Connecting within-host dynamics to the rate of viral molecular evolution

Optimized quantification of intra-host viral diversity in SARS-CoV-2 and influenza virus sequence data

High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant-calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller and use of replicate sequencing have the most significant impact on single-nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false-negative rates. When replicates are not available, using a combination of multiple callers with more stringent cutoffs is recommended. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intra-host viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intra-host variation, viral diversity, and viral evolution. IMPORTANCE When viruses replicate inside a host cell, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus nor strongly beneficial can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in the inclusion of false-positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant-calling tools. We used simulated and synthetic data to test their performance against a true set of variants and then used these studies to inform variant identification in data from SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.

Optimized Quantification of Intrahost Viral Diversity in SARS-CoV-2 and Influenza Virus Sequence Data

High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller, and use of replicate sequencing have the most significant impact on single nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false negative rates. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intrahost viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intrahost variation, viral diversity, and viral evolution.

IMPORTANCE

When viruses replicate inside a host, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus, nor strongly beneficial, can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in inclusion of false positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant calling tools. We used simulated and synthetic data to test their performance against a true set of variants, and then used these studies to inform variant identification in data from clinical SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.

Time and Mode of Epidemic HCV-2 Subtypes Spreading in Europe: Phylodynamics in Italy and Albania

Hepatitis C virus (HCV) genotype 2 causes about 10% of global infections and has the most variable circulation profile in Europe. The history of “endemic” HCV-2 subtypes has been satisfactorily reconstructed, instead there is little information about the recent spread of the “epidemic” subtypes, including HCV-2c. To investigate the origin and dispersion pathways of HCV-2c, 245 newly characterized Italian and Albanian HCV-2 NS5B sequences were aligned with 247 publicly available sequences and included in phylogeographic and phylodynamic analyses using the Bayesian framework. Our findings show that HCV-2c was the most prevalent subtype in Italy and Albania. The phylogeographic analysis suggested an African origin of HCV-2c before it reached Italy about in the 1940s. Phylodynamic analysis revealed an exponential increase in the effective number of infections and Re in Italy between the 1940s and 1960s, and in Albania between the 1990s and the early 2000s. It seems very likely that HCV-2c reached Italy from Africa at the time of the second Italian colonization but did not reach Albania until the period of dramatic migration to Italy in the 1990s. This study contributes to reconstructing the history of the spread of epidemic HCV-2 subtypes to Europe.

Cross-scale dynamics and the evolutionary emergence of infectious diseases

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

A Turkey-origin H9N2 Avian Influenza Virus Shows Low Pathogenicity but Different Within-Host Diversity in Experimentally Infected Turkeys, Quail and Ducks

Avian influenza virus (AIV) is a highly diverse and widespread poultry pathogen. Its evolution and adaptation may be affected by multiple host and ecological factors, which are still poorly understood. In the present study, a turkey-origin H9N2 AIV was used as a model to investigate the within-host diversity of the virus in turkeys, quail and ducks in conjunction with the clinical course, shedding and seroconversion. Ten birds were inoculated oculonasally with a dose of 10⁶ EID₅₀ of the virus and monitored for 14 days. Virus shedding, transmission and seroconversion were evaluated, and swabs collected at selected time-points were characterized in deep sequencing to assess virus diversity. In general, the virus showed low pathogenicity for the examined bird species, but differences in shedding patterns, seroconversion and clinical outcome were noted. The highest heterogeneity of the virus population as measured by the number of single nucleotide polymorphisms and Shannon entropy was found in oropharyngeal swabs from quail, followed by turkeys and ducks. This suggests a strong bottleneck was imposed on the virus during replication in ducks, which can be explained by its poor adaptation and stronger selection pressure in waterfowl. The high within-host virus diversity in quail with high level of respiratory shedding and asymptomatic course of infection may contribute to our understanding of the role of quail as an intermediate host for adaptation of AIV to other species of poultry. In contrast, low virus complexity was observed in cloacal swabs, mainly from turkeys, showing that the within-host diversity may vary between different replication sites. Consequences of these observations on the virus evolution and adaptation require further investigation.

Effects of Transmission Bottlenecks on the Diversity of Influenza A Virus

We investigate the fate of de novo mutations that occur during the in-host replication of a pathogenic virus, predicting the probability that such mutations are passed on during disease transmission to a new host. Using influenza A virus as a model organism, we develop a life-history model of the within-host dynamics of the infection, deriving a multitype branching process with a coupled deterministic model to capture the population of available target cells. We quantify the fate of neutral mutations and mutations affecting five life-history traits: clearance, attachment, budding, cell death, and eclipse phase timing. Despite the severity of disease transmission bottlenecks, our results suggest that in a single transmission event, several mutations that appeared de novo in the donor are likely to be transmitted to the recipient. Even in the absence of a selective advantage for these mutations, the sustained growth phase inherent in each disease transmission cycle generates genetic diversity that is not eliminated during the transmission bottleneck.

Complexities of Viral Mutation Rates

Many viruses evolve rapidly. This is due, in part, to their high mutation rates. Mutation rate estimates for over 25 viruses are currently available. Here, we review the population genetics of virus mutation rates. We specifically cover the topics of mutation rate estimation, the forces that drive the evolution of mutation rates, and how the optimal mutation rate can be context-dependent.

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

The evolutionary dynamics of influenza virus ultimately derive from processes that take place within and between infected individuals. Here we define influenza virus dynamics in human hosts through sequencing of 249 specimens from 200 individuals collected over 6290 person-seasons of observation. Because these viruses were collected from individuals in a prospective community-based cohort, they are broadly representative of natural infections with seasonal viruses. Consistent with a neutral model of evolution, sequence data from 49 serially sampled individuals illustrated the dynamic turnover of synonymous and nonsynonymous single nucleotide variants and provided little evidence for positive selection of antigenic variants. We also identified 43 genetically-validated transmission pairs in this cohort. Maximum likelihood optimization of multiple transmission models estimated an effective transmission bottleneck of 1-2 genomes. Our data suggest that positive selection is inefficient at the level of the individual host and that stochastic processes dominate the host-level evolution of influenza viruses.

Persistent infections in immunocompromised hosts are rarely sources of new pathogen variants

Many viruses, including human norovirus and influenza, cause self-limiting diseases of short duration. However, infection by the same viruses in an immunocompromised host can result in prolonged illness in the absence of effective treatment. Such persistent infections are often characterized by increased genetic diversity with potentially elevated rates of evolution compared to acute infections, leading to suggestions that immunocompromised hosts represent an important reservoir for the emergence of novel viral variants. Here, we develop a mathematical model that combines epidemiological dynamics with within-host evolution to quantify the relative contribution of immunocompromised hosts to the overall rate of pathogen evolution. Using human norovirus as a case study we show that the majority of evolutionary substitutions are expected to occur in acute infections of immunocompetent hosts. Hence, despite their potential to generate a high level of diversity, infections of immunocompromised hosts likely contribute less to the evolution and emergence of new genetic variants at the epidemiological scale because such hosts are rare and tend to be isolated. This result is robust to variation in key parameters, including the proportion of the population immunocompromised, and provides a means to understand the adaptive significance of mutations that arise during chronic infections in immunocompromised hosts.