Literature DB >> 19374767

Ace-1 duplication in Anopheles gambiae: a challenge for malaria control.

Luc Djogbénou1, Pierrick Labbé, Fabrice Chandre, Nicole Pasteur, Mylène Weill.   

Abstract

BACKGROUND: Insecticide resistance is a rapid and recent evolutionary phenomenon with serious economic and public health implications. In the mosquito Anopheles gambiae s.s., main vector of malaria, resistance to organophosphates and carbamates is mainly due to a single amino-acid substitution in acetylcholinesterase 1 (AChE1). This mutation entails a large fitness cost. However, a resistant duplicated allele of the gene encoding AChE1 (ace-1), potentially associated to a lower fitness cost, recently appeared in An. gambiae.
METHODS: Using molecular phenotype data collected from natural populations from West Africa, the frequency of this duplicated allele was investigated by statistical inference. This method is based on the departure from Hardy-Weinberg phenotypic frequency equilibrium caused by the presence of this new allele.
RESULTS: The duplicated allele, Ag-ace-1(D), reaches a frequency up to 0.65 in Ivory Coast and Burkina Faso, and is potentially present in Benin. A previous study showed that Ag-ace-1(D), present in both M and S molecular forms in different West Africa countries, was generated by a single genetic event. This single origin and its present distribution suggest that this new allele is currently spreading.
CONCLUSION: The spread of this less costly resistance allele could represent a major threat to public health, as it may impede An. gambiae control strategies, and thus increases the risk of malaria outbreaks.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19374767      PMCID: PMC2679766          DOI: 10.1186/1475-2875-8-70

Source DB:  PubMed          Journal:  Malar J        ISSN: 1475-2875            Impact factor:   2.979


Background

Since early 1950s, humans have controlled the populations of many agricultural or medical arthropod pests, mostly with chemical insecticides. After years of success, evolutionary adaptations to these new conditions began to occur and resistance spread rapidly; more than 500 species are now resistant to at least one insecticide [1]. Insecticide resistance is a rapid and recent evolutionary phenomenon, providing insight into the processes of adaptation through natural selection, but it has serious economic and public health implications. In the arms race between arthropods and humans, the mosquito Anopheles gambiae, the main vector of malaria, seems to have just moved up a gear with the emergence of a resistant duplicated allele of the gene encoding acetylcholinesterase 1 (AChE1). AChE1 is a critical enzyme in nerve transmission and the target of two of the most commonly used types of insecticides (organophosphates, OPs, and carbamates, CXs). Like several other mosquito species (including Culex pipiens, the well-studied vector of West Nile virus), An. gambiae displays resistance due to a single amino-acid substitution, from a glycine to a serine at the position 119, in the AChE1 catalytic site (G119S)[2]. In C. pipiens, there is direct and indirect evidence that the resistance allele (ace-1) entails a large fitness cost, probably due to the mutated AChE1 having a much lower level of activity. Homozygous ace-1mosquitoes survive in the presence of insecticide, but are rapidly outcompeted in the absence of insecticide (see review in [3]). Heterozygotes are subject to smaller costs than resistant homozygotes in the absence of insecticide. In treated areas, they survive better than susceptible homozygotes, but are less resistant than ace-1homozygotes. Due to the patchy nature of mosquito control, the generalist heterozygote is advantaged across treated and non-treated areas, although the more specialist resistant and susceptible homozygotes are locally selected in treated and non-treated environments respectively. Moreover, heterozygotes cannot invade due to the segregation burden leading to the loss of the advantage in half of their progeny. Several duplicated alleles (ace-1) have recently appeared, which link a susceptible and a resistant copy of the ace-1 gene on the same chromosome [4]. Duplication thus creates a "permanent heterozygote" allele. The first case of ace-1 gene duplication was recently discovered in An. gambiae [5]. Molecular analysis showed this duplicated allele (Ag-ace-1) to be present at several sites and to have probably spread among the two molecular forms S and M of An. gambiae s.s, by introgression. Unfortunately, it is not possible to design a simple test for studying the frequency of Ag-ace-1due to the lack of features specific to this duplication, as with available genotyping methods carriers of this duplicated allele cannot be distinguished from classical heterozygotes. Thus an indirect method previously developed for C. pipiens was used to estimate Ag-ace-1frequency in the field [6]. The results of this analysis and the potential consequences for An. gambiae population management and on malaria control are discussed.

Methods

Data collection

The study area is shown in Figure 1. Both published data [5,7] and data from new samples were used. The date and location of the sampling sites are shown in Table 1. For each locality, several ponds where sampled in an area a few hundred meter-squares to insure a representative sample of the local population.
Figure 1

. The frequency of Ag-ace-1is given for each An. gambiae molecular form: M (red) and S blue). Samples are described in Table 1. Samples in which Ag-ace-1was detected by molecular analysis are bolded and underlined (Table 2). Significant presence of the duplicated allele (before Bonferroni correction, see Methods) is given with * for P < 0.05, ** for P < 0.01 and *** for P < 0.001.

Table 1

Sample data

#LocalityCountrySampling dateRef
1AbomeyBeninjune 06[5]
2BohiconBeninmay 06[5]
3HouegboBeninapr 06This study
4NiaouliBeninapr 06This study
5PaouignanBeninjune 06[5]
6ZogbodomeyBeninmay 06[5]
7CanaBeninmay 06This study
8BemberekeBeninoct-07This study
9ParakouBeninoct-06This study
10BassilaBeninoct-07This study
11TanguietaBeninoct-07This study
12NatitingouBeninoct-07This study
13DjougouBeninoct-07This study
14DassaBeninoct-07This study
15SavalouBeninoct-07This study
16DarsalamyBurkina Fasoaug 06[7]
17DioulassobaBurkina Fasoapr 06[5,7]
18KuinimaBurkina Fasoapr 06[7]
19MombambaBurkina Fasoaug 06This study
20SabouBurkina Fasoaug 06This study
21SamandeniBurkina Fasoaug 06[7]
22SéguéréBurkina Fasoaug 06[5,7]
23SoumoussoBurkina Fasoaug 06This study
24Vallée du KouBurkina Fasoapr 05[7]
25YegueressoBurkina Fasoaug 06[7]
26BoromoBurkina Fasoaug 06[5]
27ToumodiIvory Coastsept-04[5]
28NiamoueIvory Coastsept-04[5]
29ToumbokroIvory Coastsept-04[5]
30YaokoffikroIvory Coastsept-04[5]
31LoméTogomarch 05This study

For each population shown in Fig. 1 (the corresponding number is indicated in column #), the country, sampling date and study of reference are given.

. The frequency of Ag-ace-1is given for each An. gambiae molecular form: M (red) and S blue). Samples are described in Table 1. Samples in which Ag-ace-1was detected by molecular analysis are bolded and underlined (Table 2). Significant presence of the duplicated allele (before Bonferroni correction, see Methods) is given with * for P < 0.05, ** for P < 0.01 and *** for P < 0.001. Sample data For each population shown in Fig. 1 (the corresponding number is indicated in column #), the country, sampling date and study of reference are given.

Molecular analysis

All samples were collected at the larval stage and reared to adulthood in the laboratory. Genomic DNA was extracted from each field mosquito. The protocol used is a simplified version of Collins et al. [8]: a single mosquito is homogenized in a 1.5 ml Eppendorf tube containing 200 μl of CTAB buffer (100 mM Tris HCL, pH 8.0, 10 mM EDTA, 1.4 M NaCl, 2% CTAB) and incubated at 65°C for 5 min; then 200 μl of chloroform are added. After centrifugation (room temperature, 5 min, 12000 g), the supernatant is moved to a fresh tube, 200 μl of iso-propyl alcohol are added, and the mix is centrifuged again (12000 g, 15 min). After discarding supernatant, the pellet is washed with 70% ethanol, dried and resuspended in DNAse Free water. The molecular form of each individual was determined by a PCR-based test, as described in [9]. The ace-1 genotype was assessed by RFLP analysis (see [5,7]).

Statistical analyses

The presence of a duplicated allele causes an apparent excess of heterozygous [RS] phenotypes and thus a departure from the Hardy-Weinberg proportions expected with two alleles only (ace-1and ace-1) [6]. This departure is related to the frequency of the duplicated allele and was used to estimate Ag-ace-1frequency in An. gambiae populations. The presence of Ag-ace-1was investigated by fitting two models to the phenotypic data for each sample independently: i) a two-alleles-only model (ace-1and ace-1) and ii) a three-allele model, adding the duplicated allele Ag-ace1. The frequency of the duplicated allele was estimated from the excess of heterozygotes observed in each sample, assuming that this excess was due exclusively to the presence of Ag-ace-1[6]. This method is not as accurate as a direct identification of genotypes, but the two methods gave highly concordant results for field samples of C. pipiens [6]. This indirect estimate of Ag-ace1frequency may be biased if the genotypes are not in Hardy-Weinberg equilibrium. However, such a bias is not expected as An. gambiae populations large size prevents drift and as no overdominance leading to heterozygote excess was ever found for resistance [10]. Moreover, previous studies of neutral markers in An. gambiae show either no departure from Hardy-Weinberg expectations or a deficit in heterozygotes, but never an excess, ensuring that this method is conservative (e.g. [11,12]). For each sample, the expected phenotypic distributions were calculated for the S and M molecular forms, using allelic distributions and assuming the ace-1 locus to be at Hardy-Weinberg equilibrium. Phenotype was considered to be a three-state random variable ([RR] corresponding to (R/R) genotype, [RS] corresponding to (R/S), (D/S), (D/R) and (D/D) genotypes, and [SS] corresponding to (S/S) genotype). The log-likelihood of a sample was calculated from the phenotypic multinomial distribution. Let nand fbe the observed number and expected frequency of individuals with phenotype i in population j, respectively. The log likelihood L of observing all the data is proportional to L was maximized, using the Metropolis algorithm [13,14]. Model likelihoods were compared using F-tests: by construction, the three-allele model has a higher likelihood, but the presence of the duplication is considered to be confirmed only if the likelihood of this model is significantly higher than that of the two-allele model (significant P-value). The support limits for the frequency of each allele were also estimated. Finally, the P-values obtained were corrected for multiple testing, using Hommel's sequential Bonferroni correction [15]. The different samples from each country were also pooled to get a higher statistical power at a larger geographical scale (Table 2), and the same analysis as for independent collection sites has been done. As pooling data from different populations is likely to result in a heterozygote deficit (Wahlund effect), this analysis is likely to underestimate any global excess of heterozygotes [6], making the detection of such excess more significant.
Table 2

Ag-ace-1frequency in West Africa.

M formS form


#LocalityNRSDP-valueNRSDP-value
1Abomey3-1--6800.870.130.144 NS
2Bohicon2-1--300.820.180.654 NS
3Houegbo9-1--6200.970.030.715 NS
4Niaouli50-1--1200.960.040.835 NS
5Paouignan0----4100.90.10.352 NS
6Zogbodomey13-1--900.940.060.808 NS
7Cana38-1--2600.830.170.227 NS
8Bembereke0----6200.960.040.647 NS
9Parakou0----2000.970.030.873 NS
10Bassila0----7600.970.030.68 NS
11Tanguieta0----4700.960.040.673 NS
12Natitingou0----4800.990.010.918 NS
13Djougou0----4600.970.030.750 NS
14Dassa0----6400.960.040.652 NS
15Savalou0----2900.960.040.789 NS
Total Bénin115-1--22100.910.090.052 NS
16Darsalamy7-1--20010.096 NS
17Dioulassoba1-1--230.210.550.240.044 *
18Kuinima0----2700.580.420.002 **
19Mombamba8-1--700.850.150.563 NS
20Sabou2-1--1400.760.240.198 NS
21Samandeni20-1--2500.570.430.002 **
22Séguéré10-1--800.50.50.049 *
23Soumousso32-1--1200.710.290.153 NS
24Vallée du Kou8600.960.040.641 NS800.160.340.510.000 ***
25Yegueresso800.870.130.592 NS200.710.290.560 NS
26Boromo380.050.9501.000 NS200.710.290.560 NS
Total Burkina Faso2120.030.9701.000 NS2020.120.530.350.000 ***
27Toumodi1800.410.590.001 ***0----
28Niamoue240.3500.650.000 ***0----
29Toumbokro190.230.610.160.195 NS50010.008 **
30Yaokoffikro0----190.320.320.350.009 **
Total Ivory Coast610.260.40.340.000 ***240.290.290.420.001 ***
31Lomé (Togo)7300.930.070.391 NS1300.880.120.531 NS

For each population sampled, the number of mosquitoes of each of the S and M molecular forms of An. gambiae is given, together with the estimated frequency of the various alleles: R, S and D for ace-1, ace-1and ace-1, respectively. A global estimation is also presented for each country sampled. The populations in italics are those in which Ag-ace-1has been identified by molecular analysis [5]. Finally, the p-value for the test for the presence of ace-1is also given for each population (see Methods), with NS for P ≥ 0.05, * for P < 0.05, ** for P < 0.01 and *** for P < 0.001 (except when no estimate was possible, i.e. when all the mosquitoes of a sample were susceptible). The P-values that remained significant after Bonferroni correction (see methods) are presented in bold; P-values no longer significant after Bonferroni correction are shown in italics.

Ag-ace-1frequency in West Africa. For each population sampled, the number of mosquitoes of each of the S and M molecular forms of An. gambiae is given, together with the estimated frequency of the various alleles: R, S and D for ace-1, ace-1and ace-1, respectively. A global estimation is also presented for each country sampled. The populations in italics are those in which Ag-ace-1has been identified by molecular analysis [5]. Finally, the p-value for the test for the presence of ace-1is also given for each population (see Methods), with NS for P ≥ 0.05, * for P < 0.05, ** for P < 0.01 and *** for P < 0.001 (except when no estimate was possible, i.e. when all the mosquitoes of a sample were susceptible). The P-values that remained significant after Bonferroni correction (see methods) are presented in bold; P-values no longer significant after Bonferroni correction are shown in italics.

Results and discussion

The frequency of the recently discovered duplicated allele of the ace-1 gene in An. gambiae, Ag-ace-1, was investigated in natural populations from West Africa by considering the departure from Hardy-Weinberg proportions caused by its presence [6]. Figure 1 shows the predicted spatial distribution of Ag-ace-1in the S and M forms of An. gambiae, as shown by previous molecular investigations and analyses of heterozygote excess. The probability of Ag-ace-1being present was significant in nine samples (five after Bonferroni correction) from Ivory Coast (four samples) and Burkina Faso (five samples), in both M (two samples) and S (seven samples) molecular forms of An. gambiae (Figure 1 and Table 2). In these samples, the frequency of Ag-ace-1was up to 0.65, with the lowest significant frequency being 0.24, consistent with the expected highly conservative output of the method used. Indeed, this method will detect low frequencies only in large samples; for example, Ag-ace-1was not detected with this method in one of the analysed populations (Boromo, population #26, Table 2), whereas molecular methods proved this duplication to be present [5]. The frequency and the geographic distribution of this duplication are therefore probably underestimated. For example, the analysis of each Benin population independently did not provide any indication supporting the presence of the duplication in this country (Figure 1 and Table 2). Nevertheless, the pooled analysis yields a P-value of 0.052, which points toward the potential presence of Ag-ace-1as this method underestimate the excess of heterozygotes and thus its frequency. However, more data are required to confirm the presence of the duplicated allele in Benin (Table 2). The complete lack of variation of the Ag-ace-1sequence over several countries [5] indicates that this allele was generated by a single genetic event and its current distribution suggests that it is probably spreading. Unfortunately, the spread of this new resistance allele poses a potential major threat to public health, as An. gambiae is the main vector of malaria. Indeed, several studies of a similar allele in C. pipiens have indicated that the duplication entails a lower fitness cost than the single-copy resistance gene, ace-1[4,6] (but see [16]). This is probably also the case for An. gambiae, as the mutated AChE1 gene is also associated with a strong decrease in enzyme activity [17]. The presence and spread of the Ag-ace-1allele may greatly impede An. gambiae control strategies designed to maintain resistance alleles at low frequencies through the use of different insecticides with no cross-resistance in a mosaic or rotation strategy. It has been clearly demonstrated [18,19] that the efficiency of such strategies increases with the fitness cost of resistance.

Conclusion

Insecticides for controlling malaria vectors are a major weapon in the battle between humans and malaria. Unfortunately, these insecticides exert strong selection pressure on vector populations, causing the spread of resistance genes, such as the resistance allele observed at the ace-1 locus in An. gambiae. The long-term use of an insecticide promotes the selection of new resistant variants, with a high risk of selecting a low (or null)-cost variant. The ace-1 duplicated allele recently appeared in An. gambiae is probably an example of such a low-cost variant. It is shown here that the presence of this duplicated allele, known from the molecular analysis of a few mosquitoes in some samples from Burkina Faso and Ivory Coast [5] is largely distributed in several countries of Western Africa, sometimes at high frequencies, and that it is probably spreading. To prevent such spreads of resistance genes, it is crucial to develop the largest possible number of complementary means of control (e.g. larval insecticides, mosquito nets, biological agents, etc.) and to use them wisely. However, the emergence of ace-1 duplication in natural populations of An. gambiae, has just given mosquitoes the edge in this particular battle, seriously undermining our efforts to control vector populations and increasing the risk of malaria outbreaks.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

LD designed the study, acquired the data and wrote the manuscript. PL analysed the data and wrote the manuscript. NP, FC and MW contributed to the design of the study and for draft and revision of the manuscript. All authors read and approved the final manuscript.
  13 in total

1.  Tracking the evolution of insecticide resistance in the mosquito Culex pipiens.

Authors:  T Lenormand; D Bourguet; T Guillemaud; M Raymond
Journal:  Nature       Date:  1999-08-26       Impact factor: 49.962

2.  Comparative genomics: Insecticide resistance in mosquito vectors.

Authors:  Mylène Weill; Georges Lutfalla; Knud Mogensen; Fabrice Chandre; Arnaud Berthomieu; Claire Berticat; Nicole Pasteur; Alexandre Philips; Philippe Fort; Michel Raymond
Journal:  Nature       Date:  2003-05-08       Impact factor: 49.962

3.  Genetic differentiation of Anopheles gambiae populations from East and west Africa: comparison of microsatellite and allozyme loci.

Authors:  T Lehmann; W A Hawley; L Kamau; D Fontenille; F Simard; F H Collins
Journal:  Heredity (Edinb)       Date:  1996-08       Impact factor: 3.821

4.  Molecular identification of sympatric chromosomal forms of Anopheles gambiae and further evidence of their reproductive isolation.

Authors:  G Favia; A della Torre; M Bagayoko; A Lanfrancotti; N Sagnon; Y T Touré; M Coluzzi
Journal:  Insect Mol Biol       Date:  1997-11       Impact factor: 3.585

5.  Comparison of Anopheles gambiae and Culex pipiens acetycholinesterase 1 biochemical properties.

Authors:  Haoués Alout; Luc Djogbénou; Claire Berticat; Fabrice Chandre; Mylène Weill
Journal:  Comp Biochem Physiol B Biochem Mol Biol       Date:  2008-03-28       Impact factor: 2.231

6.  Complexities in the genetic structure of Anopheles gambiae populations in west Africa as revealed by microsatellite DNA analysis.

Authors:  G C Lanzaro; Y T Touré; J Carnahan; L Zheng; G Dolo; S Traoré; V Petrarca; K D Vernick; C E Taylor
Journal:  Proc Natl Acad Sci U S A       Date:  1998-11-24       Impact factor: 11.205

7.  Independent duplications of the acetylcholinesterase gene conferring insecticide resistance in the mosquito Culex pipiens.

Authors:  Pierrick Labbé; Arnaud Berthomieu; Claire Berticat; Haoues Alout; Michel Raymond; Thomas Lenormand; Mylène Weill
Journal:  Mol Biol Evol       Date:  2007-02-05       Impact factor: 16.240

8.  A ribosomal RNA gene probe differentiates member species of the Anopheles gambiae complex.

Authors:  F H Collins; M A Mendez; M O Rasmussen; P C Mehaffey; N J Besansky; V Finnerty
Journal:  Am J Trop Med Hyg       Date:  1987-07       Impact factor: 2.345

9.  Characterization of insensitive acetylcholinesterase (ace-1R) in Anopheles gambiae (Diptera: Culicidae): resistance levels and dominance.

Authors:  L Djogbénou; M Weill; J M Hougard; M Raymond; M Akogbéto; F Chandre
Journal:  J Med Entomol       Date:  2007-09       Impact factor: 2.278

10.  Identification and geographic distribution of the ACE-1R mutation in the malaria vector Anopheles gambiae in south-western Burkina Faso, West Africa.

Authors:  Luc Djogbénou; Roch Dabiré; Abdoulaye Diabaté; Pierre Kengne; Martin Akogbéto; Jean Marc Hougard; Fabrice Chandre
Journal:  Am J Trop Med Hyg       Date:  2008-02       Impact factor: 2.345

View more
  35 in total

1.  Crystal structure of acetylcholinesterase catalytic subunits of the malaria vector Anopheles gambiae.

Authors:  Qian Han; Dawn M Wong; Howard Robinson; Haizhen Ding; Polo C H Lam; Maxim M Totrov; Paul R Carlier; Jianyong Li
Journal:  Insect Sci       Date:  2017-05-08       Impact factor: 3.262

Review 2.  Copy number variation (CNV) and insecticide resistance in mosquitoes: evolving knowledge or an evolving problem?

Authors:  David Weetman; Luc S Djogbenou; Eric Lucas
Journal:  Curr Opin Insect Sci       Date:  2018-04-13       Impact factor: 5.186

3.  Distribution of ace-1R and resistance to carbamates and organophosphates in Anopheles gambiae s.s. populations from Côte d'Ivoire.

Authors:  Ludovic P Ahoua Alou; Alphonsine A Koffi; Maurice A Adja; Emmanuel Tia; Philippe K Kouassi; Moussa Koné; Fabrice Chandre
Journal:  Malar J       Date:  2010-06-16       Impact factor: 2.979

4.  Insecticide resistance allele frequencies in Anopheles gambiae before and after anti-vector interventions in continental Equatorial Guinea.

Authors:  Michael R Reddy; Adrian Godoy; Kirstin Dion; Abrahan Matias; Kevin Callender; Anthony E Kiszewski; Immo Kleinschmidt; Frances C Ridl; Jeffrey R Powell; Adalgisa Caccone; Michel A Slotman
Journal:  Am J Trop Med Hyg       Date:  2013-02-25       Impact factor: 2.345

5.  The genome of Anopheles darlingi, the main neotropical malaria vector.

Authors:  Osvaldo Marinotti; Gustavo C Cerqueira; Luiz Gonzaga Paula de Almeida; Maria Inês Tiraboschi Ferro; Elgion Lucio da Silva Loreto; Arnaldo Zaha; Santuza M R Teixeira; Adam R Wespiser; Alexandre Almeida E Silva; Aline Daiane Schlindwein; Ana Carolina Landim Pacheco; Artur Luiz da Costa da Silva; Brenton R Graveley; Brian P Walenz; Bruna de Araujo Lima; Carlos Alexandre Gomes Ribeiro; Carlos Gustavo Nunes-Silva; Carlos Roberto de Carvalho; Célia Maria de Almeida Soares; Claudia Beatriz Afonso de Menezes; Cleverson Matiolli; Daniel Caffrey; Demetrius Antonio M Araújo; Diana Magalhães de Oliveira; Douglas Golenbock; Edmundo Carlos Grisard; Fabiana Fantinatti-Garboggini; Fabíola Marques de Carvalho; Fernando Gomes Barcellos; Francisco Prosdocimi; Gemma May; Gilson Martins de Azevedo Junior; Giselle Moura Guimarães; Gustavo Henrique Goldman; Itácio Q M Padilha; Jacqueline da Silva Batista; Jesus Aparecido Ferro; José M C Ribeiro; Juliana Lopes Rangel Fietto; Karina Maia Dabbas; Louise Cerdeira; Lucymara Fassarella Agnez-Lima; Marcelo Brocchi; Marcos Oliveira de Carvalho; Marcus de Melo Teixeira; Maria de Mascena Diniz Maia; Maria Helena S Goldman; Maria Paula Cruz Schneider; Maria Sueli Soares Felipe; Mariangela Hungria; Marisa Fabiana Nicolás; Maristela Pereira; Martín Alejandro Montes; Maurício E Cantão; Michel Vincentz; Miriam Silva Rafael; Neal Silverman; Patrícia Hermes Stoco; Rangel Celso Souza; Renato Vicentini; Ricardo Tostes Gazzinelli; Rogério de Oliveira Neves; Rosane Silva; Spartaco Astolfi-Filho; Talles Eduardo Ferreira Maciel; Turán P Urményi; Wanderli Pedro Tadei; Erney Plessmann Camargo; Ana Tereza Ribeiro de Vasconcelos
Journal:  Nucleic Acids Res       Date:  2013-06-12       Impact factor: 16.971

6.  Insecticide resistance to organophosphates in Culex pipiens complex from Lebanon.

Authors:  Mike A Osta; Zeinab J Rizk; Pierrick Labbé; Mylène Weill; Khouzama Knio
Journal:  Parasit Vectors       Date:  2012-07-03       Impact factor: 3.876

7.  Development of an allele-specific, loop-mediated, isothermal amplification method (AS-LAMP) to detect the L1014F kdr-w mutation in Anopheles gambiae s. l.

Authors:  Athanase Badolo; Kyioshi Okado; Wamdaogo M Guelbeogo; Hiroka Aonuma; Hironori Bando; Shinya Fukumoto; N'Fale Sagnon; Hirotaka Kanuka
Journal:  Malar J       Date:  2012-07-06       Impact factor: 2.979

8.  Ivermectin to reduce malaria transmission: a research agenda for a promising new tool for elimination.

Authors:  Carlos J Chaccour; Kevin C Kobylinski; Quique Bassat; Teun Bousema; Chris Drakeley; Pedro Alonso; Brian D Foy
Journal:  Malar J       Date:  2013-05-07       Impact factor: 2.979

9.  Dissecting the mechanisms responsible for the multiple insecticide resistance phenotype in Anopheles gambiae s.s., M form, from Vallée du Kou, Burkina Faso.

Authors:  Rachel M Kwiatkowska; Naomi Platt; Rodolphe Poupardin; Helen Irving; Roch K Dabire; Sara Mitchell; Christopher M Jones; Abdoulaye Diabaté; Hilary Ranson; Charles S Wondji
Journal:  Gene       Date:  2013-02-01       Impact factor: 3.688

10.  Multiple insecticide resistance in Anopheles gambiae s.l. populations from Burkina Faso, West Africa.

Authors:  Moussa Namountougou; Frédéric Simard; Thierry Baldet; Abdoulaye Diabaté; Jean Bosco Ouédraogo; Thibaud Martin; Roch K Dabiré
Journal:  PLoS One       Date:  2012-11-26       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.