scholarly journals Inferring Transmission Bottleneck Size from Viral Sequence Data Using a Novel Haplotype Reconstruction Method

2020 ◽  
Vol 94 (13) ◽  
Author(s):  
Mahan Ghafari ◽  
Casper K. Lumby ◽  
Daniel B. Weissman ◽  
Christopher J. R. Illingworth
Keyword(s):  
Influenza A ◽  
Evolutionary Dynamics ◽  
Sequence Data ◽  
Viral Evolution ◽  
Population Bottleneck ◽  
Reconstruction Method ◽  
Haplotype Reconstruction ◽  
Viral Sequence ◽  
Viral Particles ◽  
Transmission Bottleneck

ABSTRACT The transmission bottleneck is defined as the number of viral particles that transmit from one host to establish an infection in another. Genome sequence data have been used to evaluate the size of the transmission bottleneck between humans infected with the influenza virus; however, the methods used to make these estimates have some limitations. Specifically, viral allele frequencies, which form the basis of many calculations, may not fully capture a process which involves the transmission of entire viral genomes. Here, we set out a novel approach for inferring viral transmission bottlenecks; our method combines an algorithm for haplotype reconstruction with maximum likelihood methods for bottleneck inference. This approach allows for rapid calculation and performs well when applied to data from simulated transmission events; errors in the haplotype reconstruction step did not adversely affect inferences of the population bottleneck. Applied to data from a previous household transmission study of influenza A infection, we confirm the result that the majority of transmission events involve a small number of viruses, albeit with slightly looser bottlenecks being inferred, with between 1 and 13 particles transmitted in the majority of cases. While influenza A transmission involves a tight population bottleneck, the bottleneck is not so tight as to universally prevent the transmission of within-host viral diversity. IMPORTANCE Viral populations undergo a repeated cycle of within-host growth followed by transmission. Viral evolution is affected by each stage of this cycle. The number of viral particles transmitted from one host to another, known as the transmission bottleneck, is an important factor in determining how the evolutionary dynamics of the population play out, restricting the extent to which the evolved diversity of the population can be passed from one host to another. Previous study of viral sequence data has suggested that the transmission bottleneck size for influenza A transmission between human hosts is small. Reevaluating these data using a novel and improved method, we largely confirm this result, albeit that we infer a slightly higher bottleneck size in some cases, of between 1 and 13 virions. While a tight bottleneck operates in human influenza transmission, it is not extreme in nature; some diversity can be meaningfully retained between hosts.

scholarly journals Inferring transmission bottleneck size from viral sequence data using a novel haplotype reconstruction method

2020 ◽  
Author(s):  
Mahan Ghafari ◽  
Casper K. Lumby ◽  
Daniel B. Weissman ◽  
Christopher J. R. Illingworth
Keyword(s):  
Influenza A ◽  
Sequence Data ◽  
Viral Population ◽  
Reconstruction Method ◽  
Haplotype Reconstruction ◽  
Reconstruction Process ◽  
Household Transmission ◽  
Novel Approach ◽  
Maximum Likelihood Methods ◽  
Transmission Bottleneck

The transmission bottleneck is defined as the number of viral particles transmitted from one host to another. Genome sequence data has been used to evaluate the size of the transmission bottleneck between humans infected with the influenza virus, however, the methods used to make these estimates have some limitations. Specifically, approaches using viral allele frequency data may not fully capture a process which involves the transmission of entire viral genomes. Here we set out a novel approach for inferring viral transmission bottlenecks; our method combines haplotype reconstruction, a method for inferring the composition of genomes in a viral population, with two maximum likelihood methods for bottleneck inference, tailored for small and large bottleneck sizes respectively. Our method allows for rapid calculation, and performs well when applied to data from simulated transmission events, being robust to errors in the haplotype reconstruction process. Applied to data from a previous household transmission study of influenza A infection we confirm the result that the majority of transmission events involve a small number of viruses, albeit with slightly looser bottlenecks being inferred, with between 1 and 13 particles transmitted in the majority of cases. While influenza A transmission involves a tight population bottleneck, the bottleneck is not so tight as to universally prevent the transmission of within-host viral diversity.

scholarly journals Stochastic processes dominate the within and between host evolution of influenza virus

2017 ◽  
Author(s):  
John T. McCrone ◽  
Robert J. Woods ◽  
Emily T. Martin ◽  
Ryan E. Malosh ◽  
Arnold S. Monto ◽  
...  
Keyword(s):  
Influenza Virus ◽  
Stochastic Processes ◽  
Influenza A ◽  
Evolutionary Dynamics ◽  
Sequence Data ◽  
Influenza A Viruses ◽  
Effective Population ◽  
The Individual ◽  
Host Evolution

AbstractThe global evolutionary dynamics of influenza virus ultimately derive from processes that take place within and between infected individuals. Here we define the dynamics of influenza A virus populations in human hosts through next generation sequencing of 249 specimens from 200 individuals collected over 6290 person-seasons of observation. Because these viruses were collected over 5 seasons from individuals in a prospective community-based cohort, they are broadly representative of natural human infections with seasonal viruses. We used viral sequence data from 35 serially sampled individuals to estimate a within host effective population size of 30-70 and an in vivo mutation rate of 4x10−5 per nucleotide per cellular infectious cycle. These estimates are consistent across several models and robust to the models' underlying assumptions. We also identified 43 epidemiologically linked and genetically validated transmission pairs. Maximum likelihood optimization of multiple transmission models estimates an effective transmission bottleneck of 1-2 distinct genomes. Our data suggest that positive selection of novel viral variants is inefficient at the level of the individual host and that genetic drift and other stochastic processes dominate the within and between host evolution of influenza A viruses.

scholarly journals A29 Genetic heterogeneity of influenza A (H3N2) viruses in the United Kingdom, 2016–8

2019 ◽  
Vol 5 (Supplement_1) ◽  
Author(s):  
M Galiano ◽  
S Miah ◽  
O Akinbami ◽  
S Gonzalez Gonoggia ◽  
J Ellis ◽  
...  
Keyword(s):  
Amino Acid ◽  
Genetic Heterogeneity ◽  
Influenza A ◽  
Evolutionary Dynamics ◽  
Sequence Data ◽  
Influenza Viruses ◽  
Clinical Samples ◽  
Gene Trees ◽  
Emerging Viruses ◽  
The Uk

Abstract For the last four influenza seasons in the UK, genetic characterization of seasonal influenza viruses has shifted from single hemagglutinin (HA) and neuraminidase (NA) genes to whole genome (WG) analysis, allowing for better insight into the evolutionary dynamics of this virus. Sequences (WG or HA/NA) were obtained from >900A (H3N2) viruses sampled in the UK during influenza seasons 2016/7 and 2017/8 and the inter-seasonal period. Viral RNA was extracted from clinical samples and amplified using a multi-segment RT-PCR. Amplicons were sequenced using Nextera library preparation for Illumina MiSeq sequencing. Sequence data ????were processed using BAM-SAM tools and PHE in-house scripts. Phylogenetic analysis of the HA gene indicates that they belong to genetic group 3C.2a, which has circulated since 2014. Season 2016/7 was characterized by the emergence of cluster 3C.2a.1; further genetic heterogeneity was seen with 6 new subclusters within 3C.2a and 3C.2a.1, with predominance of those characterized by amino acid changes N121K and S144K (3C.2a) and N121K, N171K, I406K, G484E (3C.2a.1). The NA genes clustered with a similar topology to the HA. Season 2017/8 was characterized by persistence of some clades from previous season with further diversification. Three of the 3C.2a clusters continued to circulate, with predominance of clade showing T131K, R142K, and R261Q (clade 3C.2a.2). The majority of HA sequences in 3C.2a1 fall into a new subcluster which has become predominant within this subgroup, with amino acid changes E62G, K92R, and T135K (3C.2a.1b). The topology of NA and internal gene trees showed evidence of reassortment events occurring at some point between the two seasons, with group 3C.2a2 acquiring NA and some internal genes from 3C.2a1 lineage viruses. The predominance of this group during 2017–8 might be due to fitness advantage related to the new genetic constellation. Emerging viruses from group 3C.3a also have acquired genes from lineage 3C.2a1, which could be the reason for their increased frequency to 20 per cent by the end of season 2017–8. Molecular epidemiology indicates emerging genetic diversity in A(H3N2) viruses during the period of study, leading to co-circulation of variants. The frequency of circulating HA genetic groups was quite variable, with rapidly changing patterns of predominance. Evidence of reassortment events was observed which could be responsible for the rise and predominance of some clades, and might predict the emergence of other variants.

scholarly journals A two-tiered model for simulating the ecological and evolutionary dynamics of rapidly evolving viruses, with an application to influenza

2010 ◽  
Vol 7 (50) ◽  
pp. 1257-1274 ◽  
Author(s):  
Katia Koelle ◽  
Priya Khatri ◽  
Meredith Kamradt ◽  
Thomas B. Kepler
Keyword(s):  
Influenza A ◽  
Evolutionary Dynamics ◽  
De Novo ◽  
Sequence Data ◽  
Nucleotide Composition ◽  
Sequence Length ◽  
Influenza B ◽  
Model Parameters ◽  
De Novo Mutations ◽  
Estimation Of Model Parameters

Understanding the epidemiological and evolutionary dynamics of rapidly evolving pathogens is one of the most challenging problems facing disease ecologists today. To date, many mathematical and individual-based models have provided key insights into the factors that may regulate these dynamics. However, in many of these models, abstractions have been made to the simulated sequences that limit an effective interface with empirical data. This is especially the case for rapidly evolving viruses in which de novo mutations result in antigenically novel variants. With this focus, we present a simple two-tiered ‘phylodynamic’ model whose purpose is to simulate, along with case data, sequence data that will allow for a more quantitative interface with observed sequence data. The model differs from previous approaches in that it separates the simulation of the epidemiological dynamics (tier 1) from the molecular evolution of the virus's dominant antigenic protein (tier 2). This separation of phenotypic dynamics from genetic dynamics results in a modular model that is computationally simpler and allows sequences to be simulated with specifications such as sequence length, nucleotide composition and molecular constraints. To illustrate its use, we apply the model to influenza A (H3N2) dynamics in humans, influenza B dynamics in humans and influenza A (H3N8) dynamics in equine hosts. In all three of these illustrative examples, we show that the model can simulate sequences that are quantitatively similar in pattern to those empirically observed. Future work should focus on statistical estimation of model parameters for these examples as well as the possibility of applying this model, or variants thereof, to other host–virus systems.

scholarly journals The effective population size and mutation rate of influenza A virus in acutely infected individuals

2020 ◽  
Author(s):  
John T. McCrone ◽  
Robert J. Woods ◽  
Arnold S. Monto ◽  
Emily T. Martin ◽  
Adam S. Lauring
Keyword(s):  
Population Size ◽  
Effective Population Size ◽  
Mutation Rate ◽  
Influenza A ◽  
Evolutionary Dynamics ◽  
Sequence Data ◽  
Influenza Viruses ◽  
Influenza A Viruses ◽  
Effective Population

AbstractThe global evolutionary dynamics of influenza viruses ultimately derive from processes that take place within and between infected individuals. Recent work suggests that within-host populations are dynamic, but an in vivo estimate of mutation rate and population size in naturally infected individuals remains elusive. Here we model the within-host dynamics of influenza A viruses using high depth of coverage sequence data from 200 acute infections in an outpatient, community setting. Using a Wright-Fisher model, we estimate a within-host effective population size of 32-72 and an in vivo mutation rate of 3.4×10−6 per nucleotide per generation.

scholarly journals Challenges in evaluating the use of viral sequence data to identify HIV transmission networks for public health

2020 ◽  
Vol 12 (s1) ◽  
Author(s):  
Rami Kantor ◽  
John P. Fulton ◽  
Jon Steingrimsson ◽  
Vladimir Novitsky ◽  
Mark Howison ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Hiv Transmission ◽  
Sequence Data ◽  
The United States ◽  
Viral Sequence ◽  
Transmission Networks ◽  
New Methods ◽  
Hiv Epidemic ◽  
The World

AbstractGreat efforts are devoted to end the HIV epidemic as it continues to have profound public health consequences in the United States and throughout the world, and new interventions and strategies are continuously needed. The use of HIV sequence data to infer transmission networks holds much promise to direct public heath interventions where they are most needed. As these new methods are being implemented, evaluating their benefits is essential. In this paper, we recognize challenges associated with such evaluation, and make the case that overcoming these challenges is key to the use of HIV sequence data in routine public health actions to disrupt HIV transmission networks.

scholarly journals Different Within-Host Viral Evolution Dynamics in Severely Immunosuppressed Cases with Persistent SARS-CoV-2

Biomedicines ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 808
Author(s):  
Laura Pérez-Lago ◽  
Teresa Aldámiz-Echevarría ◽  
Rita García-Martínez ◽  
Leire Pérez-Latorre ◽  
Marta Herranz ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Evolutionary Dynamics ◽  
Viral Evolution ◽  
Special Focus ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
New Variant ◽  
History Of ◽  
Evolution Dynamics ◽  
The Uk

A successful Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variant, B.1.1.7, has recently been reported in the UK, causing global alarm. Most likely, the new variant emerged in a persistently infected patient, justifying a special focus on these cases. Our aim in this study was to explore certain clinical profiles involving severe immunosuppression that may help explain the prolonged persistence of viable viruses. We present three severely immunosuppressed cases (A, B, and C) with a history of lymphoma and prolonged SARS-CoV-2 shedding (2, 4, and 6 months), two of whom finally died. Whole-genome sequencing of 9 and 10 specimens from Cases A and B revealed extensive within-patient acquisition of diversity, 12 and 28 new single nucleotide polymorphisms, respectively, which suggests ongoing SARS-CoV-2 replication. This diversity was not observed for Case C after analysing 5 sequential nasopharyngeal specimens and one plasma specimen, and was only observed in one bronchoaspirate specimen, although viral viability was still considered based on constant low Ct values throughout the disease and recovery of the virus in cell cultures. The acquired viral diversity in Cases A and B followed different dynamics. For Case A, new single nucleotide polymorphisms were quickly fixed (13–15 days) after emerging as minority variants, while for Case B, higher diversity was observed at a slower emergence: fixation pace (1–2 months). Slower SARS-CoV-2 evolutionary pace was observed for Case A following the administration of hyperimmune plasma. This work adds knowledge on SARS-CoV-2 prolonged shedding in severely immunocompromised patients and demonstrates viral viability, noteworthy acquired intra-patient diversity, and different SARS-CoV-2 evolutionary dynamics in persistent cases.

scholarly journals Learning the language of viral evolution and escape

Science ◽  
2021 ◽  
Vol 371 (6526) ◽  
pp. 284-288 ◽  
Author(s):  
Brian Hie ◽  
Ellen D. Zhong ◽  
Bonnie Berger ◽  
Bryan Bryson
Keyword(s):  
Immune System ◽  
Natural Language ◽  
Vaccine Development ◽  
Sequence Data ◽  
Viral Evolution ◽  
Machine Learning Algorithms ◽  
Language Models ◽  
Viral Escape ◽  
Human Immune System ◽  
Influenza Hemagglutinin

The ability for viruses to mutate and evade the human immune system and cause infection, called viral escape, remains an obstacle to antiviral and vaccine development. Understanding the complex rules that govern escape could inform therapeutic design. We modeled viral escape with machine learning algorithms originally developed for human natural language. We identified escape mutations as those that preserve viral infectivity but cause a virus to look different to the immune system, akin to word changes that preserve a sentence’s grammaticality but change its meaning. With this approach, language models of influenza hemagglutinin, HIV-1 envelope glycoprotein (HIV Env), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Spike viral proteins can accurately predict structural escape patterns using sequence data alone. Our study represents a promising conceptual bridge between natural language and viral evolution.

scholarly journals Population Diversity and Collective Interactions during Influenza Virus Infection

2017 ◽  
Vol 91 (22) ◽  
Author(s):  
Christopher B. Brooke
Keyword(s):  
Genome Organization ◽  
Influenza A ◽  
Evolutionary Dynamics ◽  
Influenza Virus Infection ◽  
Population Diversity ◽  
Genomic Diversity ◽  
Global Public Health ◽  
Public Health Threat ◽  
Genetic Makeup ◽  
Collective Interactions

ABSTRACT Influenza A virus (IAV) continues to pose an enormous and unpredictable global public health threat, largely due to the continual evolution of escape from preexisting immunity and the potential for zoonotic emergence. Understanding how the unique genetic makeup and structure of IAV populations influences their transmission and evolution is essential for developing more-effective vaccines, therapeutics, and surveillance capabilities. Owing to their mutation-prone replicase and unique genome organization, IAV populations exhibit enormous amounts of diversity both in terms of sequence and functional gene content. Here, I review what is currently known about the genetic and genomic diversity present within IAV populations and how this diversity may shape the replicative and evolutionary dynamics of these viruses.

scholarly journals Improving pandemic influenza risk assessment

eLife ◽  
2014 ◽  
Vol 3 ◽  
Author(s):  
Colin A Russell ◽  
Peter M Kasson ◽  
Ruben O Donis ◽  
Steven Riley ◽  
John Dunbar ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Pandemic Influenza ◽  
Influenza A ◽  
Sequence Data ◽  
Virus Genome ◽  
Influenza Viruses ◽  
Influenza Surveillance ◽  
Human Influenza ◽  
Influenza A Viruses ◽  
Virus Genotype

Assessing the pandemic risk posed by specific non-human influenza A viruses is an important goal in public health research. As influenza virus genome sequencing becomes cheaper, faster, and more readily available, the ability to predict pandemic potential from sequence data could transform pandemic influenza risk assessment capabilities. However, the complexities of the relationships between virus genotype and phenotype make such predictions extremely difficult. The integration of experimental work, computational tool development, and analysis of evolutionary pathways, together with refinements to influenza surveillance, has the potential to transform our ability to assess the risks posed to humans by non-human influenza viruses and lead to improved pandemic preparedness and response.

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