Stochastic processes constrain the within and between host evolution of influenza virus

Quantifying the impact of vaccination on transmission and diversity of influenza A variants in pigs

Global evolutionary dynamics of influenza A virus (IAV) are fundamentally driven by the extent of virus diversity generated, transmitted, and shaped in individual hosts. How vaccination affects the degree of IAV genetic diversity that can be transmitted and expanded in pigs is unknown. To evaluate the effect of vaccination on the transmission of genetically distinct IAV variants and their diversity after transmission in pigs, we examined the whole genome of IAV recovered from the nasal cavities of pigs vaccinated with different influenza immunization regimens after being infected simultaneously by H1N1 and H3N2 IAVs using a seeder pig model. We found that the seeder pigs harbored more diversified virus populations than the contact pigs. Among contact pigs, H3N2 and H1N1 viruses recovered from pigs vaccinated with a single dose of an unmatched modified live vaccine generally accumulated more extensive genetic mutations than non-vaccinated pigs. Furthermore, the non-sterilizing immunity elicited by the single-dose-modified live vaccine may have exerted positive selection on H1 antigenic regions as we detected significantly higher nonsynonymous but lower synonymous evolutionary rates in H1 antigenic regions than non-antigenic regions. In addition, we observed that the vaccinated pigs shared significantly less proportion of H3N2 variants with seeder pigs than unvaccinated pigs. These results indicated that vaccination might reduce the impact of transmitted influenza variants on the overall diversity of IAV populations harbored in recipient pigs and that within-host genetic selection of IAV is more likely to occur in pigs vaccinated with improperly matched vaccines.IMPORTANCEUnderstanding how vaccination shapes the diversity of influenza variants that transmit and propagate among pigs is essential for designing effective IAV surveillance and control programs. Current knowledge about the transmission of IAV variants has primarily been explored in humans during natural infection. However, how immunity elicited by improperly matched vaccines affects the degree of IAV genetic diversity that can be transmitted and expanded in pigs at the whole-genome level is unknown. We analyzed IAV sequences from samples collected daily from experimentally infected pigs vaccinated with various protocols in a field-represented IAV co-infection model. We found that vaccine-induced non-sterilizing immunity might promote genetic variation on the IAV genome and drive positive selection at antigenic sites during infection. In addition, a smaller proportion of H3N2 viral variants were shared between seeder pigs and vaccinated pigs, suggesting the influence of vaccination on shaping the virus genomic diversity in recipient pigs during the transmission events.

In depth sequencing of a serially sampled household cohort reveals the within-host dynamics of Omicron SARS-CoV-2 and rare selection of novel spike variants

SARS-CoV-2 has undergone repeated and rapid evolution to circumvent host immunity. However, outside of prolonged infections in immunocompromised hosts, within-host positive selection has rarely been detected. The low diversity within-hosts and strong genetic linkage among genomic sites make accurately detecting positive selection difficult. Longitudinal sampling is a powerful method for detecting selection that has seldom been used for SARS-CoV-2. Here we combine longitudinal sampling with replicate sequencing to increase the accuracy of and lower the threshold for variant calling. We sequenced 577 specimens from 105 individuals from a household cohort primarily during the BA.1/BA.2 variant period. There was extremely low diversity and a low rate of divergence. Specimens had 0-12 intrahost single nucleotide variants (iSNV) at >0.5% frequency, and the majority of the iSNV were at frequencies <2%. Within-host dynamics were dominated by genetic drift and purifying selection. Positive selection was rare but highly concentrated in spike. Two individuals with BA.1 infections had S:371F, a lineage defining substitution for BA.2. A Wright Fisher Approximate Bayesian Computational model identified positive selection at 14 loci with 7 in spike, including S:448 and S:339. We also detected significant genetic hitchhiking between synonymous changes and nonsynonymous iSNV under selection. The detectable immune-mediated selection may be caused by the relatively narrow antibody repertoire in individuals during the early Omicron phase of the SARS-CoV-2 pandemic. As both the virus and population immunity evolve, understanding the corresponding shifts in SARS-CoV-2 within-host dynamics will be important.

Genomic epidemiology reveals the variation and transmission properties of SARS-CoV-2 in a single-source community outbreak

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the coronavirus disease 2019 (COVID-19) pandemic, which is still a global public health concern. During March 2022, a rapid and confined single-source outbreak of SARS-CoV-2 was identified in a community in Nanjing municipal city. Overall, 95 individuals had laboratory-confirmed SARS-CoV-2 infection. The whole genomes of 61 viral samples were obtained, which were all members of the BA.2.2 lineage and clearly demonstrated the presence of one large clade, and all the infections could be traced back to the original index case. The most distant sequence from the index case presented a difference of 4 SNPs, and 118 intrahost single-nucleotide variants (iSNVs) at 74 genomic sites were identified. Some minor iSNVs can be transmitted and subsequently rapidly fixed in the viral population. The minor iSNVs transmission resulted in at least two nucleotide substitutions among all seven SNPs identified in the outbreak, generating genetically diverse populations. We estimated the overall transmission bottleneck size to be 3 using 11 convincing donor-recipient transmission pairs. Our study provides new insights into genomic epidemiology and viral transmission, revealing how iSNVs become fixed in local clusters, followed by viral transmission across the community, which contributes to population diversity.

Experimental viral spillover across 25 million year gap in Rodentia reveals limited viral transmission and purifying selection of a picornavirus

When a virus crosses from one host species to another, the consequences can be devastating. However, animal models to empirically evaluate cross-species transmission can fail to recapitulate natural transmission routes, physiologically relevant doses of pathogens, and population structures of naturally circulating viruses. Here, we present a new model of cross-species transmission where deer mice (Peromyscus maniculatus) are exposed to the natural virome of pet store mice (Mus musculus). Using RNA sequencing, we tracked viral transmission via fecal-oral routes and found the evidence of transmission of murine astroviruses, coronaviruses, and picornaviruses. Deep sequencing of murine kobuvirus revealed tight bottlenecks during transmission and purifying selection that leaves limited diversity present after transmission from Mus to Peromyscus. This work provides a structure for studying viral bottlenecks across species while keeping natural variation of viral populations intact and a high resolution look at within-host dynamics that occur during the initial stages of cross-species viral transmission.IMPORTANCEViral spillover events can have devastating public health consequences. Tracking cross-species transmission in real-time and evaluating viral evolution during the initial spillover event are useful for understanding how viruses adapt to new hosts. Using our new animal model and next generation sequencing, we develop a framework for understanding intrahost viral evolution and bottleneck events, which are very difficult to study in natural transmission settings.

Local patterns of spread of influenza A H3N2 virus in coastal Kenya over a 1-year period revealed through virus sequence data

The patterns of spread of influenza A viruses in local populations in tropical and sub-tropical regions are unclear due to sparsity of representative spatiotemporal sequence data. We sequenced and analyzed 58 influenza A(H3N2) virus genomes sampled between December 2015 and December 2016 from nine health facilities within the Kilifi Health and Demographic Surveillance System (KHDSS), a predominantly rural region, covering approximately 891 km2 along the Kenyan coastline. The genomes were compared with 1571 contemporaneous global sequences from 75 countries. We observed at least five independent introductions of A(H3N2) viruses into the region during the one-year period, with the importations originating from Africa, Europe, and North America. We also inferred 23 virus location transition events between the nine facilities included in the study. International virus imports into the study area were captured at the facilities of Chasimba, Matsangoni, Mtondia, and Mavueni, while all four exports from the region were captured from the Chasimba facility, all occurring to Africa destinations. A strong spatial clustering of virus strains at all locations was observed associated with local evolution. Our study shows that influenza A(H3N2) virus epidemics in local populations appear to be characterized by limited introductions followed by significant local spread and evolution. Knowledge of the viral lineages that circulate within specific populations in understudied tropical and subtropical regions is required to understand the full diversity and global ecology of influenza viruses and to inform vaccination strategies within these populations.

Influenza A virus within-host evolution and positive selection in a densely sampled household cohort over three seasons

While influenza A virus (IAV) antigenic drift has been documented globally, in experimental animal infections, and in immunocompromised hosts, positive selection has generally not been detected in acute infections. This is likely due to challenges in distinguishing selected rare mutations from sequencing error, a reliance on cross-sectional sampling, and/or the lack of formal tests of selection for individual sites. Here, we sequenced IAV populations from 346 serial, daily nasal swabs from 143 individuals collected over three influenza seasons in a household cohort. Viruses were sequenced in duplicate, and intrahost single nucleotide variants (iSNVs) were identified at a 0.5% frequency threshold. Within-host populations exhibited low diversity, with >75% mutations present at <2% frequency. Children (0-5 years) had marginally higher within-host evolutionary rates than adolescents (6-18 years) and adults (>18 years, 4.4 × 10-6 vs. 9.42 × 10-7 and 3.45 × 10-6, P < .001). Forty-five iSNVs had evidence of parallel evolution but were not over-represented in HA and NA. Several increased from minority to consensus level, with strong linkage among iSNVs across segments. A Wright-Fisher approximate Bayesian computational model identified positive selection at 23/256 loci (9%) in A(H3N2) specimens and 19/176 loci (11%) in A(H1N1)pdm09 specimens, and these were infrequently found in circulation. Overall, we found that within-host IAV populations were subject to genetic drift and purifying selection, with only subtle differences across seasons, subtypes, and age strata. Positive selection was rare and inconsistently detected.

Examining intra-host genetic variation of RSV by short read high-throughput sequencing

Every viral infection entails an evolving population of viral genomes. High-throughput sequencing technologies can be used to characterize such populations, but to date there are few published examples of such work. In addition, mixed sequencing data are sometimes used to infer properties of infecting genomes without discriminating between genome-derived reads and reads from the much more abundant, in the case of a typical active viral infection, transcripts. Here we apply capture probe-based short read high-throughput sequencing to nasal wash samples taken from a previously described group of adult hematopoietic cell transplant (HCT) recipients naturally infected with respiratory syncytial virus (RSV). We separately analyzed reads from genomes and transcripts for the levels and distribution of genetic variation by calculating per position Shannon entropies. Our analysis reveals a low level of genetic variation within the RSV infections analyzed here, but with interesting differences between genomes and transcripts in 1) average per sample Shannon entropies; 2) the genomic distribution of variation 'hotspots'; and 3) the genomic distribution of hotspots encoding alternative amino acids. In all, our results suggest the importance of separately analyzing reads from genomes and transcripts when interpreting high-throughput sequencing data for insight into intra-host viral genome replication, expression, and evolution.

Influenza A virus within-host evolution and positive selection in a densely sampled household cohort over three seasons

While influenza A virus (IAV) antigenic drift has been documented globally, in experimental animal infections, and in immunocompromised hosts, positive selection has generally not been detected in acute infections. This is likely due to challenges in distinguishing selected rare mutations from sequencing error, a reliance on cross-sectional sampling, and/or the lack of formal tests of selection for individual sites. Here, we sequenced IAV populations from 346 serial, daily nasal swabs from 143 individuals collected over three influenza seasons in a household cohort. Viruses were sequenced in duplicate, and intrahost single nucleotide variants (iSNV) were identified at a 0.5% frequency threshold. Within-host populations were subject to purifying selection with >75% mutations present at <2% frequency. Children (0-5 years) had marginally higher within-host evolutionary rates than adolescents (6-18 years) and adults (>18 years, 4.4×10-6 vs. 9.42×10-7 and 3.45×10-6, p <0.001). Forty-five iSNV had evidence of parallel evolution, but were not overrepresented in HA and NA. Several increased from minority to consensus level, with strong linkage among iSNV across segments. A Wright Fisher Approximate Bayesian Computational model identified positive selection at 23/256 loci (9%) in A(H3N2) specimens and 19/176 loci (11%) in A(H1N1)pdm09 specimens, and these were infrequently found in circulation. Overall, we found that within-host IAV populations were subject to purifying selection and genetic drift, with only subtle differences across seasons, subtypes, and age strata. Positive selection was rare and inconsistently detected.

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.

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.

Barcoded SARS-CoV-2 viruses define the impact of time and route of transmission on the transmission bottleneck in a Syrian hamster model

The transmission bottleneck, defined as the number of viruses that transmit from one host to infect another, is an important determinant of the rate of virus evolution and the level of immunity required to protect against virus transmission. Despite its importance, SARS-CoV-2's transmission bottleneck remains poorly characterized, in part due to a lack of quantitative measurement tools. To address this, we adapted a SARS-CoV-2 reverse genetics system to generate a pool of >200 isogenic SARS-CoV-2 viruses harboring specific 6-nucleotide barcodes inserted in ORF10, a non-translated ORF. We directly inoculated donor Syrian hamsters intranasally with this barcoded virus pool and exposed a paired naïve contact hamster to each donor. Following exposure, the nasal turbinates, trachea, and lungs were collected, viral titers were measured, and the number of barcodes in each tissue were enumerated to quantify the transmission bottleneck. The duration and route (airborne, direct contact, and fomite) of exposure were varied to assess their impact on the transmission bottleneck. In airborne-exposed hamsters, the transmission bottleneck increased with longer exposure durations. We found that direct contact exposure produced the largest transmission bottleneck (average 27 BCs), followed by airborne exposure (average 16 BCs) then fomite exposure (average 8 BCs). Interestingly, we detected unique BCs in both the upper and lower respiratory tract of contact animals from all routes of exposure, suggesting that SARS-CoV-2 can directly infect hamster lungs. Altogether, these findings highlight the utility of barcoded viruses as tools to rigorously study virus transmission. In the future, barcoded SARS-CoV-2 will strengthen studies of immune factors that influence virus transmission.

Influenza A genomic diversity during human infections underscores the strength of genetic drift and the existence of tight transmission bottlenecks

Influenza infections result in considerable public health and economic impacts each year. One of the contributing factors to the high annual incidence of human influenza is the virus's ability to evade acquired immunity through continual antigenic evolution. Understanding the evolutionary forces that act within and between hosts is therefore critical to interpreting past trends in influenza virus evolution and in predicting future ones. Several studies have analyzed longitudinal patterns of influenza A virus genetic diversity in natural human infections to assess the relative contributions of selection and genetic drift on within-host evolution. However, in these natural infections, within-host viral populations harbor very few single-nucleotide variants, limiting our resolution in understanding the forces acting on these populations in vivo. Furthermore, low levels of within-host viral genetic diversity limit the ability to infer the extent of drift across transmission events. Here, we propose to use influenza virus genomic diversity as an alternative signal to better understand within- and between-host patterns of viral evolution. Specifically, we focus on the dynamics of defective viral genomes (DVGs), which harbor large internal deletions in one or more of influenza virus's eight gene segments. Our longitudinal analyses of DVGs show that influenza A virus populations are highly dynamic within hosts, corroborating previous findings based on viral genetic diversity that point toward the importance of genetic drift in driving within-host viral evolution. Furthermore, our analysis of DVG populations across transmission pairs indicates that DVGs rarely appeared to be shared, indicating the presence of tight transmission bottlenecks. Our analyses demonstrate that viral genomic diversity can be used to complement analyses based on viral genetic diversity to reveal processes that drive viral evolution within and between hosts.

Persistence of SARS-CoV-2 infection and viral intra- and inter-host evolution in COVID-19 hospitalized patients

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) persistence in COVID-19 patients could play a key role in the emergence of variants of concern. The rapid intra-host evolution of SARS-CoV-2 may result in an increased transmissibility, immune and therapeutic escape which could be a direct consequence of COVID-19 epidemic currents. In this context, a longitudinal retrospective study on eight consecutive COVID-19 patients with persistent SARS-CoV-2 infection, from January 2022 to March 2023, was conducted. To characterize the intra- and inter-host viral evolution, whole genome sequencing and phylogenetic analysis were performed on nasopharyngeal samples collected at different time points. Phylogenetic reconstruction revealed an accelerated SARS-CoV-2 intra-host evolution and emergence of antigenically divergent variants. The Bayesian inference and principal coordinate analysis analysis showed a host-based genomic structuring among antigenically divergent variants, that might reflect the positive effect of containment practices, within the critical hospital area. All longitudinal antigenically divergent isolates shared a wide range of amino acidic (aa) changes, particularly in the Spike (S) glycoprotein, that increased viral transmissibility (K417N, S477N, N501Y and Q498R), enhanced infectivity (R346T, S373P, R408S, T478K, Q498R, Y505H, D614G, H655Y, N679K and P681H), caused host immune escape (S371L, S375F, T376A, K417N, and K444T/R) and displayed partial or complete resistance to treatments (G339D, R346K/T, S371F/L, S375F, T376A, D405N, N440K, G446S, N460K, E484A, F486V, Q493R, G496S and Q498R). These results suggest that multiple novel variants which emerge in the patient during persistent infection, might spread to another individual and continue to evolve. A pro-active genomic surveillance of persistent SARS-CoV-2 infected patients is recommended to identify genetically divergent lineages before their diffusion.

Highly Pathogenic Avian Influenza (HPAI) H5 Clade 2.3.4.4b Virus Infection in Birds and Mammals

Avian influenza viruses (AIVs) are highly contagious respiratory viruses of birds, leading to significant morbidity and mortality globally and causing substantial economic losses to the poultry industry and agriculture. Since their first isolation in 2013-2014, the Asian-origin H5 highly pathogenic avian influenza viruses (HPAI) of clade 2.3.4.4b have undergone unprecedented evolution and reassortment of internal gene segments. In just a few years, it supplanted other AIV clades, and now it is widespread in the wild migratory waterfowl, spreading to Asia, Europe, Africa, and the Americas. Wild waterfowl, the natural reservoir of LPAIVs and generally more resistant to the disease, also manifested high morbidity and mortality with HPAIV clade 2.3.4.4b. This clade also caused overt clinical signs and mass mortality in a variety of avian and mammalian species never reported before, such as raptors, seabirds, sealions, foxes, and others. Most notably, the recent outbreaks in dairy cattle were associated with the emergence of a few critical mutations related to mammalian adaptation, raising concerns about the possibility of jumping species and acquisition of sustained human-to-human transmission. The main clinical signs and anatomopathological findings associated with clade 2.3.4.4b virus infection in birds and non-human mammals are hereby summarized.

The airborne transmission of viruses causes tight transmission bottlenecks

The transmission bottleneck describes the number of viral particles that initiate an infection in a new host. Previous studies have used genome sequence data to suggest that transmission bottlenecks for influenza and SARS-CoV-2 involve few viral particles, but the general principles of virus transmission are not fully understood. Here we show that, across a broad range of circumstances, tight transmission bottlenecks are a simple consequence of the physical process of airborne viral transmission. We use mathematical modelling to describe the physical process of the emission and inhalation of infectious particles, deriving the result that that the great majority of transmission bottlenecks involve few viral particles. While exceptions to this rule exist, the circumstances needed to create these exceptions are likely very rare. We thus provide a physical explanation for previous inferences of bottleneck size, while predicting that tight transmission bottlenecks prevail more generally in respiratory virus transmission.

Within-host influenza viral diversity in the pediatric population as a function of age, vaccine, and health status

Seasonal influenza virus predominantly evolves through antigenic drift, marked by the accumulation of mutations at antigenic sites. Because of antigenic drift, influenza vaccines are frequently updated, though their efficacy may still be limited due to strain mismatches. Despite the high levels of viral diversity observed across populations, most human studies reveal limited intrahost diversity, leaving the origin of population-level viral diversity unclear. Previous studies show host characteristics, such as immunity, might affect within-host viral evolution. Here we investigate influenza A viral diversity in children aged between 6 months and 18 years. Influenza virus evolution in children is less well characterized than in adults, yet may be associated with higher levels of viral diversity given the lower level of pre-existing immunity and longer durations of infection in children. We obtained influenza isolates from banked influenza A-positive nasopharyngeal swabs collected at the Children's Hospital of Philadelphia during the 2017-18 influenza season. Using next-generation sequencing, we evaluated the population of influenza viruses present in each sample. We characterized within-host viral diversity using the number and frequency of intrahost single-nucleotide variants (iSNVs) detected in each sample. We related viral diversity to clinical metadata, including subjects' age, vaccination status, and comorbid conditions, as well as sample metadata such as virus strain and cycle threshold. Consistent with previous studies, most samples contained low levels of diversity with no clear association between the subjects' age, vaccine status, or health status. Further, there was no enrichment of iSNVs near known antigenic sites. Taken together, these findings are consistent with previous observations that the majority of intrahost influenza virus infection is characterized by low viral diversity without evidence of diversifying selection.

Estimating the reproduction number and transmission heterogeneity from the size distribution of clusters of identical pathogen sequences

Quantifying transmission intensity and heterogeneity is crucial to ascertain the threat posed by infectious diseases and inform the design of interventions. Methods that jointly estimate the reproduction number R and the dispersion parameter k have however mainly remained limited to the analysis of epidemiological clusters or contact tracing data, whose collection often proves difficult. Here, we show that clusters of identical sequences are imprinted by the pathogen offspring distribution, and we derive an analytical formula for the distribution of the size of these clusters. We develop and evaluate an inference framework to jointly estimate the reproduction number and the dispersion parameter from the size distribution of clusters of identical sequences. We then illustrate its application across a range of epidemiological situations. Finally, we develop a hypothesis testing framework relying on clusters of identical sequences to determine whether a given pathogen genetic subpopulation is associated with increased or reduced transmissibility. Our work provides tools to estimate the reproduction number and transmission heterogeneity from pathogen sequences without building a phylogenetic tree, thus making it easily scalable to large pathogen genome datasets.

Antigenic drift expands viral escape pathways from imprinted host humoral immunity

An initial virus exposure can imprint antibodies such that future responses to antigenically drifted strains are dependent on the identity of the imprinting strain. Subsequent exposure to antigenically distinct strains followed by affinity maturation can guide immune responses toward generation of cross-reactive antibodies. How viruses evolve in turn to escape these imprinted broad antibody responses is unclear. Here, we used clonal antibody lineages from two human donors recognizing conserved influenza virus hemagglutinin (HA) epitopes to assess viral escape potential using deep mutational scanning. We show that even though antibody affinity maturation does restrict the number of potential escape routes in the imprinting strain through repositioning the antibody variable domains, escape is still readily observed in drifted strains and attributed to epistatic networks within HA. These data explain how influenza virus continues to evolve in the human population by escaping even broad antibody responses.

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.

Extreme infectious titer variability in individual Aedes aegypti mosquitoes infected with Sindbis virus is associated with both differences in virus population structure and dramatic disparities in specific infectivity

Variability in how individuals respond to pathogens is a hallmark of infectious disease, yet the basis for individual variation in host response is often poorly understood. The titer of infectious virus among individual mosquitoes infected with arboviruses is frequently observed to vary by several orders of magnitude in a single experiment, even when the mosquitoes are highly inbred. To better understand the basis for this titer variation, we sequenced populations of Sindbis virus (SINV) obtained from individual infected Aedes aegypti mosquitoes that, despite being from a highly inbred laboratory colony, differed in their titers of infectious virus by approximately 10,000-fold. We observed genetic differences between these virus populations that indicated the virus present in the midguts of low titer mosquitoes was less fit than that of high titer mosquitoes, possibly due to founder effects that occurred during midgut infection. Furthermore, we found dramatic differences in the specific infectivity or SI (the ratio of infectious units/viral genome equivalents) between these virus populations, with the SI of low titer mosquitoes being up to 10,000-fold lower than that of high titer mosquitoes. Despite having similar amounts of viral genomes, low titer mosquitoes appeared to contain less viral particles, suggesting that viral genomes were packaged into virions less efficiently than in high titer mosquitoes. Finally, antibiotic treatment, which has been shown to suppress mosquito antiviral immunity, caused an increase in SI. Our results indicate that the extreme variation that is observed in SINV infectious titer between individual Ae. aegypti mosquitoes is due to both genetic differences between virus populations and to differences in the proportion of genomes that are packaged into infectious particles.

Within-host evolutionary dynamics and tissue compartmentalization during acute SARS-CoV-2 infection

The global evolution of SARS-CoV-2 depends in part upon the evolutionary dynamics within individual hosts with varying immune histories. To characterize the within-host evolution of acute SARS-CoV-2 infection, we sequenced saliva and nasal samples collected daily from vaccinated and unvaccinated individuals early during infection. We show that longitudinal sampling facilitates high-confidence genetic variant detection and reveals evolutionary dynamics missed by less-frequent sampling strategies. Within-host dynamics in both unvaccinated and vaccinated individuals appeared largely stochastic; however, in rare cases, minor genetic variants emerged to frequencies sufficient for forward transmission. Finally, we detected significant genetic compartmentalization of viral variants between saliva and nasal swab sample sites in many individuals. Altogether, these data provide a high-resolution profile of within-host SARS-CoV-2 evolutionary dynamics.IMPORTANCEWe detail the within-host evolutionary dynamics of SARS-CoV-2 during acute infection in 31 individuals using daily longitudinal sampling. We characterized patterns of mutational accumulation for unvaccinated and vaccinated individuals, and observed that temporal variant dynamics in both groups were largely stochastic. Comparison of paired nasal and saliva samples also revealed significant genetic compartmentalization between tissue environments in multiple individuals. Our results demonstrate how selection, genetic drift, and spatial compartmentalization all play important roles in shaping the within-host evolution of SARS-CoV-2 populations during acute infection.

Genetic consequences of effective and suboptimal dosing with mutagenic drugs in a hamster model of SARS-CoV-2 infection

Mutagenic antiviral drugs have shown promise against multiple viruses, but concerns have been raised about whether their use might promote the emergence of new and harmful viral variants. Recently, genetic signatures associated with molnupiravir use have been identified in the global SARS-COV-2 population. Here, we examine the consequences of using favipiravir and molnupiravir to treat SARS-CoV-2 infection in a hamster model, comparing viral genome sequence data collected from (1) untreated hamsters, and (2) from hamsters receiving effective and suboptimal doses of treatment. We identify a broadly linear relationship between drug dose and the extent of variation in treated viral populations, with a high proportion of this variation being composed of variants at frequencies of less than 1 per cent, below typical thresholds for variant calling. Treatment with an effective dose of antiviral drug was associated with a gain of between 7 and 10 variants per viral genome relative to drug-free controls: even after a short period of treatment a population founded by a transmitted virus could contain multiple sequence differences to that of the original host. Treatment with a suboptimal dose of drug showed intermediate gains of variants. No dose-dependent signal was identified in the numbers of single-nucleotide variants reaching frequencies in excess of 5 per cent. We did not find evidence to support the emergence of drug resistance or of novel immune phenotypes. Our study suggests that where onward transmission occurs, a short period of treatment with mutagenic drugs may be sufficient to generate a significant increase in the number of viral variants transmitted.

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.

Viral expansion after transfer is a primary driver of influenza A virus transmission bottlenecks

For many viruses, narrow bottlenecks acting during transmission sharply reduce genetic diversity in a recipient host relative to the donor. Since genetic diversity represents adaptive potential, such losses of diversity are though to limit the opportunity for viral populations to undergo antigenic change and other adaptive processes. Thus, a detailed picture of evolutionary dynamics during transmission is critical to understanding the forces driving viral evolution at an epidemiologic scale. To advance this understanding, we used a novel barcoded virus library and a guinea pig model of transmission to decipher where in the transmission process diversity is lost for influenza A viruses. In inoculated guinea pigs, we show that a high level of viral genetic diversity is maintained across time. Continuity in the barcodes detected furthermore indicates that stochastic effects are not pronounced within inoculated hosts. Importantly, in both aerosol-exposed and direct contact-exposed animals, we observed many barcodes at the earliest time point(s) positive for infectious virus, indicating robust transfer of diversity through the environment. This high viral diversity is short-lived, however, with a sharp decline seen 1-2 days after initiation of infection. Although major losses of diversity at transmission are well described for influenza A virus, our data indicate that events that occur following viral transfer and during the earliest stages of natural infection have a predominant role in this process. This finding suggests that immune selection may have greater opportunity to operate during influenza A transmission than previously recognized.

Co-evolution of immunity and seasonal influenza viruses

Seasonal influenza viruses cause recurring global epidemics by continually evolving to escape host immunity. The viral constraints and host immune responses that limit and drive the evolution of these viruses are increasingly well understood. However, it remains unclear how most of these advances improve the capacity to reduce the impact of seasonal influenza viruses on human health. In this Review, we synthesize recent progress made in understanding the interplay between the evolution of immunity induced by previous infections or vaccination and the evolution of seasonal influenza viruses driven by the heterogeneous accumulation of antibody-mediated immunity in humans. We discuss the functional constraints that limit the evolution of the viruses, the within-host evolutionary processes that drive the emergence of new virus variants, as well as current and prospective options for influenza virus control, including the viral and immunological barriers that must be overcome to improve the effectiveness of vaccines and antiviral drugs.

A Simulation Framework for Modeling the Within-Patient Evolutionary Dynamics of SARS-CoV-2

The global impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs. Such genomic scans for rarely acting positive selection are best performed via comparison of empirical data with simulated data wherein commonly acting evolutionary factors, including mutation and recombination, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. Although there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intrahost evolutionary dynamics. To construct such a baseline model, we develop a simulation framework that enables one to establish expectations for underlying levels and patterns of patient-level variation. By varying eight key parameters, we evaluated 12,096 different model-parameter combinations and compared them with existing empirical data. Of these, 592 models (∼5%) were plausible based on the resulting mean expected number of segregating variants. These plausible models shared several commonalities shedding light on intrahost SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed toward strongly deleterious mutations. We also describe important areas of model uncertainty and highlight additional sequence data that may help to further refine a baseline model. This study lays the groundwork for the improved analysis of existing and future SARS-CoV-2 within-patient data.

Genetic drift and purifying selection shape within-host influenza A virus populations during natural swine infections

Patterns of within-host influenza A virus (IAV) diversity and evolution have been described in natural human infections, but these patterns remain poorly characterized in non-human hosts. Elucidating these dynamics is important to better understand IAV biology and the evolutionary processes that govern spillover into humans. Here, we sampled an IAV outbreak in pigs during a week-long county fair to characterize viral diversity and evolution in this important reservoir host. Nasal wipes were collected on a daily basis from all pigs present at the fair, yielding up to 421 samples per day. Subtyping of PCR-positive samples revealed the co-circulation of H1N1 and H3N2 subtype IAVs. PCR-positive samples with robust Ct values were deep-sequenced, yielding 506 sequenced samples from a total of 253 pigs. Based on higher-depth re-sequenced data from a subset of these initially sequenced samples (260 samples from 168 pigs), we characterized patterns of within-host IAV genetic diversity and evolution. We find that IAV genetic diversity in single-subtype infected pigs is low, with the majority of intra-host single nucleotide variants (iSNVs) present at frequencies of <10%. The ratio of the number of nonsynonymous to the number of synonymous iSNVs is significantly lower than under the neutral expectation, indicating that purifying selection shapes patterns of within-host viral diversity in swine. The dynamic turnover of iSNVs and their pronounced frequency changes further indicate that genetic drift also plays an important role in shaping IAV populations within pigs. Taken together, our results highlight similarities in patterns of IAV genetic diversity and evolution between humans and swine, including the role of stochastic processes in shaping within-host IAV dynamics.

Loss of West Nile virus genetic diversity during mosquito infection due to species-dependent population bottlenecks

Vector competence (VC) refers to the efficiency of pathogen transmission by vectors. Each step in the infection of a mosquito vector constitutes a barrier to transmission that may impose bottlenecks on virus populations. West Nile virus (WNV) is maintained by multiple mosquito species with varying VC. However, the extent to which bottlenecks and VC are linked is poorly understood. Similarly, quantitative analyses of mosquito-imposed bottlenecks on virus populations are limited. We used molecularly barcoded WNV to quantify tissue-associated population bottlenecks in three variably competent WNV vectors. Our results confirm strong population bottlenecks during mosquito infection that are capable of dramatically reshaping virus population structure in a non-selective manner. In addition, we found that mosquitoes with differing VC uniquely shape WNV population structure: highly competent vectors are more likely to contribute to the maintenance of rare viral genotypes. These findings have important implications for arbovirus emergence and evolution.

Influenza virus transcription and progeny production are poorly correlated in single cells

The ultimate success of a viral infection at the cellular level is determined by the number of progeny virions produced. However, most single-cell studies of infection quantify the expression of viral transcripts and proteins, rather than the amount of progeny virions released from infected cells. Here, we overcome this limitation by simultaneously measuring transcription and progeny production from single influenza virus-infected cells by embedding nucleotide barcodes in the viral genome. We find that viral transcription and progeny production are poorly correlated in single cells. The cells that transcribe the most viral mRNA do not produce the most viral progeny and often represent aberrant infections that fail to express the influenza NS gene. However, only some of the discrepancy between transcription and progeny production can be explained by viral gene absence or mutations: there is also a wide range of progeny production among cells infected by complete unmutated virions. Overall, our results show that viral transcription is a relatively poor predictor of an infected cell's contribution to the progeny population.

Immune response in influenza virus infection and modulation of immune injury by viral neuraminidase

Influenza A viruses cause severe respiratory illnesses in humans and animals. Overreaction of the innate immune response to influenza virus infection results in hypercytokinemia, which is responsible for mortality and morbidity. The influenza A virus surface glycoprotein neuraminidase (NA) plays a vital role in viral attachment, entry, and virion release from infected cells. NA acts as a sialidase, which cleaves sialic acids from cell surface proteins and carbohydrate side chains on nascent virions. Here, we review progress in understanding the role of NA in modulating host immune response to influenza virus infection. We also discuss recent exciting findings targeting NA protein to interrupt influenza-induced immune injury.

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.

A simulation framework for modeling the within-patient evolutionary dynamics of SARS-CoV-2

The global impact of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs. Such genomic scans for positive selection are best performed via comparison of empirical data to simulated data wherein evolutionary factors, including mutation and recombination rates, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. While there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intra-host evolutionary dynamics. To construct such a baseline model, we develop a simulation framework that enables one to establish expectations for underlying levels and patterns of patient-level variation. By varying eight key parameters, we evaluated 12,096 different model-parameter combinations and compared them to existing empirical data. Of these, 592 models (~5%) were plausible based on the resulting mean expected number of segregating variants. These plausible models shared several commonalities shedding light on intra-host SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed towards strongly deleterious mutations. We also describe important areas of model uncertainty and highlight additional sequence data that may help to further refine a baseline model. This study lays the groundwork for the improved analysis of existing and future SARS-CoV-2 within-patient data.

Host obesity impacts genetic variation in influenza A viral populations

Obesity 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. Obesity is well established as a risk factor for many noncommunicable diseases; however, its consequences for infectious disease are poorly understood. 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. Here, we investigated the impact of host obesity on IAV genetic variation using a diet induced obesity ferret model. We infected obese and lean male ferrets with the A/Hong Kong/1073/1999 (H9N2) IAV 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 recurrent low-frequency mutations throughout the genome that were specific to obese hosts. Despite these obese-specific variants, 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 (HA) and polymerase genes (PB2 and PB1). As with single nucleotide variants, we identified a class of defective viral genomes (DVGs) that were found uniquely in either obese or lean hosts, but overall DVG diversity and dynamics did not differ between the two groups. 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.

From vaccine to pathogen: Modeling Sabin 2 vaccine virus reversion and evolutionary epidemiology in Matlab, Bangladesh

The oral poliovirus vaccines (OPVs) are one of the most effective disease eradication tools in public health. However, the OPV strains are genetically unstable and can cause outbreaks of circulating, vaccine-derived Type 2 poliovirus (cVDPV2) that are clinically indistinguishable from wild poliovirus (WPV) outbreaks. Here, we developed a Sabin 2 reversion model that simulates the reversion of Sabin 2 to reacquire a WPV-like phenotype based on the clinical differences in shedding duration and infectiousness between individuals vaccinated with Sabin 2 and those infected with WPV. Genetic reversion is informed by a canonical reversion pathway defined by three gatekeeper mutations (A481G, U2909C, and U398C) and the accumulation of deleterious nonsynonymous mutations. Our model captures essential aspects of both phenotypic and molecular evolution and simulates transmission using a multiscale transmission model that consolidates the relationships among immunity, susceptibility, and transmission risk. Despite rapid Sabin 2 attenuation reversal, we show that the emergence of a revertant virus does not guarantee a cVDPV2 outbreak. When simulating outbreaks in Matlab, Bangladesh, we found that cVDPV2 outbreaks are most likely in areas with low population-level immunity and poor sanitation. In Matlab, our model predicted that declining immunity against Type 2 poliovirus following the cessation of routine OPV vaccination was not enough to promote cVDPV2 emergence. However, cVDPV2 emergencedepended on the average viral exposure dose per contact, which was modeled as a combination of the viral concentration per fecal gram and the average fecal-oral dose per contact. These results suggest that cVDPV2 emergence risk can be mitigated by reducing the amount of infectious fecal material individuals are exposed to. Thus, a combined strategy of assessing and improving sanitation levels in conjunction with high-coverage vaccination campaigns could limit the future cVDPV2 emergence.

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.

The evolution of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths and substantial morbidity worldwide. Intense scientific effort to understand the biology of SARS-CoV-2 has resulted in daunting numbers of genomic sequences. We witnessed evolutionary events that could mostly be inferred indirectly before, such as the emergence of variants with distinct phenotypes, for example transmissibility, severity and immune evasion. This Review explores the mechanisms that generate genetic variation in SARS-CoV-2, underlying the within-host and population-level processes that underpin these events. We examine the selective forces that likely drove the evolution of higher transmissibility and, in some cases, higher severity during the first year of the pandemic and the role of antigenic evolution during the second and third years, together with the implications of immune escape and reinfections, and the increasing evidence for and potential relevance of recombination. In order to understand how major lineages, such as variants of concern (VOCs), are generated, we contrast the evidence for the chronic infection model underlying the emergence of VOCs with the possibility of an animal reservoir playing a role in SARS-CoV-2 evolution, and conclude that the former is more likely. We evaluate uncertainties and outline scenarios for the possible future evolutionary trajectories of SARS-CoV-2.

Developing an appropriate evolutionary baseline model for the study of SARS-CoV-2 patient samples

Over the past 3 years, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread through human populations in several waves, resulting in a global health crisis. In response, genomic surveillance efforts have proliferated in the hopes of tracking and anticipating the evolution of this virus, resulting in millions of patient isolates now being available in public databases. Yet, while there is a tremendous focus on identifying newly emerging adaptive viral variants, this quantification is far from trivial. Specifically, multiple co-occurring and interacting evolutionary processes are constantly in operation and must be jointly considered and modeled in order to perform accurate inference. We here outline critical individual components of such an evolutionary baseline model-mutation rates, recombination rates, the distribution of fitness effects, infection dynamics, and compartmentalization-and describe the current state of knowledge pertaining to the related parameters of each in SARS-CoV-2. We close with a series of recommendations for future clinical sampling, model construction, and statistical analysis.

Viral intra-host evolutionary dynamics revealed via serial passage of Japanese encephalitis virus in vitro

Analyses of viral inter- and intra-host mutations could better guide the prevention and control of infectious diseases. For a long time, studies on viral evolution have focused on viral inter-host variations. Next-generation sequencing has accelerated the investigations of viral intra-host diversity. However, the theoretical basis and dynamic characteristics of viral intra-host mutations remain unknown. Here, using serial passages of the SA14-14-2 vaccine strain of Japanese encephalitis virus (JEV) as the in vitro model, the distribution characteristics of 1,788 detected intra-host single-nucleotide variations (iSNVs) and their mutated frequencies from 477 deep-sequenced samples were analyzed. Our results revealed that in adaptive (baby hamster kidney (BHK)) cells, JEV is under a nearly neutral selection pressure, and both non-synonymous and synonymous mutations represent an S-shaped growth trend over time. A higher positive selection pressure was observed in the nonadaptive (C6/36) cells, and logarithmic growth in non-synonymous iSNVs and linear growth in synonymous iSNVs were observed over time. Moreover, the mutation rates of the NS4B protein and the untranslated region (UTR) of the JEV are significantly different between BHK and C6/36 cells, suggesting that viral selection pressure is regulated by different cellular environments. In addition, no significant difference was detected in the distribution of mutated frequencies of iSNVs between BHK and C6/36 cells.

A Cold Case of Equine Influenza Disentangled with Nanopore Sequencing

Massive sequencing techniques have allowed us to develop straightforward approaches for the whole genome sequencing of viruses, including influenza viruses, generating information that is useful for improving the levels and dimensions of data analysis, even for archival samples. Using the Nanopore platform, we determined the whole genome sequence of an H3N8 equine influenza virus, identified from a 2005 outbreak in Apulia, Italy, whose origin had remained epidemiologically unexplained. The virus was tightly related (>99% at the nucleotide level) in all the genome segments to viruses identified in Poland in 2005–2008 and it was seemingly introduced locally with horse trading for the meat industry. In the phylogenetic analysis based on the eight genome segments, strain ITA/2005/horse/Bari was found to cluster with sub-lineage Florida 2 in the HA and M genes, whilst in the other genes it clustered with strains of the Eurasian lineage, revealing a multi-reassortant nature.

Influenza A virus coinfection dynamics are shaped by distinct virus-virus interactions within and between cells

When multiple viral populations propagate within the same host environment, they often shape each other's dynamics. These interactions can be positive or negative and can occur at multiple scales, from coinfection of a cell to co-circulation at a global population level. For influenza A viruses (IAVs), the delivery of multiple viral genomes to a cell substantially increases burst size. However, despite its relevance for IAV evolution through reassortment, the implications of this positive density dependence for coinfection between distinct IAVs has not been explored. Furthermore, the extent to which these interactions within the cell shape viral dynamics at the level of the host remains unclear. Here we show that, within cells, diverse coinfecting IAVs strongly augment the replication of a focal strain, irrespective of their homology to the focal strain. Coinfecting viruses with a low intrinsic reliance on multiple infection offer the greatest benefit. Nevertheless, virus-virus interactions at the level of the whole host are antagonistic. This antagonism is recapitulated in cell culture when the coinfecting virus is introduced several hours prior to the focal strain or under conditions conducive to multiple rounds of viral replication. Together, these data suggest that beneficial virus-virus interactions within cells are counterbalanced by competition for susceptible cells during viral propagation through a tissue. The integration of virus-virus interactions across scales is critical in defining the outcomes of viral coinfection.

Investigating Epidemiologic and Molecular Links Between Patients With Community- and Hospital-Acquired Influenza A: 2017-2018 and 2019-2020, Michigan

Background

Hospital-acquired influenza virus infection (HAII) can cause severe morbidity and mortality. Identifying potential transmission routes can inform prevention strategies.

Methods

We identified all hospitalized patients testing positive for influenza A virus at a large, tertiary care hospital during the 2017-2018 and 2019-2020 influenza seasons. Hospital admission dates, locations of inpatient service, and clinical influenza testing information were retrieved from the electronic medical record. Time-location groups of epidemiologically linked influenza patients were defined and contained ≥1 presumed HAII case (first positive ≥48 hours after admission). Genetic relatedness within time-location groups was assessed by whole genome sequencing.

Results

During the 2017-2018 season, 230 patients tested positive for influenza A(H3N2) or unsubtyped influenza A including 26 HAIIs. There were 159 influenza A(H1N1)pdm09 or unsubtyped influenza A-positive patients identified during the 2019-2020 season including 33 HAIIs. Consensus sequences were obtained for 177 (77%) and 57 (36%) of influenza A cases in 2017-2018 and 2019-2020, respectively. Among all influenza A cases, there were 10 time-location groups identified in 2017-2018 and 13 in 2019-2020; 19 of 23 groups included ≤4 patients. In 2017-2018, 6 of 10 groups had ≥2 patients with sequence data, including ≥1 HAII case. Two of 13 groups met this criteria in 2019-2020. Two time-location groups from 2017-2018 each contained 3 genetically linked cases.

Conclusions

Our results suggest that HAIIs arise from outbreak transmission from nosocomial sources as well as single infections from unique community introductions.

Rapid transmission and tight bottlenecks constrain the evolution of highly transmissible SARS-CoV-2 variants

Transmission bottlenecks limit the spread of novel mutations and reduce the efficiency of selection along a transmission chain. While increased force of infection, receptor binding, or immune evasion may influence bottleneck size, the relationship between transmissibility and the transmission bottleneck is unclear. Here we compare the transmission bottleneck of non-VOC SARS-CoV-2 lineages to those of Alpha, Delta, and Omicron. We sequenced viruses from 168 individuals in 65 households. Most virus populations had 0-1 single nucleotide variants (iSNV). From 64 transmission pairs with detectable iSNV, we identify a per clade bottleneck of 1 (95% CI 1-1) for Alpha, Delta, and Omicron and 2 (95% CI 2-2) for non-VOC. These tight bottlenecks reflect the low diversity at the time of transmission, which may be more pronounced in rapidly transmissible variants. Tight bottlenecks will limit the development of highly mutated VOC in transmission chains, adding to the evidence that selection over prolonged infections may drive their evolution.

Heterosubtypic immune pressure accelerates emergence of influenza A virus escape phenotypes in mice

Rapid antigenic evolution of the influenza A virus surface antigen hemagglutinin undermines protection conferred by seasonal vaccines. Protective correlates targeted by universal vaccines such as cytotoxic T cells or HA stem directed broadly neutralizing antibodies have been shown to select for immune escape mutants during infection. We developed an in vivo serial passage mouse model for viral adaptation and used next generation sequencing to evaluate full genome viral evolution in the context of broadly protective immunity. Heterosubtypic immune pressure increased the incidence of genome-wide single nucleotide variants, though mutations found in early adapted populations were predominantly stochastic in nature. Prolonged adaptation under heterosubtypic immune selection resulted in the manifestation of highly virulent phenotypes that ablated vaccine mediated protection from mortality. High frequency mutations unique to escape phenotypes were identified within the polymerase encoding segments. These findings suggest that a suboptimial usage of population-wide universal influenza vaccine may drive formation of escape variants attributed to polygenic changes.

Rapid evolution of a bacterial parasite during outbreaks in two Daphnia populations

Myriad ecological and evolutionary factors can influence whether a particular parasite successfully transmits to a new host during a disease outbreak, with consequences for the structure and diversity of parasite populations. However, even though the diversity and evolution of parasite populations are of clear fundamental and applied importance, we have surprisingly few studies that track how genetic structure of parasites changes during naturally occurring outbreaks in non-human populations. Here, we used population genetic approaches to reveal how genotypes of a bacterial parasite, Pasteuria ramosa, change over time, focusing on how infecting P. ramosa genotypes change during the course of epidemics in Daphnia populations in two lakes. We found evidence for genetic change - and, therefore, evolution - of the parasite during outbreaks. In one lake, P. ramosa genotypes were structured by sampling date; in both lakes, genetic distance between groups of P. ramosa isolates increased with time between sampling. Diversity in parasite populations remained constant over epidemics, although one epidemic (which was large) had low genetic diversity while the other epidemic (which was small) had high genetic diversity. Our findings demonstrate that patterns of parasite evolution differ between outbreaks; future studies exploring the feedbacks among epidemic size, host diversity, and parasite genetic diversity would improve our understanding of parasite dynamics and evolution.

SARS-CoV-2 Genomic Diversity in Households Highlights the Challenges of Sequence-Based Transmission Inference

The reliability of sequence-based inference of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission is not clear. Sequence data from infections among household members can define the expected genomic diversity of a virus along a defined transmission chain. SARS-CoV-2 cases were identified prospectively among 2,369 participants in 706 households. Specimens with a reverse transcription-PCR cycle threshold of ≤30 underwent whole-genome sequencing. Intrahost single-nucleotide variants (iSNV) were identified at a ≥5% frequency. Phylogenetic trees were used to evaluate the relationship of household and community sequences. There were 178 SARS-CoV-2 cases in 706 households. Among 147 specimens sequenced, 106 yielded a whole-genome consensus with coverage suitable for identifying iSNV. Twenty-six households had sequences from multiple cases within 14 days. Consensus sequences were indistinguishable among cases in 15 households, while 11 had ≥1 consensus sequence that differed by 1 to 2 mutations. Sequences from households and the community were often interspersed on phylogenetic trees. Identification of iSNV improved inference in 2 of 15 households with indistinguishable consensus sequences and in 6 of 11 with distinct ones. In multiple-infection households, whole-genome consensus sequences differed by 0 to 1 mutations. Identification of shared iSNV occasionally resolved linkage, but the low genomic diversity of SARS-CoV-2 limits the utility of "sequence-only" transmission inference. IMPORTANCE We performed whole-genome sequencing of SARS-CoV-2 from prospectively identified cases in three longitudinal household cohorts. In a majority of multi-infection households, SARS-CoV-2 consensus sequences were indistinguishable, and they differed by 1 to 2 mutations in the rest. Importantly, even with modest genomic surveillance of the community (3 to 5% of cases sequenced), it was not uncommon to find community sequences interspersed with household sequences on phylogenetic trees. Identification of shared minority variants only occasionally resolved these ambiguities in transmission linkage. Overall, the low genomic diversity of SARS-CoV-2 limits the utility of "sequence-only" transmission inference. Our work highlights the need to carefully consider both epidemiologic linkage and sequence data to define transmission chains in households, hospitals, and other transmission settings.

Rapid transmission and tight bottlenecks constrain the evolution of highly transmissible SARS-CoV-2 variants

Transmission bottlenecks limit the spread of novel mutations and reduce the efficiency of natural selection along a transmission chain. Many viruses exhibit tight bottlenecks, and studies of early SARS-CoV-2 lineages identified a bottleneck of 1-3 infectious virions. While increased force of infection, host receptor binding, or immune evasion may influence bottleneck size, the relationship between transmissibility and the transmission bottleneck is unclear. Here, we compare the transmission bottleneck of non-variant-of-concern (non-VOC) SARS-CoV-2 lineages to those of the Alpha, Delta, and Omicron variants. We sequenced viruses from 168 individuals in 65 multiply infected households in duplicate to high depth of coverage. In 110 specimens collected close to the time of transmission, within-host diversity was extremely low. At a 2% frequency threshold, 51% had no intrahost single nucleotide variants (iSNV), and 42% had 1-2 iSNV. In 64 possible transmission pairs with detectable iSNV, we identified a bottleneck of 1 infectious virion (95% CI 1-1) for Alpha, Delta, and Omicron lineages and 2 (95% CI 2-2) in non-VOC lineages. The latter was driven by a single iSNV shared in one non-VOC household. The tight transmission bottleneck in SARS-CoV-2 is due to low genetic diversity at the time of transmission, a relationship that may be more pronounced in rapidly transmissible variants. The tight bottlenecks identified here will limit the development of highly mutated VOC in typical transmission chains, adding to the evidence that selection over prolonged infections in immunocompromised patients may drive their evolution.

A Comprehensive Review on the Current Vaccines and Their Efficacies to Combat SARS-CoV-2 Variants

Since the first case of Coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2019, SARS-CoV-2 infection has affected many individuals worldwide. Eventually, some highly infectious mutants-caused by frequent genetic recombination-have been reported for SARS-CoV-2 that can potentially escape from the immune responses and induce long-term immunity, linked with a high mortality rate. In addition, several reports stated that vaccines designed for the SARS-CoV-2 wild-type variant have mixed responses against the variants of concern (VOCs) and variants of interest (VOIs) in the human population. These results advocate the designing and development of a panvaccine with the potential to neutralize all the possible emerging variants of SARS-CoV-2. In this context, recent discoveries suggest the design of SARS-CoV-2 panvaccines using nanotechnology, siRNA, antibodies or CRISPR-Cas platforms. Thereof, the present comprehensive review summarizes the current vaccine design approaches against SARS-CoV-2 infection, the role of genetic mutations in the emergence of new viral variants, the efficacy of existing vaccines in limiting the infection of emerging SARS-CoV-2 variants, and efforts or challenges in designing SARS panvaccines.