Spatial and temporal variation in the kdr allele L1014S in Anopheles gambiae s.s. and phenotypic variability in susceptibility to insecticides in Western Kenya.

Abstract

Malaria vector control in Africa depends upon effective insecticides in bed nets and indoor residual sprays. This study investigated the extent of insecticide resistance in Anopheles gambiae s.l., Anopheles gambiae s.s. and Anopheles arabiensis in western Kenya where ownership of insecticide-treated bed nets has risen steadily from the late 1990s to 2010. Temporal and spatial variation in the frequency of a knock down resistance (kdr) allele in A. gambiae s.s. was quantified, as was variation in phenotypic resistance among geographic populations of A. gambiae s.l.
To investigate temporal variation in kdr frequency, individual specimens of A. gambiae s.s. from two sentinel sites were genotyped using RT-PCR from 1996-2010. Spatial variation in kdr frequency, species composition, and resistance status were investigated in additional populations of A. gambiae s.l. sampled in western Kenya in 2009 and 2010. Specimens were genotyped for kdr as above and identified to species via conventional PCR. Field-collected larvae were reared to adulthood and tested for insecticide resistance using WHO bioassays.
Anopheles gambiae s.s. showed a dramatic increase in kdr frequency from 1996 - 2010, coincident with the scale up of insecticide-treated nets. By 2009-2010, the kdr L1014S allele was nearly fixed in the A. gambiae s.s. population, but was absent in A. arabiensis. Near Lake Victoria, A. arabiensis was dominant in samples, while at sites north of the lake A. gambiae s.s was more common but declined relative to A. arabiensis from 2009 to 2010. Bioassays demonstrated that A. gambiae s.s. had moderate phenotypic levels of resistance to DDT, permethrin and deltamethrin while A. arabiensis was susceptible to all insecticides tested.
The kdr L1014S allele has approached fixation in A. gambiae s.s. populations of western Kenya, and these same populations exhibit varying degrees of phenotypic resistance to DDT and pyrethroid insecticides. The near absence of A. gambiae s.s. from populations along the lakeshore and the apparent decline in other populations suggest that insecticide-treated nets remain effective against this mosquito despite the increase in kdr allele frequency. The persistence of A. arabiensis, despite little or no detectable insecticide resistance, is likely due to behavioural traits such as outdoor feeding and/or feeding on non-human hosts by which this species avoids interaction with insecticide-treated nets.

Full text

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RESEARCH Open Access
Spatial and temporal variation in the kdr allele
L1014S in Anopheles gambiae s.s. and phenotypic
variability in susceptibility to insecticides in
Western Kenya
Derrick K Mathias1,2,5,6, Eric Ochomo1,2, Francis Atieli1,2, Maurice Ombok1,2, M Nabie Bayoh1,2, George Olang1,2,
Damaris Muhia3, Luna Kamau3, John M Vulule1, Mary J Hamel2,4, William A Hawley4, Edward D Walker5*,
John E Gimnig4*
Abstract
Background: Malaria vector control in Africa depends upon effective insecticides in bed nets and indoor residual
sprays. This study investigated the extent of insecticide resistance in Anopheles gambiae s.l., Anopheles gambiae s.s.
and Anopheles arabiensis in western Kenya where ownership of insecticide-treated bed nets has risen steadily from
the late 1990s to 2010. Temporal and spatial variation in the frequency of a knock down resistance (kdr) allele in
A. gambiae s.s. was quantified, as was variation in phenotypic resistance among geographic populations of
A. gambiae s.l.
Methods: To investigate temporal variation in kdr frequency, individual specimens of A. gambiae s.s. from two
sentinel sites were genotyped using RT-PCR from 1996-2010. Spatial variation in kdr frequency, species
composition, and resistance status were investigated in additional populations of A. gambiae s.l. sampled in
western Kenya in 2009 and 2010. Specimens were genotyped for kdr as above and identified to species via
conventional PCR. Field-collected larvae were reared to adulthood and tested for insecticide resistance using WHO
bioassays.
Results: Anopheles gambiae s.s. showed a dramatic increase in kdr frequency from 1996 - 2010, coincident with the
scale up of insecticide-treated nets. By 2009-2010, the kdr L1014S allele was nearly fixed in the A. gambiae s.s.
population, but was absent in A. arabiensis. Near Lake Victoria, A. arabiensis was dominant in samples, while at sites
north of the lake A. gambiae s.s was more common but declined relative to A. arabiensis from 2009 to 2010.
Bioassays demonstrated that A. gambiae s.s. had moderate phenotypic levels of resistance to DDT, permethrin and
deltamethrin while A. arabiensis was susceptible to all insecticides tested.
Conclusions: The kdr L1014S allele has approached fixation in A. gambiae s.s. populations of western Kenya, and
these same populations exhibit varying degrees of phenotypic resistance to DDT and pyrethroid insecticides. The
near absence of A. gambiae s.s. from populations along the lakeshore and the apparent decline in other
populations suggest that insecticide-treated nets remain effective against this mosquito despite the increase in kdr
allele frequency. The persistence of A. arabiensis, despite little or no detectable insecticide resistance, is likely due to
behavioural traits such as outdoor feeding and/or feeding on non-human hosts by which this species avoids
interaction with insecticide-treated nets.
* Correspondence: hzg1@cdc.gov; dmathias@jhsph.edu
4Division of Parasitic Diseases, Centers for Disease Control and Prevention,
4770 Buford Hwy, Mailstop F-42, Atlanta, GA, 30341, USA
5Department of Microbiology and Molecular Genetics, Michigan State
University, East Lansing, MI, 48824, USA
Full list of author information is available at the end of the article
Mathias et al. Malaria Journal 2011, 10:10
http://www.malariajournal.com/content/10/1/10
© 2011 Mathias et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons
Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in
any medium, provided the original work is properly cited.

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Background
Malaria vector control programmes in sub-Saharan
Africa continue to rely heavily on indoor residual spray-
ing (IRS) or insecticide-treated nets (ITNs), both of
which depend on vector susceptibility to the insecticides
used. ITNs are a common component of malaria control
programs, largely due to their ease of implementation,
cost effectiveness [1-3], and record of success across
transmission settings [4]. As a consequence, ITNs have
been heavily promoted by the public-health community;
and as of 2010, it was estimated that 42% of households
owned at least one ITN across 44 countries in sub-
Saharan Africa [5]. These advances in vector control,
combined with effective new anti-malarial drugs, have
renewed optimism for regional elimination [6,7].
Few insecticides are available for use in malaria vector
control and only pyrethroid compounds are considered
safe for the treatment of ITNs [8]. Therefore, the con-
tinued success of ITNs and essentially the current
vector-control paradigm depend on continued mosquito
susceptibility to a single class of insecticides. Two
mechanisms of insecticide resistance, which may co-
occur, are commonly measured: (1) metabolic resistance
and (2) target-site insensitivity [9]. The former results
from the over expression or amplification of genes cod-
ing for enzymes that either biochemically alter the
insecticidal compound making it less toxic to the mos-
quito (e.g. P450 monooxygenases), or sequester the
compound preventing reactions detrimental to normal
physiology (e.g. esterases) [9,10]. In contrast, target-site
insensitivity involves one or more mutations that make
the physiologic target of an insecticide less reactive to
the chemical [11]. Target-site insensitivity in the malaria
vector Anopheles gambiae s.s. (hereafter referred to as
A. gambiae) includes two kdr mutations (for knock-
down resistance) which result in an amino acid substitu-
tion in the S6 hydrophobic segment of domain II in the
voltage-gated sodium channel of neuronal membranes
[9,11]. Both mutations reduce susceptibility to DDT and
to the pyrethroid class of insecticides and occur at dif-
ferent nucleotides of the same amino acid (residue
1014). In wild-type mosquitoes, this residue codes for
leucine (TTA), while in mutant mosquitoes single
nucleotide changes result in either a phenylalanine
(TTT) or serine (TCA) substitution [12,13]. The former
is commonly referred to as West African kdr, or
L1014F; while the latter is called East African kdr, or
L1014S. Molecular data suggest that each mutation has
risen independently at least twice in A. gambiae [14],
and, although the names of each allele suggest distinct
geographic distributions, co-occurrence has been
reported in multiple countries including Uganda,
Gabon, Cameroon, Equatorial Guinea, and Angola [15].
L1014F is thought to confer a greater degree of insensi-
tivity to pyrethroid insecticides than L1014S [11],
although bioassay data comparing each mutation within
the same genetic background do not exist. Nevertheless,
it has been speculated that selection for L1014F should
be stronger than for L1014S, a hypothesis supported by
recent molecular data showing that signatures of selec-
tive sweeps (i.e. reduced nucleotide variability) are more
extensive around L1014F than L1014S mutations in the
genomes of wild-caught mosquitoes [16]. A third
mechanism of resistance–behavioural–is poorly under-
stood and difficult to measure, although the excitatory
effects of DDT in IRS and permethrin in certain ITN
formulations suggest that a primary mode of action of
these two chemicals is on vector behaviour and not
survival [17-20].
When monitoring or investigating insecticide resis-
tance in vector populations, at least three approaches
can be taken, each with advantages and disadvantages:
(1) measures of phenotypic resistance provide a direct
indication of how resistance mechanisms impact vector
control activities but require access to testing kits, insec-
ticide impregnated papers, rearing facilities, and large
numbers of mosquitoes, any of which may be limiting;
(2) frequencies of target site mutations (e.g. kdr) are
easier to measure, but it is unclear how much this
mechanism contributes to resistant phenotypes; (3) mea-
sures of metabolic resistance (e.g. biochemical assays or
gene expression arrays) are likely to be strong indicators
of phenotypic resistance but are technically challenging.
Malaria vectors in western Kenya, where the present
study was conducted, include two sibling species of the
A. gambiae species complex, A. gambiae and Anopheles
arabiensis, as well as Anopheles funestus s.s. Historically,
A. gambiae has been the primary vector in the study
area, but this species has declined proportionately to
A. arabiensis (a secondary vector), possibly due to
greater effectiveness of ITNs against the former, more
anthropophilic species [21]. Development of insecticide
resistance in the local A. gambiae population could
reverse this trend and might reduce effectiveness of the
malaria control program in the region.
Two of the study sites included in the present study
are within or adjacent to areas included in a small ITN
trial conducted in 1990 and a large-scale trial conducted
from 1996 to 1999. The former involved just six villages
[22], while the latter covered a 500 km2area that
encompassed 221 villages [23]. In the smaller trial,
A. gambiae mosquitoes collected from villages with per-
methrin-treated nets and curtains showed increased
tolerance to permethrin after one year, leading to estab-
lishment of a laboratory strain with reduced sensitivity
to permethrin [24]. However, this tolerance did not
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persist in field populations, and required constant selec-
tion in the laboratory to maintain the phenotype [25].
The tolerant field population had increased activity of
metabolic enzymes as well as a novel mutation in the
sodium channel gene (i.e. kdr L1014S) [13,26]. Studies
of insecticide resistance following the larger ITN trial
have varied with respect to both levels of phenotypic
resistance and frequency of the kdr L1014S mutation. In
2004, Stump et al. [27] reported that kdr frequency was
8.0% in A. gambiae and had only risen slightly since
1987. A more recent study reported a range of 0.5% to
15.0% among sites in western Kenya for A. gambiae and
0.9% for A. arabiensis, but “conservative” population
estimates for the former were given as 1.0% or less
when accounting for relatedness of the specimens [28].
That study also reported an increase in monooxygenase
activity in field-collected specimens. Another recent
study reported a kdr L1014S frequency of 25.4% in
a sub-population of A. gambiae from western Kenya
[29]. WHO bioassays, however, provided no evidence of
phenotypic resistance. Whether genotypic or phenotypic
insecticide resistance is evolving in the A. gambiae
population in direct response to the rapid rise in use of
ITNs in western Kenya, in parallel with the profound
changes in species composition of the A. gambiae com-
plex there [21], is currently unknown. Therefore, the
objective of this study was to quantify temporal
variation in kdr L1014S frequency in populations of
A. gambiae (1996 - 2010) from two areas of western
Kenya having markedly different histories of ITN distri-
bution and use; and to assess the spatial variation in fre-
quency of the kdr L1014S allele, species composition, and
phenotypic resistance among populations of A. gambiae
s.l. sampled from multiple sites in western Kenya.
Methods
Temporal variation in kdr allele frequency
Adult and larval A. gambiae s.l. were sampled in the
communities of Asembo from 1996 to 2010 and Seme
from 2000 to 2008. These adjacent communities are situ-
ated 40-50 km west of the city of Kisumu along the
northern shore of the Winam Gulf of Lake Victoria
(Figure 1B), and are described in detail elsewhere
[21,30,31]. The malaria vector populations in Asembo
have been broadly exposed to pyrethroid insecticides in
ITNs for about 13 years, beginning with Asembo’s invol-
vement in a village randomized, controlled trial of per-
methrin-treated bed nets in 1997. Initially, half of the
villages in Asembo were provided permethrin-treated
bed nets. Nets were re-treated with permethrin at
approximately six-month intervals [23]. From 1999-2003,
all villages were provided permethrin-treated bed nets
and free house-to-house re-treatment [30]. Beginning in
2003, permethrin was replaced with alphacypermethrin
(40 mg/m2) at 9 to 11 month intervals until the end of
2006. In early 2007, nets were treated with a KO Tab 1-
2-3 wash resistant retreatment kit containing deltame-
thrin at a dose of 25 mg/m2[32]. Thereafter, residents
were responsible for insecticide retreatment of their nets.
At the conclusion of the large-scale trial in Asembo in
2000, entomological studies began in Seme, located on
Asembo’s eastern border [21,31]. Seme did not partici-
pate in or receive ITNs as part of the cluster rando-
mized trial that was conducted in Asembo. Net
ownership in Seme began to rise only after the Kenya
Ministry of Health and other partners increased access
to ITNs through free and subsidized distributions begin-
ning in 2004. ITNs were initially available to pregnant
women and children <5 years old at a subsidized price
at government-run health clinics. In 2006, ITNs were
distributed free to children <5 years of age as part of
a mass campaign [33] and the subsidy for ITNs distribu-
ted at government clinics was significantly increased. By
2009, ITNs were distributed at clinics to pregnant
women and children <1 year of age free of charge.
Mosquito sampling methods have been described pre-
viously [21]. Sampling commenced in 1996 when adult
female A. gambiae s.l. mosquitoes were collected from
bed-net traps. From 1997 to 1999, mosquitoes were col-
lected using pyrethrum spray catches (PSCs) inside
houses in Asembo using 0.025% pyrethrum and 0.1%
piperonyl butoxide mixed in kerosene. Houses for sam-
pling were identified by selection from a geographic
informationsystemdatabase
2003-2008, mosquitoes were collected along transects
running east to west during and immediately after the
rainy season of each year (typically, April to July). From
2007 to 2010, adult samples were supplemented with
larvae sampled from aquatic habitats along the same
transect [21]. All larva-positive habitats encountered
were exhaustively sampled for L3 and L4 stage larvae to
obtain specimens for genotyping and bioassays as
needed. Larvae and adults were morphologically identi-
fied to the A. gambiae complex, and categorized by
stage; adults were categorized by sex, and by abdominal
status if an adult female. Mosquitoes were desiccated in
anhydrous calcium sulfate or silica gel for 48 hours. Fol-
lowing desiccation, samples were stored at room tem-
perature until DNA extraction (see below).
[21,31,34]. From
Geographic variation in kdr allele
In 2009 and 2010, the geographic scope of the study was
expanded to estimate the frequency of the kdr L1014S
allele in A. gambiae and A. arabiensis regionally in wes-
tern Kenya to include Budalangi (2010 only), Kisian,
Kakamega, Bungoma (2009 only), Malaba, and Busia in
Nyanza and Western provinces (Figure 1A, B). Adult
and larval stages of A. gambiae s.l. were sampled and
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processed from these other sites using similar proce-
dures as for Asembo and Seme.
Species identification and genotyping
DNA was extracted from A. gambiae s.l. larvae and
adults following the protocol of Collins et al [35]. For
adult males and larvae, whole bodies were ground in the
initial step. For fed and half-gravid females, DNA was
extracted from legs and wings only, while extraction
from unfed and gravid females utilized legs, wings, and
abdomens. Conventional polymerase chain reaction
(PCR) was used to distinguish between the two sibling
species of the A. gambiae species complex native to
western Kenya, A. gambiae and A. arabiensis [36]. Real-
time polymerase chain reaction (RT-PCR) was used to
determine kdr genotype at amino acid position 1014 of
the voltage-gated sodium channel. Following a modified
version of the protocol by Bass et al. [37] , samples were
genotyped using probes for the wild type (5’-CTTAC-
GACTAAATTTC-3’, labeled with HEX) and L1014S (5’-
ACGACTGAATTTC-3’, labeled with 6-FAM) alleles. A
subset of samples was also genotyped for the L1014F
allele (5’-ACGACAAAATTTC-3’, labeled with 6-FAM).
RT-PCR reactions were run on a Stratagene MxPro
3000 machine using a 96-well format. Each reaction
included 5.0 μl of 2× Taqman RT-PCR master mix
(Applied Biosystems), 0.2 μM kdr forward primer (5’-
GCTGCGAGTTGTAGAGATGCG-3’), 0.2 μM kdr
reverse primer (5’-GCTTACTGGTTTGGTCGGCA
TGT-3’), the wild type and L1014S probes at respective
concentrations of 0.2 μM and 0.15 μM, ~50 ng DNA
template, and sterile water in a final volume of 10 μl.
Each 96-well plate included positive controls for all
three genotypes in triplicate along with a no-template
negative control. PCR conditions included an initial
melting step at 95°C for 10 minutes followed by 45
cycles of 95° for 25 seconds and 64°C for 1 minute.
Reaction curves for each set of reactions were visualized
using Stratagene MxPro QPCR software and genotypes
were scored by eye. Absence of alleles was confirmed by
the text reports generated by the Stratagene MxPro
QPCR software.
Sporozoite infection association with kdr
To test the hypothesis that mosquitoes with the kdr
L1014S allele are longer lived, more fit, and therefore
more likely to acquire a malaria infection in the context
of high ITN coverage, a case-control study was con-
ducted using specimens collected in Asembo and Gem,
an area just to the north of Asembo and to the north-
west of Seme, from 2003 through 2007. Mosquitoes
were collected monthly using light traps set overnight
next to persons sleeping under bed nets. Female A. gam-
biae s.l. were tested for the presence of Plasmodium
falciparum sporozoites using the antigen-capture
ELISA method of Wirtz et al [38]. All ELISA positive
A. gambiae s.l. were identified to species by PCR, and
each A. gambiae was analysed for the L1014S allele as
described above. For each ELISA positive A. gambiae,
three ELISA-negative A. gambiae mosquitoes collected
in the same village in the same month were randomly
selected as controls for a matched analysis, and were
genotyped for the kdr allele as well.
Bioassays
To assess insecticide resistance phenotypically, field-
collected A. gambiae s.l. mosquitoes were assayed for
susceptibility to various insecticides using WHO tube
Figure 1 Map of study area. A. Map of Kenya showing where studies were conducted in western Kenya, indicated by the box. B. Map showing
sampling locations in western Kenya study area, near Kisumu, Kenya’s third largest city.
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tests [39]. Mosquitoes were collected from study sites as
larvae and transported to an insectary, where they were
reared in spring water and fed daily a mixture of finely
ground fish food and brewer’s yeast. Upon pupation,
individuals were transferred to cages (40 cm3metal
frames covered with untreated mosquito netting) and
allowed to emerge. Upon emergence, all adults were
held for 2-5 days and provided sugar solution until used
in bioassays. Insecticide impregnated papers for five
insecticides were obtained from WHO at standard con-
centrations for determining resistance in field popula-
tions [39]: bendiocarb (0.1%), DDT (4%), deltamethrin
(0.05%), malathion (5%), and permethrin (0.75%). Bioas-
says performed in early 2009 only used DDT, deltame-
thrin, and permethrin, while those performed in late
2009 and 2010 used all five insecticides. Due to variation
in larval numbers, as well as time to pupation and emer-
gence, the number of replicates per insecticide and
number of mosquitoes per assay varied. The number of
individuals used in any single assay ranged from 8 - 20
and the minimum number of replicates was three. For
each bioassay, the plastic tube from the test kit was
lined with the appropriate test paper and mosquitoes
were transferred from a holding cage to the tube via an
aspirator. Following transfer, tubes were placed horizon-
tally on a flat surface to ensure maximal contact with
the impregnated papers. Exposure for each replicate was
60 minutes for all insecticides, after which individuals
were transferred to cohort cages (approximately 1 L
volume) and allowed to recover. During recovery, mos-
quitoes were provided with sugar solution and main-
tained at 25˚C and relative humidity ≥ 80%. Mortality
was scored at 24 hours post-bioassay. Following the late
2009 and 2010 bioassays, DNA was extracted from
assayed individuals and used to determine kdr L1014S
genotype and species identification as described above.
Data analysis
For analysis of changes in the frequency of the kdr
L1014S allele over time, samples collected from each
year and location were treated as separate populations.
The frequency of L1014S homozygotes was analysed
using multiple logistic regression in Stata (v. 11.0) with
the dependent variable being the loge(odds of kdr
L1014S homozygosity), modeled as a function of year
and location. The frequency of kdr L1014S homozy-
gotes, rather than frequency of kdr L1014S alleles, was
selected as the dependent variable because the kdr
mutation is only partially recessive and functionally
more significant in the homozygous state [13,16]. For
the 2009 and 2010 samples, the frequency of kdr
L1014S homozygotes was modeled in a similar manner
but with sub-population and month of collection as the
independent variables.
Similarly, for analysis of spatial variability, samples
collected in 2009-10 were analysed separately by loca-
tion, as were samples from the same location collected
at different times of the year. However, because previous
population-genetic studies of A. gambiae suggest that
western Kenya has a single, panmictic population [40],
the 2009 and 2010 location-specific samples are referred
to as sub-populations throughout to acknowledge their
genetic non-independence. For each sub-population,
genotype frequencies were compared to Hardy-
Weinberg expectations using the program Genepop
(v. 4.0), Option 1 (Hardy-Weinberg Exact Tests), Sub-
option 3 (Probability test) [41]. Genepop was also used to
estimate Wright’s inbreeding coefficient (FIS) using the
method of Weir and Cockerham [42]; and for sub-
populations out of Hardy-Weinberg equilibrium, these
values were used to test for heterozygote deficiency and
excess (Genepop Option 1, Sub-options 1 and 2, respec-
tively) using the U test as described in Raymond and
Rousset [41]. A Bonferroni correction was applied to the
level of significance for each procedure to adjust for mul-
tiple tests. To determine if mosquitoes with the kdr geno-
type were more likely to be infected with P. falciparum
sporozoites, PROC LOGISTIC in SAS was used to model
sporozoite infection status against kdr genotype.
Data from bioassays were pooled for each sub-popula-
tion and insecticide, and mortality was calculated as the
percentage of individuals that died within 24 hours of
exposure. For bioassays performed in 2009, variation in
survival was assessed using multiple logistic regression
with the dependent variable being the loge(odds of sur-
vival) modelled as a function of sub-population and
insecticide. Following regression, estimates of binomial
95% percent confidence intervals were used to compare
bioassay outcomes between insecticides within a given
sub-population. Further, levels of resistance were classi-
fied according to WHO guidelines [39]. Those with an
overall mortality ≥ 98% were considered susceptible,
those with mortality <98% but ≥ 80% were considered
potentially resistant, and those with mortality <80%
were strongly suspected to be resistant.
Results
Temporal variation in kdr genotype frequencies and
species composition
A total of 799 samples of A. gambiae were genotyped
for the kdr L1014S mutation in sub-populations from
Asembo (1996-2010) and Seme (2000-2008). Results
showed a sharp increase in homozygote frequencies
from complete absence in both locations initially to
80.5% for Seme in 2008 and 91.7% for Asembo in 2010
(Table 1, Figure 2). Logistic regression indicated that
the proportion of kdr L1014S homozygotes increased
significantly by year for both Asembo (O.R. = 2.108,
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95% CI = 1.81 - 2.45, P < 0.001) and Seme (2.547, 95% CI
= 2.04 - 3.17, P < 0.001). Exact tests for Hardy-Weinberg
equilibrium for each year and location showed that geno-
type frequencies differed significantly from expectation
only in 2008 after correcting for multiple tests (Table 1).
The West African allele (1014F) was not detected in any
genotyped A. gambiae individuals (n = 88) from Asembo
and Seme in 2008. A single A. arabiensis from Busia that
was homozygous for the kdr 1014S allele was detected in
44 A. arabiensis from Bungoma, Busia, Kakamega, and
Kisian in 2009 and 2010.
Geographic variation in kdr genotype frequencies and
species composition
3,172 specimens were identified to species within the
A. gambiae complex from seven sites from 2009 and
2010. The proportion of the sibling species A. gambiae
and A. arabiensis varied among sampling location but
patterns were similar between 2009 and 2010 (Table 2,
Figure 3A, B). In 2009, the percentage of A. gambiae
was highest in Busia (89.7%) and Malaba (91.2%), close
to the border with Uganda, and lowest at sites to the
southeast near Lake Victoria, namely Kisian (12.8%) and
Table 1 Genotype frequencies for kdr 1014S in Anopheles gambiae s.s. according location and date of sample
collection
Location Year/Montha
Sample Size Genotype Countsb
S/S
kdr Homo- zygosity S.E.FISc
S/EE/E
Asembo 1996
2000
2004
2005
2007
2008
2009
2010
2000
2003
2005
2007
2008
2009/Apr
2009/May
2009/Jul
2010/May
2009/May
2009/Jul
2009/May
2009/Oct
2009/Nov
2010/May
2009/Apr
2009/May
2009/Jul
2009/Sep
2010/May
2009/Feb
2009/Jun
2010/May
95
27
126
98
20
56
36
8
30
130
116
16
41
129
107
76
134
378
83
38
100
36
152
67
22
39
46
38
27
27
33
85
27
69
42
7
13
2
0
27
102
50
6
5
11
0
1
0
2
0
0
3
1
4
1
1
0
2
0
0
1
0
10
0
41
39
6
6
1
0
3
23
52
5
3
15
5
1
3
25
3
1
3
2
1
2
1
1
0
1
1
1
0
0
0
0.0
0.0
12.7
17.4
35.0
66.1
91.7
100
0.0
3.8
12.1
31.2
80.5
79.8
95.3
97.4
97.8
92.9
96.4
97.4
94.0
91.7
96.7
95.5
90.9
97.4
95.6
97.4
96.3
92.6
100.0
–
–
-0.0503
–
0.2053*
0.1537
0.4213
0.7416***
0.7904**
–
-0.0357
0.1934*
0.0122
0.4000
0.7315***
0.5295***
-0.0192
0.6637*
-0.0076
0.1049
-0.0123
–
0.6538***
0.4815
0.8862***
0.4903*
0.6557
–
1.0000***
–
–
0.6579*
–
16†
17
7
37‡
33†
8
0
5†
14
5
33‡
103‡
102
74†
131
351
80
37
94‡
33
147
64†
20
38
44‡
37
26
25†
33
2.98
3.94
10.94
6.38
4.67
0.00
–
1.69
3.04
11.97
6.27
3.55
2.05
1.85
1.28
1.33
2.06
2.63
2.39
4.67
1.45
2.55
6.27
2.56
3.04
2.63
3.70
5.14
0.00
Seme
Busia
Malaba
Bungoma
Kakamega
Kisian
aYear of sample collection only is given for the kdr time series for Asembo and Seme although sampling was typically performed during the peak of the rainy
season in May or June. Month of sampling is given for the 2009 and 2010 collections from sites across western Kenya.
bThree possible kdr genotypes are S/S, S/E, and EE, where S represents the susceptible wild type allele and E (for East African) represents the L1014S allele. The
symbols † and ‡ indicate that genotype frequencies depart from Hardy-Weinberg expectations, although those with † are no longer significant following a
Bonferroni correction for multiple tests.
cFISvalues > 0 indicate heterozygote deficiency, while values < 0 indicate heterozygote excess. A double dash (–) indicates values that were undefined.
Significance level indicates rejection of the null hypothesis FIS= 0, where *, **, and *** indicate p < 0.05, p < 0.01, and p < 0.001, respectively. After a Bonferroni
correction for multiple tests, only those values with *** remain significant at the corrected significance level (a = 0.0017).
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Asembo/Seme (11.8%). In 2010, the percentage of
A. gambiae were similarly lowest at Kisian (9.5%) and
Asembo/Seme (2.8%), but were highest in Bungoma
(88.9%) rather than Busia (50.4%). Overall, the percen-
tage of A. arabiensis in all samples was higher in 2010
compared to 2009.
A total of 1,532 A. gambiae were genotyped for the
kdr L1014S allele from samples taken in 2009 and 2010
in Busia, Malaba, Bungoma, Kakamega, and Kisian
(Table 1). The frequency of kdr L1014S homozygotes in
A. gambiae was high at all sites, and did not differ by
location for either year (P = 0.254) (Table 1, Figure 3C,
D). Within locations, homozygote frequency only dif-
fered between collections for one site, Busia in 2009 (O.
R. = 2.67, 95% CI = 1.51 - 4.73, P < 0.01, Table 1).
When including this site in the analysis, all locations
had kdr L1014S homozygote frequencies of 79% or
greater; but when excluding the Busia sample from
April of 2009, homozygote frequencies were all greater
than 90%. There was no statistical difference in geno-
type frequencies between larval and adult samples (O.R.
= 1.15, 95% CI = 0.73 - 1.84, P = 0.537). Estimates of
Wright’s inbreeding coefficient (FIS) for both the time-
series and 2009/2010 sub-populations indicated that
genotype frequencies out of Hardy-Weinberg equili-
brium tended toward heterozygote deficiency (Table 1).
Sporozoite infection
Between 2003 and 2007, a total of 43 A. gambiae mos-
quitoes were found to be infected with P. falciparum by
sporozoite ELISA. These were genotyped for kdr L1014S
along with 129 control mosquitoes. Among the sporo-
zoite positive mosquitoes, 11.6% were homozygous for
the kdr L1014S allele. Among sporozoite negative
Figure 2 Frequency of the kdr L1014S allele in Anopheles
gambiae s.s. (top) and bed net ownership (bottom) by year in
Asembo and Seme, western Kenya. Bed net ownership is the
percentage of households that own at least one bed net, including
both treated conventional nets and long-lasting impregnated nets.
Table 2 Species composition in combined samples of Anopheles gambiae s.l. from sites in western Kenya collected in
2009 and 2010
LocationYear
Anopheles gambiae s.s.
Anopheles arabiensis
Total Genotyped
Busia2009
2010
2009
2010
2009
2010
2009
2010
2009
2010
2009
2010
89.7 (347)
50.4 (134)
91.2 (479)
-
71.6 (78)
88.9 (152)
70.3 (211)
35.2 (38)
11.8 (38)
2.8 (4)
12.8 (63)
9.5 (33)
10.3 (40)
49.6 (132)
8.8 (46)
-
28.4 (31)
11.1 (19)
29.7 (89)
64.8 (70)
88.2 (284)
97.2 (141)
87.2 (430)
90.5 (313)
387
266
525
-
109
171
300
108
322
145
493
346
Malaba
Bungoma
Kakamega
Asembo/Seme
Kisian
In each column, the proportion of each species is presented by location and year with the absolute number of each species presented in parentheses. The total
number of A. gambiae s.l. that were genotyped is provided in the last column.
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mosquitoes, 5.4% were homozygous for the kdr L1014S
allele (Table 3). However, these percentages were not
significantly different (P = 0.177).
Bioassays
A total of 3,432 individual A. gambiae s.l. were tested in
phenotypic assays in 2009, and 1,027 individuals in
2010. Samples varied in their phenotypic susceptibility
to different insecticides in standardized WHO bioassays.
Of the three compounds tested in 2009, mosquitoes
(grouped only within species complex) were generally
most susceptible to deltamethrin, least susceptible to
DDT, and intermediate in susceptibility to permethrin
(Table 4). However, in late 2009/2010, there was more
variability in the response to different insecticides with
resistance highest to deltamethrin in A. gambiae from
Bungoma. In Busia, the highest degree of resistance was
to permethrin. Susceptibility to malathion was nearly
100% in all populations. There were marked differences
among species, with A. arabiensis being susceptible to
all insecticides, and A. gambiae having reduced suscept-
ibility to most insecticides.
Discussion
Three processes have marked the dynamics of the Ano-
pheles gambiae species complex in western Kenya dur-
ing the course of national scale-up of ITNs: (1)
a decline in density of indoor resting mosquitoes
[31,43], (2) a shift from a predominance of A. gambiae
Figure 3 Proportion of A. gambiae s.s. and A. arabiensis at sites in western Kenya in 2009 (A) and 2010 (B); Proportion of kdr
genotypes observed in A. gambiae s.s. at sites in western Kenya in 2009 (C) and 2010 (D).
Table 3 kdr L1014S genotype frequencies of A. gambiae
s.s. from 2003-2007 in association with sporozoite
infection
kdr L1014S genotype
ELISASS ESEE Total
Negative
Positive
64 (49.6)
21 (48.8)
58 (45.0)
17 (39.5)
7 (5.4)
5 (11.6)
129 (100)
43 (100)
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to A. arabiensis in adult and larval stages [21], and (3)
a decrease in longevity of adult females, but no change
in host preference patterns [21]. These changes correlate
with a sustained reduction in the malaria burden in the
human population [30]. The rapid rise in the frequency
of the kdr L1014S allele to near fixation in A. gambiae
as reported here, could herald a reversal of these posi-
tive outcomes. The marked rise in frequency of the kdr
L1014S allele over 13 years in Asembo and Seme sug-
gests that A. gambiae has been undergoing strong selec-
tion for resistance to the pyrethroid insecticides used in
ITNs distributed there. Allele frequencies ranged from
2.5% to 3.8% in A. gambiae in western Kenya in 1987
[27]. The kdr allele frequency we report from Asembo
for 1996 (5.3%, n = 95) is nearly identical to that of
Stump et al [27] for the same year. Therefore, when
ITNs were distributed in Asembo for the intervention
trial in 1996, alleles for kdr-mediated resistance were
already present in the A. gambiae population. Although
direct comparisons with other populations are con-
founded by many factors, the rise in the L1014S allele
observed in western Kenya was nearly as rapid as that
observed for the L1014F allele in Ghana [16].
The rise in the mutation’s frequency followed similar
trajectories in Asembo and Seme despite substantial dif-
ferences in net coverage between the areas for a decade
(Figure 2). Net ownership rose modestly in Seme from
2000 to 2003 and then substantially increased with sub-
sidized distribution of ITNs to pregnant women and
children <5 years of age from government health facil-
ities beginning in 2004, followed by a mass campaign in
2006 [21,33]. The similar patterns of emergence of resis-
tance likely reflect details of migration and selection
pressure not measured in our study. While A. gambiae
came into ever increasing contact with pyrethroids in
Asembo over the past 13 years, selection pressures out-
side of Asembo due to either malaria control or agricul-
tural pesticide use are unknown.
Other studies have also reported increases in fre-
quency of the kdr L1014S allele in A. gambiae from
Burundi [44] and Uganda [45] associated with vector
control using pyrethroid insecticides; while studies in
Niger [46] and Equatorial Guinea [47] have observed
sharp rises in the kdr L1014F allele in response to ITNs
and IRS, respectively. In Burundi and Rwanda, the rise
in the kdr L1014S allele was ascribed to use of insecti-
cides as indoor residual sprays to control adult stages of
malaria vectors. However, in Burundi, the allele fre-
quency actually increased in an unsprayed control area
as well as in the sprayed area. In Uganda, there were
marked regional variations in allele frequency without
clear correlation with intensity of use of IRS or ITNs,
and allele frequency and phenotypic resistance were
noted particularly in areas with a history of cotton agri-
culture where insecticide use is often intense [45].
In other settings, agricultural use of insecticides has
been cited as the primary cause of the emergence of
insecticide resistance in A. gambiae s.l. populations in
sub-Saharan Africa [48-50]. Anopheles gambiae s.l. lar-
vae may face strong selection pressure for resistance to
insecticides if exposed in breeding sites located near cul-
tivated fields where insecticides are applied to control
agricultural pests. In a cotton-growing region of north-
ern Cameroon, investigators sampled mosquito larvae
from breeding sites within cotton fields at different
times during the rainy season [51]. Bioassays of emerged
adults revealed that vector susceptibility to DDT and
permethrin decreased over time in accordance with
Table 4 Percent mortality in WHO bioassays 24 hours after exposure to discriminating concentrations of insecticide
SpeciesSub-PopulationYear DDT PermethrinDeltamethrinBendiocarbMalathion
A. gambiae s.l.Bungoma
Busia
Kakamega
Kisian
Malaba
2009
2009
2009
2009
2009
78 (54)
21 (78)
78 (188)
ND
64 (59)
84 (148)
54 (347)
85 (225)
84 (231)
68 (627)
89 (88)
78 (249)
87 (342)
91 (22)
89 (774)
ND
ND
ND
ND
ND
ND
ND
ND
ND
ND
A. gambiae s.s.Bungoma
Busia
2009-2010
2009-2010
62 (37)
33 (15)
74 (74)
16 (25)
42 (19)
48 (21)
96 (25)
79 (19)
100 (44)
100 (15)
A. arabiensis
Asembo
Budalangi
Busia
Kakamega
Kisian
2010
2010
100 (36)
100 (23)
98 (42)
100 (8)
100 (32)
97 (64)
100 (21)
87 (23)
82 (11)
87 (63)
83 (29)
100 (25)
100 (18)
100 (15)
94 (70)
100 (34)
94 (17)
93 (15)
82 (11)
100 (24)
100 (24)
100 (32)
100 (18)
100 (10)
100 (16)
2009-2010
2009-2010
2009-2010
The number of adult mosquitoes assayed (n) is given in parentheses and bioassays with mortality <80% are highlighted in boldface.
aMortality not determined.
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a spraying schedule in the cotton fields that included
two applications of an organochlorine compound (endo-
sulfan) followed by a pyrethroid/organophosphate mix-
ture (cypermethrin/profenofos). In Burkina Faso, the
spatial heterogeneity of kdr L1014F was associated with
cotton agriculture; the mutation was present at 16 of 21
sites and ranged in frequency from 4.7% to 97.0% with
the highest frequencies occurring in the so-called “cot-
ton belt” [52]. Although data are lacking, current agri-
cultural use of pesticides in western Kenya is likely low
owing to the prevalence of subsistence agriculture. How-
ever, use of permethrin for cattle dips is common, and
the region produces some cash crops (sugar cane and
cotton) that may require insecticide use. In addition, the
low level of resistance to bendiocarb implies that agri-
cultural use of insecticides may play a role in the evolu-
tion of resistance in malaria vectors in western Kenya.
However, the strong temporal association reported here
between net ownership and kdr L1014S frequency
(Figure 2) suggests that ITNs have been the most
important selection pressure in this study population.
Given the trends in net ownership and kdr L1014S
frequency in Seme, it is not surprising that similarly
high homozygote frequencies were found in samples of
A. gambiae throughout western Kenya in 2009 and
2010. One unexpected finding is the apparently greater
magnitude of phenotypic resistance near the Ugandan
border, as well as the dramatic differences in species
composition near Lake Victoria compared to sites
further north. Due to the decline in A. gambiae along
the lakeshore, inadequate numbers of this species were
available for testing in phenotypic assays. It is, therefore,
possible that phenotypic resistance in A. gambiae along
the lakeshore is similar to that of sites further away and
the few mosquitoes that were tested (<5 per insecticide)
suggest that this is the case. Therefore, the question is
why A. gambiae remains the predominant species in sites
located further from the lakeshore. The current hypoth-
esis is that ITNs have not been in place sufficiently long
in Busia, Malaba, Bungoma, and Kakamega to drive
down local abundance of A. gambiae. Qualitative com-
parisons of the ratio of A. arabiensis to A. gambiae
amongst all these sites suggests that the former species is
rising in frequency in the sites away from the lake shore
as it has at sites near the lake [21]. Indeed, the presence
of A. arabiensis at Bungoma and Kakamega, both sites at
relatively high altitudes where A. gambiae has tradition-
ally been the only species in the complex present, is
particularly striking [53]. However, because historical
data on net ownership in these areas are lacking, baseline
levels prior to the national scale-up of ITN are unknown.
In Asembo and Seme, the change from sub-populations
dominated by A. gambiae to those dominated by
A. arabiensis took about a decade and occurred in
Asembo first, as would be expected if ITNs were the pri-
mary cause [21]. This hypothesis is one that could be
tested by monitoring both ITN coverage and species
composition over the next several years in the region.
One trend that was consistent throughout all popula-
tions examined was the high degree of susceptibility of
A. arabiensis to all insecticides but moderate to high
resistance to pyrethroids in A. gambiae. The persistence
of a species with little to no pyrethroid resistance
(A. arabiensis) compared to a species with moderate to
high levels of pyrethroid resistance (A. gambiae) in an
area with high ITN coverage is somewhat counterintui-
tive. However, it is likely explained by the behaviour of
A. arabiensis which often feeds outdoors and on cattle
and may avoid the insecticide on nets. Anopheles ara-
biensis populations are therefore able to persist, appar-
ently with little to no selection from the pyrethroid
insecticides on nets [21]. Anopheles gambiae popula-
tions, despite having some resistance to pyrethroid
insecticides, are still in decline possibly due to irritancy
of the insecticide on the nets or the physical barrier
imposed by the nets. These observations also suggest
there is a limit to the degree of resistance conferred by
the molecular and biochemical mechanisms currently
present in western Kenya. Similar observations were
made in the early 1990s during a small scale study of
permethrin-treated nets where resistance was detected
within a year of implementation [24], but reached a pla-
teau and even regressed after three years [25]. However,
other resistance mechanisms, possibly coupled with sec-
ondary compensatory mutations, may lead to further
increases in pyrethroid resistance which could lead to a
resurgence of A. gambiae. Despite the rapid decline in
A. gambiae along the lakeshore, malaria transmission-
presumably maintained by A. arabiensis–remains high
with parasite prevalence in children over 45%
(M. Hamel, unpublished data). As ITNs and IRS are
increasingly scaled up throughout Africa, behavioural
avoidance of these interventions may become increas-
ingly important and tools to address species or popula-
tions exhibiting these traits are urgently needed.
Although pyrethroid resistance has been reported
locally or regionally in many parts of sub-Saharan
Africa, the impact of resistance on vector control is not
always consistent between locations. In West Africa, for
example, ITNs treated with the pyrethroid lambdacyha-
lothrin remained effective in reducing malaria preva-
lence in the face of kdr L1014F resistance in Cote
d’Ivoire [54]. In contrast, the failure of IRS using pyre-
throids in Bioko Island was associated with a high fre-
quency of the kdr L1014F allele [47], while in Benin,
N’Guessan et al [55] reported significantly reduced
effectiveness of both ITNs and IRS in a region where
kdr 1014F frequency was 83%. Data from western Kenya
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suggest that the rise of the kdr allele has had limited
impact on the effectiveness of ITNs at least at sites
along the lakeshore. Annual malaria surveys in Asembo
indicated a decline in the prevalence of malaria until
2008. However, prevalence rose in 2009 and remained
high in 2010 (M. Hamel, unpublished data). While the
rise in malaria coincided with the period when the kdr
allele was peaking in A. gambiae, entomologic data sug-
gest that increasing pyrethroid resistance in this species
is not the reason for increasing malaria in Asembo. The
shift from a population dominated by A. gambiae to
A. arabiensis along with the analysis of sporozoite rates
by kdr genotype indicates that the rise of the kdr L1014S
allele has not compromised the efficacy of ITNs along
the Lake Victoria basin. On the other hand, the persis-
tence of A. gambiae in sites further from the lakeshore
where detectable levels of phenotypic resistance were
observed is more worrisome. Nevertheless, the decline
in A. gambiae relative to A. arabiensis from 2009 to
2010 in these sites where A. arabiensis has traditionally
been rare or absent suggests that the hypothesis that
these areas are more recent recipients of ITNs is correct
and further increases in ITN coverage may continue to
suppress A. gambiae populations to the levels observed
along the lakeshore. However, the possibility that
further increases in insecticide resistance, possibly attri-
butable to changes in metabolic enzymes associated
with pyrethroid resistance, are spreading east cannot be
discounted. Continued surveillance of these populations
is needed to monitor for additional changes in insecti-
cide resistance and to assess its impact on the effective-
ness of ITNs.
Conclusions
While the continuing effectiveness of ITNs against
A. gambiae populations along the Lake Victoria basin is
encouraging, the dramatic rise of the kdr L1014S allele
and the detection of phenotypic resistance to pyrethroid
insecticides in this region is alarming. Control failure
due to insecticide resistance can arise rapidly, as has
been observed in IRS programs in South Africa [56] and
Equatorial Guinea [47]. However, it is possible that low
levels of insecticide resistance existed undetected in
these areas and only became apparent when IRS was no
longer effective. Anopheles gambiae populations in wes-
tern Kenya may be primed for further increases in pyre-
throid resistance to a point where ITNs begin to lose
their effectiveness. Monitoring is, therefore, imperative
to quantify changes in insecticide resistance and to elu-
cidate the specific resistance mechanisms operating in
the populations, so that mitigation strategies can be
implemented if and when pyrethroid resistance compro-
mises the effectiveness of ITNs.
Acknowledgements
We gratefully acknowledge the field and laboratory work of Samson Otieno,
Ben Oloo, Richard Owera, Richard Nyawalo, Laban Adero, Walter Nyawade,
George Masula, Richard Amito, Gideon Nyansikera and Joseph Nduati. We
also would like to thank Doug Norris for comments on an earlier version of
the manuscript. This study was supported by grants from the Bill and
Melinda Gates Foundation and the National Science Foundation (NSF grant
EF-072377). Field work was also supported with funding from the US
President’s Malaria Initiative. DKM was partially supported by a postdoctoral
fellowship from the American Society for Microbiology. The findings and
conclusions in this manuscript are those of the authors and do not
necessarily represent the views of the Centers for Disease Control and
Prevention. This paper is published with the permission of the director of
the Kenya Medical Research Institute.
Author details
1Centre for Global Health Research, Kenya Medical Research Institute, PO Box
1578, Kisumu, Kenya.2Centers for Disease Control and Prevention, PO Box
1578, Kisumu, Kenya.3Centre for Biotechnology Research and Development,
Kenya Medical Research Institute, P.O Box 54840 - 00200, Nairobi, Kenya.
4Division of Parasitic Diseases, Centers for Disease Control and Prevention,
4770 Buford Hwy, Mailstop F-42, Atlanta, GA, 30341, USA.5Department of
Microbiology and Molecular Genetics, Michigan State University, East
Lansing, MI, 48824, USA.6Department of Molecular Microbiology and
Immunology, Johns Hopkins Bloomberg School of Public Health, 615 N
Wolfe St, Baltimore, MD, 21205, USA.
Authors’ contributions
DKM, MNB, JMV, MJH, WAH, EDW and JEG designed the study and wrote
the manuscript. DKM, EO, DM, LK performed species identification and RT-
PCR analysis of A. gambiae kdr genotypes. EO, FA, MO and GO conducted
and analysed the phenotypic bioassay data. DKM, EO, EDW and JEG
analysed the data. All authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Received: 15 October 2010 Accepted: 14 January 2011
Published: 14 January 2011
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doi:10.1186/1475-2875-10-10
Cite this article as: Mathias et al.: Spatial and temporal variation in the
kdr allele L1014S in Anopheles gambiae s.s. and phenotypic variability in
susceptibility to insecticides in Western Kenya. Malaria Journal 2011
10:10.
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