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Medical and Veterinary Entomology (2016), doi: 10.1111/mve.12173
Comparative analysis of midgut bacterial communities
in three aedine mosquito species from dengue-endemic
and non-endemic areas of Rajasthan, India
S. S. CHARAN
1,K.D.PAWAR
1,†, S. D. GAVHALE
1, C. V. TIKHE
1,
N. S. CHARAN
1, B. ANGEL2, V. JOSHI
2,M.S.PATOLE
1and
Y. S. SHOUCHE
1
1Molecular Biology Unit, National Centre for Cell Science, Pune, Maharashtra, India and 2Desert Medicine Research Centre,
Jodhpur, Rajasthan, India
Abstract. Dengue viruses are transmitted to humans through the bites of infected
female aedine mosquitoes. Differences in the composition and structure of bacterial
communities in the midguts of mosquitoes may affect the vector’s ability to transmit
the disease. To investigate and analyse the role of midgut bacterial communities
in viral transmission, midgut bacteria from three species, namely Stegomyia aegypti
(=Aedes aegypti), Fredwardsius vittatus (=Aedes vittatus) and Stegomyia albopicta
(=Aedes albopictus) (all: Diptera: Culicidae), from dengue-endemic and non-endemic
areas of Rajasthan, India were compared. Construction and analyses of six 16S rRNA
gene libraries indicated that Serratia spp.-related phylotypes dominated all clone
libraries of the three mosquito species from areas in which dengue is not endemic.
In dengue-endemic areas, phylotypes related to Aeromonas,Enhydrobacter spp. and
uncultivated bacterium dominated the clone libraries of S. aegypti,F. vittatus and
S. albopicta, respectively. Diversity indices analysis and real-time TaqMan polymerase
chain reaction assays showed bacterial diversity and abundance in the midguts of
S. aegypti to be higher than in the other two species. Signicant differences observed
among midgut bacterial communities of the three mosquito species from areas in which
dengue is and is not endemic, respectively, may be related to the vectorial capacity of
mosquitoes to carry dengue viruses and, hence, to the prevalence of disease in some
areas.
Key words. Aedes,Stegomyia, 16S rRNA gene, dengue, midgut bacteria, real-time
PCR.
Introduction
Mosquitoes are medically important arthropod vectors that
transmit numerous human diseases, such as malaria, dengue
fever and lariasis. Aedine mosquitoes are the principal vec-
tors of dengue and dengue hemorrhagic fever (DHF). Amongst
various mosquito species, the most efcient epidemic vector is
Stegomyia aegypti (=Aedes aegypti); however, depending on the
Correspondence: Shakti S. Charan and Yogesh S. Shouche, Molecular Biology Unit, National Centre for Cell Science, Ganeshkhind, Pune,
Maharashtra 411007, India. Tel.:+91 20 25708051; Fax: +91 20 25692259; E-mail: sscharan17@gmail.com, yogesh@nccs.res.in
†Present address: School of Nanoscience and Biotechnology, Shivaji University, Vidyanagar, Kolhapur, Maharashtra, India.
specic geographic region in question, other species are also
important vectors (Gubler, 1998b, 1988a). Stegomyia albopicta
(=Aedes albopictus) is ranked second only to S. aegypti as a vec-
tor of dengue viruses (Knudsen, 1995) and, along with other
anthropophilic aedine species, serves as a maintenance vec-
tor for these viruses. Currently, dengue epidemics are occur-
ring frequently all over the world: around 2.5 billon people
are considered to be at high risk for this disease and around
© 2016 The Royal Entomological Society 1
2S. S. Charan et al.
ve million cases of the disease are reported annually. Nearly
50 000 of these cases can be attributed to DHF, which causes
22 000 deaths per year, predominantly in children (World Health
Organization, 2010). Hyperendemicity with multiple serotypes
and genotypes of dengue viruses and the hyperabundance of
mosquito vectors have contributed substantially to the emer-
gence of dengue and DHF as major public health problems.
The principal reasons for this tragic situation are mosquito pro-
liferation, inadequate vector control programmes, insecticide
resistance in vector populations, increased urbanization, rapid
transportation, unavailability of effective vaccines for virus and
declines in socioeconomic conditions in many disease-endemic
countries (Gubler, 1998b). Therefore, there is an urgent need
to develop tailored control strategies (e.g. paratransgenesis,
the development of refractory transgenic mosquitoes) against
mosquito-borne diseases (Ito et al., 2002; Riehle et al., 2007).
Mosquito–pathogen interaction is one of the important events
in the lifecycle of a pathogen that helps it to successfully mul-
tiply in the mosquito. In mosquito–pathogen interactions, the
midgut represents the rst point of contact between pathogens
ingested with a bloodmeal and the mosquito’s epithelial sur-
faces. A few previous studies have also suggested that pathogen
numbers decrease signicantly in the mosquito midgut, indicat-
ing the existence of a midgut infection barrier (MIB) (Ratcliffe
& Whitten, 2004; Michel & Kafatos, 2005). It is also believed
that the midgut bacteria of mosquitoes constitute an integral
part of this MIB and may play an important role in the drastic
reduction of pathogen load (Ratcliffe & Whitten, 2004; Riehle
et al., 2007).
Recent studies conrm an increase in the interest of the
scientic community in studying the endogenous microbiota
of the mosquito midgut with the aim of obtaining bacteria or
molecules that might have potential use in the development of
new mosquito control strategies (Chavshin et al., 2012; Terenius
et al., 2012; Bando et al., 2013; Capone et al., 2013; Charan
et al., 2013). For such strategies to be developed, an understand-
ing of the structure of the microbial community of the mosquito
midgut is necessary. This will help identify the organisms suit-
able for paratransgenesis because such bacteria must be adapted
to the environment in the midgut. A better understanding of
interactions between midgut bacteria and dengue viruses in
wild mosquito populations may elucidate how vector potential
for virus transmission is modulated by environmental factors,
such as the acquisition of different types of bacteria.
Stegomyia albopicta is considered to be the secondary vec-
tor of dengue virus (DENV) transmission in Southeast Asia, the
Western Pacic and, increasingly, in Central and South America
(Gratz, 2004). In recent decades, S. albopicta has spread to North
America, most probably from Japan, and its range stretches far-
ther north than that of S. aegypti (Hawley et al., 1987; Gratz,
2004). Eggs of S. albopicta are resistant to sub-freezing tem-
peratures, which make them potentially suitable to mediate a
re-emergence of dengue in the U.S.A. or in Europe (Hawley
et al., 1987). Many studies have compared the vectorial capaci-
ties of different aedine species and S. albopicta has been found
to be less susceptible to infection with DENV than S. aegypti
(Gratz, 2004). However, whereas S. aegypti does not vertically
transmit DENV very efciently, S. albopicta very efciently
transmits DENV vertically as well as sexually (i.e. during the
mating process), thereby indicating its main role in the main-
tenance of dengue viruses in areas in which the disease is
not endemic. There are few references indicating the natural
occurrence of vertical transmission of DENV in the species
S. aegypti and S. albopicta (Chow et al., 1998; Kow et al., 2001;
Lee & Rohani, 2005; Gunther et al., 2007; Rohani et al., 2007;
Thenmozhi et al., 2007). Many factors, including genetic and
environmental factors, may be responsible for the vectorial
competence of these different Stegomyia species. One study
observed that vector competence in S. aegypti was mutually
inuenced by polygenic inheritance and environmental factors
(Bosio et al., 1998). Different geographic strains of S. albopicta
were found to vary phenotypically in their susceptibility to
DENV (Gubler & Rosen, 1976). An earlier study performed to
clarify the dynamics of dengue transmission in a rural area in
south India found that S. aegypti (Linn.), S. albopicta (Skuse)
and Fredwardsius vittatus (=Aedes vittatus) (Bigot) were the
prevalent vector species. Although S. aegypti is the predominant
vector in most dengue-endemic countries, F. vittatus has been
found to breed throughout the year and its mean larval indices
were higher than those of S. albopicta, although it played no role
in dengue transmission in the study villages (Tewari et al., 2004).
In addition, the mosquito midgut environment may play a role
in determining the vectorial competence of these mosquitoes to
carry DENV. Zhang & He (1989) observed a mosquito midgut
barrier to be responsible for the differential vector competence
of different S. albopicta strains. As naturally occurring midgut
bacteria are an important factor in the mosquito midgut environ-
ment, it may be that these midgut bacteria play an important part
in the differential vectorial capacity of different mosquitoes.
The role of midgut bacteria in determining vectorial capacity
is investigated herein by isolating the midgut bacterial com-
munities of three aedine species, S. aegypti,S. albopicta and
F. vittatus, from areas of Rajasthan in which dengue is and is not
endemic, respectively. Rajasthan is one of the dengue-endemic
states in India (Ghosh & Sheikh, 1974; Ghosh et al., 1974;
Chuhan et al., 1985). Previously, Angel & Joshi (2008) cited
unpublished hospital data that reported DHF as the major cause
of sustained morbidity and mortality among human cases of
dengue in this area. In dengue-endemic areas of Rajasthan,
15.6% of sampled S. aegypti female mosquitoes were positive
in indirect uorescent antibody tests that employed monoclonal
antibodies against DENV 1, 2, 3 and 4 (Angel & Joshi, 2008).
Among various dengue-endemic areas of Rajasthan, a desert
area (Jodhpur) showed the highest (21.6%) rate of mosquito
infectivity (Angel & Joshi, 2009). By contrast, a hospital-based
serosurveillance study of dengue infection in Rajasthan reported
that 18.99% of dengue cases were specically immunoglobu-
lin M (IgM)-positive and that 23.51% (n=510) were secondary
dengue cases (Sood, 2013).
Materials and methods
Mosquito collection
Three mosquito species, S. aegypti,S. albopicta and F. vittatus,
were collected from dengue-endemic and non-endemic areas
of Jodhpur district, Rajasthan, India. The mosquitoes were
© 2016 The Royal Entomological Society, Medical and Veterinary Entomology, doi: 10.1111/mve.12173
Midgut bacteria in Aedes mosquitoes 3
identied to species using morphological keys. Only female
mosquitoes that had not fed on blood were chosen for the studies.
Captured mosquitoes were separated according to species and
area and then transported to the laboratory in separate tubes.
Cultivation-dependent bacterium identication
Mosquitoes were surface-sterilized with 70% ethanol for
5–10 min, then rinsed twice in sterile saline (0.9% NaCl)
and carefully dissected under sterile conditions as previously
described (Pidiyar et al., 2004). Five midguts for each mosquito
species were pooled and suspended in 250 μL of 0.85% NaCl
(w/v) and triturated with a plastic grinder. An aliquot (100μL)
of each sample was serially diluted up to 10−7and streaked
on plates containing lysogeny broth (LB) agar, trypticase soy
agar (TSA) and Columbia blood agar with 5% human blood
(HiMedia Laboratories Pvt. Ltd, Mumbai, India). Plates were
then incubated at 37 ∘C for 24–48 h. Isolates were screened by
examining the colony characteristics (including colony size,
shape, colour, opacity, margin, elevation and consistency) along
with Gram staining and motility. Colonies showing distinct
morphological characters were subcultured on fresh plates and
stored in 25% glycerol at −80 ∘C. The protocol was repeated
for bacterial enumeration by counting the colony-forming units
(CFUs). Bacterial isolates were identied using a colony poly-
merase chain reaction (PCR) protocol that employed universal
bacterial primers 27F and 1492R, as previously described (Rani
et al., 2009).
Cultivation-independent bacterium identication
The remaining midgut contents of each sample were used
for genomic DNA isolation by the standard phenol/chloroform
method. DNA was checked on 0.8% agarose gel (USB Corp.,
Cleveland, OH, U.S.A.) for purity and quantied using Nan-
oDrop (ThermoFisher Scientic, Inc., Waltham, MA, U.S.A.).
16S rRNA genes from midgut community genomic DNA were
amplied using universal bacterial primers 530F and 1490R as
previously described (Wani et al., 2006). The number of cycles
in the PCR was reduced to 25 in order to minimize PCR bias
(Suzuki & Giovannoni, 1996; Polz & Cavanaugh, 1998). The
PCR products were puried using the QIAquick PCR Purica-
tion Kit (Qiagen, Inc., Valencia, CA, U.S.A.) and ligated into
theTOPOpCR
®2.1 vector (Invitrogen, Inc., Carlsbad, CA,
U.S.A.). The resulting ligated products were transformed into
One Shot®TOP10 chemically competent Escherichia coli cells
(Invitrogen, Inc.) by following the manufacturer’s instructions.
After PCR screening of clones, positive clones were sequenced
using M13 vector primers. Sequencing was performed on an
ABI PRISM 3730 DNA Analyzer (Applied BioSystems, Inc.,
Foster City, CA, U.S.A.) using the ABI Big-Dye Sequencing
Kit Version 3.1 (Applied BioSystems, Inc.) according to the
manufacturer’s instructions.
Nucleotide sequence accession numbers
Sequences from this study were deposited in GenBank under
accession numbers KC484906–KC484965.
Phylogenetic analysis
The 16S rRNA gene sequences were assembled and
edited using ChromasPro 1.34 software (www.technely
sium.com.au/ChromasPro.html). Edited 16S rRNA gene
sequences were compared with the nucleotide sequence
database at n (http://www.ncbi.nlm.nih.gov/BLAST/)
and Ribosomal Database Project II (RDP II) (http://rdp.cme.
msu.edu) using the RDP query program (Maidak et al., 1999).
The possible chimeric artefacts were checked with the Pintail
1.01 module of Mallard 1.02 (Ashelford et al., 2006) and
further analysed by Bellerophon (Huber et al., 2004). Multi-
ple sequence alignment was performed using ClustalX 1.83
(Thompson et al., 1994) and aligned sequences were edited
manually using (Xia & Xie, 2001) to obtain an unam-
biguous sequence alignment. Nucleotide distance matrices
were constructed with from Version 3.61
(Felsenstein, 1989). Operational taxonomic units (OTUs) were
generated at a 97% sequence similarity cut-off in Ver-
sion 1.53 (Schloss & Handelsman, 2005) using the nucleotide
distance matrices. Various diversity indices [rarefaction curves,
phylotype richness, evenness (Pielous’s index), Shannon diver-
sity index (H), Simpson index and Chao value] were also
calculated in . The sequences belonging to each OTU
were compared with nucleotide database sequences at GenBank
and the RDP, and the sequences of the closest database relatives
were obtained. Phylogenetic trees were constructed using the
neighbour-joining method with Kimura 2 parameter distances
in Version 4.0 (Tamura et al., 2007).
UniFrac analyses
For weighted UniFrac distance metric analyses, the sequences
were aligned with ClustalW and a phylogenetic tree was con-
structed using MrBayes Version 3.0b4 (Ronquist & Huelsen-
beck, 2003). The phylogenetic tree was exported in Newick
format and the environmental le linking the sequences to dif-
ferent mosquito species from endemic and non-endemic regions
was used in UniFrac calculations. This created a UPGMA
(unweighted pair-group method with arithmetic mean, a tech-
nique that merges the closest pair of environments or cluster of
environments at each step) cluster of samples based on the phy-
logenetic lineages they contained.
Real-time PCR analysis
Real-time PCR was performed to enumerate 16S rRNA
gene copy numbers in the midguts of the three Stegomyia
species from areas in which dengue is and is not endemic,
respectively. Each reaction was performed in triplicate using
TaqMan Universal PCR Master Mix (Applied Biosystems,
Inc.) on an ABI 7300 Real-time PCR System (Applied
Biosystems, Inc.). Real-time TaqMan PCR-based bacterial
quantication was performed using 331F and 797R primers
(numbering based on the E. coli 16S rRNA gene) and (6-FAM)
-5′-CGTATTACCGCGGCTGCTGGCAC-3′-(TAMRA) probe
(Nadkarni et al., 2002). Puried Serratia marcescens DNA
© 2016 The Royal Entomological Society, Medical and Veterinary Entomology, doi: 10.1111/mve.12173
4S. S. Charan et al.
Tab l e 1 . Identities of isolates from the midguts of three mosquito species collected from dengue-endemic and non-endemic areas in Rajasthan, India.
Endemic Non-endemic
Mosquito species Bacterial division Isolate code Closest database relative Isolate code Closest database relative
Stegomyia aegypti Gammaproteobacteria CulaeenE715 Yersinia pseudotuberculosis CulaenoE818 Pseudomonas oryzihabitans
Firmicutes CulaeenE9D Bacillus cereus CulaenoE10E B. cereus
CulaeenE9C Bacillus thuringiensis CulaenoE10I Bacillus rmus
CulaeenE9A Exiguobacterium aurantiacum CulaenoE88 Enterococcus durans
CulaeenE9S Staphylococcus cohnii CulaenoE10F Staphylococcus haemolyticus
CulaeenE9M Staphylococcus epidermidis CulaenoE10O S. epidermidis
CulaeenE9Q Bacillus exus ——
CulaeenE9U Bacillus clausii ——
Stegomyia albopicta Firmicutes CulalenE32 B. cereus CulalnoE420 B. cereus
CulalenE33 Bacillus amyloliquefaciens CulalnoE422 B. rmus
CulalenE38 E. aurantiacum ——
CulalenE36 Staphylococcus hominis ——
Fredwardsius vittatus Firmicutes CulvienE13 B. cereus CulvinoE21 B. cereus
CulvienE12 B. rmus CulvinoE210 B. amyloliquefaciens
Total number of isolates retrieved: 58.
Stegomyia aegypti from endemic area: 18.
Stegomyia aegypti from non-endemic area: 13.
Stegomyia albopicta from endemic area: 10.
Stegomyia albopicta from non-endemic area: 6.
Fredwardsius vittatus from endemic area: 7.
Fredwardsius vittatus from non-endemic area: 4.
was used in a 1 : 10 dilution series (6 pg to 60 ng) to generate
a standard graph. Mass of the Se. marcescens genome with a
single copy of the 16S rRNA gene was calculated according to
the following equation:
M=(n)(
1.096 e −21 g∕bp)∕16S rRNA gene copies
per genome,
where n =genome size.
The cycle threshold or CTvalues (i.e. the cycle number in
which the exponential amplication of PCR products crosses the
threshold) were determined on the basis of uorescence signals
at the mean baseline during the early cycles of amplication. The
efciency of the PCR was calculated on the basis of standard
using the following formula:
Efciency =10(−1∕slope)−1
Results
Comparison of cultivated midgut bacteria
Amplication and analysis of 16S rRNA gene sequences from
isolates identied 14 bacterial species of six genera in S. aegypti.
These isolates were identied as Bacillus spp., Exiguobacterium
aurantiacum,Yersinia pseudotuberculosis and Staphylococcus
spp. in S. aegypti mosquitoes from dengue-endemic areas, and
as Pseudomonas oryzihabitans,Staphylococcus spp., Entero-
coccus durans and Bacillus spp. in S. aegypti mosquitoes from
non-endemic areas (Table 1). In S. albopicta, 16S rRNA gene
sequences identied different species of Bacillus in mosquitoes
from both types of sampling area. Along with these Bacillus
spp., Ex. aurantiacum and Staphylococcus hominis were found
only in mosquitoes from dengue-endemic areas. In F. vittatus,
16S rRNA gene sequences identied various species of Bacillus
in mosquitoes from both types of sampling area.
16S rRNA gene clone library analysis
Six 16S rRNA gene libraries were constructed from the midgut
bacteria of the three mosquito species from disease-endemic
and non-endemic areas. Comparative analyses of these clone
libraries showed notable differences among the midgut bacteria
from the three mosquito species studied.
Comparison of uncultivated midgut bacteria of S. aegypti
The sequencing of 172 randomly picked clones from the 16S
rRNA gene library of S. aegypti from dengue-endemic areas
resulted in 116 good-quality sequences. Of these, 10 sequences
were found to be chimeras and were therefore excluded from
further analysis. analysis of the remaining 106 sequences
identied nine OTUs that were phylogenetically afliated to
Alphaproteobacteria,Betaproteobacteria,Gammaproteobacte-
ria and Firmicutes (Fig. 1A). The OTU Aeen9175 dominated
the library with 46% relative abundance and showed max-
imum identity (99%) to Aeromonas sp. (GQ184148). The
OTUs Aeen918, Aeen9163 and Aeen9256 were phyloge-
netically afliated to uncultured bacteria and accounted for
21% of total sequences (Table 2). The OTUs Aeen9137 and
Aeen9188 showed maximum levels of similarity in identity to
Pseudomonas sp. (EU221384) and Bacillus sp. (EU73323),
© 2016 The Royal Entomological Society, Medical and Veterinary Entomology, doi: 10.1111/mve.12173
Midgut bacteria in Aedes mosquitoes 5
(A)
(B)
Fig. 1. Neighbour-joining trees constructed from 16S rRNA gene library sequences for midgut bacteria of Stegomyia aegypti sampled from areas
(A) endemic and (B) not endemic for dengue in Rajasthan, India. Trees were generated using the neighbour-joining method with the Kimura 2
distance parameter in Version 4.0. Numbers at nodes indicate percentage bootstrap values above 50 (1000 replicates). Scale bars indicate the
Jukes–Cantor evolutionary distance. Names in bold represent operational taxonomic units (OTUs) obtained from this study. Accession numbers of the
nearest neighbours are given in parentheses.
© 2016 The Royal Entomological Society, Medical and Veterinary Entomology, doi: 10.1111/mve.12173
6S. S. Charan et al.
Tab l e 2 . Percentage distribution of bacterial phylotypes in mosquitoes from dengue-endemic and non-endemic areas in Rajasthan, India.
Stegomyia aegypti Stegomyia albopicta Fredwardsius vittatus
Endemic areas Non-endemic areas Endemic areas Non-endemic areas Endemic areas Non-endemic areas
OTU
name
Closest
database
relative
OTU
name
Closest
database
relative
OTU
name
Closest
database
relative
OTU
name
Closest
database
relative
OTU
name
Closest
database
relative
OTU
name
Closest
database
relative
Aeen9175
(46)∗
Aeromonas sp. Aeno10239
(84)
Serratia sp. AlenB1017
(7)
Uncultured
bacterium
Alno16114
(34)
Serratia sp. VienA52
(15)
Roseomonas sp. VinoA27
(39)
Serratia sp.
Aeen918 (4) Uncultured
bacterium
Aeno1027
(3)
Sphingomonas
sp.
AlenA510
(2)
Uncultured
bacterium
Alno16278
(19)
Serratia sp. VienA1
(13)
Pseudomonas sp. VinoC11
(7)
Serratia sp.
Aeen9163
(14)
Uncultured
bacterium
Aeno10213
(3)
Bacillus sp. AlenB11
(69)
Uncultured
bacterium
Alno1616
(42)
Pseudomonas sp. VienD73
(12)
Shigella sp. VinoD60
(14)
Pseudomonas sp.
Aeen9256
(3)
Uncultured
bacterium
Aeno10273
(1)
Burkholderia
sp.
AlenA2955
(10)
Rahnella sp. Alno16116
(5)
Uncultured
bacterium
VienA15
(54)
Moraxella sp. VinoA28
(11)
Bacillus sp.
Aeen9137
(10)
Pseudomonas
sp.
Aeno10235
(4)
Uncultured
bacterium
AlenB2032
(12)
Rahnella sp. — — VienB53
(6)
Ralstonia sp. VinoC62
(28)
Bacillus sp.
Aeen9188
(5)
Bacillus sp. Aeno10226
(5)
Uncultured
bacterium
— — — — — — VinoD29
(1)
Uncultured
bacterium
Aeen9221
(7)
Sphingomonas
sp.
—— —— —— —— ——
Aeen9129
(10)
Alpha
proteobac-
terium
—— —— —— —— ——
Aeen9376
(1)
Moraxella sp.——————————
∗Values in parenthesis correspond to the percentage abundance of the respective OTU in the 16S rRNA gene library.
OTU, operational taxonomic unit.
© 2016 The Royal Entomological Society, Medical and Veterinary Entomology, doi: 10.1111/mve.12173
Midgut bacteria in Aedes mosquitoes 7
respectively. The sequences representing OTUs Aeen9221
and Aeen9129, which accounted for 17% of all sequences,
were closely related to Sphingomonas sp. (FJ194436) and
Alphaproteobacterium (AB452969), respectively. A singleton
OTU (Aeen9376) showed maximum homology (98%) with
Moraxella sp. (DQ497238).
In the 16S rRNA gene library of S. aegypti from areas not
endemic for dengue, the sequencing of 135 clones resulted
in 110 good-quality sequences. Seven possible chimeric
artefacts were removed and 103 sequences were taken for
nal phylogenetic analysis that resulted in the identica-
tion of six OTUs. Like S. aegypti from dengue-endemic
areas, mosquitoes from areas not endemic for dengue also
harboured bacteria afliated to the Alphaproteobacteria,
Betaproteobacteria,Gammaproteobacteria and Firmicute s
groups (Fig. 1B). Serratia sp. (AY689057)-related clones (OTU
Aeno10239) dominated the library, with relative abundance of
84% (Table2). The OTUs Aeno1027 and Aeno10213, which
accounted for 6% of all sequences, were closely related to the
16S rRNA gene sequences of Sphingomonas sp. (DQ340860)
and Bacillus sp. (AB211013), respectively. One singleton OTU
Aeno10273 shared maximum identity with Burkholderia sp.
(GQ181147), but 9% of library sequences (representing OTUs
Aeno10235 and Aeno10226) did not afliate with cultivated
bacteria.
Comparison of uncultivated midgut bacteria of S. albopicta
Initially, 150 clones were sequenced from the 16S rRNA gene
library of S. albopicta from dengue-endemic areas. After the
removal of chimeric sequences, 125 sequences were taken for
nal phylogenetic analysis. analysis of these sequences
facilitated the retrieval of ve OTUs that showed afliation
with Betaproteobacteria and Gammaproteobacteria (Fig. 2A).
This library was dominated (78%) by phylotypes (AlenB1017,
AlenA510 and AlenB11) that had no cultivated representatives
in the database (Table2). The OTUs AlenA2955 and AlenB2032
(representing 22% of the library) were found to be closely
related to Rahnella sp. (EU181369).
For S. albopicta from areas in which dengue is not endemic,
96 sequences were analysed after the removal of six chimeric
sequences. Similarly to S. albopicta from dengue-endemic
areas, bacteria afliated to Betaproteobacteria and Gammapro-
teobacteria were found in the midguts of S. albopicta from
areas in which dengue is not endemic (Fig. 2B). A total of
53% of sequences represented by OTUs Alno16114 and
Alno16278 were closely related to Serratia sp. (AY689057).
Pseudomonas sp. (HQ641264)-related phylotypes (OTU
Alno1616) accounted for 42% of all sequences. The remaining
5% of sequences were not afliated with any cultivated bacteria
(Table 2).
Comparison of uncultivated midgut bacteria of F. vittatus
In the clone library for F. vittatus from dengue-endemic
areas, 104 sequences were considered for nal analysis after
the removal of chimeras. These sequences were afliated to
Alphaproteobacteria,Betaproteobacteria and Gammapro-
teobacteria (Fig. 3A). Phylogenetic analysis identied ve
OTUs, amongst which Moraxella sp. (HM217989)-related
sequences dominated the library with 54% relative abundance
(Table2). The OTUs VienA52, VienA1 and VienD73 (repre-
senting 40% of the library sequences) were closely related to
16S rRNA gene sequences of Roseomonas,Pseudomonas and
Shigella spp., respectively. The remaining 6% of sequences
were found to be afliated to Ralstonia sp. (AB503703).
For F. vittatus from areas in which dengue is not endemic, 94
sequences were chosen for phylogenetic analysis, resulting in
the identication of six OTUs. In F. vittatus from non-endemic
areas, bacteria related to Alphaproteobacteria and Betapro-
teobacteria were absent and only members of the Gammapro-
teobacteria and Firmicutes were found (Fig. 3B). Similarly to
S. aegypti and S. albopicta from areas in which dengue is not
endemic, phylotypes (OTUs VinoA27 and VinoC11) related
to Serratia sp. (HQ407251) dominated (46%) the midguts of
F. vittatus. Phylotypes (OTUs VinoD60, VinoA28 andVinoC62)
afliated with Pseudomonas and Bacillus spp. accounted for 25
and 28% of all sequences, respectively (Table 2). A singleton
OTU showed maximum identity with an uncultivated bacterium
clone sequence (AM696762).
UniFrac cluster analyses
UniFrac cluster analysis was used to compare the bacterial
communities on the basis of phylogenetic information in the
three different mosquito species from areas in which dengue
is and is not endemic, respectively. In the cluster analysis
of the clone libraries, bacterial communities in each of the
mosquito species under study from dengue-endemic areas were
well separated from those from non-endemic areas (Fig. 4). This
clearly indicates the notable differences in the structures of the
bacterial communities in the three mosquito species from areas
in which dengue is and is not endemic.
Bacterial diversity indices analysis
Bacterial diversity and richness in the midguts of the three
mosquito species from the two types of sampling area were also
estimated. Diversity indices revealed relatively low bacterial
diversity in all libraries (Table 3). The Shannon diversity index
varied from 1.14 to 1.70, and was highest in the library
constructed for S. aegypti from dengue-endemic areas. Evenness
values were almost the same in all six libraries and were
estimated to be between 0.70 and 0.86. Simpson diversity index
values varied from 0.25 to 0.42. Chao values were comparable
with the total number of OTUs retrieved from the respective
libraries, except for that of F. vittatus from areas in which
dengue is not endemic. This indicates that the sequencing
efforts had sufciently sampled the majority of the dominant
phylotypes from the midguts of these mosquitoes. Rarefaction
curve analyses for these six libraries were also in congruence
with this observation as all the curves of the respective libraries
reached saturation (Fig. 5).
© 2016 The Royal Entomological Society, Medical and Veterinary Entomology, doi: 10.1111/mve.12173
8S. S. Charan et al.
(A)
(B)
Fig. 2. Neighbour-joining trees constructed from 16S rRNA gene library sequences for midgut bacteria of Stegomyia albopicta sampled from areas
(A) endemic and (B) not endemic for dengue in Rajasthan, India. Trees were generated using the neighbour-joining method with the Kimura 2
distance parameter in Version 4.0. Numbers at nodes indicate percentage bootstrap values above 50 (1000 replicates). Scale bars indicate the
Jukes–Cantor evolutionary distance. Names in bold represent operational taxonomic units (OTUs) obtained from this study. Accession numbers of the
nearest neighbours are given in parentheses.
Estimation of bacterial load
The total bacterial load in the three mosquito species was
quantied using quantitative real-time PCR that employed
the highly specic Taqman probe. A cultivation-dependent
approach was also used to quantitate cultivatable bacteria with
the CFU counting method. In real-time PCR analysis, the 16S
rRNA gene of Se. marcescens was used to generate a stan-
dard graph. The mass of the Se. marcescens genome with a
single copy of the 16S rRNA gene was calculated as 1.39fg
(functional gene) and the slope of the DNA standard graph
was estimated as −3.29, indicating 101% PCR efciency
(Figure S1). Both real-time PCR and CFU counting approaches
indicated that the 16S rRNA gene copy numbers were highest
in S. aegypti, followed by S. albopicta and F. vittatus,respec-
tively. In addition, mosquitoes from disease-endemic areas
had more 16S rRNA gene copy numbers than the respective
mosquito species from non-endemic areas (Fig. 6). Real-time
PCR showed that 16S rRNA gene copy numbers varied from
8.2 ×105copies (in F. vittatus from areas in which dengue is not
endemic) to 1.2 ×109copies (in S. aegypti from dengue-endemic
areas).
© 2016 The Royal Entomological Society, Medical and Veterinary Entomology, doi: 10.1111/mve.12173
Midgut bacteria in Aedes mosquitoes 9
(A)
(B)
Fig. 3. Neighbour-joining trees constructed from 16S rRNA gene library sequences for midgut bacteria of Fredwardsius vittatus sampled from
areas (A) endemic and (B) not endemic for dengue in Rajasthan, India. Trees were generated using the neighbour-joining method with the Kimura
2 distance parameter in Version 4.0. Numbers at nodes indicate percentage bootstrap values above 50 (1000 replicates). Scale bars indicate the
Jukes–Cantor evolutionary distance. Names in bold represent operational taxonomic units (OTUs) obtained from this study. Accession numbers of the
nearest neighbours are given in parentheses.
Discussion
This study provides initial information on the composition
of microbiota of three mosquito species. Currently, extensive
research is underway to study the comparative genetics of
mosquitoes that are naturally refractory or less potent vectors
of pathogens, as well as of mosquitoes that are susceptible to
pathogen transmission, to nd the causative factors of these
refractory or susceptible characteristics (Morlais et al., 2003;
Yan & Severson, 2003; Behura et al., 2011; Chauhan et al.,
2012). Along with these studies, others have investigated the cor-
relation between the presence of midgut bacteria and the devel-
opment of Plasmodium in mosquitoes. Results show that midgut
bacteria can signicantly inhibit sporogonic development of
© 2016 The Royal Entomological Society, Medical and Veterinary Entomology, doi: 10.1111/mve.12173
10 S. S. Charan et al.
S. aegypti Endemic
S. aegypti Non-endemic
S. albopicta Endemic
S. albopicta Non-endemic
F. vittatus Non-endemic
F. vittatus Endemic
0.1
Fig. 4. Dendrogram from the UniFrac environment cluster analysis
of 16S rRNA gene libraries for midgut bacteria of Stegomyia aegypti,
Stegomyia albopicta and Fredwardsius vittatus. Analysis involved
weighted data; numbers at nodes indicate the frequency with which
nodes were supported by environment cluster analysis.
Plasmodium (Pumpuni et al., 1993, 1996; Gonzalez-Ceron
et al., 2003). Also, a few recent studies have suggested the role
of natural microbiota of mosquitoes in stimulating basal-level
immunity, which may be an important factor in determining the
mosquito’s susceptibility to various pathogens and its vectorial
capacity (Frolet et al., 2006; Dong et al., 2009). By contrast with
studies on the inhibition of parasite development by the presence
of bacteria, one investigation reported a correlation between
the presence of Gram-negative midgut bacteria (Pseudomonas
sp.) and enhanced development of Plasmodium (Jadin et al.,
1966). Similarly, another study indicated that midgut bacteria
of S. aegypti have a signicant effect on the survival of dengue
viruses and play a role in determining the mosquito’s vectorial
capacity for virus (Mourya et al., 2002). Xi et al. (2008) also
reported that naturally occurring midgut bacteria of S. aegypti
mosquitoes can modulate dengue virus infection by activating
the Toll immune pathway. The implications of natural midgut
symbionts of mosquitoes in transmitting the pathogens are still
not clear.
In the present study, the midgut bacterial communities in three
mosquito species from areas in which dengue is and is not
endemic, respectively, were analysed to clarify whether there
are signicant differences that can be implicated in the trans-
mission of pathogens. The study was based on the assumption
that mosquitoes from the two types of sampling area might dif-
fer in their ability to transmit viruses and, therefore, might be
Fig. 5. Rarefaction curves generated for six 16S rRNA gene libraries
for midgut bacteria of Stegomyia aegypti,Stegomyia albopicta and
Fredwardsius vittatus from areas endemic and not endemic for dengue
in Rajasthan, India. OTUs, operational taxonomic units.
responsible for specic disease patterns. Several naturally occur-
ring symbiotic bacteria were identied, including some that
have been previously reported and a few new ones. With both
cultivation-dependent and -independent approaches, Staphylo-
coccus,Exiguobacterium,Bacillus,Enterococcus,Aeromonas,
Pseudomonas,Serratia and Shigella spp. were identied. These
have also been reported earlier as occurring in the midguts of
different mosquitoes (Vasanthi & Hoti, 1992; Gonzalez-Ceron
et al., 2003; Pidiyar et al., 2004; Favia et al., 2007; Riehle et al.,
2007; Rani et al., 2009; Gusmão et al., 2011; Apte-Deshpande
et al., 2012; Chavshin et al., 2012; Terenius et al., 2012). Rah-
nella,Burkholderia,Ralstonia,Moraxella,Sphingomonas and
Roseomonas spp. were previously reported in the guts of other
insects (Campbell et al., 2004; Yu et al., 2008; Morales-Jiménez
Tab l e 3 . Comparison of diversity indices and richness of 16S rRNA gene libraries prepared from three mosquito species collected from
dengue-endemic and non-endemic areas in Rajasthan, India.
Stegomyia aegypti Fredwardsius vittatus Stegomyia albopicta
Index Endemic areas Non-endemic areas Endemic areas Non-endemic areas Endemic areas Non-endemic areas
Clones, n∗106 103 104 93 125 94
Phylotype richness†96 56 54
Shannon index (H)‡1.70 1.35 1.30 1.32 1.21 1.14
Evenness (E)§ 0.72 0.70 0.75 0.84 0.86 0.83
Simpson index¶ 0.25 0.42 0.32 0.33 0.39 0.42
Chao 96 57 54
Numbers were calculated with and operational taxonomic units (OTUs) were dened using a distance level of 3%.
∗Total numbers of sequences taken for nal analysis.
†Total numbers of OTUs in the 16S rRNA gene library.
‡Shannon–Weaver diversity index (H). H was calculated as follows: H =Σ (pi) (log2 p −i), where p represents the proportion of a distinct phylotype
relative to the sum of all.
§Evenness/Pielous’s index (E) was calculated as: E =H/log2 (S), where log2 (S) =Hmax.
¶Simpson coverage index.
© 2016 The Royal Entomological Society, Medical and Veterinary Entomology, doi: 10.1111/mve.12173
Midgut bacteria in Aedes mosquitoes 11
Fig. 6. Real-time polymerase chain reaction-based quantication of
midgut bacteria of Stegomyia aegypti,Stegomyia albopicta and Fred -
wardsius vittatus from areas endemic and not endemic for dengue in
Rajasthan, India.
et al., 2009; Martinson et al., 2011; Priya et al., 2012; Sant’Anna
et al., 2012).
Using the cultivation-dependent approach, different species
of Bacillus were identied from the three mosquito species,
thereby indicating that Bacillus spp. were common inhabitants
of these mosquitoes’ midguts. Some notable differences among
the midgut bacteria of S. aegypti and S. albopicta from areas in
which dengue is and is not endemic were observed. However,
no such noteworthy differences at genus level were observed in
F. vittatus from the two types of sampling area.
Similarly, the cultivation-independent approach also revealed
many differences among the midgut bacterial communities of
the three mosquito species from the two types of sampling area.
The most important observation was the dominance of Ser-
ratia spp. in all three mosquito species from areas in which
dengue is not endemic and their absence from all three mosquito
species from dengue-endemic areas. Previous studies have also
observed the dominance of Se. marcescens among midgut bac-
terial communities of Anopheles stephensi (Diptera: Culici-
dae) and S. aegypti (Rani et al., 2009; Gusmão et al., 2011).
Additionally, Serratia spp. were reported to completely inhibit
the development of Plasmodium vivax and Trypanosoma cruzi
(Gonzalez-Ceron et al., 2003; Azambuja et al., 2004), thereby
playing a potential role in the transmission of other pathogens.
However, contrary to this, other researchers observed that the
presence of Serratia odorifera increased the arbovirus infec-
tion level in S. aegypti and predicted that these bacteria may
play a role in enhancing the susceptibility of mosquitoes to
dengue viruses (Apte-Deshpande et al., 2012). The dominance
of these bacteria in the midguts of mosquitoes from areas in
which dengue is not endemic and their total absence from sam-
ples from dengue-endemic areas may be an important linking
factor in the prevalent disease pattern observed. However, with
the available results, it is difcult to speculate anything with
regard to the exact role of these bacteria in the transmission
of DENV. The other signicant feature observed in the present
study was the dominance of Aeromonas spp. in S. aegypti from
dengue-endemic areas. Previously, the presence of Aeromonas
in the midguts of S. aegypti was shown to increase viral load
and to consequently make these mosquitoes more susceptible to
dengue virus transmission (Mourya et al., 2002). Taken together,
these two observations may suggest that physiological proper-
ties of these bacteria affect the disease transmission capacity of
mosquitoes.
The diversity indices analysis indicated very low bacterial
diversity in the midguts of wild-caught mosquitoes. Interest-
ingly, S. aegypti from dengue-endemic areas were observed to
have higher midgut bacterial diversity and species richness than
mosquitoes from non-endemic areas. The bacterial quantica-
tion analyses indicated that S. aegypti had a greater bacterial
load in their midguts than other mosquito species from the
respective sampling areas. Further, mosquitoes from endemic
areas harboured more midgut bacteria than mosquitoes from
non-endemic areas.
Previously, all studies on midgut bacteria of mosquitoes
were conducted using S. aegypti as this species constitutes the
principal vector for the transmission of dengue (Rodhain &
Rosen, 1997). In India, the three mosquito species studied
herein are the main DENV vectors, as is evident from previous
studies that reported the prevalence and importance of these
three species in disease transmission (Joshi et al., 2006; Angel &
Joshi, 2008; Angel et al., 2008). Despite the importance of other
mosquito species in the maintenance of dengue viruses, little
to nothing is known about the diversity of midgut bacteria in
these mosquitoes. To the best of the present authors’ knowledge,
this study is the rst to compare the midgut bacteria of three
mosquito species.
In conclusion, these results highlight a link between the
prevalence of dengue in some areas and bacterial diversity
and richness in the midguts of wild mosquitoes from those
areas. As viruses transmitted by mosquitoes coexist with their
midgut bacteria, characterizing the composition and diversity of
the bacterial communities in the midguts of these mosquitoes
represents a further step towards understanding the ecology
and the multipartite interactions occurring in these vectors of
arbovirus.
Supporting Information
Additional Supporting Information may be found in the
online version of this article under the DOI reference: DOI:
10.1111/mve.12173
Figure S1. Standard graph of cycle threshold (CT) vs. log of
copy number in real-time analysis.
Acknowledgements
The authors are grateful to Dr C. P. Antony, National Centre
for Cell Science (NCCS), Pune, for his suggestions and criti-
cal reading of the manuscript. SSC acknowledges the award of a
© 2016 The Royal Entomological Society, Medical and Veterinary Entomology, doi: 10.1111/mve.12173
12 S. S. Charan et al.
Senior Research Fellowship by the University Grants Commis-
sion, Government of India.
SSC, YSS and MSP designed the study; SSC, KDP, SG and
CT performed the clone library construction and sequencing.
SSC, NSC and KDP participated in qPCR analysis. AB and VJ
collected, dissected and supplied the mosquito gut samples for
the study. SSC, KDP and YSS analyzed the data and drafted the
manuscript. All authors read and approved the nal manuscript.
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