Transmission patterns and evolution of respiratory syncytial virus in a community outbreak identified by genomic analysis

Charles N Agoti, Patrick K Munywoki, My V T Phan, James R Otieno, Everlyn Kamau, Anne Bett, Ivy Kombe, George Githinji, Graham F Medley, Patricia A Cane, Paul Kellam, Matthew Cotten, D James Nokes, Charles N Agoti, Patrick K Munywoki, My V T Phan, James R Otieno, Everlyn Kamau, Anne Bett, Ivy Kombe, George Githinji, Graham F Medley, Patricia A Cane, Paul Kellam, Matthew Cotten, D James Nokes

Abstract

Detailed information on the source, spread and evolution of respiratory syncytial virus (RSV) during seasonal community outbreaks remains sparse. Molecular analyses of attachment (G) gene sequences from hospitalized cases suggest that multiple genotypes and variants co-circulate during epidemics and that RSV persistence over successive seasons is characterized by replacement and multiple new introductions of variants. No studies have defined the patterns of introduction, spread and evolution of RSV at the local community and household level. We present a whole genome sequence analysis of 131 RSV group A viruses collected during 6-month household-based RSV infection surveillance in Coastal Kenya, 2010 within an area of 12 km2. RSV infections were identified by regular symptom-independent screening of all household members twice weekly. Phylogenetic analysis revealed that the RSV A viruses in nine households were closely related to genotype GA2 and fell within a single branch of the global phylogeny. Genomic analysis allowed the detection of household-specific variation in seven households. For comparison, using only G gene analysis, household-specific variation was found only in one of the nine households. Nucleotide changes were observed both intra-host (viruses identified from same individual in follow-up sampling) and inter-host (viruses identified from different household members) and these coupled with sampling dates enabled a partial reconstruction of the within household transmission chains. The genomic evolutionary rate for the household dataset was estimated as 2.307 × 10 - 3 (95% highest posterior density: 0.935-4.165× 10 - 3) substitutions/site/year. We conclude that (i) at the household level, most RSV infections arise from the introduction of a single virus variant followed by accumulation of household specific variation and (ii) analysis of complete virus genomes is crucial to better understand viral transmission in the community. A key question arising is whether prevention of RSV introduction or spread within the household by vaccinating key transmitting household members would lead to a reduced onward community-wide transmission.

Keywords: RSV; WAIFW; community transmission; full-genome sequencing; household transmission.

Figures

Figure 1.
Figure 1.
Geographical distribution of the nine studied households which each had at least one assembled genome. Also shown is the Mombasa-Malindi highway, roads and schools in the study area. Light grey lines indicate administrative sub-location boundaries.
Figure 2.
Figure 2.
Nucleotide differences between viruses (total = 130) detected within the individual households. Each panel is a single household. The viruses were compared to the earliest virus genome sequenced from the same household. Vertical colored bars show the nucleotide differences. Red is a change to T, orange is a change to A, purple is a change to C and blue is a change to G. Grey is a deletion or an non-sequenced portion of the genome. Household six is excluded as only a single genome sequence was obtained. A python script to generate this figure is available at https://github.com/mlcotten/RSV_household_scripts.
Figure 3.
Figure 3.
A ML inferred phylogenetic tree showing the global phylogenetic context of the RSV A household study genomes. The taxa of the household study viruses (n= 103) are in red while viruses from the rest of Kenya (inpatient) are colored blue. The taxa of RSV A viruses from around the globe are colored by continent of origin. Asterisk mark has been placed next to major branches with a bootstrap support of >70%.
Figure 4.
Figure 4.
The sequence relatedness of the household study RSV A viruses. (a) A time-scaled phylogenetic tree of the 103 genome sequenced household study viruses inferred in BEAST program. The genomes are represented by a filled circle colored differently for each household (color scheme similar to Fig. 1). (b) A median-joining (MJ) haplotype network constructed from the 103 household genomes. Each colored vertex represents a sampled viral haplotype, with different colors indicating the different households of origin. The size of the vertex is relative to the number of sampled isolates. Hatch marks indicate the number of mutations along each edge. Small black circles within the network indicate unobserved internal nodes.
Figure 5.
Figure 5.
Inferred virus transmission patterns within household 14. (a) Temporal infection patterns. Every rectangular box represent a sample collected from members of the household 14, if there is a circle inside implies the sample was RSV A positive. Unfilled circle implies specimen was not sequenced while filled colored circle implies sample was sequenced (whole genome). (b) A ML phylogenetic tree from whole genome sequences of 12/18 sequences sequenced. Same circle color for sample from the same individual. (c) A median joining haplotype network of 12 genomes. Each vertex presents a sampled viral haplotype, with different colors indicating different individuals who provided the sample. The size of the each vertex is relative to the number of sampled isolates. Hatch marks indicate the number of mutations along each edge. (d) The putative inferred transmission events. Continuous arrow indicates where the transmission link was inferred as highly likely while dotted arrows indicate where multiple alternative scenarios could have been the source of infection.

References

    1. Agoti C. N. et al. (2015a) ‘Successive Respiratory Syncytial Virus Epidemics in Local Populations Arise from Multiple Variant Introductions, Providing Insights into Virus Persistence’, Journal of Virology, 89/22: 11630–42.
    1. Agoti C. N. et al. (2015b) ‘Local Evolutionary Patterns of Human Respiratory Syncytial Virus Derived From Whole-Genome Sequencing’, Journal of Virology, 89/7: 3444–54.
    1. Bankevich A. et al. (2012) ‘SPAdes: A New Genome Assembly Algorithm and its Applications to Single-Cell Sequencing’, Journal of Computational Biology, 19/5: 455–77.
    1. Bose M. E. et al. (2015) ‘Sequencing and Analysis of Globally Obtained Human Respiratory Syncytial Virus A and B Genomes’, PLoS One, 10/3: e0120098.
    1. Cane P. A. (2001) ‘Molecular Epidemiology of Respiratory Syncytial Virus’, Reviews in Medical Virology, 11/2: 103–16.
    1. Cane P. A. (2007) ‘Molecular Epidemiology and Evolution of RSV’, in Cane P. (ed.) Respiratory Syncytial Virus, pp. 89–114. Amsterdam, The Netherlands: Elsevier.
    1. Cane P. A., Matthews D. A., Pringle C. R. (1992) ‘Analysis of Relatedness of Subgroup A Respiratory Syncytial Viruses Isolated Worldwide’, Virus Research, 25/1-2: 15–22
    1. Cottam E. M. et al. (2008) ‘Transmission Pathways of Foot-and-Mouth Disease Virus in The United Kingdom in 2007’, PLoS Pathogens, 4/4: e1000050.
    1. Cotten M. et al. (2013) ‘Transmission and Evolution of the Middle East respiratory Syndrome Coronavirus in Saudi Arabia: A Descriptive Genomic Study’, Lancet, 382/9909: 1993–2002.
    1. Do L. A. et al. (2015) ‘Direct Whole-Genome Deep-Sequencing of Human Respiratory Syncytial Virus A and B From Vietnamese Children Identifies Distinct Patterns of Inter- and Intra-host Evolution’, Journal of General Virology, 96/12: 3470–83.
    1. Drummond A. J. et al. (2012) ‘Bayesian Phylogenetics With BEAUti and the BEAST 1.7’, Molecular Biology and Evolution, 29/8: 1969–73.
    1. Drummond A. J., Rambaut A. (2007) ‘BEAST: Bayesian Evolutionary Analysis by Sampling Trees’, BMC Evolutionary Biology, 7: 214..
    1. Duchene S., Holmes E. C., Ho S. Y. (2014) ‘Analyses of Evolutionary Dynamics in Viruses are Hindered by a Time-Dependent Bias in Rate Estimates’, Proceedings of the Royal Society B: Biological Science, 281/1786:
    1. Drysdale S. B., Green C. A., Sande C. J. (2016) ‘Best Practice in the Prevention and Management of Paediatric Respiratory Syncytial Virus Infection’, Therapeutic Advances in Infectious Disease, 3/2: 63–71
    1. Falsey A. R. et al. (2005) ‘Respiratory Syncytial Virus Infection in Elderly and High-Risk Adults’, The New England Journal of Medicine, 352/17: 1749–59.
    1. Grad Y. H. et al. (2014) ‘Within-Host Whole-Genome Deep Sequencing and Diversity Analysis of Human Respiratory Syncytial Virus Infection Reveals Dynamics of Genomic Diversity in the Absence and Presence of Immune Pressure’, Journal of Virology, 88/13: 7286–93.
    1. Guindon S. et al. (2010) ‘New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0’, System Biology, 59/3: 307–21.
    1. Gunson R. N., Collins T. C., Carman W. F. (2005) ‘Real-Time RT-PCR Detection of 12 Respiratory Viral Infections in Four Triplex Reactions’, Journal of Clinical Virology, 33/4: 341–4
    1. Haynes A. K. et al. (2013) ‘Respiratory Syncytial Virus Circulation in Seven Countries with Global Disease Detection Regional Centers’, The Journal of Infectious Disease, 208: S246–54.
    1. Hall C. B. et al. (1976) ‘Respiratory Syncytial Virus Infections Within Families’, The New England Journal of Medicine, 294/8: 414–9.
    1. Heikkinen T. et al. (2015) ‘Transmission of Respiratory Syncytial Virus Infection Within Families’, Open Forum Infectious Disease, 2/1: ofu118.
    1. Higgins D., Trujillo C., Keech C. (2016) ‘Advances in RSV Vaccine Research and Development — A Global Agenda’, Vaccine, 34/26: 2870–5
    1. Hughes J. et al. (2012) ‘Transmission of Equine Influenza Virus During an Outbreak is Characterized by Frequent Mixed Infections and Loose Transmission Bottlenecks’, PLoS Pathogens, 8/12: e1003081.
    1. Johnson P. R. et al. (1987) ‘The G Glycoprotein of Human Respiratory Syncytial Viruses of Subgroups A and B: Extensive Sequence Divergence Between Antigenically Related Proteins’, PNAS, 84/16: 5625–29.
    1. Katoh K. et al. (2002) ‘MAFFT: A Novel Method for Rapid Multiple Sequence Alignment Based on Fast Fourier Transform’, Nucleic Acids Research, 30/14: 3059–66.
    1. La Rosa G. et al. (2013) ‘Viral Infections Acquired Indoors Through Airborne, Droplet or Contact Transmission’, Annali Dell Istituto Superiore Di Sanita, 49/2: 124–32.
    1. Martin D. P. et al. (2015) ‘RDP4: Detection and Analysis of Recombination Patterns in Virus Genomes’, Virus Evolution, 1/1: vev003.
    1. Memish Z. A. et al. (2014) ‘Respiratory Tract Samples, Viral Load, and Genome Fraction Yield in Patients With Middle East Respiratory Syndrome’, The Journal of Infectious Disease, 210/10: 1590–4.,
    1. Minin V. N., Bloomquist E. W., Suchard M. A. (2008) ‘Smooth Skyride Through A Rough Skyline: Bayesian Coalescent-Based Inference of Population Dynamics’, Molecular Biology and Evolution, 25/7: 1459–71.
    1. Mufson M. A. et al. (1985) ‘Two Distinct Subtypes of Human Respiratory Syncytial Virus’, Journal of General Virology, 66: 2111–24.
    1. Munywoki P. K. (2013) Transmission of Respiratory syncytial Virus in Households: Who Acquires Infection From Whom, in Life and Biomolecular Sciences. p. 387 Open University: Kilifi.
    1. Munywoki P. K. et al. (2014) ‘The Source of Respiratory Syncytial Virus Infection in Infants: A Household Cohort Study in Rural Kenya’, The Journal of Infectious Disease, 209/11: 1685–92.
    1. Munywoki P. K. et al. (2015a) ‘Influence of Age, Severity of Infection, and Co-infection on the Duration of Respiratory Syncytial Virus (RSV) Shedding’, Epidemiology Infection, 143/4: 804–12.
    1. Munywoki P. K. et al. (2015b) ‘Frequent Asymptomatic Respiratory Syncytial Virus Infections During an Epidemic in a Rural Kenyan Household Cohort’, The Journal of Infectious Disease, 212: 1711–8.
    1. Nair H. et al. (2010) ‘Global Burden of Acute Lower Respiratory Infections Due to Respiratory Syncytial Virus in Young Children: A Systematic Review and Meta-Analysis’, Lancet, 375/9725: 1545–55.
    1. Nguyen L. T. et al. (2015) ‘IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies’, Molecular Biology and Evolution, 32/1: 268–74.
    1. Nokes D. J. et al. (2004) ‘Respiratory Syncytial Virus Epidemiology in a Birth Cohort From Kilifi District, Kenya: Infection During the First Year of life’, The Journal of Infectious Disease, 190/10: 1828–32.
    1. Nokes D. J. et al. (2008) ‘Respiratory Syncytial Virus Infection and Disease in Infants and Young Children Observed From Birth in Kilifi District, Kenya’, Clinical Infectious Disease, 46/1: 50–7.
    1. Nokes J. D., Cane P. A. (2008) ‘New Strategies for Control of Respiratory Syncytial Virus Infection’, Current Opinion Infectious Disease, 21/6: 639–43
    1. Nokes D. J. et al. (2009) ‘Incidence and Severity of Respiratory Syncytial Virus Pneumonia in Rural Kenyan Children Identified Through Hospital Surveillance’, Clinical Infectious Disease, 49/9: 1341–49.
    1. Orton R. J. et al. (2015) ‘Distinguishing Low Frequency Mutations From RT-PCR and Sequence Errors in Viral Deep Sequencing Data’, BMC Genomics, 16: 229.
    1. Otieno J. R. et al. (2016) ‘Molecular Evolutionary Dynamics of Respiratory Syncytial Virus Group A in Recurrent Epidemics in Coastal KENYA’, Journal of Virology, 90: 4990–5002.
    1. Peret T. C. et al. (1998) ‘Circulation Patterns of Genetically Distinct Group A and B Strains of Human Respiratory Syncytial Virus in a Community’, Journal of General Virology, 79: 2221–29.
    1. Peret T. C. et al. (2000) ‘Circulation Patterns of Group A and B Human Respiratory Syncytial Virus Genotypes in 5 Communities in North America’, The Journal of Infectious Disease, 181/6: 1891–96.
    1. Poon L. L. et al. (2016) ‘Quantifying Influenza Virus Diversity and Transmission in Humans’, Nature Genetics, 48/2: 195–200.
    1. Rambaut A. et al. (2016) ‘Exploring the Temporal Structure of Heterochronous Sequences uSing TempEst (formerly Path-O-Gen)’, Virus Evolution, 2/1: vew007.
    1. Scott J. A. et al. (2012) ‘Profile: The Kilifi Health and Demographic Surveillance System (KHDSS)’, International Journal of Epidemiology, 41/3: 650–7.
    1. Stensballe L. G., Devasundaram J. K., Simoes E. A. (2003) ‘Respiratory Syncytial Virus Epidemics: The Ups and Downs of a Seasonal Virus’, The Pediatric Infectious Disease Journal, 22: S21–32
    1. Tan L. et al. (2012) ‘Genetic Variability Among Complete Human Respiratory Syncytial Virus Subgroup A Genomes: Bridging Molecular Evolutionary Dynamics and Epidemiology’, PLoS One, 7/12: e51439.
    1. Tan L. et al. (2013) ‘The Comparative Genomics of Human Respiratory Syncytial Virus Subgroups A and B: Genetic Variability and Molecular Evolutionary Dynamics’, Journal of Virology, 87/14: 8213–26.
    1. Tamura K. et al. (2011) ‘MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods’, Molecular Biology and Evolution, 28/10: 2731–9.
    1. Thai P. Q. et al. (2014) ‘Pandemic H1N1 Virus Transmission and Shedding Dynamics in Index Case Households of a Prospective Vietnamese Cohort’, The Journal of Infectious Disease, 68/6: 581–90.
    1. Watson S. J. et al. (2013) ‘Viral Population Analysis and Minority-Variant Detection Using Short Read Next-Generation Sequencing’, Philosophical Transactions of the Royal Society of London B: Biological Science, 368/1614: 20120205
    1. Zlateva K. T. et al. (2004) ‘Molecular Evolution and Circulation Patterns of Human Respiratory Syncytial Virus Subgroup A: Positively Selected Sites in the Attachment g Glycoprotein’, Journal of Virology, 78/9: 4675–83.
    1. Zlateva K. T. et al. (2005) ‘Genetic Variability and Molecular Evolution of the Human Respiratory Syncytial Virus Subgroup B Attachment G Protein’, Journal of Virology, 79/14: 9157–67.

Source: PubMed

3
Tilaa