' experiments on high-consequence avian influenza viruses has highlighted the role of ferret transmission experiments in studying the transmission potential of novel influenza strains. However, the mapping between influenza transmission in ferrets and in humans is unsubstantiated. We address this gap by compiling and analyzing 240 estimates of influenza transmission in ferrets and humans. We demonstrate that estimates of ferret secondary attack rate (SAR) explain 66% of the variation in human SAR estimates at the subtype level. Further analysis shows that ferret transmission experiments have potential to identify influenza viruses of concern for epidemic spread in humans, though small sample sizes and biological uncertainties prevent definitive classification of human transmissibility. Thus, ferret transmission experiments provide valid predictions of pandemic potential of novel influenza strains, though results should continue to be corroborated by targeted virological and epidemiological research.

DOI:http://dx.doi.org/10.7554/eLife.07969.001

Every year, thousands of people develop influenza (flu). After being infected by the influenza virus, the immune systems of most people adapt to fight off the virus if it is encountered again. However, there are many different strains of influenza, and new strains constantly evolve. Therefore, although someone may have developed resistance to one previously encountered strain, they can still become ill if another strain infects them.

Different strains of the influenza virus have different abilities to spread between people and make them ill. One way that scientists assess whether a particular strain of influenza is a threat to people is by studying ferrets, which develop many of the same flu symptoms as humans. However, questions have been raised over how accurately ferret studies reflect whether a particular virus strain will spread between humans.

Controversy has also arisen over experiments in which ferrets are infected with genetically engineered strains of influenza that mimic how a strain that has evolved in birds could adapt to cause a pandemic in humans. In 2014, the United States government suggested that such research should be temporarily stopped until more is known about the risks and usefulness of these studies. Now, Buhnerkempe, Gostic et al. have compared the results of 240 ferret and human studies that aimed to assess how easily strains of influenza spread. Specifically, the studies looked at how often a healthy ferret or human became ill when exposed to an animal or human infected with a particular strain of influenza.

The results of the ferret transmission studies matched well with transmission patterns observed in human studies. Ferret studies that assessed how the influenza virus is transmitted through the air via sneezes and coughs were particularly good at predicting how the virus spreads in humans. But Buhnerkempe, Gostic et al. caution that ferret studies are not always accurate, partly because they involve small numbers of animals, which can skew the results. There also needs to be more effort to standardize the procedures and measurements used in ferret studies.

Still, the analysis suggests that overall, ferret studies are a useful tool for making an initial prediction of which influenza strains may cause a pandemic in humans, which can then be verified using other methods.

DOI:http://dx.doi.org/10.7554/eLife.07969.002

Fitness Inference from Short-Read Data: Within-Host Evolution of a Reassortant H5N1 Influenza Virus

We present a method to infer the role of selection acting during the within-host evolution of the influenza virus from short-read genome sequence data. Linkage disequilibrium between loci is accounted for by treating short-read sequences as noisy multilocus emissions from an underlying model of haplotype evolution. A hierarchical model-selection procedure is used to infer the underlying fitness landscape of the virus insofar as that landscape is explored by the viral population. In a first application of our method, we analyze data from an evolutionary experiment describing the growth of a reassortant H5N1 virus in ferrets. Across two sets of replica experiments we infer multiple alleles to be under selection, including variants associated with receptor binding specificity, glycosylation, and with the increased transmissibility of the virus. We identify epistasis as an important component of the within-host fitness landscape, and show that adaptation can proceed through multiple genetic pathways.