Introduction
55
Aedes aegypti (Diptera: Culicidae) is a primary mosquito vector responsible for the 56
transmission of several medically important arboviruses, including dengue virus (DENV), Zika 57
virus (ZIKV), chikungunya virus (CHIKV), and yellow fever virus (YFV) (Omuoyo et al., 58
2023). These vector -borne pathogens represent significant public health challenges globally 59
and in Kenya, where repeated outbreaks of dengue fever and other Aedes-transmitted diseases 60
have been documented along the coastal and wester n regions (Courtney & Cranston, 2015) . 61
The ecology of Ae. aegypti is shaped by its adaptability to urban and peridomestic 62
environments, high anthropophily, and ability to exploit diverse breeding habitats, making it a 63
persistent and efficient arbovirus vector (Bhatt et al., 2013). 64
In addition to their role in transmitting vertebrate-infecting arboviruses, Ae. aegypti mosquitoes 65
harbor a diverse assemblage of insect-specific viruses (ISVs), which are viruses that replicate 66
exclusively in insects and are unable to infect vertebrate hosts (Carvalho & Long, 2021; Oguzie 67
et al., 2022; Patterson et al., 2020) . ISVs have been identified in multiple viral families, 68
including Flaviviridae, Togaviridae, and others, reflecting extensive diversity within mosquito 69
viromes (Amoa-Bosompem et al., 2020). The first ISV ever described was the cell fusing agent 70
virus (CFAV), isolated from an Ae. aegypti cell culture, which does not replicate in vertebrate 71
cells and is widely regarded as the prototype insect-specific virus (Bolling et al., 2015; Martin 72
et al., 2019) . Since then, advances in high -throughput sequencing and metagenomics have 73
greatly expanded the catalogue of ISVs associated with mosquitoes (Langat, 2023) . 74
Emerging evidence suggests that ISVs may influence mosquito biology and vector competence 75
in complex ways. Some ISVs have been shown to modulate arbovirus replication, potentially 76
through mechanisms such as superinfection exclusion or interactions with the mosquito 77
immune system (Nasar et al., 2012; Vasilakis et al., 2013; Vasilakis & Tesh, 2015) . Although 78
the precise effects of many ISVs on arbovirus transmission are not fully resolved, experimental 79
studies indicate that ISVs can either suppress or alter the replication dynamics of co -infecting 80
arboviruses in mosquito hosts, with implications for d isease transmission (Fish et al., 2017; 81
Parry et al., 2021). These interactions highlight the importance of considering the broader viral 82
ecology within mosquito populations when evaluating vector competence and arbovirus 83
transmission risk. 84
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Insect-specific viruses have increasingly attracted attention for their potential use in the 85
development of novel vaccines. Because ISVs replicate exclusively in insect cells and are non-86
pathogenic to vertebrates, they provide a safe platform for the production of viral antigens and 87
virus-like particles (VLPs) for immunization purposes (Erasmus et al., 2018; Hall-Mendelin et 88
al., 2016; Hall et al., 2025) . Recombinant ISVs expressing arboviral structural proteins have 89
been shown to elicit protective immune responses in animal models without the risk of causing 90
disease in humans (Nasar et al., 2015; Tan et al., 2023) . Such approaches could serve as 91
scalable and safe alternatives to conventional live -attenuated or inactivated vaccines, 92
particularly for arboviruses such as dengue, Zika, and chikungunya that remain significant 93
public health threats in endemic regions including Kenya. 94
95
In addition to their ecological roles, ISVs have significant potential in the development of 96
ELISA-based diagnostic tools for arbovirus surveillance (Erasmus et al., 2015) . Because 97
ISV-based chimeric constructs can express structural antigens of vertebrate -infecting viruses 98
while remaining replication-restricted in vertebrate cells, they provide a safe alternative antigen 99
source for use in immunoassays. For example, chimeras based on the insect -restricted Eilat 100
virus have been successfully used as high -quality antigen in IgM ELISA formats for 101
chikungunya virus, demonstrating sensitivity and specificity comparable to traditional assays 102
while allowing handling at lower biosafety levels and reducing reliance on live pathogenic 103
virus preparations (Erasmus et al., 2015). This approach enhances the feasibility of developing 104
ELISA diagnostics that can be deployed in resource-limited settings, improve assay safety, and 105
reduce costs associated with antigen production. ISV -based antigens may thus strengthen 106
serological surveillance frameworks for arboviruses by providing robust, safe, and scalable 107
tools for early detection and outbreak monitoring 108
Despite growing interest in the ecological and evolutionary roles of ISVs, genomic data and 109
detailed characterization of these viruses from Ae. aegypti populations in East Africa remain 110
limited. Metagenomic studies in Kenya have identified a variety of ISVs, including 111
flavivirus-like agents and iflaviruses, underscoring the presence of diverse viral taxa 112
co-circulating with pathogenic arboviruses in local mosquito populations (Chiuya et al., 2021; 113
Langat et al., 2021; Omuoyo et al., 2023) . However, comprehensive genomic analyses and 114
phylogenetic studies of Kenyan ISVs are still scarce, leaving gaps in our understanding of their 115
diversity, evolutionary relationships, and potential functional interactions with arboviruses. By 116
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documenting the genomic diversity and evolutionary relationships of ISVs, studies such as ours 117
not only enrich baseline virome resources but also offer avenues for exploiting ISVs in public 118
health interventions. These findings have implications for arboviral risk assessment, vector 119
surveillance programs, and the design of innovative vector control and disease mitigation 120
strategies. In regions like coastal Kenya, where Ae. aegypti -driven arboviral outbreaks are 121
recurrent, understanding the interplay between ISVs and pathogenic arboviruses could 122
ultimately contribute to reducing disease burden and improving outbreak preparedness. 123
124
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Methodology 125
Ethical Approval 126
Ethical approval was obtained from the Kenya Medical Research Institute (KEMRI) Scientific 127
and Ethics Review Unit (SERU) under protocol number KEMRI/SERU/C VR/4702 and 128
WRAIR# 3101. Permission to conduct the study was granted by the National Council for 129
Science, Technology, and Innovation (NACOSTI). 130
Study area 131
The study was conducted in Kwale County, (4.1730°S, 39.4520°E) which lies along the coastal 132
region with a tropical climate, high temperatures (26 –32°C), and seasonal rainfall that create 133
favorable conditions for Aedes aegypti proliferation. 134
135
Figure 1. Map of the Kenyan coast showing mosquito sampling sites in Kwale County. Base 136
maps, boundaries and shape files of Kenyan map and administrative boundaries of the Counties 137
were derived from GADM data version 4.1 ( https://gadm.org) and the maps were generated 138
using ArcGIS Version 10.2.2 ( http://desktop.arcgis.com/en/arcmap) advanced license) 139
courtesy of Samuel Owaka. 140
Entomological Investigation 141
Sampling of adult mos quitoes was conducted between 12 th March and 21 st June 2022 . 142
Mosquitoes were collected using CDC miniature light traps (Model 512, John Hock Co., 143
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Gainesville, Florida, USA). Traps baited with carbonated dry ice (CO2) were deployed 144
overnight (6pm-6am) in favourable habitat, including dwelling quarters and animal sheds. The 145
samples were linked to the sites by geo-coding using a GPS. The mosquitoes were immobilized 146
by freezing at -20ºC for 20mins and identified morphologically to species under a dissecting 147
microscope using taxonomy keys, including Edwards (1941) (Road & Quaritch, 1936) , 148
Harbach (1988)(Harbach, 1988) and Jupp (1986) (Jupp, 1986). The identified mosquitoes were 149
pooled in groups of 1 to 20 samples based on species, sex and collection site. Mosquitoes were 150
consequently preserved in liquid nitrogen, and transported to the laboratory at the Kenya 151
Medical Research Institute in Kisumu, where they were stored at-80˚C until further processing. 152
153
Mosquito sample preparation 154
A total of 580 mosquitoes collected from Kwale County were pooled into 29 pools, with each 155
pool comprising 20 individual mosquitoes . The pools were homogenized using a Mini-156
Beadruptor-16 (BioSpec Products, Bartlesville, OK, USA) in 1,000 µL of homogenization 157
medium, consisting of minimum essential medium supplemented with 15% fetal bovine serum 158
(FBS) (Gibco, Life Technologies, Grand Island, NY, USA), 2% L-glutamine (Sigma-Aldrich), 159
and 2% antibiotic–antimycotic solution (Gibco, Life Technologies), together with zirconium 160
beads (2.0 mm diameter) for 40s. Homogenates were subsequently centrifuged at 10,000 rpm 161
for 10 min at 4°C using a benchtop centrifuge (Eppendorf, USA). An aliquot of 50 µL of 162
supernatant from each pool was combined to generate a single superpool for downstream 163
metagenomic analysis. 164
165
Library preparation and next generation sequencing 166
From the generated superpool, an aliquot of 140 µL of the supernatant was used for viral RNA 167
extraction with the QIAamp Viral RNA Mini Kit (Qiagen, Hilden, Germany) and eluted in a 168
single step with 60 µL of elution buffer, according to the manufacturer’s instructions. Paired -169
end sequencing libraries were prepared using the Illumina RNA Prep with Enrichment (L) 170
Tagmentation (Illumina, USA) following the manufacturer’s recommended protocol. The final 171
libraries were denatured with NaOH, diluted to a final concentration of 12 pM, and loaded onto 172
an Illumina MiSeq platform. Sequencing was performed using the MiSeq Reagent Kit v3 173
(Illumina, USA) to generate 300-bp paired-end reads. 174
175
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Sequence analysis and virus identification 176
Initial analysis was performed using the CZ -ID platform, an integrated pipeline that offers 177
quality control, de-hosting, duplicate removal, assembly, and viral identification capabilities. 178
After this initial processing, the de -hosted sequence reads were retrieved for further analysis. 179
To validate CZ-ID pipeline results, PrinseqLite v0.20.4 tool was used to filter low-quality reads 180
and remove adapters on command line. De novo sequence assembly was conducted using 181
MEGAHIT v1.2.9 (Li et al., 2015) where West Nile virus contigs were recovered and 182
compared to CZ -ID pipeline results. Only contigs with an average depth of coverage of ≥10 183
and a length of ≥500 bp were retained for further analysis. These contigs were first compared 184
against a local version of NCBI viral database using Diamond v2.0.4. To ensure specificity, 185
putative viral contigs were further compared to the entire non-redundant protein database (nr), 186
to exclude any non -viral contigs. A stringent e -value threshold of 1e -5 was employed 187
throughout the homology searches to minimize false-positive hits. 188
Phylogenetic analysis of the identified RNA viruses 189
To describe the identified viruses in an evolutionary context, publicly available viruses 190
belonging to these different groups, and more specifically those closely related to the viral 191
strains obtained in the current study were downloaded and used as reference sequences in the 192
reconstruction of phylogenetic trees. Closely related gene sequences were retrieved from NCBI 193
viral database and used as reference sequences in reconstructing the phylogenetic relationship 194
of the viral sequences. The combined set of sequences were aligned using MUSCLE software 195
with default parameters (max iterations = 16) embedded in Molecular Evolutionary Genetics 196
Analysis v.7.0 (MEGA7) (Kumar et al., 2016) platform. The aligned sequences were edited 197
using the Bioedit tool and maximum likelihood phylogenetic analysis carried out using IQ -198
TREE v1.6.12. The best model ( GTR+G4 (General Time Reversible + Gamma)) and tree 199
search was performed simultaneously based on 1000 bootstrap estimates and approximate 200
likelihood ratio test (aLRT). Genome maps were generated and visualized using Python v3.9. 201
202
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Results
203
Mosquito Collection and Sequencing Output 204
Adult Aedes aegypti mosquitoes collected from Kwale County, coastal Kenya, were processed 205
for metagenomic analysis. Sequencing on the Illumina MiSeq platform generated 233,658 206
paired-end reads. After quality filtering, host read subtraction, and duplicate removal, 172,556 207
high-quality reads were retained for downstream virome analyse s. Insect-specific viruses 208
(ISVs) were detected exclusively in the Kwale County superpool. Superpools from Kilifi 209
(Malindi) and Mombasa were also processed and sequenced, however, no sequencing reads 210
were recovered, and consequently no insect-specific viruses or human-pathogenic arboviruses 211
were detected. 212
Metagenomic analysis 213
Metagenomic analysis revealed a diverse assemblage of insect -specific viruses (ISVs) 214
associated with Ae. aegypti mosquitoes from the study area. Viral contigs were assigned to 215
multiple taxonomic groups, representing both segmented and non-segmented RNA viruses. In 216
total, five ISVs were identified, including Fako virus (FAKV), Tesano Aedes virus (TEAV), 217
Aedes partiti -like virus (AePLV), Cell fusing agent virus (CFAV), and Formosus virus 218
(FORV). Complete genome sequences were recovered for Fako virus and Tesano Aedes virus, 219
while partial genome sequences were obtained for Aedes partiti -like virus, Cell fusing agent 220
virus, and Formosus virus. Genomic features of the detected viruses, including genome length, 221
GC content, closest reference sequences, and nucleotide identity, are summarized in Table 1. 222
Table 1: Viruses identified in this study based on metagenomic analysis. The identification 223
was carried out using a homology search against reference databases, providing insights into 224
the closest known virus. 225
226
227
228
229
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Strain Length
GC
Conten
t % Closest hit Genbank ID
%
identity
KWL_2022_AePLV 1,383
48.95 Aedes partiti-like virus-
RdRp PV730257.1 99.49
1,349
48.04 Aedes partiti-like virus-
Capsid OQ305266.1 99.26
KWL_2022_FORV 10,146 44.41 Formosus virus PV730233.1 99.47
KWL_2022_CFAV 2290 50.10 Cell fusing agent virus OQ305237.1 95.83
KWL_2022_TEAV 9,640 39.02 Tesano Aedes Virus PV658504.1 91.31
KWL_2022_FAKV 3,802 31.80 Fako virus -Segment 1 OR270150.1 98.73
3,735 32.88 Fako virus -Segment 2 OR270151.1 99.06
3,849 33.78 Fako virus -Segment 3 OR270152.1 99.19
3,385 31.23 Fako virus -Segment 4 OR270153.1 98.76
3,189 32.52 Fako virus -Segment 5 OR270154.1 97.70
1,747 34.29 Fako virus -Segment 6 OR270155.1 98.50%
1,149 36.81 Fako virus -Segment 7 OR270156.1 99.09%
1,131 37.05 Fako virus -Segment 8 OR270157.1 97.87%
1,274 32.34 Fako virus -Segment 9 OR270158.1 98.06%
230
231
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Phylogenetic analysis 232
Phylogenetic analyses based on the RNA -dependent RNA polymerase (RdRp) coding region 233
were conducted to determine the evolutionary relationships of the detected ISVs. Maximum 234
likelihood trees revealed that all identified viruses clustered within well -defined ISV clades, 235
consistent with their taxonomic classifications. Aedes partiti-like virus was detected as two 236
genomic segments corresponding to the RNA-dependent RNA polymerase (RdRp) and capsid 237
regions. Both segments exhibited high nucleotide identity (>99%) to known AePLV reference 238
sequences. 239
240
Figure 2. Maximum Likelihood phylogenetic tree of Aedes partiti-like virus (AePLV) inferred 241
from nucleotide sequences, with branch support assessed using 1,000 bootstrap replicates. 242
243
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Genome organization of AePLV 244
The assembled genome of AePLV was determined to be bi -segmented, with lengths of 1,383 245
bp and 1,349 bp. Segment 1 encodes the RNA -dependent RNA polymerase (RdRp), whereas 246
Segment 2 encodes the capsid and envelope -like proteins characteristic of insect -specific 247
viruses. The genome maps reveal a linear organization for both segments, with conserved open 248
reading frames (ORFs) and predicted untranslated regions (UTRs) at the 5’ and 3’ termini. 249
250
Figure 3. Genome map of AePLV showing two segments of varying lengths, each encoding a 251
separate open reading frame. 252
253
254
255
256
257
258
259
260
261
262
263
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Phylogenetic analysis of Formosus virus (FORV) showed that the recovered genome was 264
10,146 nucleotides in length with a GC content of 44.41%. The sequence exhibited high 265
nucleotide similarity (99.47%) to the closest reference strain (PV730233.1) and clustered with 266
a Nigerian strain, supported by a bootstrap value of 100. 267
268
Figure 4. Maximum Likelihood phylogenetic tree of Formosus virus (FORV) inferred from 269
nucleotide sequences, with branch support assessed using 1,000 bootstrap replicates. 270
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The assembled genome of FORV consists of a single, continuous RNA segment of 10,146 bp. 271
The genome encodes a complete RNA -dependent RNA polymerase (RdRp) and several 272
structural proteins, including the capsid and putative envelope -associated proteins typical of 273
insect-specific viruses. Analysis of the genome map revealed a linear organization with clearly 274
defined open reading frames (ORFs) and untranslated regions (UTRs) at both the 5’ and 3’ 275
ends. 276
277
Figure 5. Genome map of Formosus virus (FORV) showing a single open reading frame in a 278
genome of 10,146 nucleotides. 279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
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Phylogenetic analysis revealed that the Tesano Aedes virus genome clustered with a Kisumu -296
derived strain with a bootstrap value of 99. The genome showed nucleotide identity to the 297
closest available reference i ndicating notable genetic divergence from previously reported 298
strains. 299
300
Figure 6 . Maximum Likelihood phylogenetic tree of Tesano Aedes virus inferred from 301
nucleotide sequences, with branch support assessed using 1,000 bootstrap replicates. 302
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The Tesano Aedes virus genome recovered in this study was 9,640 nucleotides in length and 303
contained a single open reading frame (ORF), characteristic of Iflaviruses, encoding a 304
polyprotein that is post-translationally processed into structural and non-structural proteins. 305
306
307
Figure 7. Genome map of Tesano Aedes virus (TEAV) depicting a single open reading frame 308
in a genome of 9,640 nucleotides, characteristic of Iflaviruses. 309
310
311
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Phylogenetic analysis of Fako virus revealed that the recovered genome clustered with a 312
previously reported Kenyan strain, indicating close genetic relatedness. The branching was 313
well supported in the phylogenetic tree, consistent with the virus circulating locally. 314
315
Figure 8. Maximum Likelihood phylogenetic tree of Fako virus (FAKV) inferred from RNA-316
dependent RNA polymerase (RdRp) gene sequences, with branch support assessed using 1,000 317
bootstrap replicates. 318
319
320
321
322
323
324
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The Fako virus genome recovered in this study is segmented, comprising nine distinct segments 325
of varying lengths. Each segment encodes a separate open reading frame, with the RNA -326
dependent RNA polymerase (RdRp) segment used for phylogenetic analysis. This segmented 327
genome organization is consistent with previously described Fako virus strains and other 328
related segmented viruses. 329
330
331
332
333
334
335
Figure 9. Genome map of Fako virus (FAKV) showing nine segments of varying lengths, with 336
each segment encoding a separate open reading frame. 337
338
339
340
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Phylogenetic analysis of Cell Fusing Agent Virus (CFAV) revealed that the recovered genome 341
clustered with CFAV strains previously reported from Africa, indicating close genetic 342
relatedness across the continent. The branching in the phylogenetic tree was strongly 343
supported, reflecting the conserved nature of this insect-specific flavivirus. 344
345
Figure 10. Maximum likelihood phylogenetic tree of Cell Fusing Agent Virus (CFAV). 346
Bootstrap values were calculated from 1000 replicates. 347
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