| Literature DB >> 32636827 |
Hui-Ying Ko1, Gielenny M Salem1, Gwong-Jen J Chang2, Day-Yu Chao1.
Abstract
Dengue viral (DENV) infection results in a wide spectrum of clinical manifestations from asymptomatic, mild fever to severe hemorrhage diseases upon infection. Severe dengue is the leading cause of pediatric deaths and/or hospitalizations, which are a major public health burden in dengue-endemic or hyperendemic countries. Like other RNA viruses, DENV continues to evolve. Adaptive mutations are obscured by the major consensus sequence (so-called wild-type sequences) and can only be identified once they become the dominant viruses in the virus population, a process that can take months or years. Traditional surveillance systems still rely on Sanger consensus sequencing. However, with the recent advancement of high-throughput next-generation sequencing (NGS) technologies, the genome-wide investigation of virus population within-host and between-hosts becomes achievable. Thus, viral population sequencing by NGS can increase our understanding of the changing epidemiology and evolution of viral genomics at the molecular level. This review focuses on the studies within the recent decade utilizing NGS in different experimental and epidemiological settings to understand how the adaptive evolution of dengue variants shapes the dengue epidemic and disease severity through its transmission. We propose three types of studies that can be pursued in the future to enhance our surveillance for epidemic prediction and better medical management.Entities:
Keywords: dengue; evolution; genetic variants; increasing severity epidemiology; next-generation sequencing
Year: 2020 PMID: 32636827 PMCID: PMC7318875 DOI: 10.3389/fmicb.2020.01371
Source DB: PubMed Journal: Front Microbiol ISSN: 1664-302X Impact factor: 5.640
FIGURE 1Trade-off hypotheses of dengue virus quasispecies transmission. Random mutations are introduced into virus genome during replication cycles. Transmission involves transferring minor population with variants of genome, practically assayed by single nucleotide variants (SNVs). Only SNVs with increased fitness in both mosquito and human will be kept after mosquito/human alternated transmission.
Studies utilizing deep sequencing on DENV genetic variants.
| Authors | Epidemic country/year | Virus | Host | Sequencing method | SNV calling method | Intra-host diversity estimation | References | |
| Within mosquito | Lequime S, et al. | Thailand 2010 | DENV-1 ( | Illumina full length | LoFreq | Normalized Shannon entropy (S | ||
| Mosquito to human | Sim S, et al. | Vietnam 2011 | DENV-2 ( | Illumina full length | LoFreq | The number of SNVs | ||
| Sessions OM, et al. | Singapore 2005 | DENV1 ( | Illumina full length | LoFreq | Shannon diversity index | |||
| Epidemiology | Parameswaran P, et al. | Nicaragua 2005–2009 | DENV-2 | Human ( | Roche/454 coding region | V-Phaser | A permutation test used to identify specific residues in the genome were hot spots for intra-host diversity. Residues in each genome were scored based their harbored diversity. | |
| Ko H-Y, et al. | Taiwan 2001–2003 | DENV-2 | Human ( | Illumina E gene | LoFreq | Number of variants of each sample. Samples divided into two groups by the numbers of variants boundary by medium value. | ||
| Romano CM, et al. | Brazil 2010 | DENV-2 | Human ( | Roche/454 full length | CLC’s SNP analysis tool | Synonymous changes and non-synonymous changes sits and proportion | ||
| Rodriguez-Roche R, et al. | Cuba 2001–2002 | DENV-3 | Human ( | Illumina full length | ViVAN | Synonymous variant allele rate Proportion of minor variants > 1% | ||
| Parameswaran P, et al. | Nicaragua 2009–2010 | DENV-3 | Human ( | Illumina full length | In-house python scripts | Percentage of specific loci of nucleotide, codon, and amino acid per protein. Loci indicated each coordinate that was different from consensus sequence. |
FIGURE 2Hypotheses of factors that contributing to increasing epidemic severity. Forces and factors determine the evolution of dengue viruses and the potential outcomes of dengue epidemiology.