Skip to main content
Download PDF

Whole genome sequencing and phylogenetic analysis of dengue virus in Central Nepal from 2022 to 2023

BMC Global and Public Health volume 3, Article number: 18 (2025) Cite this article

Abstract

Background

In Nepal, dengue is an emerging disease of growing concern as outbreaks are increasing in both size and geographic reach and beginning to affect areas previously thought dengue-free. Dengue genomic surveillance has previously been limited within Nepal; however, with the increase in accessibility to sequencing technologies since the COVID-19 pandemic, it has recently become more feasible.

Methods

This hospital-based retrospective study utilized banked samples from the 2022 and 2023 dengue seasons from Dhulikhel Hospital/Kathmandu University Hospital in Central Nepal. Next-generation sequencing was performed to obtain whole genome sequences of dengue virus which were analyzed phylogenetically using a maximum likelihood GTR + G model. Mutations were evaluated across viral particle region using the GISAID DengueServer.

Results

We obtained 41 full-length sequences of DENV from 80 PCR-positive samples, including 24 sequences (58.5%) from 2022 and 17 sequences (41.5%) from 2023. We identified a shift in the majority serotype of our samples from DENV1 in 2022 to DENV3 in 2023, though 3 out of the 4 serotypes were identified in both years. Phylogenetic analysis revealed clusters within genotype III of DENV1 and genotype III of DENV3 closely related to strains from an outbreak of DENV in northern India in 2018–2019. DENV2 sequences fell into the cosmopolitan genotype IV-A1 and IV-B2 clades and were related to sequences from South and Southeast Asia and the USA, pointing to the global nature of dengue transmission. NS3 showed the highest frequency of mutation, whereas NS2B, NS4, NS5, and E were the most conserved. The most common mutations found were substitutions L17M and T20I in the 2 K peptide. A high number of mutations were observed in DENV3, followed by DENV2, with some mutations being unique to specific serotypes and others matching previously reported strains.

Conclusions

We identified possible clade shifts in the DENV1 and 2 populations and a rising prevalence of DENV3. Our study showed a high level of serotype diversity of DENV circulating in Central Nepal. Furthermore, our results indicate that DENV populations in Nepal are related to a geographically diverse set of sequences but are most strongly influenced by Indian strains of DENV.

Peer Review reports

Background

Dengue fever is a vector-borne disease caused by dengue virus (DENV), which is a single-stranded RNA virus of the Flaviviridae family. Flaviviruses, such as DENV, West Nile virus, and Zika virus are primarily transmitted by mosquitoes of the Aedes genus, Aedes aegypti and Aedes albopictus [1]. Predominantly endemic in tropical and subtropical regions, the WHO estimated that about half of the world’s population is at risk for dengue, and that 100–400 million infections occur each year [1].

The first recorded case of DENV in Nepal occurred in 2004 [2]. Since then, DENV has become endemic to the country with outbreaks occurring during the rainy season (August-November) on a regular 2- to 3-year cycle [3]. In 2022, the Epidemiology and Disease Control Division (EDCD; Kathmandu, Nepal) recorded 54,784 cases and 88 deaths across all 7 provinces. This trend continued in the 2023 season which recorded 51,243 cases [4, 5]. As per the EDCD, Nepal observed outbreak of dengue in 2022, but in 2023, a high case count but no outbreak was observed, hence our use of “season” in reference to the 2023 cases [4, 5]. Previous work has identified the co-circulation of all four serotypes of DENV in Nepal, which increases risk within this population of secondary infection and the subsequent complications [6].

The DENV genome is made up of one ~ 11 kilobase long open reading frame. It contains 10 protein encoding regions, including 3 structural regions (capsid [C], pre-membrane [preM], and envelope [E]) and 7 nonstructural (NS) regions (NS1, NS2A, NS2B,NS3, NS4A, NS4B, and NS5) which perform various functions as transcription factors, cofactors, and innate immune response inhibitors [7, 8]. DENV exists as four antigenically and immunologically distinct serotypes which share approximately 65% of their genome and can be further subdivided into several genotypes within each serotype [9]. DENV genotypes are defined as clusters of sequences which diverge up to 6% within a given region at the nucleotide level [10, 11]. Infection from one serotype confers lifetime immunity to the specific serotype and up to 6-month immunity to all serotypes of DENV [12]. However, secondary infection presents an increased risk of serious complications such as dengue shock syndrome (DSS) and dengue hemorrhagic fever (DHF) through antibody-dependent enhancement (ADE) [13].

Genomic surveillance provides unique insight into the proliferation of the virus throughout space and time. Tracking the prevalence and phylogeny of dengue virus genotypes sheds light on the origins and epidemic behavior of the virus in Nepal and can further provide insight into changes in virulence, vector competence, and transmission dynamics [14,15,16]. However, due to the high cost associated with sequencing, there have not been many phylogenetic studies focusing specifically on DENV in Nepal. Next-generation sequencing (NGS) has recently made the whole genome sequencing of DENV more feasible within Nepal [17]. In order to overcome this research gap, we utilized NGS to obtain whole genome sequences of DENV originating in Nepal. In this study, we sequenced the DENV found in banked samples collected during the outbreak of 2022 (August to October) and dengue season of 2023 (August to November) to investigate the circulation of DENV within Central and Eastern Nepal in 2022 and 2023 and to explore the origins and genetic variability of DENV within this region.

Methods

Study design

This retrospective study investigated the genomics of DENV in banked dengue samples. These anonymized samples were taken from patients who visited Dhulikhel Hospital/Kathmandu University Hospital (DHKUH) for diagnosis and treatment and had received a rapid antigen test at the DHKUH Department of Microbiology. Samples were included if complete personal demographic information (age, sex, geographic region) had been entered into the electronic medical record (EMR) and were NS1 + by rapid antigen test.

Sample collection and evaluation

Eighty-nine banked NS1 + whole blood samples of August to October 2022 and 62 from August to November 2023 were obtained. These samples were in storage at − 80 °C until retrieval for this study. Basic demographic information (age, sex, geographic region) was accessed through the DHKUH EMR. The serum from patients were retested for the NS1 antigen using the InBios NS1 Detect™ (DNS1-RD; InBios, Seattle, USA) rapid diagnostic test kit.

RNA extraction and quantitative PCR

RNA extractions were performed using the Zymo Quick-RNA Viral Kit (R1035; Zymo, Orange, USA), according to the manufacturer’s instructions. A total of 200 µL of serum was used for RNA extraction. The genetic material was eluted in nuclease-free water and was stored at − 20 °C until sequencing or quantitative PCR (qPCR). For the verification of the presence of DENV RNA, qPCR was performed on the extracted samples before sequencing, using either the Dengue Virus Nucleic Acid Test Kit (M092T050B0C0; Mole Biosciences, Taizhou, People’s Republic of China) or the abTES™ DEN 4 qPCR kit (300,185; Ait Biotechnology, Singapore), and was carried out according to the manufacturer’s instructions. Samples that failed to exhibit a positive Ct value were not taken forward for sequencing. The cutoffs for positivity were determined based on the manufacturer’s instructions.

Whole genome sequencing

Viral libraries were synthesized using the Illumina COVIDSeq Test Kit (RUO Version) (20051274; Illumina, San Diego, USA). A version of the Illumina COVIDSeq protocol adapted for use in dengue virus samples described by Vogels et al. was closely followed [18]. Custom DENV-specific primers for pan-serotype amplification of dengue virus were designed and ordered from Integrated DNA Technologies (IDT) based on the Vogels et al. DengueSeq protocol. After amplification, libraries were evaluated for the presence of adapter dimers, concentration, and amplicon size of ~ 300 bp using the Agilent TapeStation 4150 (Agilent, Santa Clara, USA) and loaded for sequencing at a concentration of 120 pM. Pair-ended amplicon-based whole genome sequencing (2 × 150 bp) was performed on the iSeq100 (Illumina, San Diego, USA).

Sequence alignment and phylogenetic analysis

Consensus genomes were constructed using the Chan Zuckerberg ID viral consensus genome alignment pipeline v3.5.0 [19] using Nepalese genomes from 2022 as references for assembly (DENV1: OR821722.1; DENV2: OR821725.1; DENV3: OR821726.1). Utilizing regional sequences for our viral consensus genome assembly allowed us to achieve greater coverage breadth. Serotype and genotype of the viral genomes were determined using the Genome Detective Dengue Virus Typing tool [20]. Sequences with a viral genome coverage ≥ 70% were subjected to multiple sequence alignment in MEGA11 using MUSCLE (MUltiple Sequence Comparison by Log-Expectation) alignment. Maximum likelihood phylogenetic trees were constructed in MEGA11 using a general time-reversible model with gamma distributed rate variation (GTR + G) as identified by the IQ-TREE ModelFinder, with 1000 bootstrap replicates [21]. Phylogenetic trees were constructed by serotype using the self-produced sequences (accessible in the Global Initiative on Sharing All Influenza Data (GISAID) database; EPI_ISL_19081917—EPI_ISL_19081957) in combination with related full-length DENV sequences identified using BLAST search and accessed from GenBank [22]. GISAID accession numbers and alignment coverage of all samples included in phylogenetic analyses are available as Additional file 1: Table S1.

Mutation analysis

The mutations in all Nepalese genomes (N = 134 with 76 whole genomes), including genomes from this study (N = 41), were evaluated using DengueServer from GISAID (A*STAR Bioinformatics Institute (BII), Singapore) [23]. This platform uses well-characterized reference genomes (hDenV1/Nauru/NMRI-45AZ5PDK-0/1974 for DENV1, hDenV2/Thailand/CDC-16681/1964 for DENV2, and hDenV3/Sri Lanka/IMTSSA-1266/2000 for DENV3) with significant relevance (dominant genotype, phylogenetically distinct, and epidemiologically and clinically relevant: known to cause severe dengue, including DHF and DSS). In this study, newly observed “unique” mutations were evaluated across the viral particle region (envelope [E], capsid [C], pre-membrane [preM]) and replication complex (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5).

Statistical analysis and data representation

All statistical analyses were performed using R software (v4.3.2, R Core Team 2023). Figure 1 was generated in R using leaflet v2.2.2.9000 [24].

Fig. 1
figure 1

Map of Nepal identifying the region of residence of study subjects (N = 80) with districts shaded and colored based on total reported cases from 2022 to 2023. Circles indicate sites of unique subject regions of residency. Red circles represent sites associated with samples collected in 2022, and blue circles represent sites associated with samples collected in 2023. Yellow circle represents the location of the study site (Dhulikhel Hospital/Kathmandu University Hospital). Location data was collected from the DHKUH EMR. Map generated in R using leaflet v2.2.2.9000 [24]

Full size image

Results

Study demographics

Sociodemographic characteristics and serotype distribution of the 80 qPCR-positive samples are presented in Table 1. In 2022, an equal number of samples were from men and women, whereas in 2023, more samples were from men (63%) than women. In both 2022 and 2023, most of the samples were from patients residing within Kavrepalanchok (60% and 75%, respectively) which is a peri-urban district in Central Nepal. This population represented 53 of the total 80 samples. The remaining patients predominantly resided in neighboring districts in Central Nepal including Bhaktapur [7], Kathmandu [6], Sindhu [4], Lalitpur [2], and others (Fig. 1). One sample collected in 2022 belonged to a patient from Banke district in western Nepal.

Table 1 Demographic and serotype distribution of qPCR-positive samples stratified by year (N = 80). Statistics are shown as n (%) for categorical variables and mean (range) for continuous variables
Full size table

Serotype distribution

This study included a total of 80 qPCR-positive samples. These samples included 48 qPCR-positive samples from the dengue outbreak of 2022 and 32 samples from the dengue prevalent season of 2023 (Table 1). In 2022, most samples were identified as DENV1 (28, 58.3%) followed by DENV3 (11, 22.9%) and DENV2 (9, 18.7%), whereas in 2023 the majority of samples were identified as DENV3 (20, 62.5%) followed by DENV2 (8, 25%) and DENV1 (4, 12.5%). DENV4 was not detected in either year.

Phylogenetic analysis

Forty-one out of the 80 qPCR + samples exhibited successful sequencing, characterized by ≥ 70% genome coverage at 10 × coverage depth, and were subjected to phylogenetic analysis. Successful sequencing occurred in samples with an average Ct value of 17.84 (SD = 6.68).

DENV1

A phylogenetic tree of DENV1 sequences analyzed in the manuscript is available as Fig. 2. Seven sequences from 2022 and two sequences from 2023 were phylogenetically analyzed. All 2022 and 2023 genomes of DENV1 from Nepal were identified as genotype III. The Nepalese clade was most closely related to a Chinese genome of DENV from a traveler returning from India in 2019 (MN923086.1) and other Indian DENV1 genomes from 2019. All DENV1 genomes of this study clustered into a discrete phylogenetic group with the remaining Nepalese DENV1 sequences isolated in 2022 and 2023.

Fig. 2
figure 2

Phylogeny of Nepalese DENV1 genomes and related sequences. A maximum likelihood phylogenetic tree was constructed with the general time reversible model with gamma distribution and 1000 bootstrap replicates in MEGA11. Nepalese DENV1 genomes obtained in this study and related whole genome sequences of DENV1 accessed through the GenBank database were included in the analysis. Genomes obtained in this study are shown in red, and other Nepalese genomes are colored in blue. Sequences in black are related strains accessed from GenBank. Genome names are displayed as "GISAID accession number_Country_Year" for self-produced sequences and "GenBank accession number_Country_Year" for all other sequences. Genotype is indicated to the right of the sequences. Numbers on the branches indicate bootstrap values greater than 70%. Distance scale is displayed at the bottom left of the tree

Full size image

DENV2

A phylogenetic tree of DENV2 sequences analyzed in the manuscript is available as Fig. 3. Seven sequences from 2022 and eight sequences from 2023 were phylogenetically analyzed. All DENV2 genomes from this study were identified as cosmopolitan genotype with subgenotypes IV-A1 and IV-B2 both represented. Nepalese DENV2 genomes from 2022 and 2023 grouped phylogenetically based on year. The Nepalese sequences from 2022 formed two clusters which were related to genomes from Singapore in 2017–2019 and India in 2021. Of the 2022 samples, two singletons were also observed which were associated with the lineage of Indian DENV from 2021 and a Singaporean genome from 2012. Additionally, genomes from 2023 formed one cluster and one singleton, which were related to DENV genomes from India in 2021 and the USA from 2022 and 2023. Further, one genome from 2023 was related to a 2023 genome from Bangladesh. Interestingly, most sequences from 2022 and 2023 did not group phylogenetically with previously sequenced Nepalese sequences from 2017, which formed distinct clades within both observed subgenotypes (IV-A1 and IV-B2).

Fig. 3
figure 3

Phylogeny of Nepalese DENV2 genomes and related sequences. A maximum likelihood phylogenetic tree was constructed with the general time reversible model with gamma distribution and 1000 bootstrap replicates in MEGA11. Nepalese DENV2 genomes obtained in this study and related whole genome sequences of DENV2 accessed through the GenBank database were included in the analysis. Genomes obtained in this study are shown in red, and other Nepalese genomes are colored in blue. Sequences in black are related strains accessed from GenBank. Sequence names are displayed as “GISAID accession number_Country_Year” for self-produced sequences and “GenBank accession number_Country_Year” for all other sequences. Genotype is indicated to the right of the sequences. Numbers on the branches indicate bootstrap values greater than 70%. Distance scale is displayed at the bottom left of the tree

Full size image

DENV3

A phylogenetic tree of DENV3 sequences analyzed in the manuscript is available as Fig. 4. Nine sequences from 2022 and eight sequences from 2023 were analyzed. All DENV3 genomes, in this study, were identified as genotype III. Out of the 17 DENV3 genomes, 14 formed a cluster with the other Nepalese genomes of DENV3 from 2022. The major DENV3 cluster was most closely related to an Indian DENV genome from 2019. Further, another two-sequence cluster, comprising one sequence from 2022 and one from 2023, was also most closely related to the same 2019 Indian strain. Additionally, one singleton from 2023 was found to be related to Indian DENV3 from 2022.

Fig. 4
figure 4

Phylogeny of Nepalese DENV3 strains and related sequences. A maximum likelihood phylogenetic tree was constructed with the general time reversible model with gamma distribution and 1000 bootstrap replicates in MEGA11. Nepalese DENV3 strains obtained in this study and related whole genome sequences of DENV3 accessed through the GenBank database were included in the analysis. Genomes obtained in this study are shown in red, and other Nepalese genomes are colored in blue. Sequences in black are related strains accessed from GenBank. Sequence names are displayed as “GISAID accession number_Country_Year” for self-produced sequences and “GenBank accession number_Country_Year” for all other sequences. Genotype is indicated to the right of the sequences. Numbers on the branches indicate bootstrap values greater than 70%. Distance scale is displayed at the bottom left of the tree

Full size image

Mutational analysis

The frequency of unique mutations was variable among the genes and their corresponding proteins (Table 2). Across serotypes, the most unique mutations were observed in DENV3, followed by DENV2. Across genes, the highest unique mutation frequency was observed in NS3 (n = 20), followed by NS2A (n = 4), while the lowest (m = 2) was observed in NS2B, NS4, NS5, and E. The most frequently observed unique mutations, L17M and T20I, both occurred in the 2 K transmembrane domain of hydrophobic protein NS4A (2 K). These mutations were observed in four other genomes from Nepal and were restricted to the DENV3 serotype. Unique mutations D192B in DENV1 and L56J in DENV3 were identified in domain I and domain II of the E protein, respectively. The most common previously identified mutations in the E gene were A219T and E404A.

Table 2 Mutations and their frequency among the DENV genomes, from this study, and Nepalese genomes from the GISAID database (N = 214), separated based on their region of occurrence
Full size table

Mutations in NS3 were mostly substitutions with two leading to stop codons (D371stop and E93stop). One NS3 substitution mutation, T532V, which was observed in genomes belonging to DENV2 strain has also been identified in the Indian strain hDenV2/India/DL-IGIB1130DD0465415D/2022 from October 2022. The NS2B mutation T52A seen in two of our DENV3 genomes (EPI_ISL_19081951 and EPI_ISL_19081956) was also observed in US strain hDenV3/USA/FL-BPHL-0187/2023 from November 2023. Previously identified mutations were observed mostly in NS5 (n = 623), followed by E (n = 380), NS1 (n = 360), NS3 (n = 292), NS2A (n = 221), NS4B (n = 191), preM (n = 176), NS4A excluding 2 K (n = 135), C (n = 130), NS2B (n = 111), and 2 K (n = 34).

Discussion

This retrospective study utilized molecular methods to investigate the DENV of banked serum samples collected during 2022 and 2023 in Central Nepal. Phylogenetic analysis of the DENV whole genome sequences revealed three of the four DENV serotypes circulating in both 2022 and 2023 and a strong influence of northern Indian DENV populations on those within Central Nepal. In this set of samples, we observed a slightly higher proportion of men (55%) than women (45%) and an average age of 35 years. This finding is consistent with previous studies in Nepal, where dengue is a disease mostly observed in men and young adults (15–40 years old) [25]. The observed age and gender distribution could be attributed to the increased likelihood of these demographics of being involved in outdoor working activities [25, 26].

In the 2022 study population, we identified DENV1 as the major serotype (28/48, 58%) followed by DENV3 (11/48, 23%), reflecting the general trend within the Kathmandu Valley [26]. This is consistent with the findings of our 2022 serological study which found DENV1 to be predominant in a similar population to our study [27]. In 2023, the most common serotype within our study population shifted to DENV3 (20/32, 63%). Previous serosurveillance studies have indicated that prior major outbreaks have been caused largely by DENV1 and 2, with the 2022 Kathmandu Valley outbreak being primarily attributable by DENV1 [26,27,28,29,30,31,32]. However, there has been a recent rise in the prevalence of DENV3, an observation corroborated in our study [26]. Interestingly, a survey of serotypes circulating during 2023 in the Dhading District, which lies in the north-eastern region of the Bagmati Province, identified the vast majority (97.5%) of PCR-positive dengue cases to be DENV2 [33]. This contrasts with the serotype distribution within our 2023 study population, which identified DENV2 as the second most common serotype (25%) after DENV3. The introduction of DENV3, which likely has low population immunity within Nepal, may impact the size or severity of the next outbreak. Because immunity against DENV is serotype specific, the dominant circulation of multiple serotypes within a small region leaves populations primed for serotype invasion if a secondary or tertiary serotype starts circulating in a nonimmune population, leading to increased likelihood of more severe outcomes [13, 34].

Although we are limited by the lack of historical genomic analysis of DENV within Nepal, these findings point to a likelihood of multiple or continuous introductions of DENV2 to the country. This study revealed that 2022 and 2023 Nepalese DENV2 genomes were more closely related to sequences from India, China, Singapore, Bangladesh, and the USA than previously sequenced DENV2 within Nepal [29]. Furthermore, the lineages and genotypes in the Nepalese DENV1 and 3 populations (genotype III of DENV1 and genotype III of DENV3) closely mirror those circulating in Northern India in 2018 and 2019 as identified by Behera et al. [35] Indeed, we also observed phylogenetic grouping between recent Nepali sequences and Indian sequences from 2019. Given the short life span of the Aedes genus [36], it is probable that these lineages of DENV entered Nepal through human hosts rather than infected mosquito vectors, likely by tourists or other visitors. In 2022, the highest number of tourists to Nepal was from India and the USA, representing 34.1% and 12.5% of the total arrivals in Nepal [37]. Similarly, in 2023, the proportion of Chinese tourists rose to the third most common nationality of visitor at 6.0% after Indian and US citizens (31.5% and 9.9%, respectively) [38]. It should also be noted that the proportion of Indian visitors to Nepal is likely underrepresented by these numbers due to the open border between the two countries.

Our phylogenetic analysis also revealed intraserotype diversity between the Nepalese DENV1 and DENV2. In general, the consequence of intraserotype genetic diversity of DENV is not as well-established as that of interserotype differences. Historically, the extinct American genotype of DENV has been linked to lower virulence, milder disease presentation, and less viral replication in vectors than the Southeast Asian strain that replaced it in South America; however, differences between currently circulating genotypes are less clear [39, 40]. Some studies have found a correlation between the presence of novel genotypes and a rise in DENV infection incidence and posited increased viral fitness as responsible for genotype replacement [15, 41]. Nevertheless, further studies are required to fully understand the impact of genetic diversity on dengue disease pathogenesis and epidemiology.

The role of mutations in any virus should not be dismissed, because viruses are rapidly evolving as a result of selection pressure which can lead to drug and immune escape pathways [11, 42]. For example, common mutations T478S and R120T present in the E protein of Nepalese genomes have been shown to respectively dramatically reduce vaccine efficacy and enhance receptor affinity [43, 44]. Although literature supporting the observed substitutions D192B and L56J in E protein were not found, these mutations are present in N terminal domain I and domain II, respectively. Domain II of the E protein contains a hydrophobic fusion peptide (residues 98 to 110) involved in attaching the virus to the target cell membrane [45,46,47]. The E protein residues critical for binding of mAb did not harbor mutations in any of the genomes of our study [48].

Mutations in the 2 K peptide region of NS4 were observed in several genomes in residues 17 and 20. Though the exact effects of substitutions in residues 17 and 20 are not known, the 2 K peptide serves as signal sequence for the translocation of the adjacent NS4B into the endoplasmic reticulum (ER) lumen [49,50,51]. We also observed several mutations in the NS2 protein. Mutations of the NS2 protein are not entirely modeled; however, they have started to garner attention due to emerging evidence of their essential roles in viral replication and immunomodulation [52,53,54,55]. The NS3 and NS5 regions are highly conserved regions of the dengue genome and perform enzymatic activities involved in the viral replication cycle [56,57,58]. NS5 in DENV2 has been detected frequently in the cellular nucleus and is ultimately linked to viral pathogenesis [58]. Although information on mutation frequency and supporting literature for mutations in NS3 and NS5 observed in this study was not found, it is possible that new mutations in conserved region could affect the viral pathogenesis by altering perturbations or protein–protein interactions [49]. The differential mutational frequency between NS proteins and structural proteins observed in this study could reflect negative pressure selecting against mutations to key proteins, as well as the difference in protein size given that the totaled size of the NS proteins (~ 2250 amino acids) is more than double that of the structural proteins (~ 840) [59].

We observed a higher mutation rate in our DENV3 samples than other serotypes. DENV3 has been a more prevalent serotype in Nepal as well as globally and has been associated with severe disease outcomes during primary infection [60]. While there are not any particular studies depicting higher mutation rates in DENV3, further investigation in relation to clinical outcomes is essential to understand the effects of this high mutation rate, if any.

Until now, the vast majority of dengue surveillance efforts within Nepal have been hospital-based studies investigating the disease over only 1 or 2 years within a single population [6, 24,25,26,27,28,29]. Similarly, this study was conducted using samples banked at a tertiary care hospital, and therefore did not obtain data on clinical parameters and risk factors. We acknowledge that such hospital-based studies introduce implicit bias. Further, the samples included in this study were largely from the Bagmati Province in Central Nepal, and thus may not be representative of the overall Nepalese DENV population. We also acknowledge that the mutation profiling could be better discussed with clinical outcomes, as prior studies have related mutations to severity including neurovirulence [11, 61]. Further, the effects of mutations could also be more effectively studied by functional analysis in silico (FoldX, I-TASSER, or DMPfold) to observe their role in folding patterns and protein–protein interaction [49, 62]. However, we believe that our extensive phylogenetic analysis and mutational analyses performed are valuable even without clinical metadata as we have chosen to focus primarily on our investigation of the genomic data presented in this study.

In Nepal, dengue has seen an exponential rise in cases in the past few years. In 2022, the majority of cases occurred in the Bagmati Province in Central Nepal with three districts within the Kathmandu Valley, Kathmandu, Lalitpur, and Bhaktapur districts, being the most affected [4]. This emergence of dengue in the hilly region, which was previously thought to be protected from dengue due to its temperate climate, poses a serious threat to public health in Nepal, particularly as climate change, unplanned urbanization, and poor waste management systems exacerbate outbreaks in urban areas [63]. As the affected region and population within Nepal expands, the need for disease and viral surveillance to help understand and control the problem becomes more pressing. As we demonstrated in this study, DENV in the hilly region of Central Nepal is closely related to viruses in India, Singapore, China, and the USA, likely due to international tourism and the open-border policy between Nepal and India, where dengue is also endemic [64]. Dengue transmission is a complex, multifaceted phenomenon which requires long-term monitoring in order to enact the most effective disease control measures. Furthermore, with multiple dengue vaccines currently under development, ongoing genomic surveillance will also be critical in understanding the impact of genetic diversity on the efficacy of vaccines [65,66,67]. We were able to effectively profile the genetic diversity and displacement of DENV in a populous region of Central Nepal using whole genome sequencing during a period of high dengue incidence.

Conclusions

This retrospective study, which included banked samples from two consecutive years of high dengue burden in Nepal, leveraged amplicon-based whole genome sequencing to examine the genetic diversity of three serotypes of dengue virus circulating in Central Nepal. We identified a strong influence of Indian DENV populations on Nepalese DENV regardless of serotype, as well as several lineages of DENV2 related to those in neighboring countries in Asia and the USA. Furthermore, we identified possible clade shifts in the DENV1 and 2 populations and a high number of DENV3 cases, which is an emerging serotype in Central Nepal. Genomic surveillance and disease monitoring of dengue in Nepal are an ongoing task that requires continuous effort; however, our demonstration of successful whole genome sequencing of DENV using the iSeq100, a tool specifically designed for use in low resource settings, is encouraging.

Data availability

All sequences are accessible in the GISAID Dengue database (accession numbers available in Additional file 1: Table S1). Raw reads are available as NCBI BioProject PRJNA1155024 at https://www.ncbi.nlm.nih.gov/bioproject/?term = PRJNA1155024.

Abbreviations

2K:

2K transmembrane peptide

ADE:

Antibody-dependent enhancement

BLAST:

Basic Local Alignment Search Tool

C:

Capsid

COVID:

Coronavirus disease

DENV:

Dengue virus (DENV1 = dengue virus serotype 1)

DHF:

Dengue hemorrhagic fever

DHKUH:

Dhulikhel Hospital/Kathmandu University Hospital

DSS:

Dengue shock syndrome

E:

Envelope

ECDC:

Epidemiology and Disease Control Division

EMR:

Electronic medical record

GISAID:

Global Initiative on Sharing All Influenza Data

GTR + G:

Generalized time reversible + gamma distributed rates

IDT:

Integrated DNA Technologies

KUSMS IRC:

Institutional Review Committee at Kathmandu University School of Medical Sciences

MEGA:

Molecular Evolutionary Genetics Analysis

NGS:

Next-generation sequencing

NHRC ERB:

Ethical Review Board at Nepal Health Research Council

NS:

Nonstructural region (e.g., NS1 = nonstructural region 1)

PCR:

Polymerase chain reaction

preM:

Pre-membrane

PRC:

People’s Republic of China

qPCR:

Quantitative polymerase chain reaction

RNA:

Ribonucleic acid

RUO:

Research use only

SD:

Standard deviation

WHO:

World Health Organization

USA:

United States of America

References

  1. Dengue and severe dengue. Available from: https://www.who.int/news-room/fact-sheets/detail/dengue-and-severe-dengue. Cited 2024 May 27.

  2. Pandey BD, Rai SK, Morita K, Kurane I. First case of dengue virus infection in Nepal. Nepal Med Coll J NMCJ. 2004Dec;6(2):157–9.

    PubMed  Google Scholar 

  3. Epidemiology and Disease Control Division. National Guidelines on Preventin, Management and Control of Dengue in Nepal. Government of Nepal Ministry of Health and Population;. Available from: https://www.who.int/docs/default-source/nepal-documents/national-guidelines-on-prevention-management-and-control-of-dengue-in-nepal.pdf?sfvrsn=e02216fd_2. Cited 2024 May 28.

  4. Epidemiology and Disease Control Division. Situation updates of dengue (as of 31 Dec 2022). Government of Nepal Ministry of Health and Population; 2022. Available from: https://www.edcd.gov.np/news/situation-updates-of-dengue-as-of-30-nov-2022. Cited 2024 May 28.

  5. Epidemiology and Disease Control Division. Situation report on dengue in Nepal- 2023. Government of Nepal Ministry of Health and Population; 2023. Available from: https://www.edcd.gov.np/news/20231215-dengue-situation-update. Cited 2024 May 28.

  6. Malla S, Thakur GD, Shrestha SK, Banjeree MK, Thapa LB, Gongal G, et al. Identification of all dengue serotypes in Nepal. Emerg Infect Dis. 2008Oct;14(10):1669–70.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Lindenbach BD, Rice CM. Molecular biology of flaviviruses. In: Advances in Virus Research. Academic Press; 2003. p. 23–61. Available from: https://www.sciencedirect.com/science/article/pii/S0065352703590029. Cited 2024 May 27.

  8. Weaver SC, Vasilakis N. Molecular evolution of dengue viruses: contributions of phylogenetics to understanding the history and epidemiology of the preeminent arboviral disease. Infect Genet Evol J Mol Epidemiol Evol Genet Infect Dis. 2009Jul;9(4):523–40.

    CAS  Google Scholar 

  9. Holmes EC, Burch SS. The causes and consequences of genetic variation in dengue virus. Trends Microbiol. 2000Feb 1;8(2):74–7.

    Article  CAS  PubMed  Google Scholar 

  10. Sim S, Hibberd ML. Genomic approaches for understanding dengue: insights from the virus, vector, and host. Genome Biol. 2016Mar 2;17(1):38.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Rico-Hesse R. Microevolution and virulence of dengue viruses. Adv Virus Res. 2003;59:315–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Montoya M, Gresh L, Mercado JC, Williams KL, Vargas MJ, Gutierrez G, et al. Symptomatic versus inapparent outcome in repeat dengue virus infections is influenced by the time interval between infections and study year. PLoS Negl Trop Dis. 2013Aug 8;7(8): e2357.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Flipse J, Diosa-Toro MA, Hoornweg TE, van de Pol DPI, Urcuqui-Inchima S, Smit JM. Antibody-dependent enhancement of dengue virus infection in primary human macrophages; balancing higher fusion against antiviral responses. Sci Rep. 2016Jul 6;6(1):29201.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Drumond BP, da Silva Fagundes LG, Rocha RP, Fumagalli MJ, Araki CS, Colombo TE, et al. Phylogenetic analysis of dengue virus 1 isolated from South Minas Gerais. Brazil Braz J Microbiol. 2016Feb 17;47(1):251–8.

    Article  CAS  PubMed  Google Scholar 

  15. Hang VTT, Holmes EC, Veasna D, Quy NT, Hien TT, Quail M, et al. Emergence of the Asian 1 genotype of dengue virus serotype 2 in Viet Nam: in vivo fitness advantage and lineage replacement in South-East Asia. PLoS Negl Trop Dis. 2010Jul 20;4(7): e757.

    Article  Google Scholar 

  16. Ito M, Takasaki T, Kotaki A, Tajima S, Yuwono D, Rimal HS, et al. Molecular and virological analyses of dengue virus responsible for dengue outbreak in East Timor in 2005. Jpn J Infect Dis. 2010May;63(3):181–4.

    Article  CAS  PubMed  Google Scholar 

  17. Building in-country capacity for pathogen genetic sequencing in Nepal. Available from: https://www.who.int/nepal/news/detail/13-12-2021-building-in-country-capacity-for-pathogen-genetic-sequencing-in-nepal. Cited 2024 Aug 24.

  18. Vogels CBF, Hill V, Breban MI, Chaguza C, Paul LM, Sodeinde A, et al. DengueSeq: a pan-serotype whole genome amplicon sequencing protocol for dengue virus. BMC Genomics. 2024May 1;25(1):433.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. CZ ID Help Center. 2023. Viral Consensus Genome Pipeline. Available from: https://chanzuckerberg.zendesk.com/hc/en-us/articles/13622345578388-Viral-Consensus-Genome-Pipeline. Cited 2024 Jun 2.

  20. Fonseca V, Libin PJK, Theys K, Faria NR, Nunes MRT, Restovic MI, et al. A computational method for the identification of dengue, Zika and chikungunya virus species and genotypes. PLoS Negl Trop Dis. 2019May 8;13(5): e0007231.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Posada D, Crandall KA. MODELTEST: testing the model of DNA substitution. Bioinformatics. 1998Jan 1;14(9):817–8.

    Article  CAS  PubMed  Google Scholar 

  22. Sayers EW, Bolton EE, Brister JR, Canese K, Chan J, Comeau DC, et al. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 2021Dec 1;50(D1):D20–6.

    Article  PubMed Central  Google Scholar 

  23. Wallau GL, Abanda NN, Abbud A, Abdella S, Abera A, Ahuka-Mundeke S, et al. Arbovirus researchers unite: expanding genomic surveillance for an urgent global need. Lancet Glob Health. 2023Oct 1;11(10):e1501–2.

    Article  CAS  PubMed  Google Scholar 

  24. Cheng J, Schloerke B, Karambelkar B, Xie Y. leaflet: Create Interactive Web Maps with the JavaScript “Leaflet” library. 2024. (R package). Available from: https://rstudio.github.io/leaflet/.

  25. Gupta BP, Tuladhar R, Kurmi R, Manandhar KD. Dengue periodic outbreaks and epidemiological trends in Nepal. Ann Clin Microbiol Antimicrob. 2018Feb 23;17(1):6.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Rimal S, Shrestha S, Pandey K, Nguyen TV, Bhandari P, Shah Y, et al. Co-circulation of dengue virus serotypes 1, 2, and 3 during the 2022 dengue outbreak in Nepal: a cross-sectional study. Viruses. 2023Feb;15(2):507.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Katuwal N, Shrestha A, Ranjitkar U, Jakibanjar S, Madhup SK, Tamrakar D, et al. Molecular investigation of dengue virus serotypes in the dengue outbreak of 2022 in Nepal. Kathmnadu Univ Med J. 2024Aug 19;22(85):99–106.

    Google Scholar 

  28. Poudyal P, Sharma K, Dumre SP, Bastola A, Chalise BS, Shrestha B, et al. Molecular study of 2019 dengue fever outbreaks in Nepal. Trans R Soc Trop Med Hyg. 2021Jun 2;115(6):619–26.

    Article  CAS  PubMed  Google Scholar 

  29. Ngwe Tun MM, Pandey K, Nabeshima T, Kyaw AK, Adhikari M, Raini SK, et al. An outbreak of dengue virus serotype 2 cosmopolitan genotype in Nepal, 2017. Viruses. 2021Aug;13(8):1444.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Khetan RP, Stein DA, Chaudhary SK, Rauniyar R, Upadhyay BP, Gupta UP, et al. Profile of the 2016 dengue outbreak in Nepal. BMC Res Notes. 2018Jul;3(11):423.

    Article  Google Scholar 

  31. Gupta BP, Singh S, Kurmi R, Malla R, Sreekumar E, Manandhar KD. Re-emergence of dengue virus serotype 2 strains in the 2013 outbreak in Nepal. Indian J Med Res. 2015Dec;142(Suppl 1):S1-6.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Dumre SP, Bhandari R, Shakya G, Shrestha SK, Cherif MS, Ghimire P, et al. Dengue virus serotypes 1 and 2 responsible for major dengue outbreaks in Nepal: clinical, laboratory, and epidemiological features. Am J Trop Med Hyg. 2017Jul 31;97(4):1062–9.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Rimal S, Shrestha S, Paudel SW, Shah Y, Bhandari G, Pandey K, et al. Molecular and entomological characterization of 2023 dengue outbreak in Dhading District, Central Nepal. Viruses. 2024Apr;16(4):594.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Midgley CM, Bajwa-Joseph M, Vasanawathana S, Limpitikul W, Wills B, Flanagan A, et al. An in-depth analysis of original antigenic sin in dengue virus infection. J Virol. 2011Jan;85(1):410–21.

    Article  CAS  PubMed  Google Scholar 

  35. Behera SP, Bhardwaj P, Deval H, Srivastava N, Singh R, Misra BR, et al. Co-circulation of all the four dengue virus serotypes during 2018–2019: first report from eastern Uttar Pradesh, India. PeerJ. 2023Jan;9(11): e14504.

    Google Scholar 

  36. CDC. Mosquitoes. 2024. Life cycle of Aedes mosquitoes. Available from: https://www.cdc.gov/mosquitoes/about/life-cycle-of-aedes-mosquitoes.html. Cited 2024 Jun 3.

  37. Nepal Tourism Statistics 2022. Government of Nepal Ministry of Culture, Tourism & Civil Aviation; 2023. Available from: https://www.tourism.gov.np/files/NOTICE%20MANAGER_FILES/Setting_Nepal%20Tourism%20Statistic_2022.pdf. Cited 2024 May 28.

  38. Nepal Tourism Statistics 2023. Government of Nepal Ministry of Culture, Tourism & Civil Aviation; 2024. Available from: https://www.tourism.gov.np/files/1/Nepal%20Tourism%20Statistic_2023%20final.pdf. Cited 2024 May 28.

  39. Rico-Hesse R, Harrison LM, Salas RA, Tovar D, Nisalak A, Ramos C, et al. Origins of dengue type 2 viruses associated with increased pathogenicity in the Americas. Virology. 1997Apr 14;230(2):244–51.

    Article  CAS  PubMed  Google Scholar 

  40. Anderson JR, Rico-Hesse R. Aedas aegypti vectorial capacity is determined by the infecting genotype of dengue virus. Am J Trop Med Hyg. 2006Nov;75(5):886–92.

    Article  CAS  PubMed  Google Scholar 

  41. Hernández-García E, Muñoz M de L, David RE, Pérez-Ramírez G, Navarrete-Espinosa J, Díaz-Badillo Á, et al. Epidemiological implications of the genetic diversification of dengue virus (DENV) serotypes and genotypes in Mexico. Infect Genet Evol. 2020:84:104391.

  42. Dolan PT, Taguwa S, Rangel MA, Acevedo A, Hagai T, Andino R, et al. Principles of dengue virus evolvability derived from genotype-fitness maps in human and mosquito cells. Wittkopp PJ, Sanjuan R, Illingworth CJ, editors. eLife. 2021:10:e61921.

  43. Juraska M, Magaret CA, Shao J, Carpp LN, Fiore-Gartland AJ, Benkeser D, et al. Viral genetic diversity and protective efficacy of a tetravalent dengue vaccine in two phase 3 trials. Proc Natl Acad Sci. 2018Sep 4;115(36):E8378–87.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Hung JJ, Hsieh MT, Young MJ, Kao CL, King CC, Chang W. An external loop region of domain III of dengue virus type 2 envelope protein is involved in serotype-specific binding to mosquito but not mammalian cells. J Virol. 2004Jan;78(1):378–88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Zhang C, Mammen MP, Chinnawirotpisan P, Klungthong C, Rodpradit P, Monkongdee P, et al. Clade replacements in dengue virus serotypes 1 and 3 are associated with changing serotype prevalence. J Virol. 2005Dec;79(24):15123–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Mushtaq S, Khan MIU, Khan MT, Lodhi MS, Wei DQ. Novel mutations in structural proteins of dengue virus genomes. J Infect Public Health. 2023Dec;16(12):1971–81.

    Article  PubMed  Google Scholar 

  47. Allison SL, Schalich J, Stiasny K, Mandl CW, Heinz FX. Mutational evidence for an internal fusion peptide in Flavivirus envelope protein E. J Virol. 2001May;75(9):4268–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Matsui K, Gromowski GD, Li L, Barrett ADT. Characterization of a dengue type-specific epitope on dengue 3 virus envelope protein domain III. J Gen Virol. 2010Sep;91(Pt 9):2249–53.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Torres MC, Martins Karl AL, Müller Pereira da Silva M, Dardenne LE, Bispo de Filippis AM. In silico analysis of dengue virus serotype 2 mutations detected at the intrahost level in patients with different clinical outcomes. Microbiol Spectr. 2021:9(2):e00256–21.

  50. Miller S, Kastner S, Krijnse-Locker J, Bühler S, Bartenschlager R. The non-structural protein 4A of dengue virus is an integral membrane protein inducing membrane alterations in a 2K-regulated manner. J Biol Chem. 2007Mar 23;282(12):8873–82.

    Article  CAS  PubMed  Google Scholar 

  51. Gopala Reddy SB, Chin WX, Shivananju NS. Dengue virus NS2 and NS4: minor proteins, mammoth roles. Biochem Pharmacol. 2018Aug;154:54–63.

    Article  CAS  PubMed  Google Scholar 

  52. Xie X, Gayen S, Kang C, Yuan Z, Shi PY. Membrane topology and function of dengue virus NS2A protein. J Virol. 2013Apr 15;87(8):4609–22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Li Y, Li Q, Wong YL, Liew LSY, Kang C. Membrane topology of NS2B of dengue virus revealed by NMR spectroscopy. Biochim Biophys Acta BBA - Biomembr. 2015 Oct 1;1848(10, Part A):2244–52.

  54. Li Y, Lee MY, Loh YR, Kang C. Secondary structure and membrane topology of dengue virus NS4A protein in micelles. Biochim Biophys Acta Biomembr. 2018Feb;1860(2):442–50.

    Article  CAS  PubMed  Google Scholar 

  55. Li Y, Wong YL, Lee MY, Li Q, Wang QY, Lescar J, et al. Secondary structure and membrane topology of the full-length dengue virus NS4B in micelles. Angew Chem Int Ed Engl. 2016Sep 19;55(39):12068–72.

    Article  CAS  PubMed  Google Scholar 

  56. Neufeldt CJ, Cortese M, Acosta EG, Bartenschlager R. Rewiring cellular networks by members of the Flaviviridae family. Nat Rev Microbiol. 2018Mar;16(3):125–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Luo D, Xu T, Hunke C, Grüber G, Vasudevan SG, Lescar J. Crystal structure of the NS3 protease-helicase from dengue virus. J Virol. 2008Jan;82(1):173–83.

    Article  CAS  PubMed  Google Scholar 

  58. Yap TL, Xu T, Chen YL, Malet H, Egloff MP, Canard B, et al. Crystal structure of the dengue virus RNA-dependent RNA polymerase catalytic domain at 1.85-Angstrom resolution. J Virol. 2007:81(9):4753–65.

  59. Harapan H, Michie A, Sasmono RT. Imrie A Dengue: a minireview Viruses. 2020Jul 30;12(8):829.

    CAS  PubMed  Google Scholar 

  60. Mani S, Ghosh S, Sharma R, Ajith A, Prabhakaran P. Chapter 1 - Controlling dengue, an urban pandemic – a case study of Delhi, India. In: Katz R, Boyce M, editors. Inoculating Cities. Academic Press; 2021. p. 1–19. Available from: https://www.sciencedirect.com/science/article/pii/B9780128202043000012. Cited 2024 Nov 24

  61. Blaney JE, Johnson DH, Firestone CY, Hanson CT, Murphy BR, Whitehead SS. Chemical mutagenesis of dengue virus type 4 yields mutant viruses which are temperature sensitive in vero cells or human liver cells and attenuated in mice. J Virol. 2001Oct;75(20):9731–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Sharma A, Krishna S, Sowdhamini R. Bioinformatics analysis of mutations sheds light on the evolution of dengue NS1 protein with implications in the identification of potential functional and druggable sites. Mol Biol Evol. 2023;40(3):msad033.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Pokharel P, Khanal S, Ghimire S, Pokhrel KM, Shrestha AB. Frequent outbreaks of dengue in Nepal – causes and solutions: a narrative review. IJS Glob Health. 2023Sep;6(5): e0351.

    Google Scholar 

  64. Dengue - Nepal. Available from: https://www.who.int/emergencies/disease-outbreak-news/item/2022-DON412. Cited 2024 Jun 3

  65. Teva takeda. Phase III, double-blind, randomized, placebo-controlled trial to investigate the efficacy, safety and immunogenicity of a tetravalent dengue vaccine (tdv) administered subcutaneously in healthy children aged 4 - 16 years old. clinicaltrials.gov; 2024 May. Report No.: NCT02747927. Available from: https://clinicaltrials.gov/study/NCT02747927. Cited 2023 Dec 31

  66. Butantan Institute. Phase III, double-blind, randomized, placebo-controlled trial to evaluate the efficacy, safety, and immunogenicity of the dengue 1, 2, 3, 4 (attenuated) vaccine from Instituto Butantan. clinicaltrials.gov; 2024 Feb. Report No.: NCT02406729. Available from: https://clinicaltrials.gov/study/NCT02406729. Cited 2023 Dec 31

  67. Huits R, Grubaugh ND, Libman M, Hamer DH. Resurgence of dengue in the era of genomic surveillance and vaccines. Ann Intern Med. 2024May 21;177(5):670–1.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge all data contributors, i.e., the authors and their originating laboratories responsible for obtaining the specimens, and their submitting laboratories for generating the genetic sequence and metadata and sharing via the GISAID Initiative, on which this research is based.

Funding

This study was supported by Bill and Melinda Gates Foundation (INV008942). M. C. was supported by the US Department of State Fulbright Exchange Program.

Author information

Author notes

  1. Margaret Chi and Nishan Katuwal are co-first authors.

Authors and Affiliations

  1. Center for Infectious Disease Research and Surveillance, Dhulikhel Hospital Kathmandu University Hospital, Dhulikhel, Nepal

    Margaret Chi, Nishan Katuwal, Aastha Shrestha, Dipesh Tamrakar & Rajeev Shrestha

  2. Molecular and Genome Sequencing Research Lab, Dhulikhel Hospital Kathmandu University Hospital, Dhulikhel, Nepal

    Margaret Chi, Nishan Katuwal & Aastha Shrestha

  3. Department of Microbiology, Dhulikhel Hospital Kathmandu University Hospital, Dhulikhel, Nepal

    Surendra Kumar Madhup

  4. Department of Community Medicine, Kathmandu University School of Medical Sciences, Dhulikhel, Nepal

    Dipesh Tamrakar

  5. Department of Pharmacology, Kathmandu University School of Medical Sciences, Dhulikhel, Nepal

    Rajeev Shrestha

Authors
  1. Margaret Chi
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Nishan Katuwal
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Aastha Shrestha
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Surendra Kumar Madhup
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Dipesh Tamrakar
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Rajeev Shrestha
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

MC: Conceptualization, design, data acquisition, analysis, interpretation, original draft, revision and review. NK: Conceptualization, design, data acquisition, analysis, interpretation, original draft, revision and review. AS: Data acquisition, interpretation, original draft, revision and review. SKM: Data acquisition, revision and review. DT: Interpretation, revision and review. RS: Conceptualization, design, interpretation, revision and review. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Rajeev Shrestha.

Ethics declarations

Ethics approval and consent to participate

Ethical approval for this study was obtained by the Ethical Review Board at Nepal Health Research Council (NHRC ERB, ref.: 107/2023) and Institutional Review Committee at Kathmandu University School of Medical Sciences (KUSMS IRC, ref.: 117/2024). This study did not directly contact the human subjects or patients and only investigated banked serum samples obtained during routine dengue diagnostic procedures with secondary metadata obtained from hospital’s EMR. Therefore, informed consent from the patients was waived by the NHRC ERB and the KUSMS IRC. We declare that all research conducted in the study conformed to the principles of the Helsinki Declaration.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

44263_2025_135_MOESM1_ESM.docx

Additional file 1. Table S1. GISAID accession numbers with alignment coverage (%). Table containing the GISAID accession numbers of self-produced sequences included in phylogenetic analysis with percent alignment coverage of each sequence.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chi, M., Katuwal, N., Shrestha, A. et al. Whole genome sequencing and phylogenetic analysis of dengue virus in Central Nepal from 2022 to 2023. BMC Glob. Public Health 3, 18 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s44263-025-00135-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s44263-025-00135-z

Keywords

BMC Global and Public Health

ISSN: 2731-913X

Contact us