Genomic Epidemiology as a Public Health Tool to Combat Mosquito-Borne Virus Outbreaks

Pollett, Simon; Fauver, Joseph R.; Berry, Irina Maljkovic; Melendrez, Melanie C.; Morrison, Andrea; Gillis, Leah D; Johansson, Michael A.; Jarman, Richard G.; Grubaugh, Nathan D.

doi:10.1093/infdis/jiz302

Cited by 19 publications

(15 citation statements)

References 71 publications

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“…Genomic epidemiology is increasingly being used in dengue and other viral outbreaks to provide complementary insights into viral transmission and epidemic dynamics [4, 20]. Such information can be used for more precise tracking of viral transmission and locating possible hotspots of viral dissemination.…”

Section: Discussionmentioning

confidence: 99%

“…Viral genome sequence data, including that of DENV, have increasingly been used in epidemics and outbreaks to provide more precise reconstructions of transmission dynamics and complement conventional non-genomic epidemiologic data. This approach of genomic epidemiology for DENV has played a crucial role in analyses of spatial and temporal outbreak dynamics, virus dispersal tracking, genotype-phenotype associations, vaccine effectiveness, vector adaptation and many others [3][4][5]. Generally, genomic epidemiology studies analyse DENV consensus genomes derived from each host.…”

Section: Introductionmentioning

confidence: 99%

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Effect of low-passage number on dengue consensus genomes and intra-host variant frequencies

Fung

Pollett

et al. 2021

Journal of General Virology

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Intra-host single nucleotide variants (iSNVs) have been increasingly used in genomic epidemiology to increase phylogenetic resolution and reconstruct fine-scale outbreak dynamics. These analyses are preferably done on sequence data from direct clinical samples, but in many cases due to low viral loads, there might not be enough genetic material for deep sequencing and iSNV determination. Isolation of the virus from clinical samples with low-passage number increases viral load, but few studies have investigated how dengue virus (DENV) culture isolation from a clinical sample impacts the consensus sequence and the intra-host virus population frequencies. In this study, we investigate consensus and iSNV frequency differences between DENV sequenced directly from clinical samples and their corresponding low-passage isolates. Twenty five DENV1 and DENV2 positive sera and their corresponding viral isolates (T. splendens inoculation and C6/36 passage) were obtained from a prospective cohort study in the Philippines. These were sequenced on MiSeq with minimum nucleotide depth of coverage of 500×, and iSNVs were detected using LoFreq. For both DENV1 and DENV2, we found a maximum of one consensus nucleotide difference between clinical sample and isolate. Interestingly, we found that iSNVs with frequencies ≥5 % were often preserved between the samples, and that the number of iSNV positions, and sample diversity, at this frequency cutoff did not differ significantly between the sample pairs (clinical sample and isolate) in either DENV1 or DENV2 data. Our results show that low-passage DENV isolate consensus genomes are largely representative of their direct sample parental viruses, and that low-passage isolates often mirror high frequency within-host variants from direct samples.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Effect of low-passage number on dengue consensus genomes and intra-host variant frequencies

Fung

Pollett

et al. 2021

Journal of General Virology

Self Cite

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“…Genomic epidemiology is increasingly being used in dengue and other viral outbreaks to provide complementary insights into viral transmission and epidemic dynamics [23,24]. Such information can be used for more precise tracking of viral transmission and locating possible hotspots of viral dissemination.…”

Section: Discussionmentioning

confidence: 99%

“…Viral genome sequence data, including that of DENV, have increasingly been used in epidemics and outbreaks to provide more precise reconstructions of transmission dynamics and complement conventional non-genomic epidemiologic data. This approach of genomic epidemiology for DENV has played a crucial role in analyses of spatial and temporal outbreak dynamics, virus dispersal tracking, genotype-phenotype associations, vaccine effectiveness, vector adaptation, and many others [5][6][7][8]. Generally, genomic epidemiology studies analyze DENV consensus genomes derived from each host.…”

Section: Introductionmentioning

confidence: 99%

Vector and cell-culture passaging of dengue clinical samples for virus isolation and amplification does not significantly change genome consensus or frequencies of intra-host viral variants

Fung

Pollett

et al. 2020

Preprint

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Intra-host single nucleotide variants (iSNVs) have been increasingly used in genomic epidemiology to increase phylogenetic resolution and reconstruct fine-scale outbreak dynamics. These analyses are preferably done on sequence data from direct clinical samples, but in many cases due to low viral loads, there might not be enough genetic material for deep sequencing and iSNV determination. Isolation of the virus from clinical samples with low passage number increases viral load, but to date, no studies have investigated how dengue virus (DENV) culture isolation from a clinical sample impacts the consensus sequence, and there is no information on the intra-host virus population changes that may result from viral isolation. In this study, we investigate consensus and iSNV frequency differences between DENV sequenced directly from clinical samples and their corresponding low-passage isolates. Twenty five DENV1 and DENV2 positive sera and their corresponding viral isolates (T.splendens inoculation and C6/36 passage) were obtained from a prospective cohort study in the Philippines. These were sequenced on MiSeq with minimum nucleotide depth of coverage of 1000x, and iSNVs were detected using LoFreq. For both DENV1 and DENV2, we found that the nucleotide call concordance (including called iSNVs with variant cutoff at 5%) between direct sera sample and its cultured virus was on average 99.99%. There were a maximum of one consensus nucleotide difference between clinical sample and isolate. Interestingly, we found that iSNV frequencies were also largely preserved between the samples, with an average difference in minor variant frequency of 6.8% (95CI: 3.6%-10%) and 9.6% (95CI: 7%-12.2%) for DENV1 and DENV2, respectively. Furthermore, we found no significant differences in either DENV1 or DENV2 between the sample pairs (clinical sample and isolate) in their number of iSNV positions per genome, or in the difference in variant frequencies (p=0.36 and p=0.13, respectively, F-test). Our results show that low-passage DENV isolates may be used for identification of the majority of their human-derived within-host variant populations, which are increasingly being used for precision tracking of DENV and other RNA viruses.

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“…Utilizing a global network of partner DoD medical research and public health laboratories, GEIS funds surveillance activities in over 70 countries to inform force health protection through timely and actionable infectious disease surveillance information (Chakhunashvili et al, 2017;Chang et al, 2018;Coleman et al, 2018;Koka et al, 2018;Anyamba et al, 2019;Guerra et al, 2019;Juma et al, 2019;Rivers et al, 2019;Rocha et al, 2019;Sugiharto et al, 2019). Unsurprisingly, development of NGS and bioinformatics methods for infectious disease surveillance and control has enabled a rapid expansion of GEIS partner studies that utilize pathogen genomic information (Frey et al, 2016;Maljkovic Berry et al, 2016, 2019aLee et al, 2017;Mullins et al, 2017;Salje et al, 2017;Cowell et al, 2018;LaBreck et al, 2018;Srijan et al, 2018;Grubaugh et al, 2019;Kim et al, 2019;Mbala-Kingebeni et al, 2019;Millar et al, 2019;Pollett et al, 2019;Wiley et al, 2019). However, NGS and bioinformatics can generally be technically challenging, as it requires specific knowledge of complex wet lab and bioinformatics processes (Maljkovic Berry et al, 2019b).…”

Section: Introductionmentioning

confidence: 99%

A Department of Defense Laboratory Consortium Approach to Next Generation Sequencing and Bioinformatics Training for Infectious Disease Surveillance in Kenya

et al. 2020

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Epidemics of emerging and re-emerging infectious diseases are a danger to civilian and military populations worldwide. Health security and mitigation of infectious disease threats is a priority of the United States Government and the Department of Defense (DoD). Next generation sequencing (NGS) and Bioinformatics (BI) enhances traditional biosurveillance by providing additional data to understand transmission, identify resistance and virulence factors, make predictions, and update risk assessments. As more and more laboratories adopt NGS and BI technologies they encounter challenges in building local capacity. In addition to choosing the right sequencing platform and approach, considerations must also be made for the complexity of bioinformatics analyses, data storage, as well as personnel and computational requirements. To address these needs, a comprehensive training program was developed covering wet lab and bioinformatics approaches to NGS. The program is meant to be modular and adaptive to meet both common and individualized needs of medical research and public health laboratories across the DoD. The training program was first deployed internationally to the Basic Science Laboratory of the US Army Medical Research Directorate-Africa in Kisumu, Kenya, which is an overseas Lab of the Walter Reed Army Institute of Research (WRAIR). A week-long workshop with intensive focus on targeted sequencing and the bioinformatics of genome assembly (n = 24 participants) was held. Post-workshop self-assessment (completed by 21 participants

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Genomic Epidemiology as a Public Health Tool to Combat Mosquito-Borne Virus Outbreaks

Cited by 19 publications

References 71 publications

Effect of low-passage number on dengue consensus genomes and intra-host variant frequencies

Effect of low-passage number on dengue consensus genomes and intra-host variant frequencies

Vector and cell-culture passaging of dengue clinical samples for virus isolation and amplification does not significantly change genome consensus or frequencies of intra-host viral variants

A Department of Defense Laboratory Consortium Approach to Next Generation Sequencing and Bioinformatics Training for Infectious Disease Surveillance in Kenya

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