Arbovirus and insect-specific virus discovery in Kenya bynovel six genera multiplex high-resolution melting analysis

JANDOUWE VILLINGER,* MARTIN K. MBAYA,*† DANIEL OUSO,*† PURITY N. KIPANGA,*‡

JOEL LUTOMIAH§ and DANIEL K. MASIGA*

*International Centre of Insect Physiology and Ecology (icipe), P.O. Box 30772, Nairobi 00100, Kenya, †Jomo Kenyatta University

of Agriculture and Technology, P.O. Box 62000, Nairobi, Kenya, ‡Zoological Institute, Katholieke Universiteit, Naamsestraat 59,

P.O. Box 3000, Leuven, Belgium, §Kenya Medical Research Institute (KEMRI), Nairobi, Kenya

Abstract

A broad diversity of arthropod-borne viruses (arboviruses) of global health concern are endemic to East Africa, yet

most surveillance efforts are limited to just a few key viral pathogens. Additionally, estimates of arbovirus diversity

in the tropics are likely to be underestimated as their discovery has lagged significantly over past decades due to lim-

itations in fast and sensitive arbovirus identification methods. Here, we developed a nearly pan-arbovirus detection

assay that uses high-resolution melting (HRM) analysis of RT–PCR products from highly multiplexed assays to dif-

ferentiate broad diversities of arboviruses. We differentiated 15 viral culture controls and seven additional synthetic

viral DNA sequence controls, within Flavivirus, Alphavirus, Nairovirus, Phlebovirus, Orthobunyavirus and Thogo-

tovirus genera. Among Bunyamwera, sindbis, dengue and Thogoto virus serial dilutions, detection by multiplex RT–

PCR-HRM was comparable to the gold standard Vero cell plaque assays. We applied our low-cost method for

enhanced broad-range pathogen surveillance from mosquito samples collected in Kenya and identified diverse

insect-specific viruses, including a new clade in anopheline mosquitoes, and Wesselsbron virus, an arbovirus that

can cause viral haemorrhagic fever in humans and has not previously been isolated in Kenya, in Culex spp. and

Anopheles coustani mosquitoes. Our findings demonstrate how multiplex RT–PCR-HRM can identify novel viral

diversities and potential disease threats that may not be included in pathogen detection panels of routine surveil-

lance efforts. This approach can be adapted to other pathogens to enhance disease surveillance and pathogen discov-

ery efforts, as well as the study of pathogen diversity and viral evolutionary ecology.

Keywords: arboviruses, emerging communicable diseases, high-resolution melting analysis, insect-specific flaviviruses,

multiplex polymerase chain reaction, pathogen discovery

Received 1 January 2015; revision received 2 July 2016; accepted 5 July 2016

Introduction

Arthropod-borne viruses (arboviruses) represent a broad

category of emerging and re-emerging infectious dis-

eases that threaten global public health (Weaver & Rei-

sen 2010). Among the over 545 known RNA arbovirus

species, over 150 are of potential public health concern

and are endemic in sub-Saharan Africa (SSA) (Cleton

et al. 2012). Due to limited diagnostic capacity in most

rural health facilities in SSA, where arboviral infections

are likely to occur, most are either diagnosed as undiffer-

entiated febrile illness or misdiagnosed as malaria or

bacterial infections (Crump et al. 2013; Kipanga et al.

2014), confounding estimates of arboviral infection inci-

dence rates and disease burden (Hotez & Kamath 2009).

Moreover, many arboviruses that contribute to human

and livestock disease may still be unknown (Junglen &

Drosten 2013; Rosenberg et al. 2013).

In recent decades, climatic change, tropical urbaniza-

tion and increased global trade have facilitated dramatic

geographical expansions of arboviruses, including

chikungunya, dengue and West Nile viruses, across con-

tinents (Weaver & Reisen 2010). Meta-analysis of viral

discovery rates suggests that arbovirus discovery has

lagged over the past four decades due to limitations in

search strategies (Rosenberg et al. 2013). Indeed, recent

discoveries of novel arboviruses within the families

Togaviridae, Flaviviridae and Bunyaviridae suggest that

only a fraction of extant arboviruses have been identified

(Junglen & Drosten 2013). While hypothesis-free deep

sequencing on arthropod field samples has been pro-

posed as a feasible approach for virus discovery (Bishop-Correspondence: Jandouwe Villinger, Fax: +254-20-863-2001/2;

E-mail: jandouwe@icipe.org

© 2016 John Wiley & Sons Ltd

Molecular Ecology Resources (2016) doi: 10.1111/1755-0998.12584

Lilly et al. 2010; Masembe et al. 2012; Junglen & Drosten

2013; Hang et al. 2016), it remains costly, especially as this

blind approach will only identify viruses in the fraction

of sequenced samples that are actually infected. Hence,

there is need for rapid arbovirus screening approaches

that can facilitate virus identification and discovery from

large numbers of field samples, at least in the most com-

mon arbovirus families of Togaviridae, Flaviviridae and

Bunyaviridae (Rosenberg et al. 2013). This will greatly

enhance understanding of arboviral disease threats,

resulting in improved healthcare delivery and appropri-

ate use of the limited supply of antimalarial and antibi-

otic drugs in endemic areas (Kipanga et al. 2014).

Identification of arboviruses that contribute to disease

in humans and livestock relies heavily on serological

techniques (including IgM/IgG ELISAs and plaque

reduction neutralization assays). However, these diag-

nostic approaches are limited to screening for just a few

select viral pathogens and by potential cross-reactivity

with antibodies to other closely related viruses (Papa

et al. 2011; Hall et al. 2012). Virus detection by growth in

cell culture plaque assays, while costly and time-con-

suming, is considered a gold standard for arbovirus

detection (Kauffman et al. 2003) and is amenable to a ser-

ies of downstream molecular diagnostics for virus identi-

fications (Ochieng et al. 2013).

Molecular approaches to identifying RNA arbovirus

infections, based largely on reverse transcription poly-

merase chain reaction (RT–PCR) amplification of specific

viral gene targets, are more efficient and specific than

serological approaches (Hall et al. 2012), and faster than

detection by growth in cell culture (Kauffman et al.

2003). However, available PCR-based approaches rely on

multiple reactions that are limited to screening for a few

likely arboviral pathogens and require PCR product

sequencing confirmation (Junglen & Drosten 2013).

Moreover, RT–PCR-based arbovirus identification is

most commonly performed on sample cultures that gen-

erate cytopathic effects (CPE), as these provide sufficient

template to screen with multiple tests (Lwande et al.

2013; Ochieng et al. 2013; Rosenberg et al. 2013).

Nonetheless, high-throughput multiplex approaches,

such as MassTag PCR (Briese et al. 2005), TaqMan Arrays

(Chao et al. 2007; Liu et al. 2016) and triplex RT–PCRenzyme hybridization assay (Dong et al. 2013), have been

used to screen for sets of specific arboviruses. Specific

virus sequences can be differentiated among genus-

specific PCR amplicons by electrospray ionization mass

spectrometry (Eshoo et al. 2007) and by their high-resolu-

tion melting (HRM) profiles (Naze et al. 2009; Omondi

et al. 2015). Lambert & Lanciotti (2009) employed triplex

PCR for sequencing-based identification of diverse arbo-

viruses in the family Bunyaviridae (Orthobunyavirus, Phle-

bovirus, Nairovirus). Multiplex PCR-HRM analysis has

been performed using universal primers to differentiate

bacterial pathogens (Yang et al. 2009; Xue et al. 2012;

Athamanolap et al. 2014) and malarial parasites (Kipanga

et al. 2014), as well as with low-level multiplex PCR

products to detect and differentiate dengue viruses

(Waggoner et al. 2013). With the exception of the dengue

typing assay of Waggoner and colleagues (Waggoner

et al. 2013), reliable HRM methods have been limited to

applications in which template quality and quantity

could be controlled to generate consistent and compara-

ble profiles, using either cultured viruses (Yang et al.

2009) or synthesized templates (Naze et al. 2009).

We developed an economical high-throughput, nearly

pan-arbovirus detection assay based on multiplex PCR

using seven pairs of degenerate primers that universally

amplify arboviruses within Flavivirus (family Flaviviri-

dae), Alphavirus (family Togaviridae), Nairovirus (family

Bunyaviridae), Phlebovirus (family Bunyaviridae), Orthobu-

nyavirus (family Bunyaviridae) and Thogotovirus (family

Orthomyxoviridae) genera. Specific virus PCR products

can then be identified from their HRM profiles, distin-

guishing a wide range of known and potentially novel

viruses. We validated the assay against growth in cell

culture plaque assays using Bunyamwera (Bunyaviridae:

Orthobunyavirus), sindbis (Togaviridae: Alphavirus), den-

gue (Flaviviridae: Flavivirus) and Thogoto (Orthomyxoviri-

dae: Thogotovirus) virus stocks and used the assay to

discover novel viruses in mosquito samples.

Materials and methods

RNA extraction and reverse transcription usingnonribosomal hexamers

To ensure optimal sensitivity in molecular arbovirus

detection assays while maintaining a rapid high-through-

put workflow, we extracted viral RNA from blood,

serum, mosquito homogenates and cell cultures using

the MagNA 96 Pure DNA and Viral NA Small Volume

Kit (Roche Applied Science, Penzberg, Germany) in a

MagNA Pure 96 (Roche Applied Science) automated

extractor. Blood, serum and viral cultures can be used

directly in the extraction process. However, for arthro-

pod samples we used a Mini Bead Beater 16 (BioSpec,

Bartlesville, OK) to homogenize pools of 1–25 individualsin 1.5-mL tubes filled with 750 mg of 2.0-mm yttria-stabi-

lized zirconium oxide beads (zirconia/yttria), 150 mg of

0.1-mm zirconia/yttria beads (Glen Mills, Clifton, New

Jersey) and 450 lL of phosphate-buffered saline (PBS)

(Crowder et al. 2010). Immediately after extraction, 5 lLof the viral RNA extracts was used as templates in 10 lLHigh Capacity Reverse Transcriptase (Life Technologies,

Carlsbad, California) reverse transcription (RT) reactions

using nonribosomal hexamers (0.6 mM) selected to

© 2016 John Wiley & Sons Ltd

2 J . V ILLINGER ET AL .

favour the reverse transcription of viral genomes over

eukaryotic genomes (Endoh et al. 2005).

Multiplex PCR primer design

All sequence analyses were performed using Geneious

v8.1.4 (available from http://www.geneious.com), soft-

ware created by Biomatters (Kearse et al. 2012). We

designed seven sets of degenerate primers (Table 1) that

could be combined to universally amplify flaviviruses,

alphaviruses, thogotoviruses, nairoviruses, phleboviru-

ses and Bunyamwera group orthobunyaviruses in a sin-

gle multiplexed PCR. Based on multiple alignments of

arbovirus genomes within genera (Table 2), we modified

existing primers for universal Phlebovirus, Orthobun-

yavirus (Lambert & Lanciotti 2009) and Alphavirus (Eshoo

et al. 2007) amplifications, and designed new primers for

universal Nairovirus, Flavivirus and Thogotovirus amplifi-

cations (Table 1). Primers were designed manually, tar-

geting 100–400 nucleotide (nt) polymorphic regions

flanked by relatively conserved regions in which univer-

sal primers could be designed (Table 1). We allowed for

up to 36-fold primer degeneracy and for A-C and G-T

mismatches to target sequences (except within the five

most 30 bases), maintained annealing temperature differ-

ences and calculated according to Rychlik et al. (1990),

within 1 °C between primer pairs and within 4 °C across

the multiplex panel of primers. To minimize overall

degeneracy for the Nairovirus and Flavivirus primers, we

mixed cocktails of primers with different degeneracies

for each of the forward and reverse primers (Table 1).

We analysed potential primer sequences using the Oligo-

Calc online oligonucleotide properties calculator (Kibbe

2007) and avoided primers with 30 self-dimerization and

hairpin formations. We further evaluated and minimized

primer–primer interactions based on in silico reactions

performed using Amplify 3X software for Macintosh.

Multiplex PCR

The multiplex PCR touchdown reaction conditions

(Table 3) were performed in a Rotor-Gene Q HRM cap-

able thermocycler (Qiagen, Redwood City, California) in

10 lL reactions containing 1ul cDNA template, 5 lLMyTaq HS master mix (Bioline, London, UK), 1 lL of

50 lM SYTO-9 saturating intercalating dye (Life Tech-

nologies), 2 lL of nuclease-free water and 1 lL of multi-

plex primer mix. The empirically optimized reaction

concentrations of all individual primers within the multi-

plex reaction are indicated in Table 1. The use of SYTO-9

saturating intercalating dye (Life Technologies) was criti-

cal in the optimization of this highly multiplexed RT–PCR-HRM assay, as it has almost no PCR-inhibitory

characteristics, unlike the more commonly used

intercalating dyes such as SYBR Green or EvaGreen

(Gudnasen et al. 2007).

High-resolution melting (HRM) analysis

Immediately following PCR amplification, amplicons

were subjected to HRM analysis by first denaturing at

95 °C for 1 min, annealing at 40 °C for one minute and

equilibrating at 75 °C for 90 s, and then increasing the

temperature in 0.1 °C increments up to 90 °C, with fluo-

rescence acquisition after 2-s incremental holding peri-

ods. After completion of HRM data acquisition, we first

visually inspected the melting curves of all amplicons

and then generated normalized HRM profiles between

75 and 88 °C.To validate the assay, we used established viral cul-

tures (Table 4) and spiked them into mosquito homoge-

nates and livestock serum and blood. We included

cultures of multiple representatives of flaviviruses (West

Nile, dengue, yellow fever and Usutu viruses), alpha-

viruses (sindbis, Middelburg, Ndumu, chikungunya and

Semliki Forest viruses), thogotoviruses (Thogoto and

Dhori viruses) and nairoviruses (Dugbe and Hazara

viruses). However, we only had single representatives of

phleboviruses (Rift Valley fever virus) and orthobun-

yaviruses (Bunyamwera virus) cultures available to us.

Therefore, we tested additional synthetic DNA

sequences (GenScript, Piscataway, NJ, USA) (Table 5).

All multiplex PCR-HRM analyses of unknown samples

were conducted alongside positive and negative controls

(mosquito DNA and water as templates). We then

matched melting profiles to those generated by positive

controls. We used ScreenClust software (Qiagen) to con-

duct ‘unsupervised’ cluster analysis among known posi-

tives for viruses with melting profiles in similar ranges

to confirm clustering with specific viruses.

Multiplex RT–PCR-HRM assay validation against goldstandard plaque assays

To establish viral stocks of Bunyamwera, sindbis, Tho-

goto and dengue viruses (Table 4) for assay sensitivity

validation, clean Vero cell lines (from the kidney of green

African monkey: Chlorocebus sabaeus) were first propa-

gated and maintained in four T25 culture flasks. Once

80% confluent, the T25 flasks were each infected with

200 lL of respective virus cultures (approximate multi-

plicity of infection = 8), labelled and incubated at 37 °Cin 5% CO2 for 1 h, with gentle rocking at 15-min inter-

vals, to allow the viruses to adsorb to cell surfaces.

Before incubating at 37 °C with 5% CO2, 5 mL of 2%

maintenance media (2% foetal bovine serum (FBS), 2%

L-glutamine and 2% ready to use antibiotic/antifungal

solution of penicillin, streptomycin and amphotericin B

© 2016 John Wiley & Sons Ltd

PAN-ARBOVIRUS SURVEILLANCE AND DISCOVERY 3

Tab

le1

Multiplexprimer

table

withtarget

sequen

cealignmen

taccessionnumbers

Gen

us

Primer

nam

esPrimer

sequen

ceTarget

gen

e

Referen

ce

gen

ome

Primer

coord

inates

Optimal

Ta(°C)

Reaction

con-cen

trations(nM)

Phlebovirus

PhleboJV

3aF

50-A

GTTTGCTTATCAAGGGTTTGATGC-3

0NP(S

segmen

t)NC_014395

1549–1573

59.86

500

PhleboJV

3bF

50-G

AGTTTGCTTATCAAGGGTTTGACC-3

01550–1574

500

PhleboJV

3R

50-C

CGGCAAAGCTGGGGTGCAT-3

01201–1220

500

Nairovirus

Nairo

L1a

F50-TCTCAAAGATATCAATCCCCCCITTACCC-3

0RdRp(L

segmen

t)NC_005301

1–28

56.2

375

Nairo

L1b

F50-TCTCAAAGACATCAATCCCCCTTWTCCC-3

01–28

375

Nairo

L1a

R50-C

TATRCTGTGRTAGAAGCAGTTCCCATC-3

0187–214

150

Nairo

L1b

R50-G

CAATACTATGATAAAAACAATTMCCATCAC-3

0185–215

150

Nairo

L1c

R50-C

AATGCTGTGRTARAARCAGTTGCCATC-3

0187–214

150

Nairo

L1d

R50-G

CAATGCTATGGTAGAAACAGTTTCCATC-3

0187–215

150

Nairo

L1e

R50-C

RAKGCTGTGGTAAAAGCAGTTRCCATC-3

0187–214

150

Bunyam

weragroup

Orthobu

nyavirus

BunyagroupF

50-C

TGCTAACACCAGCAGTACTTTTGAC-3

0NP(S

segmen

t)NC_001927

114–139

58.92

167

BunyagroupR

50-TGGAGGGTAAGACCATCGTCAGGAACTG-3

0336–363

167

Alphavirus

Vir2052

F50-TGGCGCTATGATGAAATCTGGAATGTT-3

0nsP

4NC_001449

6971–6997

58.39

400

Vir2052

R50-TACGATGTTGTCGTCGCCGATGAA-3

07086–7109

400

Flavivirus

FlaviJV

2aF

50-A

GYMGHGCCATHTGGTWCATGTGG-3

0nsP

5NC_009942

9097–9120

58.63

200

FlaviJV

2bF

50-A

GCCGYGCCATHTGGTATATGTGG-3

09097–9120

125

FlaviJV

2cF

50-A

GYCGMGCAATHTGGTACATGTGG-3

09097–9120

125

FlaviJV

2dF

50-A

GTAGAGCTATATGGTACATGTGG-3

09097–9120

50

FlaviJV

2aR

50-G

TRTCCCADCCDGCDGTRTCATC-3

09283–9305

400

FlaviJV

2bR

50-G

TRTCCCAKCCWGCTGTGTCGTC-3

09283–9305

100

Thogotovirus

Thogoto

S6F

50-G

ATGACAGYCCTTCTGCAGTGGTGT-3

0M

(seg

men

t6)

NC_006504

486–510

60.28

300

Thogoto

S6R

50-RACTTTRTTGCTGACGTTCTTGAGGAC-3

0771–797

300

DhoriS5F

50-C

GAGGAAGAGCAAAGGAAAG-3

0NP(seg

men

t5)

M17435

1024–1042

56.51

800

DhoriS5R

50-G

TGCGCCCCTCTGGGGTTT-3

01107–1125

800

© 2016 John Wiley & Sons Ltd

4 J . V ILLINGER ET AL .

from Sigma-Aldrich) was added to the T25 flasks. The

flasks were screened daily for CPE. Once 75%–85% CPE

was observed, the flasks containing the infected cells

were frozen at �80 °C for a day to enable the cells to

detach completely from flask surfaces during thawing.

The contents of each flask were then transferred into

respective 15-mL centrifuge tubes and centrifuged at

1500 relative centrifugal force (rcf) for 10 min. We col-

lected and aliquoted, in 1 mL portions, the supernatant

into 2-mL cryovials and stored them at �80 °C for later

use. Ten-fold serial dilutions up to 10�11 of the viral cul-

ture stocks were prepared using 2% MEM media (Sigma-

Aldrich, St. Louis, USA). Each dilution was frozen in

600 lL aliquots such that subsequent assays were

performed on aliquots with only one freeze–thaw cycle.

Replicates of 200 lL of each dilution were extracted and

assayed using multiplex RT–PCR-HRM, and replicates

of 50 lL of each dilution were plated onto confluent Vero

cells in 24-well sterile cell culture plates. The number of

replicates varied between viruses, as indicated in

Table 6, due to differences in available viral stock that

we were able to grow. After 1 h of incubating the

infected cells at 37 °C, 1 mL of methyl cellulose overlay

medium was added to each well and incubated at 37 °C,5% CO2 for 3 days for sindbis virus, 4 days for Bun-

yamwera virus and 10 days for Thogoto and dengue

viruses. The difference in incubation times for these

viruses was based on the time required for us to obtain

Table 2 Arbovirus GenBank accession numbers used in multiple alignments for primer design

Genus Virus Alignment GenBank accessions

Phlebovirus (S segment) Rift Valley fever DQ380143-82, EU312103-47, EU574070-87, NC_014394

Punta Toro EF201834-5

Toscana EF201833, FJ153285-6

Nairovirus (L segment) Crimean–Congohemorrhagic fever

AY389508, AY675240, AY720893, AY947890, AY995166,

GQ337055, GU477492, NC_004159

Dugbe JF785543

Hazara DQ076419

Nairobi sheep disease EU697949-51

Kupe EU257628

Bunyamwera group

Orthobunyavirus (S segment)

Bunyamwera AF325122, AM711130, AM709778, NC_001926

Batai JX846604

Nyando AM709781

Ilesha AM709779-80, KC608151

Ngari AY593729

Shokwe EU564831

Germiston M19420

Alphavirus Chikungunya AB455493-4, EU703759-62, FJ000063-9, FJ445426-504,

GQ428210-5, GU013528-30, HM045784-823, NC_004162

Middelburg EF536323

Semliki Forest AY112987, DQ189079-86, JF972635, X04129, Y14761

Sindbis J02363, JQ771797-9, NC_001547

Babanki AF339477

Ockelbo M69205

Ndumu HM147989

O’nyong-nyong M20303, AF079456

Igbo Ora AF079457

Flavivirus West Nile NC_001563, NC_009942

Dengue (serogroups 1–4) NC_001477, NC_001474-5, NC_002640

Yellow fever AF052437-46, AY839631-3, AY968064-5, U17066-7, U21055-6, U54798

Usutu NC_006551

Zika AY632535, NC_012532

Potiskum AF013395, DQ859067

Saboya AF013400, AF295070, DQ859062, EU074010

Kunjin D00246

Kadam DQ235146

Spondweni DQ859064

Wesselsbron JX423791

Thogotovirus Thogoto AF527529-30, NC_0065403

Dhori GU969311, M17435

© 2016 John Wiley & Sons Ltd

PAN-ARBOVIRUS SURVEILLANCE AND DISCOVERY 5

75%–85% CPE while growing stocks from the parent cul-

ture. The different incubations periods for the different

viruses were based on the time frames required for

obtaining reproducible CPE during virus isolation. The

overlay was then carefully removed using Pasteur pip-

ettes before adding 500 lL of 10% formaldehyde to the

wells and placing the plates under ultraviolet light for

30 min to inactivate and fix the viruses. Finally, the

plates were placed under slow running tap water to

remove the formaldehyde and stained immediately with

0.5% methyl violet dye, then washed off and left over-

night to dry. We determined the plaque assay detection

limit of each virus by visually identifying the highest

dilution that yielded any visible plaques in replicate

(Table 6) cell culture wells.

Identification of naturally occurring arboviruses inmosquitoes

To determine whether the assay could be used to iden-

tify naturally occurring viral infections in mosquitoes,

we blindly screened 2000 mosquito pool homogenates

(1–25 individuals) collected using CDC light traps in

Kenya, which included homogenates without arbovirus

infections and homogenates with arboviral infections

verified by culture (six pools with sindbis virus, six pools

with Semliki Forest virus, seven pools with Bunyamwera

virus, two pools with Ndumu virus, one pool with West

Nile virus) (unpublished, personal communication,

Rosemary Sang). We also screened 2392 mosquito pools

collected in Kenya between 2009 and 2011 (Table 7) for

arboviruses by multiplex RT–PCR-HRM. Samples with

novel HRM profiles that could not be matched with any

controls were retested by singleplex PCR-HRM assays

with each of the genus-specific sets of primers. All of the

unique melting profiles were replicated only using the

Flavivirus primer mix. The singleplex PCR products were

sequenced for initial virus identification based on Gen-

Bank Blast hits (e-value <10�40). Flaviviruses were then

further characterized from Turbo DNase (Life Technolo-

gies)-treated RNA extracts, sequencing the full NS5

genes amplified according to V�azquez et al. (2012) at

Macrogen (Seoul, Korea).

To identify how our nucleotide and translated amino

acid sequences clustered among the known diversity of

mosquito flaviviruses, we constructed maximum-

Table 3 Multiplex cycling conditions

Cycle Denaturation Annealing Extension

Initial denaturation 95°C (5 min)

1 94°C (20s) 63.5° (25s) 72° (5s)2 94°C (20s) 62.5° (25s) 72° (5s)3 94°C (20s) 61.5° (25s) 72° (10s)4 94°C (20s) 60.5° (25s) 72° (11s)5 94°C (20s) 59.5° (25s) 72° (12s)6 94°C (20s) 58.5° (40s) 72°(15s)7 94°C (20s) 57.5° (40s) 72°(15s)8 94°C (20s) 56.5° (40s) 72°(20s)9 94°C (20s) 55.5° (40s) 72°(25s)10 94°C (20s) 54.5° (50s) 72°(30s)11–15 94°C (20s) 53.5° (50s) 72°(30s)16–20 94°C (20s) 52.5° (50s) 72°(30s)21–25 94°C (20s) 51.5° (50s) 72°(30s)26–30 94°C (20s) 50.5° (50s) 72°(30s)31–40 94°C (20s) 49.5° (50s) 72°(30s)41–50 94°C (20s) 47.5° (50s) 72°(30s)Final extension 72°(3 min)

Table 4 Viral culture isolation, strain and passage histories

Genus Virus (strain) Source References Passage

Phlebovirus Rift Valley fever* Mosquito (Aedes mcintoshi) Sang et al. (2010) 2–4Nairovirus Dugbe Tick (Amblyomma gemma) Sang et al. (2006) 2–4

Hazara Tick Unpublished 2–4Orthobunyavirus Bunyamwera Mosquito (Anopheles funestus) Ochieng et al. (2013) 2–4Alphavirus Chikungunya Mosquito (Aedes aegypti) Sang et al. (2008) 2–4

Middelburg Mosquito Unpublished 2–4Semliki forest Tick (Rhipicephalus pulchellus) Lwande et al. (2013) 2–4Sindbis Mosquito (Culex sp.) Ochieng et al. (2013) 2–4Ndumu Mosquito (Culex rubinotus) Ochieng et al. (2013) 2–4

Flavivirus West Nile (lineage 1) Mosquito (Culex univittatus) Ochieng et al. (2013) 2–4Dengue (serotype 2) African Green Monkey Gil et al. (2014) 3

Yellow fever Human Onyango et al. (2004) 2–4Usutu Mosquito (Culex pipiens) Ochieng et al. (2013) 2–4

Thogotovirus Thogoto Tick (Amblyomma gemma) Sang et al. (2006) 2–4Dhori Tick (Rhipicephalus pulchellus) Sang et al. (2006) 2–4

*Inactivated lysate

© 2016 John Wiley & Sons Ltd

6 J . V ILLINGER ET AL .

likelihood phylogenetic trees, using PHYML v. 3.0 (Guin-

don et al. 2010), from MAFFT alignments (Katoh & Stan-

dley 2013) of the new Flavivirus sequences with diverse

Flavivirus NS5 gene [AB377213, AB488408, AY149904,

AY223844, AY632535, DQ318019, DQ859065, EU078325,

EU569288, EU879060-1, FJ606789, FJ644291, FJ711167,

FJ883471, GQ165808-10, HE997073, HQ634597, JF707790,

JF707815, JN819317, JQ268258, JX423791, JX627335,

KC496020, KC505248, KC692067, KF751871, KF801612,

KU647676, NC_001477, NC_002031, NC_006551,

NC_009942, NC_016997] and translated amino acid

[AAO24117, AAV34151, ABC49716, ABI54481, ABW74531,

ACD93606, ACJ64914-5, ACN73462, ACP43327, ACQ55297,

ACR56717, ACV04604-6, AEH43697, AEH43722, AET13371,

AEY84723, AEZ56186, AFW15935, AGE96693, AGG76014,

AGS41451, AHF70999, AIA58171, AIG95643, AMC33116,

BAG06229, BAH83667, CCM73253, NP_041726, NP_059433,

YP_001527877, YP_005352889, YP_164264] sequences

obtained from GenBank. The phylogeny employed the

Akaike information criterion for automatic model selec-

tion and tree topologies were estimated using nearest

neighbour interchange (NNI) and subtree pruning

and regrafting (SPR) improvements over 1000 boot-

strap replicates. Mid-point rooted phylogenetic trees

were depicted using FIGTREE (Drummond & Rambaut

2007).

Results

Arbovirus differentiation by multiplex RT–PCR-HRM

The multiplex PCR-HRM assay was able to consistently

identify mosquito homogenates and goat serum samples

with not only the different genera of virus isolates

(Table 4) and synthetic DNA standards (Table 5), but

also specific virus species (Figs 1 and 2). Additionally,

mosquito homogenates spiked with multiple viruses

(Dugbe, sindbis and Rift Valley fever (RVF); Dugbe,

sindbis and yellow fever; dengue and yellow fever; and

yellow fever and RVF) could be identified based on their

mixed melting profiles (Fig. 3). Cluster analysis of melt-

ing profiles performed using SCREENCLUST Software (Qia-

gen) in unsupervised mode also differentiated the

distinct viruses into distinct clusters.

Multiplex RT–PCR-HRM assay validation against goldstandard plaque assays

The proportions of replicates from each of the Bunyamw-

era, sindbis, dengue and Thogoto virus serial dilutions

that tested positive (Table 6) demonstrate that all viruses

were detected at equal (20–200 plaque-forming units

(PFU)/mL for dengue and Thogoto viruses) or lower

(2–20 PFU/mL for Bunyamwera and sindbis viruses)

titres using our novel multiplex universal primer RT–PCR-HRM assay than by CPE observed in plaque assays.

Virus discovery in naturally infected mosquitoes

Among the 920 mosquito homogenates with known

arbovirus infection status, the assay, run on the samples

Table 5 Synthetic DNA (sDNA) sequences tested

Genus Virus GenBank accession

Phlebovirus Rift Valley fever HM586979

Rift Valley fever

(vaccine strain MP-12)

DQ380154

Punta Toro DQ363406

Nairovirus Crimean–Congohaemorrhagic fever

DQ211619

Nairobi sheep disease DQ697949

Orthobunyavirus Batai KC168049

Alphavirus Chikungunya HM045810

O’nyong-nyong M20303

Flavivirus Zika AY632535

Wesselsbron EU707555

West Nile (lineage 1) JN819317

West Nile (lineage 2) DQ318019

Table 6 Proportions of replicates (n = denominator) from sequential ten-fold virus titre dilutions that tested positive for specific

viruses based on CPE observed in plaque assays and on multiplex RT–PCR-HRM

Virus

dilution

Bunyamwera Sindbis Dengue Thogoto

CPE Multiplex HRM CPE Multiplex HRM CPE Multiplex HRM CPE Multiplex HRM

10�3 6/6 (20 000) 4/4 (20 000) 6/6 (200 000) 4/4 (200 000) 6/6 (20 000) 3/3 (20 000) 2/2 (200) 4/4 (200)

10�4 6/6 (2000) 4/4 (2000) 6/6 (20 000) 4/4 (20 000) 6/6 (2000) 2/3 (2000) 1/2 (20) 2/4 (20)

10�5 4/6 (200) 4/4 (200) 6/6 (2000) 4/4 (2000) 2/6 (200) 3/3 (200) 0/2 (2) 0/4 (2)

10�6 1/6 (20) 3/4 (20) 4/6 (200) 4/4 (200) 1/6 (20) 2/3 (20) 0/2 (<1) 0/4 (<1)10�7 0/6 (2) 1/4 (2) 2/6 (20) 4/4 (20) 0/6 (2) 0/3 (2) 0/2 (<1) 0/4 (<1)10�8 0/6 (<1) 0/4 (<1) 0/6 (2) 2/4 (2) 0/6 (<1) 0/3 (<1) 0/2 (<1) 0/4 (<1)10�9 0/6 (<1) 0/4 (<1) 0/6 (<1) 0/4 (<1) 0/6 (<1) 0/3 (<1) 0/2 (<1) 0/4 (<1)

Numbers in parentheses indicate approximate virus titres (PFU/mL). Bold numbers indicate virus titre detection limits.

© 2016 John Wiley & Sons Ltd

PAN-ARBOVIRUS SURVEILLANCE AND DISCOVERY 7

blindly, was able to correctly identify all sindbis, Semliki

Forest, Bunyamwera, Ndumu and West Nile virus infec-

tions. Among the mosquito homogenates with unknown

arbovirus infection status, we were able to identify ten

Flavivirus sequences (Table 7) that generated distinct and

novel Flavivirus HRM profiles. After amplifying

Virus Mosquito species Location

Proportion of

infected pools

Wesselsbron Culex spp. Naivasha, Rift Valley Province 1/157

Wesselsbron An. coustani Maai Mahiu, Rift Valley Province 6/15

AnFV An. squamosus Kotile, North-Eastern Province 4/286

AnFV An. squamosus Ijara, North-Eastern Province 3/190

AnFV An. gambiae Kotile, North-Eastern Province 2/68

AeFV Aedes sp. Maai Mahiu, Rift Valley Province 1/2

AeFV Aedes tricholabis Sangailu, North-Eastern Province 4/1065

MaFV Ma. africana Marigat, Rift Valley Province 4/609

Table 7 Virus detection rates in mos-

quito pools

Nor

mal

ized

fluo

resc

ence

(%)

100

90

80

70

60

50

40

30

20

10

Temperature (ºC)

77 78 79 80 81 82 83 84 85 86 87 88

Mel

t rat

e (d

F/dT

)

1.6

1.5

1.4

1.3

1.2

1.1

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.1

0.0

0.2

Negative controlDugbe (N)Hazara (N)Dhori (T)

Bunyamwera (O)Dengue (F)Sindbis (A)Middelburg (A)

Ndumu (A)Semliki Forest (A)Usutu (F)Chikungunya (A)

Yellow fever (F)WN (F)Thogoto (T)RVF (P)

(A)

(B)

Fig. 1 Distinct multiplex RT–PCR-HRM

profiles of diverse arboviruses. Melting

profiles of specific arboviruses from the

six focal genera are plotted as (A) normal-

ized HRM profiles represented as per cent

fluorescence and (B) melt rates repre-

sented as change in fluorescence units

with increasing temperatures (df/dt).

Viruses in the legend are ordered from

lowest to highest melting temperatures.

Viral genera are indicated in italics

(N = Nairovirus, T = Thogotovirus, O =Orthobunyavirus, F = Flavivirus, A = Alpha-

virus, P = Phlebovirus). (WN = West Nile,

RVF = Rift Valley fever).

© 2016 John Wiley & Sons Ltd

8 J . V ILLINGER ET AL .

Nor

mal

ized

fluo

resc

ence

(%)

100

90

80

70

60

50

40

30

20

10

Temperature (ºC)77 78 79 80 81 82 83 84 85 86 87 88

Mel

t rat

e (d

F/dT

)

1.61.51.41.31.21.11.00.90.80.70.60.50.4

0.10.0

Negative control (MH)Dugbe (N) cDNABatai (O) sDNABunyamwera (O) cDNASindbis (A) cDNA

O’nyong-nyong (A) sDNAZika (F) sDNAWesselsbron (F) sDNA*Wesselsbron (F) cDNAChikungunya (A) sDNA

Chikungunya (A) cDNACCHF (N) sDNANSD (N) sDNAPunta Toro (P) sDNAWN L2 (F) sDNA

WN L1 (F) sDNAWN L1 (F) cDNARVF vac. (P) sDNARVF (P) sDNARVF (P) cDNA

0.20.3

(A)

(B)

Fig. 2 Distinct multiplex RT–PCR-HRM

profiles from mosquito homogenates

spiked with diverse synthetic arbovirus

sequences (sDNA) and culture extracts

(cDNA). Melting profiles of specific arbo-

viruses are plotted as (A) normalized

HRM profiles represented as per cent flu-

orescence and (B) melt rates represented

as change in fluorescence units with

increasing temperatures (df/dt). Viruses

in the legend are ordered from lowest to

highest melting temperatures. The aster-

isk indicates Wesselsbron virus cultured

from Culex mosquito pool (KM088034).

Viral genera are indicated in italics

(N = Nairovirus, O = Orthobunyavirus,

A = Alphavirus, F = Flavivirus, P = Phle-

bovirus) (MH = mosquito homogenate,

CCHF = Crimean–Congo haemorrhagic

fever, NSD = Nairobi sheep disease,

WN = West Nile, RVF = Rift Valley fever,

L1/L2 = lineage 1/2, vac. = vaccine

strain).

Temperature (ºC)77 78 79 80 81 82 83 84 85 86 87 88

Mel

t rat

e (d

f/dt)

1.21.11.00.90.80.70.60.50.40.30.20.10.0

Dugbe Dengue Yellow feverDugbe, sindbis and RVF Dengue and yellow fever Yellow fever and RVFDugbe, sindbis, yellow fever Sindbis RVF

Fig. 3 Distinct melting profiles of mos-

quito homogenates spiked with mixed

arboviruses. Melt rates, represented as

change in fluorescence units with increas-

ing temperatures (df/dt), of specific arbo-

viruses from the six focal genera are

plotted. Viruses in the legend are ordered

from lowest to highest melting tempera-

tures. (RVF = Rift Valley fever).

© 2016 John Wiley & Sons Ltd

PAN-ARBOVIRUS SURVEILLANCE AND DISCOVERY 9

approximately 950 base pairs of the nonstructural pro-

tein 5 (NS5) gene of these novel flaviviruses using a

nested PCR approach developed by V�azquez et al.

(2012), we identified, for the first time in Kenya, a mos-

quito-borne Flavivirus (MBF) [GenBank: KM088034] with

97% nucleotide identity to Wesselsbron virus [GenBank:

JX423783, JX423791] (e-value = 0.0) in one Culex spp. and

six Anopheles coustani mosquito pools (Table 7). The other

nine Flavivirus sequences were related to (67%–77%sequence identities) recently discovered culicine insect-

specific flaviviruses (ISFVs) such as Kamiti River virus

(Crabtree et al. 2003; Sang et al. 2003) [GenBank:

AY149904], cell fusing agent virus (CFAV) [GenBank:

GQ165810] (Stollar & Thomas 1975; Cook et al. 2006),

Nakiwogo virus [GenBank: GQ165809] in Mansonia mos-

quitoes (Cook et al. 2009), Palm Creek virus [GenBank:

KC505248] in Coquillettidia mosquitoes (Hobson-Peters

et al. 2013) and other ISFVs found in Culex (CxFV) [Gen-

Bank: EU569288, FJ644291, JF707815, GQ165808,

EU879060, AB377213, HQ634597], Aedes (AeFV) [Gen-

Bank: AB488408, KF801612] (Hoshino et al. 2009; Rizzo

et al. 2014) and Aedes subgenus Ochlerotatus (OcFV) [Gen-

Bank: JF707790, JQ268258] (Huhtamo et al. 2012; V�azquez

et al. 2012) mosquitoes (Fig. 4).

Five of the novel ISFV sequences were isolated from

Anopheles gambiae (AngFV) [GenBank: KM088036,

KM088037] and Anopheles squamosus (AnsFV) [GenBank:

KM088035, KM088038, KM088039] and clustered into a

new clade of ISFVs (AnFV) (Fig. 4). The AngFVs shared

99.4% nucleotide identity (100% amino acid sequence

similarity) with each other and the AnsFVs shared

99.2%–99.8% nucleotide identity (99.2%–100% amino

acid sequence similarity) with each other. However, the

AngFVs shared only 77.1%–77.6% nucleotide identity

(92.1%–92.6% amino acid sequence similarity) with the

AnsFVs. Two ISFV sequences isolated from Aedes tri-

cholabis [GenBank: KM088042] and Aedes spp. [GenBank:

KM088041] cluster among AeFV and two ISFV sequences

[GenBank: KM088040, KM088043] isolated from Manso-

nia africana (MaFV) cluster among ISFVs previously iso-

lated from Mansonia and Coquillettidia mosquito species

(Fig. 4).

All new ISFV sequences cluster with previously iden-

tified ISFV sequences with ≥65% nucleotide sequence

similarity and >67% amino acid sequence similarity to

nearest published ISFV sequences, whereas the previ-

ously reported corresponding NS5-like mosquito gen-

ome integrated nonretroviral sequence (INVS)

[GenBank: AY223844] (Crochu et al. 2004) is more dis-

tantly related to <48% nucleotide sequence similarity to

its most closely related ISFV, Kamiti River virus [Gen-

Bank: AY149904]. Amino acid translations of all ISFVs

identified are free of stop codons, unlike related INVSs

which have multiple stop codons in all reading frames

(Crochu et al. 2004; Roiz et al. 2009), and their phyloge-

nies (Fig. 5) correspond closely with those determined

by their nucleotide sequences (Fig. 4). Further, full-

length ISFV NS5 genes amplified even when RNA

extracts were treated with DNase prior to reverse

transcription.

Discussion

The technological innovation presented here significantly

expands the potential of HRM analysis of highly multi-

plexed PCRs that are robust to varying sample qualities

and concentrations to reduce the costs and enhance effi-

ciency of broad-range pathogen surveillance (Tong &

Giffard 2012). This assay requires no consumables for

post-PCR product clean-up (Briese et al. 2005), elec-

trophoresis (Lambert & Lanciotti 2009) or mass spec-

trophotometry (Briese et al. 2005; Eshoo et al. 2007). The

critical HRM analysis step occurs in the thermocycler

immediately after PCR product amplifications. In our

laboratory, PCR-HRM costs less than $1 per sample, con-

sidering all consumables employed, after RNA extraction

and reverse transcription. Although some methods may

screen a few viruses in single-tube reactions at likely

comparable costs (Chao et al. 2007; Naze et al. 2009;

Dong et al. 2013), standard PCR-based approaches

require arrays of multiple assays to screen for broad

diversities of viruses (Lwande et al. 2013; Ochieng et al.

2013; Liu et al. 2016), and rely on sequencing of all sam-

ples (Lambert & Lanciotti 2009; Lwande et al. 2013;

Ochieng et al. 2013), or require laborious PCR clean-up

and mass spectrometric analysis (Briese et al. 2005; Eshoo

et al. 2007). In contrast, multiplex PCR-HRM pathogen

detection is less laborious, but has previously only been

done on bacterial pathogens (Yang et al. 2009; Tong &

Giffard 2012; Xue et al. 2012) and among certain fla-

viviruses (dengue serotypes 1–4, West Nile and chikun-

gunya viruses) (Naze et al. 2009).

This assay can identify specific arbovirus sequences

from Flavivirus, Alphavirus, Nairovirus, Phlebovirus,

Orthobunyavirus and Thogotovirus genera in infected sam-

ples based on their melting profiles that correspond to

those of known reaction templates in a closed-tube, sin-

gle-step assay. Further, the sensitivity of the assay is

comparable to gold standard Vero cell plaque assays,

which are also significantly more laborious and require

more time for sample processing (Table 6). Therefore,

this approach allows for more efficient high-throughput

arbovirus surveillance directly from field samples.

Viruses can subsequently be isolated by cell culture from

samples with viral infections that were positive by multi-

plex RT–PCR-HRM. Samples identified with novel HRM

profiles and virus sequences can be targeted for deep

sequencing from culture and/or remaining RNA stocks.

© 2016 John Wiley & Sons Ltd

10 J . V ILLINGER ET AL .

The discovery of Wesselsbron virus circulation in

Kenya demonstrates how this approach to pathogen

surveillance can identify potential disease threats that

may not be included in pathogen detection panels of rou-

tine surveillance efforts. Although there has been sero-

logical evidence of Wesselsbron virus exposure in

humans from surveys conducted in 1968 (Geser et al.

1970; Henderson et al. 1970), to our knowledge the virus

itself has not previously been identified in Kenya. While

Wesselsbron virus is most commonly associated with

livestock disease (Swanepoel and Coetzer 1994), it has

recently been shown to cause illness in humans (Weyer

CxFV (GQ165808)-Uganda-Cx. quinquefasciatus

CxFV (JF707815)-Spain-Cx. theileri

Murray Valley encephalitis virus (KF751871)-Australia-Cx. annulirostris

Aedes albopictus (AY223844) INVS

MaFV (KM088040)-Kenya-Ma. africana

AnsFV (KM088038)-Kenya-An. squamosus

Nakiwogo virus (GQ165809)-Uganda-Ma. africana

Lammi virus (FJ606789)-Finland-mosquito

OcFV (JF707790)-Spain-Ae. Ochlerotatus caspius

Quang Binh virus (FJ644291)-Vietnam-Culex tritae

CxFV (AB377213)-Japan-Cx. pipiensCxFV (HQ634597)-USA-Cx. quinquefasciatusCxFV (EU879060)-Mexico-Cx. quinquefasciatus

AnsFV (KM088035)-Kenya-Anopheles squamosus

AngFV (KM088036)-Kenya-An. gambiae

Zika virus (AY632535)-Uganda-monkey

Dengue virus (NC_001477)

West Nile virus (NC_009942)

Usutu virus (NC_006551)-Austria-blackbird

Calbertado virus (EU569288)-Canada-Cx. tarsalis

Barkedji virus (KC496020)-Israel-Cx. perexiguus

AeFV (KM088042)-Kenya-Ae. tricholabis

MaFV (KM088043)-Kenya-Mansonia africana

Kamiti River virus (AY149904)-Kenya-Ae. macintoshi

AnsFV (KM088039)-Kenya-An. squamosus

Dongang virus (NC_016997)-China-Aedes sp.

Hanko virus (JQ268258)-Finland-mosquito

Uganda S virus (DQ859065)-Uganda-Ae. longipalpisWesselsbron virus (KM088034)-Kenya-Culex sp.Wesselsbron virus (JX423791)-South Africa-Ae. circumluteolus

Ilomantsi virus (KC692067)-Finland-mosquitoNanay virus (JX627335)-Peru-mosquito

OcFV (HE997073)-Portugal-Ae. Ochlerotatus caspius

T'Ho virus (EU879061)-Mexico-Cx. quinquefasciatus

AeFV (KM088041)-Kenya-Aedes sp.

AeFV (AB488408)-Japan-Ae. albopictusAeFV (KF801612)-Italy-Ae. albopictus

West Nile virus lineage 1 (JN819317)

AngFV (KM088037)-Kenya-An. gambiae

Palm Creek virus (KC505248)-Australia-Coquillettidia sp.

Chaoyang virus (FJ883471)-China-mosquito

CFAV (GQ165810)-Puerto Rico-Ae. aegypti

West Nile virus lineage 2 (DQ318019)

Zika virus (KU647676)-Martinique-human

Nounane virus (FJ711167)-Cote d'Ivoire-Uranotaenia sp.

Barkedji virus (EU078325)-Senegal-mosquito

Yellow fever virus vaccine strain (NC_002031)

MBF

AeFV

AnFV

MaFV

CxFV

ISFV

0.6

351

608

926

321433

187

977

999

502

977

999

290

481

466

741

382

355

998

864

570

965

162

997

1000303

989

799

970

308

464

1000

286

999

930

659

994

944

979

635

997

815

241

997

998

894

Fig. 4 Phylogenetic tree inferred from Flavivirus NS5 nucleotide sequences. The phylogenetic analysis of 779–908 nt fragments includes

36 viral reference sequences from GenBank and 10 from this study (red), as well as a related mosquito genome integrated nonretroviral

sequences (INVS) (grey). Virus classification, GenBank accession numbers (in parentheses), country of origin and mosquito vector spe-

cies from which viruses were isolated are indicated for each insect Flavivirus NS5 gene sequence. Bootstrap values at the major nodes

are of agreement among 1000 replicates. The tree forms two major clusters according to the literature: the mosquito-borne flaviviruses

(MBF) and the insect-specific flaviviruses (ISFV). The branch length scale represents substitutions per site. The new ISFV sequences clus-

ter into three distinct ISFV clades associated with Mansonia (MaFV), Aedes (AeFV) and, for the first time, Anopheles (AnFV) genera

mosquito vectors. ISFV clades associated with Culex (CxFV) genera mosquito vectors are also shown.

© 2016 John Wiley & Sons Ltd

PAN-ARBOVIRUS SURVEILLANCE AND DISCOVERY 11

et al. 2013). Wesselsbron disease symptoms overlap with

those for RVF, and the virus also shares its ecological

niche with that of RVF virus (Swanepoel and Coetzer

1994). Recent RVF outbreaks demonstrate that strains of

arboviruses can evolve greater pathogenicity and viru-

lence to humans over relatively short time frames (Nder-

itu et al. 2011, Baba et al. 2016). While this has led to

increased vigilance with regard to RVF during disease

surveillance, Wesselsbron virus is not routinely consid-

ered during arbovirus surveillance exercises. Nonethe-

less, Wesselsbron virus is of public health concern as a

potential emerging infectious disease (EID) with poten-

tial epidemiology and disease symptoms that may easily

be confused with RVF (Swanepoel and Coetzer 1994).

AeFV (AJY53441)-Kenya-Ae. tricholabis

Nanay virus (AFW15935)-Peru-mosquito

Uganda S virus (ABI54481)-Uganda-Ae. longipalpis

OcFV (AEH43697)-Spain-Aedes Ochlerotatus caspius

Hanko virus (AEY84723)-Finland-mosquito

MaFV (AJY53439)-Kenya-Ma. africana

Barkedji virus (AGS41451)-Israel-Cx. perexiguus

CxFV (AEH43722)-Spain-Cx. theileri

Calbertado virus (ACD93606)-Canada-Cx. tarsalis

Nounane virus (ACN73462)-Cote d'Ivoire-Uranotaenia sp.

Wesselsbron virus (AJY53433)-Kenya-Culex sp.

Lammi virus (ACR56717)-Finland-mosquito

Palm Creek virus (AGG76014)-Australia-Coquillettidia sp.

CxFV (BAG06229)-Japan-Cx. pipiens

CxFV (ACV04604)-Uganda-Cx. quinquefasciatus

AeFV (AIG95643)-Italy-Ae. albopictus

AnsFV (AJY53438)-Kenya-Anopheles squamosus

Wesselsbron virus (AGE96693)-South Africa-Ae. circumluteolus

AnsFV (AJY53437)-Kenya-An. squamosus

CFAV (ACV04606)-Puerto Rico-Ae. aegypti

AngFV (AJY53435)-Kenya-An. gambiae

Zika virus (AAV34151)-Uganda-monkey

Barkedji virus (ABW74531)-Senegal-mosquito

West Nile virus (YP_001527877)West Nile virus lineage 2 (ABC49716)

Usutu virus (YP_164264)-Austria-blackbird

AeFV (BAH83667)-Japan-Ae. albopictus

CxFV (ACJ64914)-Mexico-Cx. quinquefasciatus

T'Ho virus (ACJ64915)-Mexico-Cx. quinquefasciatus

Kamiti River virus (AAO24117)-Kenya-Ae. macintoshi

West Nile virus lineage 1 (AEZ56186)

Murray Valley encephalitis virus (AIA58171)-Australia-Cx. annulirostris

Zika virus (AMC33116)-Martinique-human

AngFV (AJY53436)-Kenya-An. gambiae

Ilomantsi virus (AHF70999)-Finland-mosquito

Chaoyang virus (ACP43327)-China-mosquito

Yellow fever virus vaccine strain (NP_041726)

Quang Binh virus (ACQ55297)-Vietnam-Culex tritae

MaFV (AJY53442)-Kenya-Mansonia africana

OcFV (CCM73253)-Portugal-Ae. Ochlerotatus caspius

AeFV (AJY53440)-Kenya-Aedes sp.

Dongang virus (YP_005352889)-China-Aedes sp.

CxFV (AET13371)-USA-Cx. quinquefasciatus

Nakiwogo virus (ACV04605)-Uganda-Ma. africana

AnsFV (AJY53434)-Kenya-An. squamosus

Dengue virus (NP_059433)MBF

ISFV

AeFV

AnFV

MaFV

CxFV

0.3

428224

987

994

970

1000

337

435

547

1000

530

908

748

994

975

639

399

718

991

740

994

999

760

150

864

223

444

640

697564

1000

1000

1000

946

994

603

605522

999

996

1000

790

1000

993

Fig. 5 Phylogenetic tree inferred from translated Flavivirus NS5 protein sequences. The phylogenetic analysis of 266–325 amino acid

sequence fragments includes 36 viral reference sequences from GenBank and 10 from this study (red). Virus classification, GenBank

accession numbers (in parentheses), country of origin and mosquito vector species from which viruses were isolated are indicated for

each insect Flavivirus NS5 gene sequence. Bootstrap values at the major nodes are of agreement among 1000 replicates. The tree forms

two major clusters according to the literature: the mosquito-borne flaviviruses (MBF) and the insect-specific flaviviruses (ISFV). The

branch length scale represents substitutions per site. The new ISFV sequences cluster into three distinct ISFV clades associated with

Mansonia (MaFV), Aedes (AeFV) and, for the first time, Anopheles (AnFV) genera mosquito vectors. ISFV clades associated with Culex

(CxFV) genera mosquito vectors are also shown.

© 2016 John Wiley & Sons Ltd

12 J . V ILLINGER ET AL .

The ISFVs identified in this study are unlikely to be of

any public health concern, as this group of Flavivirus has

not been shown to infect vertebrates and are generally

vertically transmitted within mosquitoes (Lutomiah et al.

2007; Saiyasombat et al. 2011; Bolling et al. 2012; Hobson-

Peters et al. 2013). However, established infections of

Palm Creek virus isolated from Coquillettidia xanthogaster,

which is in a genus closely related to Mansonia (Reinert

2010), have been found to suppress replication of West

Nile and Murray Valley encephalitis viruses in mosquito

cells (Hobson-Peters et al. 2013), and Culex flavivirus

(CxFV) suppresses growth rates of West Nile virus in cul-

ture and potentially in Culex pipiens mosquitoes (Bolling

et al. 2012). The novel clade of AnFV sequences discov-

ered in this study is unlikely to constitute INVSs such as

those identified inAedes genomes (Crochu et al. 2004; Roiz

et al. 2009), as they share high sequence similarities with

previously isolated ISFVs and lack stop codons in the

viral polyprotein coding sequences. This suggests that all

ISFV sequences identified in this study have undergone

selection as functionally expressed viral polyprotein pre-

cursor coding sequences. Curiously, the AnFV NS5 gene

sequences cluster in between those identified in the Aedes

(AeFV) and Aedes subgenus Ochlerotatus (OcFV) mosqui-

toes, suggesting possible transmission of ISFVs between

mosquito genera. Indeed, AeFV have been recently

detected in Culex mosquitoes (Grisenti et al. 2015); how-

ever, themechanism bywhich their transmission between

mosquito species may have occurred remains unknown.

These AnFVs may be explored further for potential effects

on Anopheles mosquito competency to transmit arbo-

viruses, and possibly malaria Plasmodium.

The demonstrated utility of this nearly pan-arbovirus

PCR-HRM assay in identifying novel arboviruses lends

itself as a lower-cost alternative to undirected, hypothesis-

free deep sequencing for the purposes of arbovirus

surveillance and discovery when investigating high num-

bers of field samples. Nonetheless, our broad-range arbo-

virus detection assay can be expanded further to include

primers for Bwamba group orthobunyaviruses, as well as

orbiviruses (family Reoviridae) and vesiculoviruses (family

Rhabdoviridae). However, reliable scoring of HRM profiles

does depend on comparisons to positive controls that

might not be readily available for the full panel of poten-

tial targets. By developing online database approaches by

which HRM data from different real-time PCR platforms

and laboratories can be shared, compared and classified

using machine learning algorithms (Athamanolap et al.

2014), the need for positive controls within laboratories

may be reduced. Use of this assay can accelerate identifi-

cation of novel viruses as they emerge in new geogra-

phies, such as Zika virus, a virus previously thought of as

relatively benign to humans but has recently spread to the

American continents where it is responsible for severe

neurological birth defects (Fauci & Morens 2016). Univer-

sal primer multiplex PCR-HRM analysis may be adapted

to the broad-range detection, identification and discovery

of other classes of pathogens or taxa.

Acknowledgements

We thank the Arbovirus Incidence and Diversity (AVID)

Project consortium for providing the samples used in this

study and members of the Martin L€uscher Emerging

Infectious Diseases (ML-EID) Laboratory for their sup-

port in this work. Specifically, we gratefully acknowl-

edge Rosemary Sang (Kenya Medical Research Institute

—KEMRI), Edith Chepkorir (icipe), Caroline Tigoi (icipe)

and Maamun Jeneby (Institute of Primate Research) for

providing the viral stocks used for assay optimization

and mosquito homogenates, and Anne Fischer for pro-

viding critical advice in phylogenetic analyses. We also

thank Esther Kihara and Felix Odhiambo for their assis-

tance during the early phases of assay development and

Jonathan Stiles for critically reviewing the manuscript.

This project received financial support from Google.org,

the philanthropic arm of Google, and from the Consor-

tium for National Health Research (CNHR-Kenya),

through the project ‘Community of Excellence for

Research in Neglected Vector Borne & Zoonotic Diseases

(CERNVec)’, based at icipe. We acknowledge funding

from UK’s Department for International Development

(DFID); the Swedish International Development Cooper-

ation Agency (SIDA); the Swiss Agency for Development

and Cooperation (SDC); and the Kenyan Government.

The funding bodies did not play a role in the design of

this study, the collection, analyses and interpretation of

data, the writing of the manuscript, or decision to submit

the manuscript for publication.

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J.V. designed the methodology, analysed the data and

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D.K.M. guided the project.

Data accessibility

The GenBank accession numbers for the new Flavivirus

sequences discovered in this study are KM088034-

KM088043.

© 2016 John Wiley & Sons Ltd

PAN-ARBOVIRUS SURVEILLANCE AND DISCOVERY 15