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

McCrone, John; Woods, Robert J.; Martin, Emily T.; Malosh, Ryan E.; Monto, Arnold S.; Lauring, Adam S.

doi:10.7554/elife.35962

Cited by 200 publications

(389 citation statements)

References 52 publications

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“…It is important to stress that most events leading to DVG formation, including mutations, deletions, recombination and translocations, are either non-viable or deleterious to the virus. In addition, although hundreds or even thousands of different DVGs are generated during a virus infection, the vast majority of these will be lost during the population bottlenecks that occur in vivo, for example when crossing anatomical barriers or during transmission from host to host 127 . However, there are instances where these genomes could make it through bottlenecks, such as during infections of hosts that are immunosuppressed or have comorbidities where founding populations are increased.…”

Section: Impact On Viral Evolution and Dynamicsmentioning

confidence: 99%

Defective viral genomes are key drivers of the virus–host interaction

2019

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Viruses survive often harsh host environments, yet we know little about the strategies they utilize to adapt and subsist given their limited genomic resources. We are beginning to appreciate the surprising versatility of viral genomes and how replicationcompetent and -defective virus variants can provide means for adaptation, immune escape and virus perpetuation. This Review summarizes current knowledge of the types of defective viral genomes generated during the replication of RNA viruses and the functions that they carry out. We highlight the universality and diversity of defective viral genomes during infections and discuss their predicted role in maintaining a fit virus population, their impact on human and animal health, and their potential to be harnessed as antiviral tools. Review ARticleNATuRe MicRoBiology extinction interfere with replication of a wild-type viral genome 29,30 . Hypermutations and mutations leading to frame shifts also result in defective viruses 31 (Fig. 1a). One example is mutations introduced by the cellular protein APOBEC3G into pro-retroviruses 32 . APOBEC3G deaminates deoxycytidine nucleotides in the viral DNA, leading to hypermutations that interfere with the ability of the viral genome to integrate into the host genome and replicate. Interestingly, in opposition to an interfering activity for these mutated pro-viruses, it has been proposed that defective proviruses enhance fitness and that complementation among them drives viral persistence and pathogenesis 33,34 .Deletions. The genomic viral species most commonly referred to as DVGs are truncated viral genomes resulting from large internal deletions occurring during viral replication. Deletion DVGs tend to bear single large truncations that remove several or all essential genes required for self-propagation while retaining 5′ and 3′ ends as well as other RNA structural elements required for polymerase binding, replication and/or packaging [35][36][37] . Multiple variants also exist, including DVGs that can be described as 'mosaic' in that they appear to be the result of multiple recombination and rearrangement events, including deletions, insertions, duplications and even inversions of parts of the genome [38][39][40] (Fig. 1b). Copy-backs.Copy-back and snap-back DVGs are rearranged genomes in which a sequence is duplicated in reverse complement to create theoretical stem-like structures (panhandle structures for copy-back DVGs or hairpin structures for snap-back DVGs) 41-43 . Copy-back DVGs have been reported in many negative-sense (ns) RNA viruses and are generated from the 5′ end of the genome in a process that produces DVGs with complementary 3′ and 5′ termini 44,45 . If the complementary region of the DVG comprises almost the entire sequence, the DVG can be further characterized as a snap-back DVG 43 (Fig. 1c). Copy-back DVGs are predicted to be generated when the viral RNA-dependent RNA polymerase (RdRP) detaches from the template and reattaches to the nascent strand, copying back the end of the genome 42,46 .

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Section: Impact On Viral Evolution and Dynamicsmentioning

confidence: 99%

Defective viral genomes are key drivers of the virus–host interaction

2019

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“…We have here presented an approach for jointly inferring a population bottleneck size and selection for differential transmissibility from viral sequence data describing a transmission event. While basic sampling approaches to bottleneck inference have been improved by an accounting for drift during within-host viral growth [7,[12][13][14], our approach additionally accounts for noise in genome sequence data, exploits partial haplotype data available from short-read sequencing, and separates the influence of a finite bottleneck from that induced by selection for increased transmissibility. In multiple studies, the transmission bottleneck has been found to be narrow during natural viral spread between hosts [62].…”

Section: Discussionmentioning

confidence: 99%

“…A recent publication improved this latter model, incorporating the uncertainty imposed upon allele frequencies by the process of within-host growth [12]. Two studies of within-household influenza transmission have provided strikingly different outcomes in the number of viruses involved in transmission, with estimates of 1-2 [13] and 100-200 [14] respectively, albeit that the veracity of the data used to generate the latter result has recently been challenged [15].…”

Section: Introductionmentioning

confidence: 99%

“…More fundamentally, in an event where the effective population size is small, the influences of selection and genetic drift may be of similar magnitude [28]. However selection is assessed, this implies a need to separate stochastic changes in a population from selection, especially where a transmission bottleneck may include only a small number of viruses [5,13,29]. It is possible for the attribution of a change in diversity to the action of selection, or the attribution of allele frequency change to genetic drift to be flawed.…”

Section: Introductionmentioning

confidence: 99%

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A novel framework for inferring parameters of transmission from viral sequence data

2018

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Transmission between hosts is a critical part of the viral lifecycle. Recent studies of viral transmission have used genome sequence data to evaluate the number of particles transmitted between hosts, and the role of selection as it operates during the transmission process. However, the interpretation of sequence data describing transmission events is a challenging task. We here present a novel and comprehensive framework for using short-read sequence data to understand viral transmission events, designed for influenza virus, but adaptable to other viral species. Our approach solves multiple shortcomings of previous methods for this purpose; for example, we consider transmission as an event involving whole viruses, rather than sets of independent alleles. We demonstrate how selection during transmission and noisy sequence data may each affect naive inferences of the population bottleneck, accounting for these in our framework so as to achieve a correct inference. We identify circumstances in which selection for increased viral transmission may or may not be identified from data. Applying our method to experimental data in which transmission occurs in the presence of strong selection, we show that our framework grants a more quantitative insight into transmission events than previous approaches, inferring the bottleneck in a manner that accounts for selection, both for within-host virulence, and for inherent viral transmissibility. Our work provides new opportunities for studying transmission processes in influenza, and by extension, in other infectious diseases.

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“…First, it is now possible using next-generation sequencing to differentiate the two types of transmission on the basis of genetic similarity as we have demonstrated with influenza A viruses. 33 Second, we have adapted individual-based transmission models to account for risk of infection from both the community and the household and to allow for chains of transmission. 34…”

Section: Transmission Of Influenza Virusesmentioning

confidence: 99%

Data resource profile: Household Influenza Vaccine Evaluation (HIVE) Study

Monto

Malosh

Evans

et al. 2019

International Journal of Epidemiology

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Acute respiratory infections (ARI) are a major cause of morbidity worldwide. 1 Some of the earliest studies to describe the epidemiology of these infections were household cohort studies. [2][3][4][5][6][7] The largest of these were conducted in Seattle, Washington and Tecumseh, Michigan in the 1960s and 1970s 6,7 and they provided information on the relative frequency, seasonality and symptomatic characteristics of ARI shortly after many respiratory viruses were first identified. 7 Given that the role of household structure in seasonal incidence and transmission of respiratory viruses was the primary objective, an individual's longitudinal history of infection was not a major focus. Indeed, during the first phase of the Tecumseh Study of Respiratory Illness, households were maintained on report for only 1 year, and then gradually replaced so that the entire community could be represented over time. 8 These historical studies relied on cell culture for virus identification, a method that requires specimens to be processed quickly and is considerably less sensitive than current molecular methods. 9 For this reason, the Tecumseh study and others relied extensively on serodiagnosis of influenza infection using twice yearly blood specimens. 10 It was not possible to time infections in those who only were serologically positive, limiting the ability to do robust analyses of transmission patterns. 11 With current molecular techniques, it has become much easier to identify a broad range of agents of respiratory infection. This allows documentation of infection, co-infection and subsequent re-infection. Collecting specimens within a short time from the onset of symptoms still maximizes the likelihood of accurate and timely identification of viruses associated with a respiratory illness for studies of transmission and vaccine effectiveness. Collection of regular blood specimens continues to be valuable as well, for both virus identification and for analysis of serologic correlates of protection.The Household Influenza Vaccine Evaluation (HIVE) Study is an ongoing prospective household cohort study that began in 2010. The HIVE Study was based on the original Tecumseh Study of Respiratory Illness 6 with several key modifications to illness surveillance and to laboratory methods for identification of respiratory viruses. While respiratory virus infections in general could be studied, the primary objective was to estimate the effectiveness of influenza vaccines using a cohort design for comparison with studies using the testnegative design (TND). Under the TND, specimens are collected from participants who meet a respiratory illness case V C The Author(s)

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

Cited by 200 publications

References 52 publications

Defective viral genomes are key drivers of the virus–host interaction

Defective viral genomes are key drivers of the virus–host interaction

A novel framework for inferring parameters of transmission from viral sequence data

Data resource profile: Household Influenza Vaccine Evaluation (HIVE) Study

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