Reemergence of Sylvatic Dengue Virus in Southern Senegal, 2021

Abstract

As part of the syndromic surveillance of fever in Senegal, the virology department at Institut Pasteur de Dakar (IPD) in collaboration with the Epidemiology Unit and the Senegalese Ministry of Health conducted syndromic surveillance of fever in Senegal. Sample are from all suspected arboviral infections patients attending any of the sentinel sites. Collected blood samples were sent on a weekly basis at WHOCC for arboviruses and hemorrhagic fever viruses for screening of seven medically important arboviruses, including dengue virus (DENV). From January to December 2021, 2010 suspected cases were received among them 124 for confirmed to be DENV+ by RT-qPCR attempt of serotyping led to the detection of atypical DENV case from Sare Yoba area (Kolda region) which is unable to be correctly assigned to a serotype by the available tools (TIB Molbiol Modular Dx Dengue typing kit). Performed genome sequencing et phylogenetic analysis leads to the identification of a sylvatic DENV-2 strain closely related to a virus previously detected in Guinee-Bissau in 2009. This finding constitutes proof of the contemporary circulation of DENV-2 strain belonging to the sylvatic cycle in addition to well-known epidemic strains; this adds a piece of complexity to dengue management in Senegal. Alarmingly, it calls for improved genomic surveillance of DENV to know the genetic diversity of circulating strains in order to strengthen future vaccination policies.

1. Introduction

In Africa, fever is the primary symptom that prompts patients to seek medical attention [1, 2]. The presence of a fever of unknown origin has historically been used as a starting point for treating malaria [3]. As malaria control efforts in Sub-Saharan African nations continue to yield positive results thanks to measure as large-scale implementation of malaria rapid diagnostic tests (mRDT), the incidence of this disease is decreasing, resulting in a smaller percentage of febrile illnesses attributed to malaria. During the period from 2000 to 2013, malaria mortality rates decreased by 47% worldwide and by 54% in Sub-Saharan Africa, which is the region most affected by the disease. This decline has resulted in an increase in the proportion of patients exhibiting symptoms of non-malaria febrile illness (NMFI) [4]. Among myriad of pathogens such as viruses, bacteria, and parasites can cause acute febrile episodes indistinguishable from malaria.

Dengue fever (DF) is a viral illness caused by the dengue virus (DENV) etiological agent of the disease. The virus exists in four serotypes, namely DENV1–4 [5]. They belong to flaviviridae family and flavivirus genus. DENV is prevalent in numerous tropical and subtropical regions worldwide [6]. The virus is considered a significant public health threat in these regions due to its high morbidity and mortality rates [7]. Infections with DENV cause clinical manifestations ranging from self-limited flu-like symptoms, namely dengue fever (DF) to life-threatening infection associated with hemorrhage and or shock syndrome called severe dengue [8]. According to World Health Organization (WHO) estimates each year 390 million people are infected by the virus [9] with a case fatality rate ranging between 1 and 5% [10, 11]. In contrast to American and Asian countries, the virus epidemiology is not well known in Africa despite reports of the virus circulation since the nineteenth century [12, 13]. This underestimation in the African continent is linked to many factors as low awareness, lack of surveillance activities, the prevalence of pathogens associated with similar clinical manifestations, and the lack of reliable diagnostic tools [13].

In Senegal since 2011, in collaboration with the Senegalese Ministry of Health, the virology department and the epidemiological unit of Institut Pasteur de Dakar (IPD) set up a countrywide surveillance of influenza viruses and other respiratory tract infections associated viruses, namely 4S network [14]. This system was improved in 2015 to add the surveillance of other pathogens. Thanks to noticed increased number of febrile cases around the country not linked to malaria; the list of targeted pathogens includes arboviruses (Dengue, Zika, and Rift valley fever), bacteria, etc. [15]. Following years, this human sentinel surveillance throughout fever permitted the isolation and identification of many viruses, including DENV. In 2017, Dieng and colleagues [16] implemented genomic surveillance of DENV in Senegal throughout the 4S network collected samples. This allowed the detection and mapping of molecular characterization of DENv serotypes/genotypes circulating around the country [16]. DENV serotypes are maintained in two different ecologically and evolutionary distinct transmission cycles, namely the human cycle and the sylvatic cycle. The human cycle is sustained exclusively between humans and domestic or peridomestic mosquitoes, while the sylvatic cycle involves arboreal mosquitoes and nonhuman primates [17]. Although sylvatic strains of DENV play a pivotal role in the evolution and emergence of the virus, there have been no documented cases of ongoing and uninterrupted transmission [18].

In Senegal, particularly in the southern region of the country (i.e., the Kédougou area), the predominance of sylvatic cycles has historically played a significant role in the spread of DENV [19]. Since 2009, there have been numerous reports of dengue epidemics in Senegal, all of which have been associated with the epidemic cycle. This chapter discusses the reemergence of contemporary sylvatic DENV-2 strain in Southern Senegal, thanks to implemented genomic surveillance and 4S network system.

2. Material and methods

2.1 4S network sentinels sites for fever surveillance

In Senegal, a Sub-Saharan African country, a surveillance system for febrile illnesses has been in place for a long time. The Senegalese Ministry of Health, the WHO country office, and the Institut Pasteur de Dakar (IPD), which hosts the WHO Collaborating Center for Arboviruses and the National Influenza Center, partnered to establish a febrile illnesses surveillance network [20]. The system initially monitored virological surveillance of Influenza-like illnesses (ILI) but was later revised with the establishment of the Senegalese Syndromic Sentinel Surveillance Network (4S network) based on a syndromic approach centered around fever. The 4S network is accountable for monitoring febrile illnesses at 20 sentinel sites across 14 administrative regions in Senegal, where population-based surveillance for ILI and other priority public health syndromes, such as malaria, dengue-like syndromes, and diarrheal syndromes, are conducted. Outpatient visits are enrolled and distributed across various regions of the country [21].

2.2 Sample collection

Clinical samples were collected from 22 sentinel sites around the country. For each suspected/ case that meets inclusion criteria, whole blood samples were collected using dry tubes and stored at +4 until shipping to the reference lab located at the virology department at IPD.

2.3 Sample shipping to reference lab

On a weekly basis collected suspected arboviral samples are shipped with epidemiological and demographic forms at the virology lab based at Institut Pasteur de Dakar. At the lab, samples were identified and a unique number of six digits is provided.

2.4 Sample handling and RNA extraction

Briefly, dry tubes were centrifuged at 2000 rpm for 5 minutes and the serum was harvested on cryotubes and then stored at – 80 for biobanking purposes. For the purpose of molecular screening, RNA extraction was performed from 140 μl of serum using Qiagen viral RNA mini kit (Qiagen, Hildan, Germany), according to the manufacture’s recommendations. RNA is eluted on 60 μl of molecular grade water and stored on ice until further use.

2.5 RT-PCR diagnostic assays

2.5.1 panDENV detection

RNA was detected using Lightmix 1 step (Roche). Master mix for virus detection was prepared according to the table (Table 1) using a set of primers targeting DENV 3’-UTR region previously described by Wagner and colleagues [22]. The real-time PCR assay was performed using a CFX96 thermocycler (Biorad, France). The thermal profile used is described in Table 1. Any DENV RNA with Ct values below 32 was considered positive.

Reagents	Volume	Step	Condition
Lightmix enzyme mix	9.5	RT	55° - 10mn
Forward primer	0.8		95° - 1 mn
Reverse primer	0.8	40 Cycles	95° - 15 sec
Probe	0.4		60° - 30 sec
Grade water	3.5

Table 1.

Mixture preparation and conditions for RT-qPCR detection of DENV.

2.5.2 DENV serotyping assay

In the case of panDENV positivity, same RNA was systematically subjected to RT-qPCR to determine the associated DENV serotype using TIB Molbiol Modular Dx Dengue typing kit (cat. no. 40–0700-24; TIB Molbiol, Berlin, Germany) [19]. Using different probes serotype-specific and labeled with different fluorophores, the system allows discrimination of serotypes from 5 μl of RNA input. Surprisingly, at the end of the reaction used system fail to define the serotype of DENV+ samples collected from Sare Yoba in the Kolda region in 2021 (Table 2).

Reagents	Volume	Step	Condition
Lightmix enzyme mix	10	RT	55° - 10mn
PSR; (Dengue typing primer and probe)	0.5		95° - 1 mn
		40 Cycles	95° - 15 sec
			60° - 30 sec
Grade water	4.5

Table 2.

Mixture preparation and conditions for RT-qPCR DENV serotyping.

2.6 Sequencing of NS5 gene using nanopore sequencing

Using a set of primers FU1/FD3 specific to the flavivirus genus and previously described by Kuno and colleagues [23] we amplify ≈ 1 kb of NS5 gene. Obtained amplicons were visualized on agarose gel and then purified at 1:0.8 ratio using.

AMPure beads (Beckman Coulter Inc., Brea, CA, USA). Purified DNA was subjected to library preparation and sequencing using Oxford Nanopore MinION (Oxford Nanopore Technologies plc, Oxford, UK). The Rapid barcoding kit (SQK RBQ110.96), which uses a transposase-based barcode binding was used during library prep steps. The prepared library was loaded onto the R9 flow cell and a sequencing reaction was performed MinION MK1C device. After 24 hours of run, the raw data were collected on flash drive; base called was performed using guppy (https://community.nanoporetech.com) to generate fastq files. Bioinformatic analysis was performed using in-house script; Nanofilt (10) was used to trim barcode adapters (options -headcrop 50 and -tailcrop 50). Minimap 2 was used to map reads to DENV-2 reference genome (NC_001474.2) (11). Finally, generated consensus was subjected to National Center for Biotechnology Information (NCBI) BLASTn, which shows 99.66% identity with sylvatic DENV-2 (JF260983).

2.7 Development of specific sylvatic DENV-2 primer scheme

Since NS5 gene sequence provides a partial overview of virus genetic makeup based on the result from BLAStn using this gene. We downloaded full genome sequences of closely related sylvatic DENV-2 sequences. Obtained dataset (n = 16) was aligned using MAFFT [24] and manually curated using geneious prime (Biomatters, New Zealand). Tilling PCR primal scheme was designed using the web-based tool (https://primalscheme.com/), and parameters sets to generate amplicons of around 900 bp and covering the coding region of sylvatic DENV-2 strains. Designed primers were synthesized generated by TIBMolBiol (Berlin, Germany), according to the manufacturer’s recommendations.

2.8 Sequencing of full coding DENV polyprotein using nanopore technology

Amplicons were generated using Q5® High-Fidelity 2X Master Mix (New England Biolabs, Ipswich, MA, USA), according to a protocol previously described by Dieng and colleagues [25]. Briefly, primers were organized in two separate pools and then were used to generate overlapping fragments covering the full coding region of the detected sylvatic DENV-2 strain. Raw data were collected after 24 hours of sequencing and data analysis procedures were identical to those previously employed for NS5 gene sequencing.

2.9 Phylogenetic reconstruction

In order to establish and contextualize the evolutionary history of detected DENV strain, from Genbank database we downloaded representative sequences of described genotypes of DENV-2 and then aligned the resulting dataset using MAFFT [24]. We constructed a maximum likelihood (ML) tree using IQ-TREE [26] and then plotted the resulting phylogenetic tree and its associated metadata as years of sampling and host using R statistical software (version 3.6.0.).

2.10 Data management and statistical analysis

Patient information and results were recorded in a database, including patient ID, date of sample collection, and laboratory results. Weekly, the database was sent to Senegalese Ministry of Health for case notification and epidemiological report. Graphs were performed using the R statistical software (version 3.6.0.).

3. Results

From January 2021 to December 2021, 2010 blood samples suspected of arboviral infections were received at the WHOOC for arboviruses and hemorrhagic fever viruses. Samples were tested for DENV by RT-qPCR; among them, 123 shows dengue positivity. The algorithm for laboratory testing for DENV is presented in Figure 1.

Figure 1.

Diagnostic algorithm for DENV molecular testing and serotyping.

The highest number of RT-qPCR DENV+ samples were recorded during the months of October and November with 53 and 63 confirmed cases, respectively (Table 3). At the serotype level, how most of the detected DENV-positive samples are DENV-3, followed by DENV-1, and finally DENV-2.

Year	Month	Suspected	Rt-qPCR+	IgM+
2021	Jan	70	1	1
2021	Fev	69	1	0
2021	Mar	54	0	0
2021	Apr	90	0	0
2021	Mai	121	0	0
2021	Jun	118	0	0
2021	Jul	149	0	0
2021	Aug	146	0	0
2021	Sep	198	1	2
2021	Oct	355	53	13
2021	Nov	562	63	22
2021	Dec	78	4	4

Table 3.

Samples tested for DENV and lab results from january, 2021 to December, 2021.

Untypable strain from Sare Yoba (Kolda region) was successfully sequenced using the proposed workflow (Figure 2).

Figure 2.

Used workflow to identify and sequence sylvatic DENV-2 strain in Saré Yoba area (Kolda, region).

Indeed, designed primers allow us to retrieve the nearly complete genome of the previously untypable DENV strain. Blast analysis shows that the strain is closely related to the sequences with accession number JF260983. The strain obtained during this work shares 99.66% identity nucleotide identity with the sequence JF260983. Genotyping of the sequences using the dengue typing tool shows the isolate cluster on the sylvatic DENV-2 group. This was confirmed by performing a phylogenetic analysis (Figure 3).

Figure 3.

Drawn maximum likelihood (ML) phylogenetic tree based on the nearly complete genome of DENV-2 sylvatic strain obtained during this study. The heatmap shows sequences genotype. The sequences obtained during this study are colored in red. The sylvatic genotype sequences are highlighted in light pink.

4. Discussion

This chapter presents findings from molecular surveillance of DENV conducted in Senegal in 2021 using the 4S network system, which allowed for the detection of the first cases of DENV during multiple outbreaks [14, 19]. From January to December 2021, 123 confirmed dengue cases were obtained out of the 2010 collected samples (Figure 4 and Table 3).

Figure 4.

Number of cases per months. The horizontal bar plot shows the number of people that were tested every month from January 2021 to December 2021. The red and blue bars represent positive and negative cases, respectively.

The molecular surveillance of identified strains provided insights into the distribution of DENV serotypes/genotypes in Senegal [16]. We encountered a patient with an unusual dengue case in November 2021, and despite obtaining a high Ct value of 26.04 using the panDENV assay, we were unable to determine the virus serotype. Using the designed workflow (as shown in the figure), we were able to detect the presence of contemporary sylvatic DENV-2 strain circulating in Sare Yoba, located in the Kolda region. This paper presents the latest report on sylvatic DENV virus in Africa, and the first detection of circulating sylvatic DENV-2 in Senegal since 2000 [27]. The Kolda region, where the contemporary sylvatic DENV-2 strain was identified, shares a border with the Niokolo-Koba National Park, a habitat of monkey species, such as Papio papio and Erythrocebus patas, which serve as reservoirs for sylvatic DENV [17, 28]. Moreover, experimental studies using surrogate human models and cultured cells have indicated that the emergence of sylvatic DENV in human populations may not have a significant adaptive barrier, possibly due to the virus’s opportunistic nature and ability to infect a diverse range of primate species [17].

In the context of utilizing genomic epidemiology to inform health policies, we have developed a user-friendly workflow for obtaining almost complete genome sequences using nanopore sequencing in less than 24 hours. Our generated Maximum Likelihood (ML) tree (Figure 3.) indicates that our strain, based on its near-full genome sequence, belongs to the West African DENV-2 sylvatic genotype and is closely related to a strain associated with hemorrhagic DENV found in a tourist who traveled to Guinea-Bissau via Senegal in 2009 [29]. This finding suggests that our strain is not related to the DENV-2 cosmopolitan genotype, which caused the most recent DENV-2 epidemic in Senegal [16, 25] highlighting a reemergence of sylvatic DENV-2 in southern Senegal.

The lower number of samples collected from the Kolda region in the 4S network suggests a potential underestimation of the DENV burden in this area. This suspicion was corroborated by the discovery of IgM-positive cases during a seroprevalence study in Senegal in 2021 (Unpublished data). Given the high suspicion of dengue circulation in the southern region, a “One health” approach is urgently needed, encompassing human, nonhuman primates, and vectors. This approach can enhance dengue fever surveillance via existing human malaria-like illness surveillance within the 4S network. Real-time genomic surveillance of DENV could be instrumental in discriminating between sylvatic and epidemic strains and improving virus surveillance across the country, with complex transmission dynamics involving both urban and sylvatic DENV cycles. Developing portable mobile platforms for epidemic virus surveillance in resource-poor regions is crucial, and lessons learned from previous epidemics, such as the Ebola outbreak and the SARS-CoV-2 pandemic, will enable better management of future epidemics and improved genomic surveillance of pathogens with epidemic potential.

Acknowledgments

We would like to thank the all workers at the WHO collaborating center for arboviruses and hemorrhagic fever viruses.

Conflict of interest

No conflict of interest for any of the authors was declared.

Funding statement

This work was supported by the Foundation Institut Pasteur de Dakar and the Talent awards earned by Dr. Oumar Faye.