Mutation and Epistasis in Influenza Virus Evolution

Characterization of A(H1N1)pdm09 influenza viruses isolated between 2016 and 2019

The A(H1N1)pdm09 virus, which caused the 2009 influenza pandemic, has continued to circulate in humans for over a decade. Understanding its biological properties is crucial for effective surveillance, prevention, and control. Here, we characterized recently circulating A(H1N1)pdm09 viruses, focusing on strains isolated between 2016 and 2019. HA gene-based phylogenetic tree analysis revealed that post-pandemic A(H1N1)pdm09 virus strains circulating between 2016 and 2019 form two clusters: subclade 6B.1 and subclade 6B.1 A.5a. Growth kinetics of nine selected representative strains from these clusters showed that subclade 6B.1 viruses replicated well in human lung cells, whereas some subclade 6B.1 A.5a viruses replicated poorly. In vivo, all viruses from both subclades caused significantly less weight loss in infected mice compared to the prototypic pandemic strain A/California/04/2009 (Cal04/2009). Additionally, virus titers in the lungs of mice infected with most viruses from subclade 6B.1 or 6B.1 A.5a were significantly lower than those in mice infected with Cal04/2009. Furthermore, evolutionary analysis suggested multiple transitions to a less pathogenic phenotype, indicating an evolutionary trend towards attenuation. These results demonstrate that A(H1N1)pdm09 viruses isolated between 2016 and 2019 are attenuated in mice, although the mutations responsible for this attenuation require further investigation. Our findings emphasize the need for continued monitoring of A(H1N1)pdm09 viruses to understand their evolutionary dynamics and potential impact on public health.

Whole-Genome Conservation Analysis for the Specific and Accurate Detection of Influenza A and B Viruses and Respiratory Syncytial Virus by Quadruplex RT-qPCR

Influenza virus (Flu) and respiratory syncytial virus (RSV) are the primary pathogens responsible for acute respiratory infections. Both viruses are prone to mutations due to the seasonal epidemic, leading to an increasing rate of false-negative results. In this study, comprehensive meta-analyses of the genomes focusing on most conserved fragments have been performed for the four seasonal influenza viruses (two subtypes of Flu A: H1N1 and H3N2; two subtypes of Flu B: Yamagata and Victoria) and the two types of RSV: RSVA and RSVB), respectively. The most conserved sequences of 200 bp were identified as targets of the designed primer/probe sets for RT-qPCR were screened and optimized. Good sensitivities of the optimized primer/probe sets were obtained with the limits of detections of 2.95, 2.82, 1.57, 2.8, 1.19, and 2.12 copies/reaction for H1N1, H3N2, Yamagata, Victoria, RSVA and RSVB, respectively. Eventually, quadruplex qPCR using the four designed primer/probe sets can achieve simultaneous screening of the four viruses at a single tube. Furthermore, the assay's good performance in detecting target viruses from clinical throat swab samples demonstrated its potential for diagnosis of these viruses. The method, based on the identified conserved sequences and primer/probe sets, can effectively reduce false-negative results and rapidly respond to these viruses during respiratory disease outbreaks, or even before their widespread emergence, which aid in preventing outbreaks and guiding clinical treatment.

Advantages of Broad-Spectrum Influenza mRNA Vaccines and Their Impact on Pulmonary Influenza

Influenza poses a significant global health challenge due to its rapid mutation and antigenic variability, which often leads to seasonal epidemics and frequent outbreaks. Traditional vaccines struggle to offer comprehensive protection because of mismatches with circulating viral strains. The development of a broad-spectrum vaccine is therefore crucial. This paper explores the potential of mRNA vaccine technology to address these challenges by providing a swift, adaptable, and broad protective response against evolving influenza strains. We detail the mechanisms of antigenic variation in influenza viruses and discuss the rapid design and production, enhanced immunogenicity, encoding of multiple antigens, and safety and stability of mRNA vaccines compared to traditional methods. By leveraging these advantages, mRNA vaccines represent a revolutionary approach in influenza prevention, potentially offering broad-spectrum protection and significantly improving global influenza management and response strategies.

Evaluation of Trends in Influenza A and B Viruses in Wastewater and Human Surveillance Data: Insights from the 2022-2023 Season in Italy

Wastewater-based epidemiology (WBE) is a recognized, dynamic approach to monitoring the transmission of pathogens in communities through urban wastewater. This study aimed to detect and quantify influenza A and B viruses in Italian wastewater during the 2022-2023 season (October 2022 to April 2023). A total of 298 wastewater samples were collected from 67 wastewater treatment plants (WTPs) across the country. These samples were analyzed for influenza A and B viruses (IAV, IBV) using primers originally developed by the Centers for Disease Control and Prevention (CDC) for real-time PCR and adapted for digital PCR. The overall detection rates of IAV and IBV across the entire study period were 19.1% and 16.8%, respectively. The prevalence of IAV in wastewater showed a gradual increase from October to December 2022, peaking at 61% in December. In contrast, IBV peaked at 36% in February 2023. This temporal discrepancy in peak concentrations suggests different seasonal patterns for the two influenza types. These trends mirrored human surveillance data, which showed influenza A cases peaking at 46% in late December and declining to around 2% by April 2023, and influenza B cases starting to increase significantly in January 2023 and peaking at about 14% in March. IAV concentrations ranged from 9.80 × 102 to 1.94 × 105 g.c./L, while IBV concentrations ranged from 1.07 × 103 to 1.43 × 104 g.c./L. Overall, the environmental data were consistent with the human surveillance trends observed during the study period in the country. These results demonstrate the value of WBE in tracking epidemiological patterns and highlight its potential as a complementary tool to infectious diseases surveillance systems.

Local and Noninvasive Glyco-Virus Checkpoint Nanoblockades Restrict Sialylation for Prolonged Broad-Spectrum Epidemic Virus Therapy

The coronavirus disease 2019 (COVID-19) pandemic has driven major advances in virus research. The role of glycans in viral infection has been revealed, with research demonstrating that terminal sialic acids are key receptors during viral attachment and infection into host cells. However, there is an urgent demand for universal tools to study the mechanism of sialic acids in viral infections, as well as to develop therapeutic agents against epidemic viruses through the downregulation of terminal sialic acid residues on glycans acting as a glyco-virus checkpoint to accelerate virus clearance. In this study, we developed a robust sialic acids blockade tool termed local and noninvasive glyco-virus checkpoint nanoblockades (LONG NBs), which blocked cell surface sialic acids by endogenously and continuously inhibiting the de novo sialic acids biosynthesis pathway. Furthermore, LONG NBs could accurately characterize the sialic acid-dependent profiles of multiple virus variants and protected the host against partial SARS-CoV-2, rotavirus, and influenza A virus infections after local and noninvasive administration. Our results suggest that LONG NBs represent a promising tool to facilitate in-depth research on the mechanism of viral infection, and serve as a broad-spectrum protectant against existing and emerging viral variants via glyco-virus checkpoint blockade.

Preparation of a thioxoimidazolidin-linked sialoside BSA conjugate for the inhibition of influenza virus

A novel thioxoimidazolidin-linked sialoside bovine serum albumin (WM-BSA) conjugate was synthesized and evaluated as an inhibitor of influenza virus hemagglutinin (HA) and neuraminidase (NA). The multivalent conjugate was prepared by the attachment of thioxoimidazolidin-sialoside monomer (WM) to BSA via adipate linker. Surface plasmon resonance analysis revealed that WM-BSA exhibited potent binding to recombinant influenza HA and NA proteins, with dissociation constants in the submicromolar range. WM-BSA also demonstrated inhibitory activities in the low micromolar range against HA and NA proteins from multiple influenza strains. Investigation of cytopathic effects in infected MDCK cells indicated that WM-BSA possessed antiviral activity with EC50 values of 35-55 μM. The multivalent presentation of sialosides on the BSA scaffold significantly enhanced both the binding affinity and degree of inhibition compared to the monomeric compound WM. These results demonstrate the potential of multivalent sialoside-protein conjugate as a platform for developing novel anti-influenza agent.

Error thresholds in the presence of epistatic interactions

Models for viral populations with high replication error rates (such as RNA viruses) rely on the quasispecies concept, in which mutational pressure beyond the so-called "error threshold" leads to a loss of essential genetic information and population collapse, an effect known as the "error catastrophe." We explain how crossing this threshold, as a result of increasing mutation rates, can be understood as a second-order phase transition, even in the presence of lethal mutations. In particular, we show that, in fitness landscapes with a single peak, this collapse is equivalent to a ferroparamagnetic transition, where the back-mutation rate plays the role of the external magnetic field. We then generalize this framework to rugged fitness landscapes, like the ones that arise from epistatic interactions, and provide numerical evidence that there is a transition from a high average fitness regime to a low average fitness one, similarly to single-peaked landscapes. The onset of the transition is heralded by a sudden change in the susceptibility to variations in the mutation rate. We use insight from replica symmetry breaking mechanisms in spin glasses, in particular by considering the fluctuations of the genotype similarity distribution as the order parameter.

Efficient epistasis inference via higher-order covariance matrix factorization

Epistasis can profoundly influence evolutionary dynamics. Temporal genetic data, consisting of sequences sampled repeatedly from a population over time, provides a unique resource to understand how epistasis shapes evolution. However, detecting epistatic interactions from sequence data is technically challenging. Existing methods for identifying epistasis are computationally demanding, limiting their applicability to real-world data. Here, we present a novel computational method for inferring epistasis that significantly reduces computational costs without sacrificing accuracy. We validated our approach in simulations and applied it to study HIV-1 evolution over multiple years in a data set of 16 individuals. There we observed a strong excess of negative epistatic interactions between beneficial mutations, especially mutations involved in immune escape. Our method is general and could be used to characterize epistasis in other large data sets.

High-resolution and programmable RNA-IN and RNA-OUT genetic circuit in living mammalian cells

RNAs and their encoded proteins intricately regulate diverse cell types and states within the human body. Dysregulated RNA expressions or mutations can lead to various diseased cell states, including tumorigenesis. Detecting and manipulating these endogenous RNAs offers significant promise for restoring healthy cell states and targeting tumors both in research and clinical contexts. This study presents an RNA-IN and RNA-OUT genetic circuit capable dynamically sensing and manipulating any RNA target in a programmable manner. The RNA-IN module employes a programmable CRISPR-associated protease (CASP) complex for RNA detection, while the RNA-OUT module utilizes an engineered protease-responsive dCas9-VPR activator. Additionally, the CASP module can detect point mutations by harnessing an uncovered dual-nucleotide synergistic switching effect within the CASP complex, resulting in the amplification of point-mutation signals from initially undetectable levels (1.5-fold) to a remarkable 94-fold. We successfully showcase the circuit's ability to rewire endogenous RNA-IN signals to activate endogenous progesterone biosynthesis pathway, dynamically monitor adipogenic differentiation of mesenchymal stem cells (MSCs) and the epithelial-to-mesenchmal trans-differentiation, as well as selective killing of tumor cells. The programmable RNA-IN and RNA-OUT circuit exhibits tremendous potential for applications in gene therapy, biosensing and design of synthetic regulatory networks.

Influenza in feral cat populations: insights from a study in North-East Italy

Influenza A virus (IAV) can cause high morbidity and mortality in domestic and wild avian species and it is able to infect mammals as well. IAV in cats is sporadic and self-limiting but the recent findings of high pathogenicity avian influenza virus (HPAIV) with genetic signatures of mammalian adaptation, in domestic cats, has raised new concerns about the potential role of cats in the virus ecology. The present study aimed to investigate the circulation of IAV in companion animals' shelters in North-eastern Italy. All samples were collected from feral cats living in feline colonies that were hosted in the companion animals' shelters for the requisite period to administer the veterinary treatments. Between 2021 and 2022, 389 oropharyngeal swabs and 279 sera were collected. All swabs tested negative for IAV and the only one ELISA positive serum sample resulted H5 positive by HI test with a titer of 1:80. Despite the sporadic occurrence of influenza in cats, continuous monitoring is crucial due to the evolving zoonotic nature of the virus.

Waning immunity drives respiratory virus evolution and reinfection

Reinfections with respiratory viruses such as influenza viruses and coronaviruses are thought to be driven by ongoing antigenic immune escape in the viral population. However, this does not explain why antigenic variation is frequently observed in these viruses relative to viruses such as measles that undergo systemic replication. Here, we suggest that the rapid rate of waning immunity in the respiratory tract is the key driver of antigenic evolution in respiratory viruses. Waning immunity results in hosts with immunity levels that protect against homologous reinfection but are insufficient to protect against infection with a heterologous, antigenically different strain. As such, when partially immune hosts are present at a high enough density, an immune escape variant can invade the viral population even though that variant cannot infect fully immune hosts. Invasion can occur even when the variant's immune escape mutation incurs a fitness cost, and we expect the expanding mutant population will evolve compensatory mutations that mitigate this cost. Thus the mutant lineage should replace the wild-type, and as immunity to it builds, the process will repeat. Our model provides a new explanation for the pattern of successive emergence and replacement of antigenic variants that has been observed in many respiratory viruses. We discuss our model relative to others for understanding the drivers of antigenic evolution in these and other respiratory viruses.

Host obesity impacts genetic variation in influenza A viral populations

Obesity is well established as a risk factor for many noncommunicable diseases; however, its consequences for infectious disease are poorly understood. Here, we investigated the impact of host obesity on influenza A virus (IAV) genetic variation using a diet-induced obesity ferret model and the A/Hong Kong/1073/1999 (H9N2) strain. Using a co-caging study design, we investigated the maintenance, generation, and transmission of intrahost IAV genetic variation by sequencing viral genomic RNA obtained from nasal wash samples over multiple days of infection. We found evidence for an enhanced role of positive selection acting on de novo mutations in obese hosts that led to nonsynonymous changes that rose to high frequency. In addition, we identified numerous cases of mutations throughout the genome that were specific to obese hosts and that were preserved during transmission between hosts. Despite detection of obese-specific variants, the overall viral genetic diversity did not differ significantly between obese and lean hosts. This is likely due to the high supply rate of de novo variation and common evolutionary adaptations to the ferret host regardless of obesity status, which we show are mediated by variation in the hemagglutinin and polymerase genes (PB2 and PB1). We also identified defective viral genomes (DVGs) that were found uniquely in either obese or lean hosts, but the overall DVG diversity and dynamics did not differ between the two groups. Our study suggests that obesity may result in a unique selective environment impacting intrahost IAV evolution, highlighting the need for additional genetic and functional studies to confirm these effects.IMPORTANCEObesity is a chronic health condition characterized by excess adiposity leading to a systemic increase in inflammation and dysregulation of metabolic hormones and immune cell populations. Influenza A virus (IAV) is a highly infectious pathogen responsible for seasonal and pandemic influenza. Host risk factors, including compromised immunity and pre-existing health conditions, can contribute to increased infection susceptibility and disease severity. During viral replication in a host, the negative-sense single-stranded RNA genome of IAV accumulates genetic diversity that may have important consequences for viral evolution and transmission. Our study provides the first insight into the consequences of host obesity on viral genetic diversity and adaptation, suggesting that host factors associated with obesity alter the selective environment experienced by a viral population, thereby impacting the spectrum of genetic variation.

A systematic review of influenza virus in water environments across human, poultry, and wild bird habitats

Influenza, a highly contagious acute respiratory disease, remains a major global health concern. This study aimed to comprehensively assess the prevalence of influenza virus in different aquatic environments. Using 43 articles from four databases, we thoroughly examined water matrices from wastewater treatment plants (WTPs) and other human environments, as well as poultry habitats and areas frequented by migratory wild birds. In WTP influents (10 studies), positivity rates for influenza A ranged from 0.0 % to 97.6 %. For influenza B (8 studies), most studies reported no positivity, except for three studies reporting detection in 0.8 %, 5.6 %, and 46.9 % of samples. Within poultry habitats (13 studies), the prevalence of influenza A ranged from 4.3 % to 76.4 %, while in environments frequented by migratory wild birds (11 studies), it ranged from 0.4 % to 69.8 %. Geographically, the studies were distributed as follows: 39.5 % from the Americas, 18.6 % from Europe, 2.3 % from South-East Asia and 39.5 % from the Western Pacific. Several influenza A subtypes were found in water matrices, including avian influenza (H3N6, H3N8, H4N1, H4N2, H4N6, H4N8, H5N1, H5N8, H6N2, H6N6, H7N9, H0N8, and H11N9) and seasonal human influenza (H1N1 and H3N2). The existing literature indicates a crucial requirement for more extensive future research on this topic. Specifically, it emphasizes the need for method harmonization and delves into areas deserving of in-depth research, such as water matrices pertaining to pig farming and prevalence studies in low-income countries.

High-precision rapid testing of omicron SARS-CoV-2 variants in clinical samples using AI-nanopore

A digital platform that can rapidly and accurately diagnose pathogenic viral variants, including SARS-CoV-2, will minimize pandemics, public anxiety, and economic losses. We recently reported an artificial intelligence (AI)-nanopore platform that enables testing for Wuhan SARS-CoV-2 with high sensitivity and specificity within five minutes. However, which parts of the virus are recognized by the platform are unknown. Similarly, whether the platform can detect SARS-CoV-2 variants or the presence of the virus in clinical samples needs further study. Here, we demonstrated the platform can distinguish SARS-CoV-2 variants. Further, it identified mutated Wuhan SARS-CoV-2 expressing spike proteins of the delta and omicron variants, indicating it discriminates spike proteins. Finally, we used the platform to identify omicron variants with a sensitivity and specificity of 100% and 94%, respectively, in saliva specimens from COVID-19 patients. Thus, our results demonstrate the AI-nanopore platform is an effective diagnostic tool for SARS-CoV-2 variants.

Forecasting influenza hemagglutinin mutations through the lens of anomaly detection

The influenza virus hemagglutinin is an important part of the virus attachment to the host cells. The hemagglutinin proteins are one of the genetic regions of the virus with a high potential for mutations. Due to the importance of predicting mutations in producing effective and low-cost vaccines, solutions that attempt to approach this problem have recently gained significant attention. A historical record of mutations has been used to train predictive models in such solutions. However, the imbalance between mutations and preserved proteins is a big challenge for the development of such models that need to be addressed. Here, we propose to tackle this challenge through anomaly detection (AD). AD is a well-established field in Machine Learning (ML) that tries to distinguish unseen anomalies from normal patterns using only normal training samples. By considering mutations as anomalous behavior, we could benefit existing rich solutions in this field that have emerged recently. Such methods also fit the problem setup of extreme imbalance between the number of unmutated vs. mutated training samples. Motivated by this formulation, our method tries to find a compact representation for unmutated samples while forcing anomalies to be separated from the normal ones. This helps the model to learn a shared unique representation between normal training samples as much as possible, which improves the discernibility and detectability of mutated samples from the unmutated ones at the test time. We conduct a large number of experiments on four publicly available datasets, consisting of three different hemagglutinin protein datasets, and one SARS-CoV-2 dataset, and show the effectiveness of our method through different standard criteria.

Clinical, epidemiological, and genomic characteristics of a seasonal influenza A virus outbreak in Beijing: A descriptive study

China experienced a severe influenza season that began at the end of February 2023. The aim of this post hoc analysis was to investigate the clinical, epidemiological, and genomic features of this outbreak in Beijing. The number of cases increased rapidly from the end of February and reached its peak in March, with 7262 confirmed cases included in this study. The median age was 33 years, and 50.3% of them were male. The average daily positive rate reached 69% during the peak period. The instantaneous reproduction number (Rt) showed a median of 2.1, exceeded 2.5 initially, and remaining above 1 for the following month. The most common symptoms were fever (75.0%), cough (51.0%), and expectoration (42.9%), with a median body temperature of 38.5°C (interquartile range 38-39). Eight clinical symptoms were more likely to be observed in cases with fever, with odds ratio greater than 1. Viral shedding time ranged from 3 to 25 days, with median of 7.5 days. The circulating viruses in Beijing mainly included H1N1pdm09 (clades 5a.2a and 5a.2a.1), following with H3N2 (clade 2a.2a.3a.1). The descriptive study suggests that influenza viruses in this influenza season had a higher transmissibility and longer shedding duration, with fever being the most common symptom.

Mutual information networks reveal evolutionary relationships within the influenza A virus polymerase

The influenza A virus (IAV) RNA polymerase is an essential driver of IAV evolution. Mutations that the polymerase introduces into viral genome segments during replication are the ultimate source of genetic variation, including within the three subunits of the IAV polymerase (polymerase basic protein 2, polymerase basic protein 1, and polymerase acidic protein). Evolutionary analysis of the IAV polymerase is complicated, because changes in mutation rate, replication speed, and drug resistance involve epistatic interactions among its subunits. In order to study the evolution of the human seasonal H3N2 polymerase since the 1968 pandemic, we identified pairwise evolutionary relationships among ∼7000 H3N2 polymerase sequences using mutual information (MI), which measures the information gained about the identity of one residue when a second residue is known. To account for uneven sampling of viral sequences over time, we developed a weighted MI (wMI) metric and demonstrate that wMI outperforms raw MI through simulations using a well-sampled severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) dataset. We then constructed wMI networks of the H3N2 polymerase to extend the inherently pairwise wMI statistic to encompass relationships among larger groups of residues. We included hemagglutinin (HA) in the wMI network to distinguish between functional wMI relationships within the polymerase and those potentially due to hitch-hiking on antigenic changes in HA. The wMI networks reveal coevolutionary relationships among residues with roles in replication and encapsidation. Inclusion of HA highlighted polymerase-only subgraphs containing residues with roles in the enzymatic functions of the polymerase and host adaptability. This work provides insight into the factors that drive and constrain the rapid evolution of influenza viruses.

Epistasis reduces fitness costs of influenza A virus escape from stem-binding antibodies

The hemagglutinin (HA) stem region is a major target of universal influenza vaccine efforts owing to the presence of highly conserved epitopes across multiple influenza A virus (IAV) strains and subtypes. To explore the potential impact of vaccine-induced immunity targeting the HA stem, we examined the fitness effects of viral escape from stem-binding broadly neutralizing antibodies (stem-bnAbs). Recombinant viruses containing each individual antibody escape substitution showed diminished replication compared to wild-type virus, indicating that stem-bnAb escape incurred fitness costs. A second-site mutation in the HA head domain (N129D; H1 numbering) reduced the fitness effects observed in primary cell cultures and likely enabled the selection of escape mutations. Functionally, this putative permissive mutation increased HA avidity for its receptor. These results suggest a mechanism of epistasis in IAV, wherein modulating the efficiency of attachment eases evolutionary constraints imposed by the requirement for membrane fusion. Taken together, the data indicate that viral escape from stem-bnAbs is costly but highlights the potential for epistatic interactions to enable evolution within the functionally constrained HA stem domain.

Compositional biases and evolution of the largest plant RNA virus order Patatavirales

Patatavirales is the largest order of plant RNA viruses and exclusively contains the family Potyviridae, accounting for 30 % of all known plant viruses. The composition bias of animal RNA viruses and several plant RNA viruses has been determined. However, the comprehensive nucleic acid composition, codon pair usage patterns, dinucleotide preference and codon pair preference of plant RNA viruses have not been investigated to date. In this study, integrated analysis and discussion of the nucleic acid composition, codon usage patterns, dinucleotide composition and codon pair bias of potyvirids were performed using 3732 complete genome coding sequences. The nucleic acid composition of potyvirids was significantly enriched in A/U. Interestingly, the A/U-rich nucleotide composition of Patatavirales is essential for determining the preferred A-ended and U-ended codons and the overexpression of UpG and CpA dinucleotides. The codon usage patterns and codon pair bias of potyvirids were significantly correlated with their nucleic acid composition. Additionally, the codon usage pattern, dinucleotide composition and codon-pair bias of potyvirids are more dependent on the classification of the virus compared with their hosts. Our analysis provides a better understanding of future research on the origin and evolution patterns of the order Patatavirales.

Mutual information networks reveal evolutionary relationships within the influenza A virus polymerase

The influenza A (IAV) RNA polymerase is an essential driver of IAV evolution. Mutations that the polymerase introduces into viral genome segments during replication are the ultimate source of genetic variation, including within the three subunits of the IAV polymerase (PB2, PB1, and PA). Evolutionary analysis of the IAV polymerase is complicated, because changes in mutation rate, replication speed, and drug resistance involve epistatic interactions among its subunits. In order to study the evolution of the human seasonal H3N2 polymerase since the 1968 pandemic, we identified pairwise evolutionary relationships among ∼7000 H3N2 polymerase sequences using mutual information (MI), which measures the information gained about the identity of one residue when a second residue is known. To account for uneven sampling of viral sequences over time, we developed a weighted MI metric (wMI) and demonstrate that wMI outperforms raw MI through simulations using a well-sampled SARS-CoV-2 dataset. We then constructed wMI networks of the H3N2 polymerase to extend the inherently pairwise wMI statistic to encompass relationships among larger groups of residues. We included HA in the wMI network to distinguish between functional wMI relationships within the polymerase and those potentially due to hitchhiking on antigenic changes in HA. The wMI networks reveal coevolutionary relationships among residues with roles in replication and encapsidation. Inclusion of HA highlighted polymerase-only subgraphs containing residues with roles in the enzymatic functions of the polymerase and host adaptability. This work provides insight into the factors that drive and constrain the rapid evolution of influenza viruses.

Evolutionary dynamics of respiratory syncytial virus in Buenos Aires: Viral diversity, migration, and subgroup replacement

Globally, the human respiratory syncytial virus (RSV) is one of the major causes of lower respiratory tract infections (LRTIs) in children. The scarcity of complete genome data limits our understanding of RSV spatiotemporal distribution, evolution, and viral variant emergence. Nasopharyngeal samples collected from hospitalized pediatric patients from Buenos Aires tested positive for RSV LRTI during four consecutive outbreaks (2014-2017) were randomly subsampled for RSV complete genome sequencing. Phylodynamic studies and viral population characterization of genomic variability, diversity, and migration of viruses to and from Argentina during the study period were performed. Our sequencing effort resulted in one of the largest collections of RSV genomes from a given location (141 RSV-A and 135 RSV-B) published so far. RSV-B was dominant during the 2014-2016 outbreaks (60 per cent of cases) but was abruptly replaced by RSV-A in 2017, with RSV-A accounting for 90 per cent of sequenced samples. A significant decrease in RSV genomic diversity-represented by both a reduction in genetic lineages detected and the predominance of viral variants defined by signature amino acids-was observed in Buenos Aires in 2016, the year prior to the RSV subgroup predominance replacement. Multiple introductions to Buenos Aires were detected, some with persistent detection over seasons, and also, RSV was observed to migrate from Buenos Aires to other countries. Our results suggest that the decrease in viral diversity may have allowed the dramatic predominance switch from RSV-B to RSV-A in 2017. The immune pressure generated against circulating viruses with limited diversity during a given outbreak may have created a fertile ground for an antigenically divergent RSV variant to be introduced and successfully spread in the subsequent outbreak. Overall, our RSV genomic analysis of intra- and inter-outbreak diversity provides an opportunity to better understand the epochal evolutionary dynamics of RSV.

Antiviral effects of Atractyloside A on the influenza B virus (Victoria strain) infection

Influenza viruses pose a serious threat to human health, infecting hundreds of millions of people worldwide each year, resulting in a significant increase in global morbidity and mortality. Influenza activity has declined at the onset of the COVID-19 pandemic, but the genetic diversity of B/Victoria lineage viruses has increased significantly during this period. Therefore, the prevention and treatment of the influenza B Victoria strain virus should continue to attract research attention. In this study, we found that Atractyloside A (AA), one of the effective components in Atractylodes lancea (Thunb.) DC shows potential antiviral properties. This study shows that AA not only possesses anti-influenza B virus infection effects in vivo and in vitro but also can regulate macrophage polarization to the M2 type, which can effectively attenuate the damage caused by influenza B virus infection. Therefore, Atractyloside A may be an effective natural drug against B/Victoria influenza infection.

NOX2 oxidase inhibitor GSK2795039 possess antiviral activity against H1N1 influenza A virus in vitro and vivo

The continuous zoonotic circulation and reassortment potential of influenza A viruses (IAV) in nature represents an enormous public health threat to humans. Beside vaccination antivirals are needed to efficiently control spreading of the disease. The previous research has shown that NOX2 involved in IAV replication, but the detailed mechanism has not been reported. In the present study we investigated the roles of NOX2 in host inflammatory response and IAV replication using a novel inhibitor GSK2795039. The drug significantly reduced H1N1 virus induced NOX2 activity and ROS release in human lung epithelial cells. The results of time course experiments suggested that GSK2795039 inhibited an early post-entry step of viral infection. Concomitantly, there was a decreased expression of pro-inflammatory cytokines (tumor necrosis factor (TNF)-α, interferon (IFN)-β and interleukin (IL)-6) in NOX2 suppressed cells. In vivo, compared with control groups, suppression of NOX2 improved the survival rate of mice infected with H1N1 virus (42.9% in GSK2795039 treated mice versus >0% of control mice) and viral burden also decreased in the GSK2795039 treated group. Thus, our data demonstrated a critical role for NOX2 in the establishment of H1N1 infection and subsequent inflammatory reactions, which suggest that GSK2795039 may be a potential therapeutic drug for IAV infection.

Influence of viral genome properties on polymerase fidelity

The first step of viral evolution takes place during genome replication via the error-prone viral polymerase. Among the mutants that arise through this process, only a few well-adapted variants will be selected by natural selection, renewing the viral genome population. Viral polymerase-mediated errors are thought to occur stochastically. However, accumulating evidence suggests that viral polymerase-mediated mutations are heterogeneously distributed throughout the viral genome. Here, we review work that supports this concept and provides mechanistic insights into how specific features of the viral genome could modulate viral polymerase-mediated errors. A predisposition to accumulate viral polymerase-mediated errors at specific loci in the viral genome may guide evolution to specific pathways, thus opening new directions of research to better understand viral evolutionary dynamics.

Pathogen diversity in meta-population networks

The pathogen diversity means that multiple strains coexist, and widely exist in the biology systems. The new mutation of SARS-CoV-2 leading to worldwide pathogen diversity is a typical example. What are the main factors of inducing the pathogen diversity? Previous studies indicated the pathogen mutation is the most important reason for inducing the pathogen diversity. The traffic network and gene network are crucial in shaping the dynamics of pathogen contagion, while their roles for the pathogen diversity still lacking a theoretical study. To this end, we propose a reaction-diffusion process of pathogens with mutations on meta-population networks, which includes population movement and strain mutation. We extend the Microscopic Markov Chain Approach (MMCA) to describe the model. Traffic networks make pathogen diversity more likely to occur in cities with lower infection densities. The likelihood of pathogen diversity is low in cities with short effective distances in the traffic network. Star-type gene network is more likely to lead to pathogen diversity than lattice-type and chain-type gene networks. When pathogen localization is present, infection is localized to strains that are at the endpoints of the gene network. Both the increased probability of movement and mutation promote pathogen diversity. The results also show that the population tends to move to cities with short effective distances, resulting in the infection density is high.

Airborne transmission of biological agents within the indoor built environment: a multidisciplinary review

The nature and airborne dispersion of the underestimated biological agents, monitoring, analysis and transmission among the human occupants into building environment is a major challenge of today. Those agents play a crucial role in ensuring comfortable, healthy and risk-free conditions into indoor working and leaving spaces. It is known that ventilation systems influence strongly the transmission of indoor air pollutants, with scarce information although to have been reported for biological agents until 2019. The biological agents' source release and the trajectory of airborne transmission are both important in terms of optimising the design of the heating, ventilation and air conditioning systems of the future. In addition, modelling via computational fluid dynamics (CFD) will become a more valuable tool in foreseeing risks and tackle hazards when pollutants and biological agents released into closed spaces. Promising results on the prediction of their dispersion routes and concentration levels, as well as the selection of the appropriate ventilation strategy, provide crucial information on risk minimisation of the airborne transmission among humans. Under this context, the present multidisciplinary review considers four interrelated aspects of the dispersion of biological agents in closed spaces, (a) the nature and airborne transmission route of the examined agents, (b) the biological origin and health effects of the major microbial pathogens on the human respiratory system, (c) the role of heating, ventilation and air-conditioning systems in the airborne transmission and (d) the associated computer modelling approaches. This adopted methodology allows the discussion of the existing findings, on-going research, identification of the main research gaps and future directions from a multidisciplinary point of view which will be helpful for substantial innovations in the field.

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

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

Prevalence and mechanisms of evolutionary contingency in human influenza H3N2 neuraminidase

Neuraminidase (NA) of human influenza H3N2 virus has evolved rapidly and been accumulating mutations for more than half-century. However, biophysical constraints that govern the evolutionary trajectories of NA remain largely elusive. Here, we show that among 70 natural mutations that are present in the NA of a recent human H3N2 strain, >10% are deleterious for an ancestral strain. By mapping the permissive mutations using combinatorial mutagenesis and next-generation sequencing, an extensive epistatic network is revealed. Biophysical and structural analyses further demonstrate that certain epistatic interactions can be explained by non-additive stability effect, which in turn modulates membrane trafficking and enzymatic activity of NA. Additionally, our results suggest that other biophysical mechanisms also contribute to epistasis in NA evolution. Overall, these findings not only provide mechanistic insights into the evolution of human influenza NA and elucidate its sequence-structure-function relationship, but also have important implications for the development of next-generation influenza vaccines.

Serial Passaging of Seasonal H3N2 Influenza A/Singapore/G2-31.1/2014 Virus in MDCK-SIAT1 Cells and Primary Chick Embryo Cells Generates HA D457G Mutation and Other Variants in HA, NA, PB1, PB1-F2, and NS1

Influenza remains one of the most prevalent viruses circulating amongst humans and has resulted in several pandemics. The prevention and control of H3N2 influenza is complicated by its propensity for evolution, which leads to vaccine mismatch and reduced vaccine efficacies. This study employed the strategy of serial passaging to compare the evolution of the human seasonal influenza strain A/Singapore/G2-31.1/2014(H3N2) in MDCK-SIAT1 versus primary chick embryo fibroblast (CEF) cells. Genetic analysis of the HA, NS1, NA, and PB1 gene segments by Sanger sequencing revealed the presence of specific mutations and a repertoire of viral quasispecies following serial passaging. Most quasispecies were also found in PB1, which exhibited consistently high transversion-to-transition ratios in all five MDCK-SIAT1 passages. Most notably, passage 5 virus harbored the D457G substitution in the HA2 subunit, while passage 3 virus acquired K53Q and Q69H mutations in PB1-F2. An A971 variant leading to a non-synonymous R316Q substitution in PB1 was also identified in MDCK-SIAT1 passages 2 and 4. With an increasing number of passages, the proportion of D457G mutations progressively increased and was associated with larger virus plaque sizes. However, microneutralization assays revealed no significant differences in the neutralizing antibody profiles of human-influenza-immune serum samples against pre-passaged virus and passage 5 virus. In contrast, viable virus was only detected in passage 1 of CEF cells, which gave rise to multiple viral RNA quasispecies. Our findings highlight that serial passaging is able to drive differential adaptation of H3N2 influenza in different host species and may alter viral virulence. More studies are warranted to elucidate the complex relationships between H3N2 virus evolution, viral virulence changes, and low vaccine efficacy.

Seleno-Metabolites and Their Precursors: A New Dawn for Several Illnesses?

Selenium (Se) is an essential element for human health as it is involved in different physiological functions. Moreover, a great number of Se compounds can be considered potential agents in the prevention and treatment of some diseases. It is widely recognized that Se activity is related to multiple factors, such as its chemical form, dose, and its metabolism. The understanding of its complex biochemistry is necessary as it has been demonstrated that the metabolites of the Se molecules used to be the ones that exert the biological activity. Therefore, the aim of this review is to summarize the recent information about its most remarkable metabolites of acknowledged biological effects: hydrogen selenide (HSe-/H2Se) and methylselenol (CH3SeH). In addition, special attention is paid to the main seleno-containing precursors of these derivatives and their role in different pathologies.

Development of the H3N2 influenza microneedle vaccine for cross-protection against antigenic variants

Due to the continuously mutating nature of the H3N2 virus, two aspects were considered when preparing the H3N2 microneedle vaccines: (1) rapid preparation and (2) cross-protection against multiple antigenic variants. Previous methods of measuring hemagglutinin (HA) content required the standard antibody, thus rapid preparation of H3N2 microneedle vaccines targeting the mutant H3N2 was delayed as a result of lacking a standard antibody. In this study, H3N2 microneedle vaccines were prepared by high performance liquid chromatography (HPLC) without the use of an antibody, and the cross-protection of the vaccines against several antigenic variants was observed. The HA content measured by HPLC was compared with that measured by ELISA to observe the accuracy of the HPLC analysis of HA content. The cross-protection afforded by the H3N2 microneedle vaccines was evaluated against several antigenic variants in mice. Microneedle vaccines for the 2019–20 seasonal H3N2 influenza virus (19–20 A/KS/17) were prepared using a dip-coating process. The cross-protection of 19–20 A/KS/17 H3N2 microneedle vaccines against the 2015–16 seasonal H3N2 influenza virus in mice was investigated by monitoring body weight changes and survival rate. The neutralizing antibody against several H3N2 antigenic variants was evaluated using the plaque reduction neutralization test (PRNT). HA content in the solid microneedle vaccine formulation with trehalose post-exposure at 40℃ for 24 h was 48% and 43% from the initial HA content by HPLC and ELISA, respectively. The vaccine was administered to two groups of mice, one by microneedles and the other by intramuscular injection (IM). In vivo efficacies in the two groups were found to be similar, and cross-protection efficacy was also similar in both groups. HPLC exhibited good diagnostic performance with H3N2 microneedle vaccines and good agreement with ELISA. The H3N2 microneedle vaccines elicited a cross-protective immune response against the H3N2 antigenic variants. Here, we propose the use of HPLC for a more rapid approach in preparing H3N2 microneedle vaccines targeting H3N2 virus variants.

Prospective Medicinal Plants and Their Phytochemicals Shielding Autoimmune and Cancer Patients Against the SARS-CoV-2 Pandemic: A Special Focus on Matcha

Background

Being "positive" has been one of the most frustrating words anyone could hear since the end of 2019. This word had been overused globally due to the high infectious nature of SARS-CoV-2. All citizens are at risk of being infected with SARS-CoV-2, but a red warning sign has been directed towards cancer and immune-compromised patients in particular. These groups of patients are not only more prone to catch the virus but also more predisposed to its deadly consequences, something that urged the research community to seek other effective and safe solutions that could be used as a protective measurement for cancer and autoimmune patients during the pandemic.

Aim

The authors aimed to turn the spotlight on specific herbal remedies that showed potential anticancer activity, immuno-modulatory roles, and promising anti-SARS-CoV-2 actions.

Methodology

To attain the purpose of the review, the research was conducted at the States National Library of Medicine (PubMed). To search databases, the descriptors used were as follows: "COVID-19"/"SARS-CoV-2", "Herbal Drugs", "Autoimmune diseases", "Rheumatoid Arthritis", "Asthma", "Multiple Sclerosis", "Systemic Lupus Erythematosus" "Nutraceuticals", "Matcha", "EGCG", "Quercetin", "Cancer", and key molecular pathways.

Results

This manuscript reviewed most of the herbal drugs that showed a triple action concerning anticancer, immunomodulation, and anti-SARS-CoV-2 activities. Special attention was directed towards "matcha" as a novel potential protective and therapeutic agent for cancer and immunocompromised patients during the SARS-CoV-2 pandemic.

Conclusion

This review sheds light on the pivotal role of "matcha" as a tri-acting herbal tea having a potent antitumorigenic effect, immunomodulatory role, and proven anti-SARS-CoV-2 activity, thus providing a powerful shield for high-risk patients such as cancer and autoimmune patients during the pandemic.

Design, optimization, and application of multiplex rRT-PCR in the detection of respiratory viruses

Viral respiratory infections are common and serious diseases. Because there is no effective treatment method or vaccine for respiratory tract infection, early diagnosis is vital to identify the pathogen so as to determine the infectivity of the patient and to quickly take measures to curb the spread of the virus, if warranted, to avoid serious public health problems. Real-time reverse transcriptase PCR (rRT-PCR), which has high sensitivity and specificity, is the best approach for early diagnosis. Among rRT-PCR methods, multiplex rRT-PCR can resolve issues arising from various types of viruses, high mutation frequency, coinfection, and low concentrations of virus. However, the design, optimization, and validation of multiplex rRT-PCR are more complicated than singleplex rRT-PCR, and comprehensive research on multiplex rRT-PCR methodology is lacking. This review summarizes recent progress in multiplex rRT-PCR methodology, outlines the principles of design, optimization and validation, and describes a scheme to help diagnostic companies to design and optimize their multiplex rRT-PCR detection panel and to assist laboratory staff to solve problems in their daily work. In addition, the analytical validity, clinical validity and clinical utility of multiplex rRT-PCR in viral respiratory tract infection diagnosis are assessed to provide theoretical guidance and useful information for physicians to understand the test results.

Evolution and host adaptability of plant RNA viruses: Research insights on compositional biases

During recent decades, many new emerging or re-emerging RNA viruses have been found in plants through the development of deep-sequencing technology and big data analysis. These findings largely changed our understanding of the origin, evolution and host range of plant RNA viruses. There is evidence that their genetic composition originates from viruses, and host populations play a key role in the evolution and host adaptability of plant RNA viruses. In this mini-review, we describe the state of our understanding of the evolution of plant RNA viruses in view of compositional biases and explore how they adapt to the host. It appears that adenine rich (A-rich) coding sequences, low CpG and UpA dinucleotide frequencies and lower codon usage patterns were found in the vast majority of plant RNA viruses. The codon usage pattern of plant RNA viruses was influenced by both natural selection and mutation pressure, and natural selection mostly from hosts was the dominant factor. The codon adaptation analyses support that plant RNA viruses probably evolved a dynamic balance between codon adaptation and deoptimization to maintain efficient replication cycles in multiple hosts with various codon usage patterns. In the future, additional combinations of computational and experimental analyses of the nucleotide composition and codon usage of plant RNA viruses should be addressed.

Immunomodulatory Effects of α-Tocopherol on the H1N1 Influenza Vaccine: Improving the Potency and Efficacy of the Influenza Vaccine in Aged Mice

Declined immune response is the main cause of decreased potency of the influenza vaccine in the elderly, regardless of virus mutations. Herein, we hypothesized that the addition of α-tocopherol to the influenza vaccine formulation might increase vaccine potency and efficacy. Hemagglutinin of the H1N1 virus was formulated in Alum and α-tocopherol, and then aged (16-20-month-old) and young (6-8-week-old) mice were immunized subcutaneously two times with 2-week intervals with 5 μg of different vaccine formulations. Two weeks after the final boosting, IFN-γ and IL-4 cytokines were assessed by using ELISA. Humoral immune responses were assessed by hemagglutination inhibition (HI). In addition, vaccine efficacy was determined by intranasal viral challenge of mice using mouse-adapted H1N1 virus. Our results showed that the new vaccine formulation improved IFN-γ and IL-4 responses in the experimental mice. However, the increase was evident mainly in the aged group and, to some extent, in the young group. Results from the HI assay showed that α-tocopherol in the vaccine formulation could increase HI activity in both young and aged mice. Furthermore, α-tocopherol, as an adjuvant, increased the protectivity of the influenza vaccine in both aged and young groups through the decreased lung viral load and increased survival rate of the experimental mice. In conclusion, it seems that α-tocopherol can not only be used as an appropriate adjuvant for aged people, but also empower old and worn out cells to increase the effectiveness of the vaccine in the elderly.

Molecular Epidemiology and Evolutionary Dynamics of Human Influenza Type-A Viruses in Africa: A Systematic Review

Genomic characterization of circulating influenza type-A viruses (IAVs) directs the selection of appropriate vaccine formulations and early detection of potentially pandemic virus strains. However, longitudinal data on the genomic evolution and transmission of IAVs in Africa are scarce, limiting Africa's benefits from potential influenza control strategies. We searched seven databases: African Journals Online, Embase, Global Health, Google Scholar, PubMed, Scopus, and Web of Science according to the PRISMA guidelines for studies that sequenced and/or genomically characterized Africa IAVs. Our review highlights the emergence and diversification of IAVs in Africa since 1993. Circulating strains continuously acquired new amino acid substitutions at the major antigenic and potential N-linked glycosylation sites in their hemagglutinin proteins, which dramatically affected vaccine protectiveness. Africa IAVs phylogenetically mixed with global strains forming strong temporal and geographical evolution structures. Phylogeographic analyses confirmed that viral migration into Africa from abroad, especially South Asia, Europe, and North America, and extensive local viral mixing sustained the genomic diversity, antigenic drift, and persistence of IAVs in Africa. However, the role of reassortment and zoonosis remains unknown. Interestingly, we observed substitutions and clades and persistent viral lineages unique to Africa. Therefore, Africa's contribution to the global influenza ecology may be understated. Our results were geographically biased, with data from 63% (34/54) of African countries. Thus, there is a need to expand influenza surveillance across Africa and prioritize routine whole-genome sequencing and genomic analysis to detect new strains early for effective viral control.

Whole-Genome Sequence Approach and Phylogenomic Stratification Improve the Association Analysis of Mutations With Patient Data in Influenza Surveillance

Each year, seasonal influenza results in high mortality and morbidity. The current classification of circulating influenza viruses is mainly focused on the hemagglutinin gene. Whole-genome sequencing (WGS) enables tracking mutations across all influenza segments allowing a better understanding of the epidemiological effects of intra- and inter-seasonal evolutionary dynamics, and exploring potential associations between mutations across the viral genome and patient’s clinical data. In this study, mutations were identified in 253 Influenza A (H3N2) clinical isolates from the 2016-2017 influenza season in Belgium. As a proof of concept, available patient data were integrated with this genomic data, resulting in statistically significant associations that could be relevant to improve the vaccine and clinical management of infected patients. Several mutations were significantly associated with the sampling period. A new approach was proposed for exploring mutational effects in highly diverse Influenza A (H3N2) strains through considering the viral genetic background by using phylogenetic classification to stratify the samples. This resulted in several mutations that were significantly associated with patients suffering from renal insufficiency. This study demonstrates the usefulness of using WGS data for tracking mutations across the complete genome and linking these to patient data, and illustrates the importance of accounting for the viral genetic background in association studies. A limitation of this association study, especially when analyzing stratified groups, relates to the number of samples, especially in the context of national surveillance of small countries. Therefore, we investigated if international databases like GISAID may help to verify whether observed associations in the Belgium A (H3N2) samples, could be extrapolated to a global level. This work highlights the need to construct international databases with both information of viral genome sequences and patient data.

Next-generation T cell-activating vaccination increases influenza virus mutation prevalence

To determine the potential for viral adaptation to T cell responses, we probed the full influenza virus genome by next-generation sequencing directly ex vivo from infected mice, in the context of an experimental T cell-based vaccine, an H5N1-based viral vectored vaccinia vaccine Wyeth/IL-15/5Flu, versus the current standard-of-care, seasonal inactivated influenza vaccine (IIV) and unvaccinated conditions. Wyeth/IL-15/5Flu vaccination was coincident with increased mutation incidence and frequency across the influenza genome; however, mutations were not enriched within T cell epitope regions, but high allele frequency mutations within conserved hemagglutinin stem regions and PB2 mammalian adaptive mutations arose. Depletion of CD4⁺ and CD8⁺ T cell subsets led to reduced frequency of mutants in vaccinated mice; therefore, vaccine-mediated T cell responses were important drivers of virus diversification. Our findings suggest that Wyeth/IL-15/5Flu does not generate T cell escape mutants but increases stochastic events for virus adaptation by stringent bottlenecks.

Understanding the Variability of Certain Biological Properties of H1N1pdm09 Influenza Viruses

The influenza virus continually evolves because of the high mutation rate, resulting in dramatic changes in its pathogenicity and other biological properties. This study aimed to evaluate the evolution of certain essential properties, understand the connections between them, and find the molecular basis for the manifestation of these properties. To that end, 21 A(H1N1)pdm09 influenza viruses were tested for their pathogenicity and toxicity in a mouse model with a ts/non-ts phenotype manifestation and HA thermal stability. The results demonstrated that, for a strain to have high pathogenicity, it must express a toxic effect, have a non-ts phenotype, and have a thermally stable HA. The ancestor A/California/07/2009 (H1N1)pdm influenza virus expressed the non-ts phenotype, after which the cycling trend of the ts/non-ts phenotype was observed in new strains of A(H1N1)pdm09 influenza viruses, indicating that the ratio of the ts phenotype will increase in the coming years. Of the 21 tested viruses, A/South Africa/3626/2013 had the high pathogenicity in the mouse model. Sequence alignment analysis showed that this virus has three unique mutations in the polymerase complex, two of which are in the PB2 gene and one that is in the PB1 gene. Further study of these mutations might explain the distinguishing pathogenicity.

Dominant clade-featured SARS-CoV-2 co-occurring mutations reveal plausible epistasis: An in silico based hypothetical model

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved into eight fundamental clades with four of these clades (G, GH, GR, and GV) globally prevalent in 2020. To explain plausible epistatic effects of the signature co-occurring mutations of these circulating clades on viral replication and transmission fitness, we proposed a hypothetical model using in silico approach. Molecular docking and dynamics analyses showed the higher infectiousness of a spike mutant through more favorable binding of G614 with the elastase-2. RdRp mutation p.P323L significantly increased genome-wide mutations (p < 0.0001), allowing for more flexible RdRp (mutated)-NSP8 interaction that may accelerate replication. Superior RNA stability and structural variation at NSP3:C241T might impact protein, RNA interactions, or both. Another silent 5'-UTR:C241T mutation might affect translational efficiency and viral packaging. These four G-clade-featured co-occurring mutations might increase viral replication. Sentinel GH-clade ORF3a:p.Q57H variants constricted the ion-channel through intertransmembrane-domain interaction of cysteine(C81)-histidine(H57). The GR-clade N:p.RG203-204KR would stabilize RNA interaction by a more flexible and hypo-phosphorylated SR-rich region. GV-clade viruses seemingly gained the evolutionary advantage of the confounding factors; nevertheless, N:p.A220V might modulate RNA binding with no phenotypic effect. Our hypothetical model needs further retrospective and prospective studies to understand detailed molecular events and their relationship to the fitness of SARS-CoV-2.

A Detailed Overview of Immune Escape, Antibody Escape, Partial Vaccine Escape of SARS-CoV-2 and Their Emerging Variants With Escape Mutations

The infective SARS-CoV-2 is more prone to immune escape. Presently, the significant variants of SARS-CoV-2 are emerging in due course of time with substantial mutations, having the immune escape property. Simultaneously, the vaccination drive against this virus is in progress worldwide. However, vaccine evasion has been noted by some of the newly emerging variants. Our review provides an overview of the emerging variants' immune escape and vaccine escape ability. We have illustrated a broad view related to viral evolution, variants, and immune escape ability. Subsequently, different immune escape approaches of SARS-CoV-2 have been discussed. Different innate immune escape strategies adopted by the SARS-CoV-2 has been discussed like, IFN-I production dysregulation, cytokines related immune escape, immune escape associated with dendritic cell function and macrophages, natural killer cells and neutrophils related immune escape, PRRs associated immune evasion, and NLRP3 inflammasome associated immune evasion. Simultaneously we have discussed the significant mutations related to emerging variants and immune escape, such as mutations in the RBD region (N439K, L452R, E484K, N501Y, K444R) and other parts (D614G, P681R) of the S-glycoprotein. Mutations in other locations such as NSP1, NSP3, NSP6, ORF3, and ORF8 have also been discussed. Finally, we have illustrated the emerging variants' partial vaccine (BioNTech/Pfizer mRNA/Oxford-AstraZeneca/BBIBP-CorV/ZF2001/Moderna mRNA/Johnson & Johnson vaccine) escape ability. This review will help gain in-depth knowledge related to immune escape, antibody escape, and partial vaccine escape ability of the virus and assist in controlling the current pandemic and prepare for the next.

Usefulness of rapid molecular tests in pediatric respiratory tract infections

OBJECTIVE

To evaluate the role and the advantages of nasopharyngeal swabs in the detection of Influenza A and B viruses and Respiratory syncytial virus through a rapid test based upon a nucleic acid amplification reaction in order to avoid improper antibiotics use.

DESIGN

Case-control retrospective study.

SETTING

Emergency Room of "Sandro Pertini" General Hospital, Rome, Italy.

PARTICIPANTS

Children (< 14 years old) who consecutively arrived in the Emergency Department (ED) for respiratory tract infections, without obvious signs of bacterial respiratory tract infections and other comorbidities, in the maximal seasonal incidence period of November-to-March of every year between 2016 and 2020.

METHODS

Medical records of children included in the study were retrospectively examined. Children were subdivided according to the following intervals: 2016-2017 and 2017-2018 (Group 1), 2018-2019 and 2019-2020 (Group 2). Children in Group 2 undertook a nasopharyngeal swab, while those in Group 1 did not undergo any specific diagnostic test.

PRIMARY OUTCOME

Avoidance of improper antibiotics administration.

RESULTS

A total of 386 children were included in the study: 174 in Group 1, 212 in Group 2. The Odd Ratio (OR) of prescribing an antibiotic in the groups of children not being swabbed compared to those of children undertaking a swab was 9.21 (CI95% 5.6-15.2, p < 0.001). The overall percentage of hospitalizations, both in the short observation unit or in the pediatric unit, did not differ between the two groups.

CONCLUSIONS

Nasopharyngeal swabs for the detection of Influenza A and B viruses and Respiratory syncytial virus proved to be a useful means to a correct and timely diagnosis and allowed for a significant reduction in the prescription of antibiotic therapy.

TRIAL REGISTRATION

Retrospectively registered.

Antigenic evolution of human influenza H3N2 neuraminidase is constrained by charge balancing

As one of the main influenza antigens, neuraminidase (NA) in H3N2 virus has evolved extensively for more than 50 years due to continuous immune pressure. While NA has recently emerged as an effective vaccine target, biophysical constraints on the antigenic evolution of NA remain largely elusive. Here, we apply combinatorial mutagenesis and next-generation sequencing to characterize the local fitness landscape in an antigenic region of NA in six different human H3N2 strains that were isolated around 10 years apart. The local fitness landscape correlates well among strains and the pairwise epistasis is highly conserved. Our analysis further demonstrates that local net charge governs the pairwise epistasis in this antigenic region. In addition, we show that residue coevolution in this antigenic region is correlated with the pairwise epistasis between charge states. Overall, this study demonstrates the importance of quantifying epistasis and the underlying biophysical constraint for building a model of influenza evolution.

Short-hairpin RNAs delivered by recombinant adeno-associated virus inhibited the replication of influenza A viruses in vitro

Antiviral short-hairpin RNAs (shRNAs) delivered by recombinant adeno-associated virus (rAAV) were investigated for their potential prophylactic and therapeutic applications related to the influenza A virus (IAV). To express shRNAs efficiently, an H1 promoter was inserted into the commercial rAAV2 system. The modified rAAV2 system could express shRNAs, and the purified rAAV was obtained at levels over 10¹³ viral genomes/ml and 10¹⁰ viral infection units/ml. The shNP-1496-n and shM2-925 delivered by rAAV could inhibit the replication of the H1N1 and H5N1 virus by targeting the conserved regions of the IAV nucleoprotein and matrix 2 genes in MDCK cells. The shNP-1496-n and shM2-925 expressed by rAAV could provide potent and long-term anti-H5N1 virus effects in rAAV-shRNA-enriched MDCK cells. Our findings provide a rational basis for developing RNA interference for the prevention and therapy of IAV infection.

Parallel evolution between genomic segments of seasonal human influenza viruses reveals RNA-RNA relationships

The influenza A virus (IAV) genome consists of eight negative-sense viral RNA (vRNA) segments that are selectively assembled into progeny virus particles through RNA-RNA interactions. To explore putative intersegmental RNA-RNA relationships, we quantified similarity between phylogenetic trees comprising each vRNA segment from seasonal human IAV. Intersegmental tree similarity differed between subtype and lineage. While intersegmental relationships were largely conserved over time in H3N2 viruses, they diverged in H1N1 strains isolated before and after the 2009 pandemic. Surprisingly, intersegmental relationships were not driven solely by protein sequence, suggesting that IAV evolution could also be driven by RNA-RNA interactions. Finally, we used confocal microscopy to determine that colocalization of highly coevolved vRNA segments is enriched over other assembly intermediates at the nuclear periphery during productive viral infection. This study illustrates how putative RNA interactions underlying selective assembly of IAV can be interrogated with phylogenetics.

The viruses responsible for influenza evolve rapidly during infection. Changes typically emerge in two key ways: through random mutations in the genetic sequence of the virus, or by reassortment. Reassortment can occur when two or more strains infect the same cell. Once in a cell, viral particles ‘open up’ to release their genetic material so it can make copies of itself using the cell’s machinery. The new copies of the genetic material of the virus are used to make new viral particles, which then envelop the genetic material and are released from the cell to infect other cells. If several strains of a virus infect the same cell, a new viral particle may pick up genetic segments from each of the infecting strains, creating a new strain via reassortment.

Several factors are known to affect the success of the reassortment process. For example, if the new strain acquires a genetic defect that hinders its replication cycle, it is likely to die out quickly. Other times, this trading of genetic information can create a strain that is more resistant to the human immune system, allowing it to sweep across the globe and cause a deadly pandemic. However, a key part of the reassortment process that still remains unclear is how genome segments from two different influenza strains recognize each other before merging together to create hybrid daughter viruses.

To explore this further, Jones et al. used a technique called fluorescence microscopy. They found that genome segments that evolved along similar paths were more likely to cluster in the same area inside infected cells, and therefore, more likely to be reassorted together into a new strain during assembly of daughter viruses. This suggests that assembly may guide the evolutionary path taken by individual genomic segments. Jones et al. also looked at the evolution of different genome segments collected from patients suffering from seasonal influenza, and found that these segments had a distinct evolutionary path to those in pandemic-causing strains.

This research provides new insights into the role of reassortment in the evolution of influenza viruses during infection. In particular, it suggests that how the genome segments interact with one another may have a previously unknown and important role in guiding this evolution. These insights could be used to predict future reassortment events based on evolutionary relationships between influenza virus genomic segments, and may in the future be used as part of risk assessment tools to predict the emergence of new pandemic strains.

Ongoing global and regional adaptive evolution of SARS-CoV-2

Understanding the trends in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution is paramount to control the COVID-19 pandemic. We analyzed more than 300,000 high-quality genome sequences of SARS-CoV-2 variants available as of January 2021. The results show that the ongoing evolution of SARS-CoV-2 during the pandemic is characterized primarily by purifying selection, but a small set of sites appear to evolve under positive selection. The receptor-binding domain of the spike protein and the region of the nucleocapsid protein associated with nuclear localization signals (NLS) are enriched with positively selected amino acid replacements. These replacements form a strongly connected network of apparent epistatic interactions and are signatures of major partitions in the SARS-CoV-2 phylogeny. Virus diversity within each geographic region has been steadily growing for the entirety of the pandemic, but analysis of the phylogenetic distances between pairs of regions reveals four distinct periods based on global partitioning of the tree and the emergence of key mutations. The initial period of rapid diversification into region-specific phylogenies that ended in February 2020 was followed by a major extinction event and global homogenization concomitant with the spread of D614G in the spike protein, ending in March 2020. The NLS-associated variants across multiple partitions rose to global prominence in March to July, during a period of stasis in terms of interregional diversity. Finally, beginning in July 2020, multiple mutations, some of which have since been demonstrated to enable antibody evasion, began to emerge associated with ongoing regional diversification, which might be indicative of speciation.

Nano-Microparticle Platforms in Developing Next-Generation Vaccines

The first vaccines ever made were based on live-attenuated or inactivated pathogens, either whole cells or fragments. Although these vaccines required the co-administration of antigens with adjuvants to induce a strong humoral response, they could only elicit a poor CD8⁺ T-cell response. In contrast, next-generation nano/microparticle-based vaccines offer several advantages over traditional ones because they can induce a more potent CD8⁺ T-cell response and, at the same time, are ideal carriers for proteins, adjuvants, and nucleic acids. The fact that these nanocarriers can be loaded with molecules able to modulate the immune response by inducing different effector functions and regulatory activities makes them ideal tools for inverse vaccination, whose goal is to shut down the immune response in autoimmune diseases. Poly (lactic-co-glycolic acid) (PLGA) and liposomes are biocompatible materials approved by the Food and Drug Administration (FDA) for clinical use and are, therefore, suitable for nanoparticle-based vaccines. Recently, another candidate platform for innovative vaccines based on extracellular vesicles (EVs) has been shown to efficiently co-deliver antigens and adjuvants. This review will discuss the potential use of PLGA-NPs, liposomes, and EVs as carriers of peptides, adjuvants, mRNA, and DNA for the development of next-generation vaccines against endemic and emerging viruses in light of the recent COVID-19 pandemic.

Development and Effects of Influenza Antiviral Drugs

Influenza virus is a highly contagious zoonotic respiratory disease that causes seasonal outbreaks each year and unpredictable pandemics occasionally with high morbidity and mortality rates, posing a great threat to public health worldwide. Besides the limited effect of vaccines, the problem is exacerbated by the lack of drugs with strong antiviral activity against all flu strains. Currently, there are two classes of antiviral drugs available that are chemosynthetic and approved against influenza A virus for prophylactic and therapeutic treatment, but the appearance of drug-resistant virus strains is a serious issue that strikes at the core of influenza control. There is therefore an urgent need to develop new antiviral drugs. Many reports have shown that the development of novel bioactive plant extracts and microbial extracts has significant advantages in influenza treatment. This paper comprehensively reviews the development and effects of chemosynthetic drugs, plant extracts, and microbial extracts with influenza antiviral activity, hoping to provide some references for novel antiviral drug design and promising alternative candidates for further anti-influenza drug development.

Aging in COVID-19: Vulnerability, immunity and intervention

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic was first reported in Wuhan, China in December 2019, moved across the globe at an unprecedented speed, and is having a profound and yet still unfolding health and socioeconomic impacts. SARS-CoV-2, a β-coronavirus, is a highly contagious respiratory pathogen that causes a disease that has been termed the 2019 coronavirus disease (COVID-19). Clinical experience thus far indicates that COVID-19 is highly heterogeneous, ranging from being asymptomatic and mild to severe and causing death. Host factors including age, sex, and comorbid conditions are key determinants of disease severity and progression. Aging itself is a prominent risk factor for severe disease and death from COVID-19. We hypothesize that age-related decline and dysregulation of immune function, i.e., immunosenescence and inflammaging play a major role in contributing to heightened vulnerability to severe COVID-19 outcomes in older adults. Much remains to be learned about the immune responses to SARS-CoV-2 infection. We need to begin partitioning all immunological outcome data by age to better understand disease heterogeneity and aging. Such knowledge is critical not only for understanding of COVID-19 pathogenesis but also for COVID-19 vaccine development.

Quantifying mechanistic traits of influenza viral dynamics using in vitro data

When analysing in vitro data, growth kinetics of influenza virus strains are often compared by computing their growth rates, which are sometimes used as proxies for fitness. However, analogous to mathematical models for epidemics, the growth rate can be defined as a function of mechanistic traits: the basic reproduction number (the average number of cells each infected cell infects) and the mean generation time (the average length of a replication cycle). Fitting a model to previously published and newly generated data from experiments in human lung cells, we compared estimates of growth rate, reproduction number and generation time for six influenza A strains. Of four strains in previously published data, A/Canada/RV733/2003 (seasonal H1N1) had the lowest basic reproduction number, followed by A/Mexico/INDRE4487/2009 (pandemic H1N1), then A/Indonesia/05/2005 (spill-over H5N1) and A/Anhui/1/2013 (spill-over H7N9). This ordering of strains was preserved for both generation time and growth rate, suggesting a positive biological correlation between these quantities which have not been previously observed. We further investigated these potential correlations using data from reassortant viruses with different internal proteins (from A/England/195/2009 (pandemic H1N1) and A/Turkey/05/2005 (H5N1)), and the same surface proteins (from A/Puerto Rico/8/34 (lab-adapted H1N1)). Similar correlations between traits were observed for these viruses, confirming our initial findings and suggesting that these patterns were related to the degree of human adaptation of internal genes. Also, the model predicted that strains with a smaller basic reproduction number, shorter generation time and slower growth rate underwent more replication cycles by the time of peak viral load, potentially accumulating mutations more quickly. These results illustrate the utility of mathematical models in inferring traits driving observed differences in in vitro growth of influenza strains.