A novel twelve class fluctuation test reveals higher than expected mutation rates for influenza A viruses

Influenza A defective viral genome production is altered by metabolites, metabolic signaling molecules, and cyanobacteria extracts

RNA virus infections are composed of a diverse mix of viral genomes that arise from low fidelity in replication within cells. The interactions between "defective" and full-length viral genomes have been shown to shape pathogenesis, leading to intense research into employing these to develop novel antivirals. In particular, Influenza A defective viral genomes (DVGs) have been associated with milder clinical outcomes. Yet, the full potential of DVGs as broad-spectrum antivirals remains untapped due to the unknown mechanisms of their de novo production. Much of the research into the factors affecting defective viral genome production has focused on the virus, while the role of the host has been neglected. We recently showed that altering host cell metabolism away from pro-growth pathways using alpelisib increased the production of Influenza A defective viral genomes. To uncover other drugs that could induce infections to create more DVGs, we subjected active influenza infections of the two circulating human subtypes (A/H1N1 & A/H3N2) to a screen of metabolites, metabolic signaling molecules, and cyanobacteria-derived biologics, after which we quantified the defective viral genomes (specifically deletion-containing viral genomes, DelVGs) and total viral genomes using third generation long-read sequencing. Here we show that metabolites and signaling molecules of host cell central carbon metabolism can significantly alter DelVG production early in Influenza A infection. Adenosine, emerged as a potent inducer of defective viral genomes, significantly amplifying DelVG production across both subtypes. Insulin had similar effects, albeit subtype-specific, predominantly enhancing polymerase segment DVGs in TX12 infections. Tricarboxylic Acid (TCA) cycle inhibitors 4-octyl itaconate and UK5099, along with the purine analog favipiravir, increased total viral genome production across subtypes. Cyanobacterial extracts primarily affected DVG and total viral genome production in TX12, with a specific, almost complete shutdown of influenza antigenic segments. These results underscore the influence of host metabolic pathways on DVG production and suggest new avenues for antiviral intervention, including PI3K-AKT and Ras-MAPK signaling pathways, TCA cycle metabolism, purine-pyrimidine metabolism, polymerase inhibition, and cyanotherapeutic approaches. More broadly, our findings suggest that the social interactions observed between defective and full-length viral genomes, depend not only on the viral actors, but can be altered by the stage provided by the host. Our study advances our fundamental understanding of DVG production mechanisms and highlights the potential of targeting host metabolism to develop broad-spectrum influenza therapeutics.

Natural variation in neuraminidase activity influences the evolutionary potential of the seasonal H1N1 lineage hemagglutinin

The antigenic evolution of the influenza A virus hemagglutinin (HA) gene poses a major challenge for the development of vaccines capable of eliciting long-term protection. Prior efforts to understand the mechanisms that govern viral antigenic evolution mainly focus on HA in isolation, ignoring the fact that HA must act in concert with the viral neuraminidase (NA) during replication and spread. Numerous studies have demonstrated that the degree to which the receptor-binding avidity of HA and receptor-cleaving activity of NA are balanced with each other influences overall viral fitness. We recently showed that changes in NA activity can significantly alter the mutational fitness landscape of HA in the context of a lab-adapted virus strain. Here, we test whether natural variation in relative NA activity can influence the evolutionary potential of HA in the context of the seasonal H1N1 lineage (pdmH1N1) that has circulated in humans since the 2009 pandemic. We observed substantial variation in the relative activities of NA proteins encoded by a panel of H1N1 vaccine strains isolated between 2009 and 2019. We comprehensively assessed the effect of NA background on the HA mutational fitness landscape in the circulating pdmH1N1 lineage using deep mutational scanning and observed pronounced epistasis between NA and residues in or near the receptor-binding site of HA. To determine whether NA variation could influence the antigenic evolution of HA, we performed neutralizing antibody selection experiments using a panel of monoclonal antibodies targeting different HA epitopes. We found that the specific antibody escape profiles of HA were highly contingent upon NA background. Overall, our results indicate that natural variation in NA activity plays a significant role in governing the evolutionary potential of HA in the currently circulating pdmH1N1 lineage.

Defective viral genomes: advances in understanding their generation, function, and impact on infection outcomes

Defective viral genomes (DVGs) are truncated derivatives of their parental viral genomes generated during an aberrant round of viral genomic replication. Distinct classes of DVGs have been identified in most families of both positive- and negative-sense RNA viruses. Importantly, DVGs have been detected in clinical samples from virally infected individuals and an emerging body of association studies implicates DVGs in shaping the severity of disease caused by viral infections in humans. Consequently, there is growing interest in understanding the molecular mechanisms of de novo DVG generation, how DVGs interact with the innate immune system, and harnessing DVGs as novel therapeutics and vaccine adjuvants to attenuate viral pathogenesis. This minireview focuses on single-stranded RNA viruses (excluding retroviridae), and summarizes the current knowledge of DVG generation, the functions and diversity of DVG species, the roles DVGs play in influencing disease progression, and their application as antivirals and vaccine adjuvants.

Cryptic proteins translated from deletion-containing viral genomes dramatically expand the influenza virus proteome

Productive infections by RNA viruses require faithful replication of the entire genome. Yet many RNA viruses also produce deletion-containing viral genomes (DelVGs), aberrant replication products with large internal deletions. DelVGs interfere with the replication of wild-type virus and their presence in patients is associated with better clinical outcomes. The DelVG RNA itself is hypothesized to confer this interfering activity. DelVGs antagonize replication by out-competing the full-length genome and triggering innate immune responses. Here, we identify an additionally inhibitory mechanism mediated by a new class of viral proteins encoded by DelVGs. We identified hundreds of cryptic viral proteins translated from DelVGs. These DelVG-encoded proteins (DPRs) include canonical viral proteins with large internal deletions, as well as proteins with novel C-termini translated from alternative reading frames. Many DPRs retain functional domains shared with their full-length counterparts, suggesting they may have activity during infection. Mechanistic studies of DPRs derived from the influenza virus protein PB2 showed that they poison replication of wild-type virus by acting as dominant-negative inhibitors of the viral polymerase. These findings reveal that DelVGs have a dual inhibitory mechanism, acting at both the RNA and protein level. They further show that DPRs have the potential to dramatically expand the functional proteomes of diverse RNA viruses.

Cryptic proteins translated from deletion-containing viral genomes dramatically expand the influenza virus proteome

Productive infections by RNA viruses require faithful replication of the entire genome. Yet many RNA viruses also produce deletion-containing viral genomes (DelVGs), aberrant replication products with large internal deletions. DelVGs interfere with the replication of wild-type virus and their presence in patients is associated with better clinical outcomes as they. The DelVG RNA itself is hypothesized to confer this interfering activity. DelVGs antagonize replication by out-competing the full-length genome and triggering innate immune responses. Here, we identify an additionally inhibitory mechanism mediated by a new class of viral proteins encoded by DelVGs. We identified hundreds of cryptic viral proteins translated from DelVGs. These DelVG-encoded proteins (DPRs) include canonical viral proteins with large internal deletions, as well as proteins with novel C-termini translated from alternative reading frames. Many DPRs retain functional domains shared with their full-length counterparts, suggesting they may have activity during infection. Mechanistic studies of DPRs derived from the influenza virus protein PB2 showed that they poison replication of wild-type virus by acting as dominant-negative inhibitors of the viral polymerase. These findings reveal that DelVGs have a dual inhibitory mechanism, acting at both the RNA and protein level. They further show that DPRs have the potential to dramatically expand the functional proteomes of diverse RNA viruses.

Genotyping SNPs in lignin biosynthesis gene (CAD1) and transcription factors (MYB1 and MYB2) exhibits association with wood density in teak (Tectona grandis L.f.)

BACKGROUND

Teak (Tectona grandis L.f.), an important source of tropical timber with immense economic value, is a highly outcrossing forest tree species. 150 unrelated accessions of teak (Tectona grandis L.f.) plus trees assembled as clones at National Teak Germplasm Bank, Chandrapur, Maharashtra, India was investigated for association mapping of candidate lignin biosynthesis gene (CAD1) and transcription factors (MYB1 and MYB2).

METHODS AND RESULTS

The CAD1, MYB1 and MYB2 were amplified using specifically designed primers. The amplified sequences were then sequenced and genotyped for 112 SNPs/11 indels. We evaluated the association between SNPs and wood density in teak accessions using GLM and MLM statistical models, with Bonferroni correction applied. The teak accessions recorded an average wood density of 416.69 kg.m-3 (CV 4.97%) and comprised of three loosely structured admixed sub-populations (K = 3), containing 72.05% genetic variation within sub-populations with low intragenic LD (0-21% SNP pairs) at P < 0.05 and high LD decay (33-934 bp) at R2 = 0.1. GLM and MLM models discounting systematic biases (Q and K matrices) to avoid false discovery revealed five loci at rare variants (MAF 0.003) and three loci at common variants (MAF 0.05) to be significantly (P < 0.05) associated with the wood density. However, the stringent Bonferroni correction (4.06-7.04 × 10-4) yielded only a single associated locus (B1485C/A) from exon of MYB1 transcription factor, contributing to about 10.35% phenotypic variation in wood density trait.

CONCLUSION

Scored SNP locus (B1485C/A) can be developed as a molecular probe for selection of improved planting stock with proven wood density trait for a large-scale teak plantation.

Transmission Bottleneck Size Estimation from De Novo Viral Genetic Variation

Sequencing of viral infections has become increasingly common over the last decade. Deep sequencing data in particular have proven useful in characterizing the roles that genetic drift and natural selection play in shaping within-host viral populations. They have also been used to estimate transmission bottleneck sizes from identified donor-recipient pairs. These bottleneck sizes quantify the number of viral particles that establish genetic lineages in the recipient host and are important to estimate due to their impact on viral evolution. Current approaches for estimating bottleneck sizes exclusively consider the subset of viral sites that are observed as polymorphic in the donor individual. However, these approaches have the potential to substantially underestimate true transmission bottleneck sizes. Here, we present a new statistical approach for instead estimating bottleneck sizes using patterns of viral genetic variation that arise de novo within a recipient individual. Specifically, our approach makes use of the number of clonal viral variants observed in a transmission pair, defined as the number of viral sites that are monomorphic in both the donor and the recipient but carry different alleles. We first test our approach on a simulated dataset and then apply it to both influenza A virus sequence data and SARS-CoV-2 sequence data from identified transmission pairs. Our results confirm the existence of extremely tight transmission bottlenecks for these 2 respiratory viruses.

Genome wide mining of SNPs and INDELs through ddRAD sequencing in Sahiwal cattle

The study was conducted in Sahiwal cattle for genome wide identification and annotation of single nucleotide polymorphisms (SNPs) and insertions and deletions (INDELs) in Sahiwal cattle. The double digest restriction-site associated DNA (ddRAD) sequencing, a reduced representation method was used for the identification of variants at nucleotide level. A total of 1,615,211 variants were identified at RD10 and Q30 consisting of 1,480,930 SNPs and 134,281 INDELs with respect to the Bos taurus reference genome. The SNPs were annotated for their location, impact and functional class. The SNPs identified in Sahiwal cattle were found to be associated with a total of 26,229 genes. A total of 1819 SNPs were annotated for 209 candidate genes associated with different production and reproduction traits. The variants identified in the present study may be useful to strengthen the existing bovine SNP chips for reducing the biasness over the taurine cattle breeds. The diversity analysis provides the insight of the genetic architecture of the Sahiwal population Studied. The large genetic variations identified at the nucleotide level provide ample scope for implementing an effective and efficient breed improvement programme for increasing the productivity of Sahiwal cattle.

Evolution of transient RNA structure-RNA polymerase interactions in respiratory RNA virus genomes

RNA viruses are important human pathogens that cause seasonal epidemics and occasional pandemics. Examples are influenza A viruses (IAV) and coronaviruses (CoV). When emerging IAV and CoV spill over to humans, they adapt to evade immune responses and optimize their replication and spread in human cells. In IAV, adaptation occurs in all viral proteins, including the viral ribonucleoprotein (RNP) complex. RNPs consist of a copy of the viral RNA polymerase, a double-helical coil of nucleoprotein, and one of the eight segments of the IAV RNA genome. The RNA segments and their transcripts are partially structured to coordinate the packaging of the viral genome and modulate viral mRNA translation. In addition, RNA structures can affect the efficiency of viral RNA synthesis and the activation of host innate immune response. Here, we investigated if RNA structures that modulate IAV replication processivity, so-called template loops (t-loops), vary during the adaptation of pandemic and emerging IAV to humans. Using cell culture-based replication assays and in silico sequence analyses, we find that the sensitivity of the IAV H3N2 RNA polymerase to t-loops increased between isolates from 1968 and 2017, whereas the total free energy of t-loops in the IAV H3N2 genome was reduced. This reduction is particularly prominent in the PB1 gene. In H1N1 IAV, we find two separate reductions in t-loop free energy, one following the 1918 pandemic and one following the 2009 pandemic. No destabilization of t-loops is observed in the influenza B virus genome, whereas analysis of SARS-CoV-2 isolates reveals destabilization of viral RNA structures. Overall, we propose that a loss of free energy in the RNA genome of emerging respiratory RNA viruses may contribute to the adaption of these viruses to the human population.

Investigating the Genetic Diversity of H5 Avian Influenza Viruses in the United Kingdom from 2020-2022

Since 2020, the United Kingdom and Europe have experienced annual epizootics of high-pathogenicity avian influenza virus (HPAIV). The first epizootic, during the autumn/winter of 2020-2021, involved six H5Nx subtypes, although H5N8 HPAIV dominated in the United Kingdom. While genetic assessments of the H5N8 HPAIVs within the United Kingdom demonstrated relative homogeneity, there was a background of other genotypes circulating at a lower degree with different neuraminidase and internal genes.  Following a small number of detections of H5N1 in wild birds over the summer of 2021, the autumn/winter of 2021-2022 saw another European H5 HPAIV epizootic that dwarfed the prior epizootic. This second epizootic was dominated almost exclusively by H5N1 HPAIV, although six distinct genotypes were defined. We have used genetic analysis to evaluate the emergence of different genotypes and proposed reassortment events that have been observed. The existing data suggest that the H5N1 viruses circulating in Europe during late 2020 continued to circulate in wild birds throughout 2021, with minimal adaptation, but then went on to reassort with AIVs in the wild bird population. We have undertaken an in-depth genetic assessment of H5 HPAIVs detected in the United Kingdom over two winter seasons and demonstrate the utility of in-depth genetic analyses in defining the diversity of H5 HPAIVs circulating in avian species, the potential for zoonotic risk, and whether incidents of lateral spread can be defined over independent incursions of infections from wild birds. This provides key supporting data for mitigation activities. IMPORTANCE High-pathogenicity avian influenza virus (HPAIV) outbreaks devastate avian species across all sectors, having both economic and ecological impacts through mortalities in poultry and wild birds, respectively. These viruses can also represent a significant zoonotic risk. Since 2020, the United Kingdom has experienced two successive outbreaks of H5 HPAIV. While H5N8 HPAIV was predominant during the 2020-2021 outbreak, other H5 subtypes were also detected. The following year, there was a shift in the subtype dominance to H5N1 HPAIV, but multiple H5N1 genotypes were detected. Through the thorough utilization of whole-genome sequencing, it was possible to track and characterize the genetic evolution of these H5 HPAIVs in United Kingdom poultry and wild birds. This enabled us to assess the risk posed by these viruses at the poultry-wild bird and the avian-human interfaces and to investigate the potential lateral spread between infected premises, a key factor in understanding the threat to the commercial sector.

Transmission bottleneck size estimation from de novo viral genetic variation

Sequencing of viral infections has become increasingly common over the last decade. Deep sequencing data in particular have proven useful in characterizing the roles that genetic drift and natural selection play in shaping within-host viral populations. They have also been used to estimate transmission bottleneck sizes from identified donor-recipient pairs. These bottleneck sizes quantify the number of viral particles that establish genetic lineages in the recipient host and are important to estimate due to their impact on viral evolution. Current approaches for estimating bottleneck sizes exclusively consider the subset of viral sites that are observed as polymorphic in the donor individual. However, allele frequencies can change dramatically over the course of an individual's infection, such that sites that are polymorphic in the donor at the time of transmission may not be polymorphic in the donor at the time of sampling and allele frequencies at donor-polymorphic sites may change dramatically over the course of a recipient's infection. Because of this, transmission bottleneck sizes estimated using allele frequencies observed at a donor's polymorphic sites may be considerable underestimates of true bottleneck sizes. Here, we present a new statistical approach for instead estimating bottleneck sizes using patterns of viral genetic variation that arose de novo within a recipient individual. Specifically, our approach makes use of the number of clonal viral variants observed in a transmission pair, defined as the number of viral sites that are monomorphic in both the donor and the recipient but carry different alleles. We first test our approach on a simulated dataset and then apply it to both influenza A virus sequence data and SARS-CoV-2 sequence data from identified transmission pairs. Our results confirm the existence of extremely tight transmission bottlenecks for these two respiratory viruses, using an approach that does not tend to underestimate transmission bottleneck sizes.

Evolution of transient RNA structure-RNA polymerase interactions in respiratory RNA virus genomes

RNA viruses are important human pathogens that cause seasonal epidemics and occasional pandemics. Examples are influenza A viruses (IAV) and coronaviruses (CoV). When emerging IAV and CoV spill over to humans, they adapt to evade immune responses and optimize their replication and spread in human cells. In IAV, adaptation occurs in all viral proteins, including the viral ribonucleoprotein (RNP) complex. RNPs consists of a copy of the viral RNA polymerase, a double-helical coil of nucleoprotein, and one of the eight segments of the IAV RNA genome. The RNA segments and their transcripts are partially structured to coordinate the packaging of the viral genome and modulate viral mRNA translation. In addition, RNA structures can affect the efficiency of viral RNA synthesis and the activation of host innate immune response. Here, we investigated if RNA structures that modulate IAV replication processivity, so called template loops (t-loops), vary during the adaptation of pandemic and emerging IAV to humans. Using cell culture-based replication assays and in silico sequence analyses, we find that the sensitivity of the IAV H3N2 RNA polymerase to t-loops increased between isolates from 1968 and 2017, whereas the total free energy of t-loops in the IAV H3N2 genome was reduced. This reduction is particularly prominent in the PB1 gene. In H1N1 IAV, we find two separate reductions in t-loop free energy, one following the 1918 pandemic and one following the 2009 pandemic. No destabilization of t-loops is observed in the IBV genome, whereas analysis of SARS-CoV-2 isolates reveals destabilization of viral RNA structures. Overall, we propose that a loss of free energy in the RNA genome of emerging respiratory RNA viruses may contribute to the adaption of these viruses to the human population.

Single-cell mutation rate of turnip crinkle virus (-)-strand replication intermediates

Viruses with single-stranded, positive-sense (+) RNA genomes incur high numbers of errors during replication, thereby creating diversified genome populations from which new, better adapted viral variants can emerge. However, a definitive error rate is known for a relatively few (+) RNA plant viruses, due to challenges to account for perturbations caused by natural selection and/or experimental set-ups. To address these challenges, we developed a new approach that exclusively profiled errors in the (-)-strand replication intermediates of turnip crinkle virus (TCV), in singly infected cells. A series of controls and safeguards were devised to ensure errors inherent to the experimental process were accounted for. This approach permitted the estimation of a TCV error rate of 8.47 X 10-5 substitution per nucleotide site per cell infection. Importantly, the characteristic error distribution pattern among the 50 copies of 2,363-base-pair cDNA fragments predicted that nearly all TCV (-) strands were products of one replication cycle per cell. Furthermore, some of the errors probably elevated error frequencies by lowering the fidelity of TCV RNA-dependent RNA polymerase, and/or permitting occasional re-replication of progeny genomes. In summary, by profiling errors in TCV (-)-strand intermediates incurred during replication in single cells, this study provided strong support for a stamping machine mode of replication employed by a (+) RNA virus.

Predicting evolutionary outcomes through the probability of accessing sequence variants

Natural selection can only operate on available genetic variation. Thus, determining the probability of accessing different sequence variants from a starting sequence can help predict evolutionary trajectories and outcomes. We define the concept of "variant accessibility" as the probability that a set of genotypes encoding a particular protein function will arise through mutations before subject to natural selection. This probability is shaped by the mutational biases of nucleotides and the structure of the genetic code. Using the influenza A virus as a model, we discuss how a more accessible but less fit variant can emerge as an adaptation rather than a more fit variant. We describe a genotype-accessibility landscape, complementary to the genotype-fitness landscape, that informs the likelihood of a starting sequence reaching different parts of genotype space. The proposed framework lays the foundation for predicting the emergence of adaptive genotypes in evolving systems such as viruses and tumors.

The combined effect of oseltamivir and favipiravir on influenza a virus evolution in patients hospitalized with severe influenza

Our previous study shows favipiravir and oseltamivir combination therapy may accelerate clinical recovery compared to oseltamivir monotherapy in severe influenza, but its effect on virological evolution and resistance mutation against oseltamivir is still unknown. In this study, we collected longitudinal respiratory samples from influenza patients who underwent combination therapy and applied them to next generation sequencing of the whole genome of the influenza A virus (IAV). We also included a cohort untreated with any antivirals to serve as the control. In total, 62 samples from 19 patients treated with combination therapy and 20 samples from 20 patients untreated were successfully sequenced. The nucleotide diversity in the whole genome of IAV in the combination group showed no difference compared to that in the control group (P > 0.05). Moreover, we observed 174 kinds of nonsynonymous nucleotide substitutions in patients with combination therapy, mostly in NA (n = 44) and HA (n = 43). Of them, the G→A transition was the dominant variant type (27%) and 46/174 (26%) was reported to have biological effects, such as increased pathogenicity and polymerase activity. Among the 29 mutations conferring reduction in oseltamivir sensitivity we investigated, H275Y was the only mutation detected in the 4 samples from 1 of 19 patients and demonstrated increasing frequency during the treatment. Mutations conferring favipiravir resistance were not observed. Our studies showed combination therapy of favipiravir and oseltamivir has little effect on virus nucleotide diversity, nor prevents the increase of oseltamivir-resistant variants.

Engineering an Optimal Y280-Lineage H9N2 Vaccine Strain by Tuning PB2 Activity

H9N2 avian influenza A viruses (AIVs) cause economic losses in the poultry industry and provide internal genomic segments for the evolution of H5N1 and H7N9 AIVs into more detrimental strains for poultry and humans. In addition to the endemic Y439/Korea-lineage H9N2 viruses, the Y280-lineage spread to Korea since 2020. Conventional recombinant H9N2 vaccine strains, which bear mammalian pathogenic internal genomes of the PR8 strain, are pathogenic in BALB/c mice. To reduce the mammalian pathogenicity of the vaccine strains, the PR8 PB2 was replaced with the non-pathogenic and highly productive PB2 of the H9N2 vaccine strain 01310CE20. However, the 01310CE20 PB2 did not coordinate well with the hemagglutinin (HA) and neuraminidase (NA) of the Korean Y280-lineage strain, resulting in a 10-fold lower virus titer compared to the PR8 PB2. To increase the virus titer, the 01310CE20 PB2 was mutated (I66M-I109V-I133V) to enhance the polymerase trimer integrity with PB1 and PA, which restored the decreased virus titer without causing mouse pathogenicity. The reverse mutation (L226Q) of HA, which was believed to decrease mammalian pathogenicity by reducing mammalian receptor affinity, was verified to increase mouse pathogenicity and change antigenicity. The monovalent Y280-lineage oil emulsion vaccine produced high antibody titers for homologous antigens but undetectable titers for heterologous (Y439/Korea-lineage) antigens. However, this defect was corrected by the bivalent vaccine. Therefore, the balance of polymerase and HA/NA activities can be achieved by fine-tuning PB2 activity, and a bivalent vaccine may be more effective in controlling concurrent H9N2 viruses with different antigenicities.

Intracellular bottlenecking permits no more than three tomato yellow leaf curl virus genomes to initiate replication in a single cell

Viruses are constantly subject to natural selection to enrich beneficial mutations and weed out deleterious ones. However, it remains unresolved as to how the phenotypic gains or losses brought about by these mutations cause the viral genomes carrying the very mutations to become more or less numerous. Previous investigations by us and others suggest that viruses with plus strand (+) RNA genomes may compel such selection by bottlenecking the replicating genome copies in each cell to low single digits. Nevertheless, it is unclear if similarly stringent reproductive bottlenecks also occur in cells invaded by DNA viruses. Here we investigated whether tomato yellow leaf curl virus (TYLCV), a small virus with a single-stranded DNA genome, underwent population bottlenecking in cells of its host plants. We engineered a TYLCV genome to produce two replicons that express green fluorescent protein and mCherry, respectively, in a replication-dependent manner. We found that among the cells entered by both replicons, less than 65% replicated both, whereas at least 35% replicated either of them alone. Further probability computation concluded that replication in an average cell was unlikely to have been initiated with more than three replicon genome copies. Furthermore, sequential inoculations unveiled strong mutual exclusions of these two replicons at the intracellular level. In conclusion, the intracellular population of the small DNA virus TYLCV is actively bottlenecked, and such bottlenecking may be a virus-encoded, evolutionarily conserved trait that assures timely selection of new mutations emerging through error-prone replication.

Fidelity of Ribonucleotide Incorporation by the SARS-CoV-2 Replication Complex

The SARS-CoV-2 coronavirus has caused a global pandemic. Despite the initial success of vaccines at preventing infection, genomic variation has led to the proliferation of variants capable of higher infectivity. Mutations in the SARS-CoV-2 genome are the consequence of replication errors, highlighting the importance of understanding the determinants of SARS-CoV-2 replication fidelity. The RNA-dependent RNA polymerase (RdRp) is the central catalytic subunit for SARS-CoV-2 RNA replication and genome transcription. Here, we report the fidelity of ribonucleotide incorporation by SARS-CoV-2 RdRp (nsp12), along with its co-factors nsp7/nsp8, using steady-state kinetic analysis. Our analysis suggests that in the absence of the proofreading subunit (nsp14), the nsp12/7/8 complex has a surprisingly low base substitution fidelity (10^-1-10^-3). This is orders of magnitude lower than the fidelity reported for other coronaviruses (10^-6-10^-7), highlighting the importance of proofreading for faithful SARS-CoV-2 replication. We performed a mutational analysis of all reported SARS-CoV-2 genomes and identified mutations in both nsp12 and nsp14 that appear likely to lower viral replication fidelity through mechanisms that include impairing the nsp14 exonuclease activity or its association with the RdRp. Our observations provide novel insight into the mechanistic basis of replication fidelity in SARS-CoV-2 and the potential effect of nsp12 and nsp14 mutations on replication fidelity, informing the development of future antiviral agents and SARS-CoV-2 vaccines.

Analysis of 3.5 million SARS-CoV-2 sequences reveals unique mutational trends with consistent nucleotide and codon frequencies

BACKGROUND

Since the onset of the SARS-CoV-2 pandemic, bioinformatic analyses have been performed to understand the nucleotide and synonymous codon usage features and mutational patterns of the virus. However, comparatively few have attempted to perform such analyses on a considerably large cohort of viral genomes while organizing the plethora of available sequence data for a month-by-month analysis to observe changes over time. Here, we aimed to perform sequence composition and mutation analysis of SARS-CoV-2, separating sequences by gene, clade, and timepoints, and contrast the mutational profile of SARS-CoV-2 to other comparable RNA viruses.

METHODS

Using a cleaned, filtered, and pre-aligned dataset of over 3.5 million sequences downloaded from the GISAID database, we computed nucleotide and codon usage statistics, including calculation of relative synonymous codon usage values. We then calculated codon adaptation index (CAI) changes and a nonsynonymous/synonymous mutation ratio (dN/dS) over time for our dataset. Finally, we compiled information on the types of mutations occurring for SARS-CoV-2 and other comparable RNA viruses, and generated heatmaps showing codon and nucleotide composition at high entropy positions along the Spike sequence.

RESULTS

We show that nucleotide and codon usage metrics remain relatively consistent over the 32-month span, though there are significant differences between clades within each gene at various timepoints. CAI and dN/dS values vary substantially between different timepoints and different genes, with Spike gene on average showing both the highest CAI and dN/dS values. Mutational analysis showed that SARS-CoV-2 Spike has a higher proportion of nonsynonymous mutations than analogous genes in other RNA viruses, with nonsynonymous mutations outnumbering synonymous ones by up to 20:1. However, at several specific positions, synonymous mutations were overwhelmingly predominant.

CONCLUSIONS

Our multifaceted analysis covering both the composition and mutation signature of SARS-CoV-2 gives valuable insight into the nucleotide frequency and codon usage heterogeneity of SARS-CoV-2 over time, and its unique mutational profile compared to other RNA viruses.

Decoding the Role of Temperature in RNA Virus Infections

RNA viruses include respiratory viruses, such as coronaviruses and influenza viruses, as well as vector-borne viruses, like dengue and West Nile virus. RNA viruses like these encounter various environments when they copy themselves and spread from cell to cell or host to host. Ex vivo differences, such as geographical location and humidity, affect their stability and transmission, while in vivo differences, such as pH and host gene expression, impact viral receptor binding, viral replication, and the host immune response against the viral infection. A critical factor affecting RNA viruses both ex vivo and in vivo, and defining the outcome of viral infections and the direction of viral evolution, is temperature. In this minireview, we discuss the impact of temperature on viral replication, stability, transmission, and adaptation, as well as the host innate immune response. Improving our understanding of how RNA viruses function, survive, and spread at different temperatures will improve our models of viral replication and transmission risk analyses.

The evolutionary potential of influenza A virus hemagglutinin is highly constrained by epistatic interactions with neuraminidase

Antigenic evolution of the influenza A virus (IAV) hemagglutinin (HA) gene limits efforts to effectively control the spread of the virus in the population. Efforts to understand the mechanisms governing HA antigenic evolution typically examine the HA gene in isolation. This can ignore the importance of balancing HA receptor binding activities with the receptor-destroying activities of the viral neuraminidase (NA) to maintain viral fitness. We hypothesize that the need to maintain functional balance with NA significantly constrains the evolutionary potential of the HA. We use deep mutational scanning and show that variation in NA activity significantly reshapes the HA fitness landscape by modulating the overall mutational robustness of HA. Consistent with this, we observe that different NA backgrounds support the emergence of distinct repertoires of HA escape variants under neutralizing antibody pressure. Our results reveal a critical role for intersegment epistasis in influencing the evolutionary potential of the HA gene.

Mechanisms of Coronavirus Genome Stability As Potential Targets for Antiviral Drugs

The COVID-19 pandemic has made it necessary to create antivirals active against the SARS-CoV-2 coronavirus. One of the widely used strategies to fight off viral infections is the use of modified nucleoside analogues that inhibit viral replication by incorporating DNA or RNA into the growing chain, thus stopping its synthesis. The difficulty of using this method of treatment in the case of SARS-CoV-2 is that coronaviruses have an effective mechanism for maintaining genome stability. Its central element is the nsp14 protein, which is characterized by exonuclease activity, due to which incorrectly included and noncanonical nucleotides are removed from the 3' end of the growing RNA chain. Inhibitors of nsp14 exonuclease and nucleoside analogues resistant to its action are viewed as potential targets for anticoronavirus therapy.

Vaccination decreases the risk of influenza A virus reassortment but not genetic variation in pigs

Although vaccination is broadly used in North American swine breeding herds, managing swine influenza is challenging primarily due to the continuous evolution of influenza A virus (IAV) and the ability of the virus to transmit among vaccinated pigs. Studies that have simultaneously assessed the impact of vaccination on the emergence of IAV reassortment and genetic variation in pigs are limited. Here, we directly sequenced 28 bronchoalveolar lavage fluid (BALF) samples collected from vaccinated and unvaccinated pigs co-infected with H1N1 and H3N2 IAV strains, and characterized 202 individual viral plaques recovered from 13 BALF samples. We identified 54 reassortant viruses that were grouped in 17 single and 16 mixed genotypes. Notably, we found that prime-boost vaccinated pigs had less reassortant viruses than nonvaccinated pigs, likely due to a reduction in the number of days pigs were co-infected with both challenge viruses. However, direct sequencing from BALF samples revealed limited impact of vaccination on viral variant frequency, evolutionary rates, and nucleotide diversity in any IAV coding regions. Overall, our results highlight the value of IAV vaccination not only at limiting virus replication in pigs but also at protecting public health by restricting the generation of novel reassortants with zoonotic and/or pandemic potential.

Swine influenza A viruses cause severe illness among pigs and financial losses on pig farms worldwide. These viruses can also infect humans and have caused deadly human pandemics in the past. Influenza A viruses are dangerous because viruses can be transferred between humans, birds and pigs. These co-infections can allow the viruses to swap genetic material. Viral genetic exchanges can result in new virus strains that are more dangerous or that can infect other types of animals more easily.

Farmers vaccinate their pigs to control the swine influenza A virus. The vaccines are regularly updated to match circulating virus strains. But the virus evolves rapidly to escape vaccine-induced immunity, and infections are common even in vaccinated pigs. Learning about how vaccination affects the evolution of influenza A viruses in pigs could help scientists prevent outbreaks on pig farms and avoid spillover pandemics in humans.

Li et al. show that influenza A viruses are less likely to swap genetic material in vaccinated and boosted pigs than in unvaccinated animals. In the experiments, Li et al. collected swine influenza A samples from the lungs of pigs that had received different vaccination protocols. Next, Li et al. used next-generation sequencing to identify new mutations in the virus or genetic swaps among different strains. In pigs infected with both the H1N1 and H3N2 strains of influenza, the two viruses began trading genes within a week. But less genetic mixing occurred in vaccinated and boosted pigs because they spent less time infected with both viruses than in unvaccinated pigs. The vaccination status of the pig did not have much effect on how many new mutations occurred in the viruses.

The experiments show that vaccinating and boosting pigs against influenza A viruses may protect against genetic swapping among influenza viruses. If future studies on pig farms confirm the results, the information gleaned from the study could help scientists improve farm vaccine protocols to further reduce influenza risks to animals and people.

Heterogeneity in viral populations increases the rate of deleterious mutation accumulation

RNA viruses have high mutation rates, with the majority of mutations being deleterious. We examine patterns of deleterious mutation accumulation over multiple rounds of viral replication, with a focus on how cellular coinfection and heterogeneity in viral output affect these patterns. Specifically, using agent-based intercellular simulations we find, in agreement with previous studies, that coinfection of cells by viruses relaxes the strength of purifying selection, and thereby increases the rate of deleterious mutation accumulation. We further find that cellular heterogeneity in viral output exacerbates the rate of deleterious mutation accumulation, regardless of whether this heterogeneity in viral output is stochastic or is due to variation in cellular multiplicity of infection. These results highlight the need to consider the unique life histories of viruses and their population structure to better understand observed patterns of viral evolution.

The extinction time under mutational meltdown driven by high mutation rates

Mutational meltdown describes an eco‐evolutionary process in which the accumulation of deleterious mutations causes a fitness decline that eventually leads to the extinction of a population. Possible applications of this concept include medical treatment of RNA virus infections based on mutagenic drugs that increase the mutation rate of the pathogen. To determine the usefulness and expected success of such an antiviral treatment, estimates of the expected time to mutational meltdown are necessary. Here, we compute the extinction time of a population under high mutation rates, using both analytical approaches and stochastic simulations. Extinction is the result of three consecutive processes: (a) initial accumulation of deleterious mutations due to the increased mutation pressure; (b) consecutive loss of the fittest haplotype due to Muller's ratchet; (c) rapid population decline toward extinction. We find accurate analytical results for the mean extinction time, which show that the deleterious mutation rate has the strongest effect on the extinction time. We confirm that intermediate‐sized deleterious selection coefficients minimize the extinction time. Finally, our simulations show that the variation in extinction time, given a set of parameters, is surprisingly small.

In Silico Analyses of the Role of Codon Usage at the Hemagglutinin Cleavage Site in Highly Pathogenic Avian Influenza Genesis

A vast diversity of 16 influenza hemagglutinin (HA) subtypes are found in birds. Interestingly, viruses from only two subtypes, H5 and H7, have so far evolved into highly pathogenic avian influenza viruses (HPAIVs) following insertions or substitutions at the HA cleavage site by the viral polymerase. The mechanisms underlying this striking subtype specificity are still unknown. Here, we compiled a comprehensive dataset of 20,488 avian influenza virus HA sequences to investigate differences in nucleotide and amino acid usage at the HA cleavage site between subtypes and how these might impact the genesis of HPAIVs by polymerase stuttering and realignment. We found that sequences of the H5 and H7 subtypes stand out by their high purine content at the HA cleavage site. In addition, fewer substitutions were necessary in H5 and H7 HAs than in HAs from other subtypes to acquire an insertion-prone HA cleavage site sequence, as defined based on in vitro and in vivo data from the literature. Codon usage was more favorable for HPAIV genesis in sequences of viruses isolated from species or geographical regions in which HPAIV genesis is more frequently observed in nature. The results of the present analyses suggest that the subtype restriction of HPAIV genesis to H5 and H7 influenza viruses might be due to the particular codon usage at the HA cleavage site in these subtypes.

Empirical estimates of the mutation rate for an alphabaculovirus

Mutation rates are of key importance for understanding evolutionary processes and predicting their outcomes. Empirical mutation rate estimates are available for a number of RNA viruses, but few are available for DNA viruses, which tend to have larger genomes. Whilst some viruses have very high mutation rates, lower mutation rates are expected for viruses with large genomes to ensure genome integrity. Alphabaculoviruses are insect viruses with large genomes and often have high levels of polymorphism, suggesting high mutation rates despite evidence of proofreading activity by the replication machinery. Here, we report an empirical estimate of the mutation rate per base per strand copying (s/n/r) of Autographa californica multiple nucleopolyhedrovirus (AcMNPV). To avoid biases due to selection, we analyzed mutations that occurred in a stable, non-functional genomic insert after five serial passages in Spodoptera exigua larvae. Our results highlight that viral demography and the stringency of mutation calling affect mutation rate estimates, and that using a population genetic simulation model to make inferences can mitigate the impact of these processes on estimates of mutation rate. We estimated a mutation rate of μ = 1×10⁻⁷ s/n/r when applying the most stringent criteria for mutation calling, and estimates of up to μ = 5×10⁻⁷ s/n/r when relaxing these criteria. The rates at which different classes of mutations accumulate provide good evidence for neutrality of mutations occurring within the inserted region. We therefore present a robust approach for mutation rate estimation for viruses with stable genomes, and strong evidence of a much lower alphabaculovirus mutation rate than supposed based on the high levels of polymorphism observed.

Virus populations can evolve rapidly, driven by the large number of mutations that occur during virus replication. It is challenging to measure mutation rates because selection will affect which mutations are observed: beneficial mutations are overrepresented in virus populations, while deleterious mutations are selected against and therefore underrepresented. Few mutation rates have been estimated for viruses with large DNA genomes, and there are no estimates for any insect virus. Here, we estimate the mutation rate for an alphabaculovirus, a virus that infects caterpillars and has a large, 134 kilobase pair DNA genome. To ensure that selection did not bias our estimate of mutation rate, we studied which mutations occurred in a large artificial region inserted into the virus genome, where mutations did not affect viral fitness. We deep sequenced evolved virus populations, and compared the distribution of observed mutants to predictions from a simulation model to estimate mutation rate. We found evidence for a relatively low mutation rate, of one mutation in every 10 million bases replicated. This estimate is in line with expectations for a DNA virus with self-correcting replication machinery and a large genome.

Genome characterization and mutation analysis of human influenza A virus in Thailand

The influenza A viruses have high mutation rates and cause a serious health problem worldwide. Therefore, this study focused on genome characterization of the viruses isolated from Thai patients based on the next-generation sequencing technology. The nasal swabs were collected from patients with influenza-like illness in Thailand during 2017-2018. Then, the influenza A viruses were detected by reverse transcription-quantitative polymerase chain reaction and isolated by MDCK cells. The viral genomes were amplified and sequenced by Illumina MiSeq platform. Whole genome sequences were used for characterization, phylogenetic construction, mutation analysis and nucleotide diversity of the viruses. The result revealed that 90 samples were positive for the viruses including 44 of A/H1N1 and 46 of A/H3N2. Among these, 43 samples were successfully isolated and then the viral genomes of 25 samples were completely amplified. Finally, 17 whole genomes of the viruses (A/H1N1, n=12 and A/H3N2, n=5) were successfully sequenced with an average of 232,578 mapped reads and 1,720 genome coverage per sample. Phylogenetic analysis demonstrated that the A/H1N1 viruses were distinguishable from the recommended vaccine strains. However, the A/H3N2 viruses from this study were closely related to the recommended vaccine strains. The nonsynonymous mutations were found in all genes of both viruses, especially in HA and NA genes. The nucleotide diversity analysis revealed negative selection in the PB1, PA, hemagglutinin (HA) and neuraminidase (NA) genes of the A/H1N1 viruses. High-throughput data in this study allow for genetic characterization of circulating influenza viruses which would be crucial for preparation against pandemic and epidemic outbreaks in the future.

Evolutionary Landscapes of Host-Virus Arms Races

Vertebrate immune systems suppress viral infection using both innate restriction factors and adaptive immunity. Viruses mutate to escape these defenses, driving hosts to counterevolve to regain fitness. This cycle recurs repeatedly, resulting in an evolutionary arms race whose outcome depends on the pace and likelihood of adaptation by host and viral genes. Although viruses evolve faster than their vertebrate hosts, their proteins are subject to numerous functional constraints that impact the probability of adaptation. These constraints are globally defined by evolutionary landscapes, which describe the fitness and adaptive potential of all possible mutations. We review deep mutational scanning experiments mapping the evolutionary landscapes of both host and viral proteins engaged in arms races. For restriction factors and some broadly neutralizing antibodies, landscapes favor the host, which may help to level the evolutionary playing field against rapidly evolving viruses. We discuss the biophysical underpinnings of these landscapes and their therapeutic implications.

Host and geographic barriers shape the competition, coexistence, and extinction patterns of influenza A (H1N1) viruses

The influenza virus mutates and spreads rapidly, making it suitable for studying evolutionary and ecological processes. The ecological factors and processes by which different lineages of influenza compete or coexist within hosts through time and across geographical space are poorly known. We hypothesized that competition would be stronger for influenza viruses infecting the same host compared to different hosts (the Host Barrier Hypothesis), and for those with a higher cross‐region transmission intensity (the Geographic Barrier Hypothesis). Using available sequences of the influenza A (H1N1) virus in GenBank, we identified six lineages, twelve clades, and several replacement events. We found that human‐hosted lineages had a higher cross‐region transmission intensity than swine‐hosted lineages. Co‐occurrence probabilities of lineages infecting the same host were lower than those infecting different hosts, and human‐hosted lineages had lower co‐occurrence probabilities and genetic diversity than swine‐hosted lineages. These results show that H1N1 lineages infecting the same host or with high cross‐region transmission rates experienced stronger competition and extinction pressures than those infecting different hosts or with low cross‐region transmission. Our study highlights how host and geographic barriers shape the competition, extinction, and coexistence patterns of H1N1 lineages and clades.

Low Pathogenicity H7N3 Avian Influenza Viruses Have Higher Within-Host Genetic Diversity Than a Closely Related High Pathogenicity H7N3 Virus in Infected Turkeys and Chickens

Within-host viral diversity offers a view into the early stages of viral evolution occurring after a virus infects a host. In recent years, advances in deep sequencing have allowed for routine identification of low-frequency variants, which are important sources of viral genetic diversity and can potentially emerge as a major virus population under certain conditions. We examined within-host viral diversity in turkeys and chickens experimentally infected with closely related H7N3 avian influenza viruses (AIVs), specifically one high pathogenicity AIV (HPAIV) and two low pathogenicity AIV (LPAIVs) with different neuraminidase protein stalk lengths. Consistent with the high mutation rates of AIVs, an abundance of intra-host single nucleotide variants (iSNVs) at low frequencies of 2–10% was observed in all samples collected. Furthermore, a small number of common iSNVs were observed between turkeys and chickens, and between directly inoculated and contact-exposed birds. Notably, the LPAIVs have significantly higher iSNV diversities and frequencies of nonsynonymous changes than the HPAIV in both turkeys and chickens. These findings highlight the dynamics of AIV populations within hosts and the potential impact of genetic changes, including mutations in the hemagglutinin gene that confers the high pathogenicity pathotype, on AIV virus populations and evolution.

Mutation bias shapes the spectrum of adaptive substitutions

How do mutational biases influence the process of adaptation? A common assumption is that selection alone determines the course of adaptation from abundant preexisting variation. Yet, theoretical work shows broad conditions under which the mutation rate to a given type of variant strongly influences its probability of contributing to adaptation. Here we introduce a statistical approach to analyzing how mutation shapes protein sequence adaptation. Using large datasets from three different species, we show that the mutation spectrum has a proportional influence on the types of changes fixed in adaptation. We also show via computer simulations that a variety of factors can influence how closely the spectrum of adaptive substitutions reflects the spectrum of variants introduced by mutation.

Evolutionary adaptation often occurs by the fixation of beneficial mutations. This mode of adaptation can be characterized quantitatively by a spectrum of adaptive substitutions, i.e., a distribution for types of changes fixed in adaptation. Recent work establishes that the changes involved in adaptation reflect common types of mutations, raising the question of how strongly the mutation spectrum shapes the spectrum of adaptive substitutions. We address this question with a codon-based model for the spectrum of adaptive amino acid substitutions, applied to three large datasets covering thousands of amino acid changes identified in natural and experimental adaptation in Saccharomyces cerevisiae, Escherichia coli, and Mycobacterium tuberculosis. Using species-specific mutation spectra based on prior knowledge, we find that the mutation spectrum has a proportional influence on the spectrum of adaptive substitutions in all three species. Indeed, we find that by inferring the mutation rates that best explain the spectrum of adaptive substitutions, we can accurately recover the species-specific mutation spectra. However, we also find that the predictive power of the model differs substantially between the three species. To better understand these differences, we use population simulations to explore the factors that influence how closely the spectrum of adaptive substitutions mirrors the mutation spectrum. The results show that the influence of the mutation spectrum decreases with increasing mutational supply (Nμ) and that predictive power is strongly affected by the number and diversity of beneficial mutations.

Virus-like Particles: Measures and Biological Functions

Virus-like particles resemble infectious virus particles in size, shape, and molecular composition; however, they fail to productively infect host cells. Historically, the presence of virus-like particles has been inferred from total particle counts by microscopy, and infectious particle counts or plaque-forming-units (PFUs) by plaque assay; the resulting ratio of particles-to-PFUs is often greater than one, easily 10 or 100, indicating that most particles are non-infectious. Despite their inability to hijack cells for their reproduction, virus-like particles and the defective genomes they carry can exhibit a broad range of behaviors: interference with normal virus growth during co-infections, cell killing, and activation or inhibition of innate immune signaling. In addition, some virus-like particles become productive as their multiplicities of infection increase, a sign of cooperation between particles. Here, we review established and emerging methods to count virus-like particles and characterize their biological functions. We take a critical look at evidence for defective interfering virus genomes in natural and clinical isolates, and we review their potential as antiviral therapeutics. In short, we highlight an urgent need to better understand how virus-like genomes and particles interact with intact functional viruses during co-infection of their hosts, and their impacts on the transmission, severity, and persistence of virus-associated diseases.

The PB1 gene from H9N2 avian influenza virus showed high compatibility and increased mutation rate after reassorting with a human H1N1 influenza virus

Background

Reassortment between human and avian influenza viruses (AIV) may result in novel viruses with new characteristics that may threaten human health when causing the next flu pandemic. A particular risk may be posed by avian influenza viruses of subtype H9N2 that are currently massively circulating in domestic poultry in Asia and have been shown to infect humans. In this study, we investigate the characteristics and compatibility of a human H1N1 virus with avian H9N2 derived genes.

Methods

The polymerase activity of the viral ribonucleoprotein (RNP) complex as combinations of polymerase-related gene segments derived from different reassortment events was tested in luciferase reporter assays. Reassortant viruses were generated by reverse genetics. Gene segments of the human WSN-H1N1 virus (A/WSN/1933) were replaced by gene segments of the avian A2093-H9N2 virus (A/chicken/Jiangsu/A2093/2011), which were both the Hemagglutinin (HA) and Neuraminidase (NA) gene segments in combination with one of the genes involved in the RNP complex (either PB2, PB1, PA or NP). The growth kinetics and virulence of reassortant viruses were tested on cell lines and mice. The reassortant viruses were then passaged for five generations in MDCK cells and mice lungs. The HA gene of progeny viruses from different passaging paths was analyzed using Next-Generation Sequencing (NGS).

Results

We discovered that the avian PB1 gene of H9N2 increased the polymerase activity of the RNP complex in backbone of H1N1. Reassortant viruses were able to replicate in MDCK and DF1 cells and mice. Analysis of the NGS data showed a higher substitution rate for the PB1-reassortant virus. In particular, for the PB1-reassortant virus, increased virulence for mice was measured by increased body weight loss after infection in mice.

Conclusions

The higher polymerase activity and increased mutation frequency measured for the PB1-reassortant virus suggests that the avian PB1 gene of H9N2 may drive the evolution and adaptation of reassortant viruses to the human host. This study provides novel insights in the characteristics of viruses that may arise by reassortment of human and avian influenza viruses. Surveillance for infections with H9N2 viruses and the emergence of the reassortant viruses in humans is important for pandemic preparedness.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-022-01745-x.

Composition and Dynamics of H1N1 and H7N9 Influenza A Virus Quasispecies in a Co-infected Patient Analyzed by Single Molecule Sequencing Technology

A human co-infected with H1N1 and H7N9 subtypes influenza A virus (IAV) causes a complex infectious disease. The identification of molecular-level variations in composition and dynamics of IAV quasispecies will help to understand the pathogenesis and provide guidance for precision medicine treatment. In this study, using single-molecule real-time sequencing (SMRT) technology, we successfully acquired full-length IAV genomic sequences and quantified their genotypes abundance in serial samples from an 81-year-old male co-infected with H1N1 and H7N9 subtypes IAV. A total of 26 high diversity nucleotide loci was detected, in which the A-G base transversion was the most abundant substitution type (67 and 64%, in H1N1 and H7N9, respectively). Seven significant amino acid variations were detected, such as NA:H275Y and HA: R222K in H1N1 as well as PB2:E627K and NA: K432E in H7N9, which are related to viral drug-resistance or mammalian adaptation. Furtherly, we retrieved 25 H1N1 and 22 H7N9 genomic segment haplotypes from the eight samples based on combining high-diversity nucleotide loci, which provided a more concise overview of viral quasispecies composition and dynamics. Our approach promotes the popularization of viral quasispecies analysis in a complex infectious disease, which will boost the understanding of viral infections, pathogenesis, evolution, and precision medicine.

Peering into Avian Influenza A(H5N8) for a Framework towards Pandemic Preparedness

2014 marked the first emergence of avian influenza A(H5N8) in Jeonbuk Province, South Korea, which then quickly spread worldwide. In the midst of the 2020-2021 H5N8 outbreak, it spread to domestic poultry and wild waterfowl shorebirds, leading to the first human infection in Astrakhan Oblast, Russia. Despite being clinically asymptomatic and without direct human-to-human transmission, the World Health Organization stressed the need for continued risk assessment given the nature of Influenza to reassort and generate novel strains. Given its promiscuity and easy cross to humans, the urgency to understand the mechanisms of possible species jumping to avert disastrous pandemics is increasing. Addressing the epidemiology of H5N8, its mechanisms of species jumping and its implications, mutational and reassortment libraries can potentially be built, allowing them to be tested on various models complemented with deep-sequencing and automation. With knowledge on mutational patterns, cellular pathways, drug resistance mechanisms and effects of host proteins, we can be better prepared against H5N8 and other influenza A viruses.

Local spread of influenza A (H1N1) viruses without a mutation for the maximum duration of an epidemic season in Japan

Close observation of the local transmission of influenza A(H1N1) viruses enabled an estimate of the length of time the virus was transmitted without a mutation. Of 4,448 isolates from 11 consecutive years, 237 isolates could be categorized into 57 strain groups with identical hemagglutinin genes, which were monitored for the entire duration of an epidemic season. In addition, 35 isolates with identical sequences were identified at the study site and in other countries within 147 days. Consequently, it can be postulated that once an influenza virus enters a temperate region, the strain rarely mutates before the end of the season.

Interface-based design of the favipiravir-binding site in SARS-CoV-2 RNA-dependent RNA polymerase reveals mutations conferring resistance to chain termination

Favipiravir is a broad‐spectrum inhibitor of viral RNA‐dependent RNA polymerase (RdRp) currently being used to manage COVID‐19. Accumulation of mutations in severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) RdRp may facilitate antigenic drift, generating favipiravir resistance. Focussing on the chain‐termination mechanism utilized by favipiravir, we used high‐throughput interface‐based protein design to generate > 100 000 designs of the favipiravir‐binding site of RdRp and identify mutational hotspots. We identified several single‐point mutants and designs having a sequence identity of 97%–98% with wild‐type RdRp, suggesting that SARS‐CoV‐2 can develop favipiravir resistance with few mutations. Out of 134 mutations documented in the CoV‐GLUE database, 63 specific mutations were already predicted as resistant in our calculations, thus attaining ˜ 47% correlation with the sequencing data. These findings improve our understanding of the potential signatures of adaptation in SARS‐CoV‐2 against favipiravir.

A Codon-Pair Bias Associated With Network Interactions in Influenza A, B, and C Genomes

A new codon-pair bias present in the genomes of different types of influenza virus is described. Codons with fewer network interactions are more frequency paired together than other codon-pairs in influenza A, B, and C genomes. A shared feature among three different influenza types suggests an evolutionary bias. Codon-pair preference can affect both speed of protein translation and RNA structure. This newly identified bias may provide insight into drivers of virus evolution.

Multiple polymerase acidic (PA) I38X substitutions in influenza A(H1N1)pdm09 virus permit polymerase activity and cause reduced baloxavir inhibition

BACKGROUND

Baloxavir marboxil is an antiviral drug that targets the endonuclease activity of the influenza virus polymerase acidic (PA) protein. PA I38T/M/F substitutions reduce its antiviral efficacy.

OBJECTIVES

To understand the effects of the 19 possible amino acid (AA) substitutions at PA 38 on influenza A(H1N1)pdm09 polymerase activity and inhibition by baloxavir acid, the active metabolite of baloxavir marboxil.

METHODS

Influenza A(H1N1)pdm09 viral polymerase complexes containing all 19 I38X AA substitutions were reconstituted in HEK293T cells in a mini-replicon assay. Polymerase complex activity and baloxavir inhibitory activity were measured in the presence or absence of 50 nM baloxavir acid.

RESULTS

Only three substitutions (R, K, P) reduced polymerase activity to <79% of I38-WT. When compared with the prototypical baloxavir marboxil resistance marker T38, 5 substitutions conferred 10%-35% reductions in baloxavir acid inhibitory activity (M, L, F, Y, C) and 11 substitutions conferred >50% reductions (R, K, S, N, G, W, A, Q, E, D, H), while two substitutions (V, P) maintained baloxavir acid inhibitory activity.

CONCLUSIONS

Most PA 38 substitutions permit a functional replication complex retaining some drug resistance in the mini-replicon assay. This study provides a targeted approach for virus rescue and analysis of novel baloxavir marboxil reduced-susceptibility markers, supports the consideration of a broader range of these markers during antiviral surveillance and adds to the growing knowledge of baloxavir marboxil resistance profiles.

Favipiravir-resistant influenza A virus shows potential for transmission

Favipiravir is a nucleoside analogue which has been licensed to treat influenza in the event of a new pandemic. We previously described a favipiravir resistant influenza A virus generated by in vitro passage in presence of drug with two mutations: K229R in PB1, which conferred resistance at a cost to polymerase activity, and P653L in PA, which compensated for the cost of polymerase activity. However, the clinical relevance of these mutations is unclear as the mutations have not been found in natural isolates and it is unknown whether viruses harbouring these mutations would replicate or transmit in vivo. Here, we infected ferrets with a mix of wild type p(H1N1) 2009 and corresponding favipiravir-resistant virus and tested for replication and transmission in the absence of drug. Favipiravir-resistant virus successfully infected ferrets and was transmitted by both contact transmission and respiratory droplet routes. However, sequencing revealed the mutation that conferred resistance, K229R, decreased in frequency over time within ferrets. Modelling revealed that due to a fitness advantage for the PA P653L mutant, reassortment with the wild-type virus to gain wild-type PB1 segment in vivo resulted in the loss of the PB1 resistance mutation K229R. We demonstrated that this fitness advantage of PA P653L in the background of our starting virus A/England/195/2009 was due to a maladapted PA in first wave isolates from the 2009 pandemic. We show there is no fitness advantage of P653L in more recent pH1N1 influenza A viruses. Therefore, whilst favipiravir-resistant virus can transmit in vivo, the likelihood that the resistance mutation is retained in the absence of drug pressure may vary depending on the genetic background of the starting viral strain.

[Identification of a metabolic immune regulator in the host that protects against influenzal pneumonia]

The 'flu, caused mostly by influenza A and B viruses, represents a major public health issue. Despite vaccines and antiviral drugs, the therapeutic arsenal is still suboptimal. Recently, several studies have reported the antiviral and anti-inflammatory properties of several host metabolites. Now, we show that a metabolite (called here "C2") has a potent anti-influenza activity by blocking the viral replication and by limiting the downstream pro-inflammatory signalling. These results pave the way for the development of innovative metabolic therapy against influenzal pneumonia.

The evolution and future of influenza pandemic preparedness

The influenza virus is a global threat to human health causing unpredictable yet recurring pandemics, the last four emerging over the course of a hundred years. As our knowledge of influenza virus evolution, distribution, and transmission has increased, paths to pandemic preparedness have become apparent. In the 1950s, the World Health Organization (WHO) established a global influenza surveillance network that is now composed of institutions in 122 member states. This and other surveillance networks monitor circulating influenza strains in humans and animal reservoirs and are primed to detect influenza strains with pandemic potential. Both the United States Centers for Disease Control and Prevention and the WHO have also developed pandemic risk assessment tools that evaluate specific aspects of emerging influenza strains to develop a systematic process of determining research and funding priorities according to the risk of emergence and potential impact. Here, we review the history of influenza pandemic preparedness and the current state of preparedness, and we propose additional measures for improvement. We also comment on the intersection between the influenza pandemic preparedness network and the current SARS-CoV-2 crisis. We must continually evaluate and revise our risk assessment and pandemic preparedness plans and incorporate new information gathered from research and global crises.

Evaluation of HA-D222G/N polymorphism using targeted NGS analysis in A(H1N1)pdm09 influenza virus in Russia in 2018-2019

Outbreaks of influenza, which is a contagious respiratory disease, occur throughout the world annually, affecting millions of people with many fatal cases. The D222G/N mutations in the hemagglutinin (HA) gene of A(H1N1)pdm09 are associated with severe and fatal human influenza cases. These mutations lead to increased virus replication in the lower respiratory tract (LRT) and may result in life-threatening pneumonia. Targeted NGS analysis revealed the presence of mutations in major and minor variants in 57% of fatal cases, with the proportion of viral variants with mutations varying from 1% to 98% in each individual sample in the epidemic season 2018-2019 in Russia. Co-occurrence of the mutations D222G and D222N was detected in a substantial number of the studied fatal cases (41%). The D222G/N mutations were detected at a low frequency (less than 1%) in the rest of the studied samples from fatal and nonfatal cases of influenza. The presence of HA D222Y/V/A mutations was detected in a few fatal cases. The high rate of occurrence of HA D222G/N mutations in A(H1N1)pdm09 viruses, their increased ability to replicate in the LRT and their association with fatal outcomes points to the importance of monitoring the mutations in circulating A(H1N1)pdm09 viruses for the evaluation of their epidemiological significance and for the consideration of disease prevention and treatment options.

Uncovering antibody cross-reaction dynamics in influenza A infections

MOTIVATION

Influenza viruses are a cause of large outbreaks and pandemics with high death tolls. A key obstacle is that flu vaccines have inconsistent performance, in the best cases up to 60% effectiveness, but it can be as low as 10%. Uncovering the hidden pathways of how antibodies (Abs) induced by one influenza strain are effective against another, cross-reaction, is a central vexation for the design of universal flu vaccines.

RESULTS

We conceive a stochastic model that successfully represents the antibody cross-reactive data from mice infected with H3N2 influenza strains and further validation with cross-reaction data of H1N1 strains. Using a High-Performance Computing cluster, several aspects and parameters in the model were tested. Computational simulations highlight that changes in time of infection and the B-cells population are relevant, however, the affinity threshold of B-cells between consecutive infections is a necessary condition for the successful Abs cross-reaction. Our results suggest a 3-D reformulation of the current influenza antibody landscape for the representation and modeling of cross-reactive data.

AVAILABILITY AND IMPLEMENTATION

The full code as a testing/simulation platform is freely available here: https://github.com/systemsmedicine/Antibody_cross-reaction_dynamics.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Uncovering antibody cross-reaction dynamics in influenza A infections

MOTIVATION

Influenza viruses are a cause of large outbreaks and pandemics with high death tolls. A key obstacle is that flu vaccines have inconsistent performance, in the best cases up to 60% effectiveness, but it can be as low as 10%. Uncovering the hidden pathways of how antibodies (Abs) induced by one influenza strain are effective against another, cross-reaction, is a central vexation for the design of universal flu vaccines.

RESULTS

We conceive a stochastic model that successfully represents the antibody cross-reactive data from mice infected with H3N2 influenza strains and further validation with cross-reaction data of H1N1 strains. Using a High-Performance Computing cluster, several aspects and parameters in the model were tested. Computational simulations highlight that changes in time of infection and the B-cells population are relevant, however, the affinity threshold of B-cells between consecutive infections is a necessary condition for the successful Abs cross-reaction. Our results suggest a 3-D reformulation of the current influenza antibody landscape for the representation and modeling of cross-reactive data.

AVAILABILITY AND IMPLEMENTATION

The full code as a testing/simulation platform is freely available here: https://github.com/systemsmedicine/Antibody_cross-reaction_dynamics.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Multidimensional Digital Bioassay Platform Based on an Air-Sealed Femtoliter Reactor Array Device

Single-molecule experiments have been helping us to get deeper inside biological phenomena by illuminating how individual molecules actually work. Digital bioassay, in which analyte molecules are individually confined in small compartments to be analyzed, is an emerging technology in single-molecule biology and applies to various biological entities (e.g., cells and virus particles). However, digital bioassay is not compatible with multiconditional and multiparametric assays, hindering in-depth understanding of analytes. This is because current digital bioassay lacks a repeatable solution-exchange system that keeps analytes inside compartments. To address this challenge, we developed a digital bioassay platform with easy solution exchanges, called multidimensional (MD) digital bioassay. We immobilized single analytes in arrayed femtoliter (10^-15 L) reactors and sealed them with airflow. The solution in each reactor was stable and showed no cross-talk via solution leakage for more than 2 h, and over 30 rounds of perfect solution exchanges were successfully performed. With multiconditional assays based on our system, we could quantitatively determine inhibitor sensitivities of single influenza A virus particles and single alkaline phosphatase (ALP) molecules, which has never been achieved with conventional digital bioassays. Further, we demonstrated that ALPs from two origins can be precisely distinguished by a single-molecule multiparametric assay with our system, which was also difficult with conventional digital bioassays. Thus, MD digital bioassay is a versatile platform to gain in-depth insight into biological entities in unprecedented resolution.

SARS-CoV-2 genomic diversity and the implications for qRT-PCR diagnostics and transmission

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 lineages that have spread throughout the world. In this study, we investigated 129 RNA-seq data sets and 6928 consensus genomes to contrast the intra-host and inter-host diversity of SARS-CoV-2. Our analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights intra-host single nucleotide variant (iSNV) and SNP similarity, albeit with differences in C > U changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of insertions and deletions contribute to the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2.

New approaches to mutation rate fold change in Luria-Delbrück fluctuation experiments

For nearly eight decades the Luria-Delbrück protocol remains the preferred method for experimentally determining microbial mutation rates. However, earnest development and rigorous applications of statistical methods for mutation rate comparison using fluctuation assay data are a relatively recent phenomenon. While likelihood ratio tests tailored for the fluctuation protocol give investigators appropriate tools, researchers sometimes may prefer to view the comparison of two mutation rates through the lens of the ratio of the two mutation rates. The idea of using the bootstrap technique to construct intervals for mutation rate fold change was proposed nearly a decade ago, but it failed to gain traction partly due to a failure to incorporate likelihood-based estimation. In addition to extending the bootstrap method, this paper proposes two new methods of constructing intervals for mutation rate fold change: a profile likelihood method and a Bayesian method utilizing Monte Carlo Markov chain. All three methods are assessed by large-scale simulations.