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Article

Contrasting Patterns of Asaia Association with Pyrethroid Resistance Escalation between the Malaria Vectors Anopheles funestus and Anopheles gambiae

by
Fleuriane Metissa Djondji Kamga
1,2,
Leon M. J. Mugenzi
1,
Magellan Tchouakui
1,
Maurice Marcel Sandeu
1,3,
Claudine Grace Tatsinkou Maffo
1,
Maximilienne Ascension Nyegue
2 and
Charles S. Wondji
1,4,*
1
Centre for Research in Infectious Diseases (CRID), Yaoundé P.O. Box 13591, Cameroon
2
Department of Microbiology, Faculty of Science, University of Yaoundé I, Yaoundé P.O. Box 812, Cameroon
3
Department of Microbiology and Infectious Diseases, School of Veterinary Medicine and Sciences, University of Ngaoundéré, Ngaoundéré P.O. Box 454, Cameroon
4
Vector Biology Department, Liverpool School of Tropical Medicine, Liverpool L3 5QA, UK
*
Author to whom correspondence should be addressed.
Microorganisms 2023, 11(3), 644; https://doi.org/10.3390/microorganisms11030644
Submission received: 24 January 2023 / Revised: 21 February 2023 / Accepted: 27 February 2023 / Published: 2 March 2023
(This article belongs to the Section Gut Microbiota)
Browse Figures
Versions Notes

Abstract

:
Microbiome composition has been associated with insecticide resistance in malaria vectors. However, the contribution of major symbionts to the increasingly reported resistance escalation remains unclear. This study explores the possible association of a specific endosymbiont, Asaia spp., with elevated levels of pyrethroid resistance driven by cytochrome P450s enzymes and voltage-gated sodium channel mutations in Anopheles funestus and Anopheles gambiae. Molecular assays were used to detect the symbiont and resistance markers (CYP6P9a/b, 6.5 kb, L1014F, and N1575Y). Overall, genotyping of key mutations revealed an association with the resistance phenotype. The prevalence of Asaia spp. in the FUMOZ_X_FANG strain was associated with the resistance phenotype at a 5X dose of deltamethrin (OR = 25.7; p = 0.002). Mosquitoes with the resistant allele for the markers tested were significantly more infected with Asaia compared to those possessing the susceptible allele. Furthermore, the abundance correlated with the resistance phenotype at 1X concentration of deltamethrin (p = 0.02, Mann-Whitney test). However, for the MANGOUM_X_KISUMU strain, findings rather revealed an association between Asaia load and the susceptible phenotype (p = 0.04, Mann-Whitney test), demonstrating a negative link between the symbiont and permethrin resistance. These bacteria should be further investigated to establish its interactions with other resistance mechanisms and cross-resistance with other insecticide classes.

1. Introduction

Malaria remains a major public health burden in the tropical world, particularly in Africa, where >90% of malaria cases and mortality have been reported [1]. Malaria prevention has recently been boosted by the adoption of the first vaccine in 2021 [2]. However, vector control through the use of insecticide-based interventions such as long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) remains the cornerstone of malaria control and elimination programs [3]. Even so, increasing reports of elevated levels of pyrethroid resistance in the major vectors, including Anopheles gambiae and Anopheles funestus, are threatening to derail the efficacy of these control tools [4]. In several countries, including Malawi [5], Uganda [6], and Ghana [7], An. funetus and An. gambiae populations were both reported to exhibit elevated levels of insecticide resistance, surviving exposure to not only 10X the discriminating concentration (DC) of pyrethroids but also piperonyl butoxide (PBO) plus pyrethroid-treated nets [6]. Similarly, in Burkina Faso, a considerable reduction in the efficacy of the treated nets was observed with An. gambiae [8] and recently in Mozambique against An. funestus s.s. [9]. The causal mechanisms underlying this phenomenon of resistance escalation remain uncharacterized and could be multifactorial. The common insecticide resistance mechanisms are metabolic resistance, notably through the overexpression of detoxification enzymes including cytochrome P450s, modification of the insecticide target site (voltage-gated sodium channel), and thickening of the cuticle [10,11]. In addition, constituents of the Anopheles microbiota have recently emerged as contributing factors to insecticide resistance [12,13,14,15].
Arthropods, like almost all other invertebrates, live in symbiosis with their microbiota, which considerably influences their life traits: fitness, nutrient supply, protection against pathogens through immune system stimulation, development, and synthesis of specific toxins [16]. Mosquito microbiota could be defined as a heterogeneous and complex environment consisting of bacteria, fungi, viruses, parasites, and other eukaryotic cells that stably or transiently infect the cuticle and internal organs. Their composition in Anopheles species has been studied mainly by culturing or sequencing 16S rRNA. Although the composition of this microbiota is dynamic and variable depending on the Anopheles species, an overview provided by Gendrin and Christophides (2013) reported the identification of approximately 41 bacterial genera in ten Anopheles species, with nine being highly abundant. These include Pseudomonas, Aeromonas, Asaia, Comamonas, Elizabethkingia, Enterobacter, Klebsiella, Pantoea, and Serratia [17]. One interesting aspect of the Anopheles microbiota is its negative influence on Plasmodium development within mosquitoes [18,19]. For instance, it has been shown that bacterial growth after a blood meal causes the synthesis of antimicrobial peptides and other immune effectors that have antiparasitic properties [20]. In addition, an Enterobacter strain (EspZ) isolated from wild Anopheles arabiensis mosquitoes was found to directly inhibit Plasmodium development via elevated synthesis of reactive oxygen species (ROS) [19].
These findings also make it plausible that a link could exist between microorganisms and the resistance of these mosquitoes to different classes of insecticide [21]. Recent studies have highlighted a link between insecticide resistance and the bacterial symbionts of arthropods. For example, in agriculture, this notion has been clearly described for the bean bug Riptortus pedestris, where Burkholderia bacteria were shown to establish a specific and beneficial symbiosis with the bugs, conferring resistance to fenitrothion (organophosphate) [22]. Similarly, in the moth Plutella xylostella, bacteria have been shown to influence some key biological traits of their hosts. Enterococcus spp. increased their resistance to chlorpyrifos (organophosphate), whereas that of Serratia spp. was rather reduced [23]. With the advent of new molecular tools, research in this field has extended to pathogen vectors such as Anopheles. Dada et al., (2018), using whole-metagenome sequencing of the microbiota of fenitrothion-sensitive and resistant strains of Anopheles albimanus, revealed a significant enrichment of organophosphate-degrading enzymes but also an overabundance of Klebsiella spp. in the resistant populations. It has been suggested that a possible selection of these bacteria may have occurred in parallel with the resistance phenotype in response to previous insecticide exposure [24]. Furthermore, in metagenomic studies carried out by Dada et al., (2019) on the F1 offspring of pyrethroid-resistant mosquitoes showed a significant increase in bacteria of the genus Pseudomonas and Pantoea species known to metabolize pyrethroids [14]. Similarly, a study conducted by Omoke in 2021, reported the significant presence of the bacterial taxa Sphingobacterium, Lysinibacillus, and Streptococcus in populations of An. gambiae that are resistant to 5X the standard dose of permethrin [12].
Recently, phylogenetic analyses of Asaia spp. Sequences, isolated from Ceratitis capitata, revealed that some strains have an ancestral pyrethroid hydrolase gene that could affect pyrethroid insecticide metabolism [25]. In Anopheles coluzzii species, a significant enrichment of Asaia bacteria was reported in susceptible mosquitoes compared to resistant mosquitoes, which highlights that the contribution of this symbiont in determining the resistance phenotype is very complex and host-specific [13]. This controversial role of Asaia spp., in pyrethroid resistance makes it an interesting target, especially as it is one of the best-characterized symbionts. Asaia spp. which belongs to the Acetobacteraceae family, was isolated for the first time from the Anopheles species. It is a gram-negative, aerobic, rod-shaped bacterium that is transmitted vertically from parent to offspring [26] and horizontally from one mosquito to another during feeding or copulation [27,28]. This enables it to form stable and long-term associations with its hosts over several generations. It can be easily cultured and transformed with exogenous DNA [26]. Considering the hypothesis that mosquito microbiota is affected by insecticide exposure, this study was conducted to comparatively characterize any association between the Asaia community and the escalation of pyrethroid resistance observed in An. funestus and An. gambiae species. These findings revealed a statistical association between the prevalence and abundance of this symbiont and deltamethrin-resistant mosquitoes in the An. funestus species. Furthermore, a negative association between the symbiont and permethrin resistance was observed in the An. gambiae strain.

2. Materials and Methods

2.1. Mosquito Strains and Rearing

This study was carried out using the major malaria vectors, An. funestus and An. gambiae. Given that the already characterized major insecticide resistance markers are almost fixed in the field mosquito populations, this hinders the possibility of clearly linking the genotypes to the presence of a particular bacterium. To overcome this issue, two reciprocal crosses between resistant and susceptible mosquitoes were established at the insectarium of the Center for Research in Infectious Diseases (CRID). For An. funestus, the fully susceptible strain FANG (homozygous susceptible to all resistance markers) colonized from southern Angola [29] was crossed with the fully resistant strain FUMOZ-R (homozygous resistant to some cytochrome P450 markers) originating from Mozambique [30]. For An. gambiae, crossings between KISUMU (the susceptible strain) [31] and field-resistant mosquitoes collected from MANGOUM (an agricultural setting located in the western region of Cameroon) [32] were established.
To commence the crossing, one hundred pupae of each strain were collected and individually placed in hemolysis tubes for the adults to emerge. Fifty females of the resistant colony were mixed in the same cage (30 cm × 30 cm) with fifty males of the susceptible mosquito colony (and reciprocally) for random mating. Females were allowed to lay eggs, and larvae were reared and fed with Tetramin® baby fish food until their emergence as adult mosquitoes in the first generation (F1). The generated hybrids were reared until the fourth progeny (F4) under standard insectary conditions of 27 ± 2 °C and 80  ±  10% relative humidity.

2.2. Evaluating the Susceptibility Profile of An. funestus and An. gambiae Strains to Pyrethroids

Susceptibility assays against pyrethroids were performed with the parental lines: FUMOZ (N = 193, 8 replicates), MANGOUM (N = 160, 8 replicates), and the An. funestus F4 hybrid strains (N = 257, 10 replicates) as well as the An. gambiae hybrid strains (N = 232, 10 replicates) following the WHO protocol [33]. They were exposed to type I pyrethroid (permethrin (0.75%)) and type II pyrethroid (deltamethrin (0.05%)). Twenty to twenty-five females (3 to 5 days old) were aspirated and transferred into holding tubes for 1 h, then introduced into tubes containing insecticide-treated papers. Control tubes with non-impregnated papers were prepared in parallel for each bioassay. After 1 h of exposure, the knockdown effect was scored, and mosquitoes were transferred into holding tubes. Mortality was recorded 24 h post-exposure. The bioassay room conditions were set up to 27 ± 2 °C and 75 ± 10% relative humidity. The guidelines for the interpretation of bioassays were established based on the WHO insecticide susceptibility testing guidelines. “Resistance” and “Susceptible” phenotypes were confirmed by mortalities below 90% and greater than 98%, respectively [33]. Based on the mortality rate observed at the diagnostic dose (1X), a total of 1311 An. funestus (58 replicates) and 1410 An. gambiae (64 replicates) hybrid mosquitoes were used to evaluate the intensity of resistance to pyrethroids using dose-response assays (5X and 10X) and the time-course exposure method. According to the WHO guidelines, we confirmed “low intensity of resistance” with a mortality rate of mosquitoes of more than 98% at 5X the diagnostic concentration of insecticide. “Moderate intensity of resistance” was considered with mortality rates below 98% at 5X and greater than 98% at 10X concentrations of insecticide. “High intensity of resistance” was therefore confirmed with a mortality rate superior to 98% at 10X concentration of the insecticide [33]. Depending on the phenotype, samples were stored in silica gel at −20 °C for molecular analysis.

2.3. Assessing the Contribution of Known Molecular Markers to the Escalation of Pyrethroid Resistance in An. funestus and An. gambiae

Before evaluating the role of Asaia in the escalation of resistance in the above strains, we first assessed the contribution of the recently detected cytochrome P450 markers (CYP6P9a, CYP6P9b, and 6.5kb-SV) and the target site mutations (L1014F and N1575Y).

2.3.1. Contribution of CYP6P9a, CYP6P9b, and 6.5 kb-SV Mutations to the Escalation of Pyrethroid Resistance in An. funestus

The individual mosquitoes (alive and dead) of hybrid An. funestus (F4) were sterilized with 70% ethanol and rinsed twice with 1X PBS (Phosphate Buffer Solution) to remove non-attached bacteria, thus preventing sample contamination. Genomic DNA was extracted following the Livak protocol [34], and the respective cytochrome P450 markers were genotyped using established protocols. CYP6P9a and CYP6P9b were genotyped using RFLP-PCR [35,36]. The primers listed in Table S1 were used in the first step of the amplification of the partial CYP6P9a and CYP6P9b upstream regions. DNA amplicons were visualized on 2.0% agarose gel stained with Midori Green, and the results were interpreted based on the observed band sizes. For the second step, the TaqI enzyme (restriction site (5′-TCGA-3′)) and Tsp45I enzyme (restriction site (5′-GTSAC-3′)) were used to digest the PCR products to detect the CYP6P9a_R and CYP6P9b_R resistant alleles, respectively, as previously described [35,36]. The structural variation of 6.5 kb-SV was also detected using the PCR method [37]. Three primers flanking the insertion region (FG_5F, FG_3R, and FZ_INS5R) were used for genotyping the mutation (Table S1). The PCR products were resolved on a 1.5% agarose gel stained with Midori Green and visualized on a UV transilluminator. Odds ratios and Fisher’s exact tests were used to establish the statistical significance of any association between these pyrethroid resistance markers and the ability of mosquitoes to survive increasing concentrations of insecticides.

2.3.2. Contribution of the Voltage-Gated Sodium Channel (VGSC) Mutations, L1014F and N1575Y, to the Escalation of Pyrethroid Resistance in An. gambiae

Genomic DNA of hybrid An. gambiae (MANGOUM_X_KISUMU F4) mosquitoes was extracted as described above and used to genotype the L1014F and N1575Y voltage-gated sodium channel (VGSC) mutations via TaqMan SNP genotyping assays [38]. Probes combined with primers were differentiated using two specific fluorescent dyes, FAM corresponding to homozygous-resistant genotypes (RR) and HEX to homozygous-susceptible (SS). The sequences of primers used for these methods are given in Table S1. The statistical test to evaluate association was performed as described above.

2.4. Assessing the Contribution of Asaia spp. in the Escalation of Pyrethroid Resistance in An. funestus and An. gambiae Mosquitoes

In addition to host-mediated resistance mechanisms, the role of Asaia spp. in insecticide resistance was investigated. First, we determined the statistical association between the prevalence of Asaia spp. and the resistance phenotype/genotype. Thereafter, we checked for any correlation between the abundance of the bacteria and the resistance phenotype/genotype.

2.4.1. Detection of Asaia spp. Frequency in Anopheles Strains

The presence of Asaia spp. was determined via a conventional PCR assay using specific primers (16S RNA_F and Asarev_R) that amplify 676 base pairs (bp) of a partial sequence of the Asaia 16S rRNA gene [39]. PCR products were visualized on a 1.5% agarose gel stained with Midori green dye using a UV transilluminator. Samples of the expected size were selected randomly and purified using Exonuclease-I (Exo I) and Shrimp Alkaline Phosphatase (Exo-SAP protocol) according to the New England Biolabs protocol (NEB, Ipswich, MA, USA), which involved incubation at 37 °C for 10 min and 80 °C for 20 min. Purified amplicons were sequenced by Microsynth Seqlab GmbH company (Göttingen city, Germany) and analyzed using BLASTn in NCBI (www.ncbi.nlm.nih.gov/blast/; accessed on 17 March 2022) to confirm effective amplification of the target Asaia spp. gene. Odds ratios and Fisher exact tests were the statistical tests used to assess the association between the prevalence of the symbiont and the resistant phenotype/genotype.

2.4.2. Quantification of Asaia spp. in Anopheles Strain

The abundance of Asaia was assessed in duplicate using quantitative polymerase chain reaction (qPCR). The AsaH1_F and Asar_R primers were used to quantify the symbiont in each DNA template (Table S1). qPCR of Ribosomal Protein S7 (single copy gene) of both species (VectorBase ID: AFUN007153 in An. funestus; orthologous to An. gambiae: AGAP010592) was performed in parallel to normalize the Asaia load (Table S1). The reactions were run in a total volume of 10 μL, containing 5 μL of 2X Brilliant II SYBR® Green QPCR Master Mix (Agilent), 1 µM of each primer, 1 μL of nuclease-free water, and 2 μL template DNA. The reactions were run on an MX3005 real-time PCR system (Agilent) following a dissociation curve (95 °C for 10 s, 65 °C for 60 s, and 97 °C for 1 s [40]. The standard curve of each gene was generated by diluting one-tenth of the DNA extracted from Asaia cultures and the purified PCR amplicons of the ribosomal protein S7 gene. Ct values of >35 were considered uninfected or undetectable. The normalized amount of bacterial DNA was estimated by the relative ratio of Asaia gene copy numbers to RSP-7 gene copy numbers. Mann Whitney and Kruskal Wallis non-parametric tests were used to compare the load of Asaia spp. between phenotype (alive and dead) and genotype, respectively, via GraphPad Prism 8.2.0.

3. Results

3.1. Resistance Profile of Anopheles Funestus and Anopheles gambiae Strains

The laboratory-resistant strain FUMOZ experienced low mortality rates when exposed to permethrin (1X: 27.6 ± 1.1%) and deltamethrin (1X: 25.9 ± 2.2%). The F4 progeny of hybrid strain FUMOZ_X_FANG showed possible resistance to permethrin (1X: 93.9 ± 3.7%), but a persistent level of resistance to deltamethrin (1X: 63.3 ± 3.1%), suggesting a greater level of resistance to type II pyrethroids. In the MANGOUM field mosquitoes, the resistance pattern to the two insecticides was as follows: permethrin (1X: 8.7 ± 3.7%) and deltamethrin (1X: 6.4 ± 3.3), and the crossing MANGOUM_X_KISUMU F4 progeny exhibited a higher mortality rate to permethrin (1X: 77.4 ± 5.6%) and deltamethrin (1X: 83.3 ± 2.9%) (Figure 1).
Due to the resistance status of An. funestus hybrid strains to permethrin and deltamethrin, we conducted intensity bioassays with 5X and 10X concentrations of these insecticides. A high intensity of resistance to deltamethrin was observed at 5X (82.3 ± 4.2%) and 10X (93.4 ± 1.6%) doses with the F4 progeny of the FUMOZ_X_FANG hybrids. A significant increase in mortality was detected in mosquitoes exposed to deltamethrin 5X compared to 10X (χ2 = 20.4, p < 0.0001). However, for the same strain, we observed a low-intensity resistance to permethrin 5X and 10X, with mortality rates of 98.9 ± 1.1% and 100%, respectively. The MANGOUM_X_KISUMU F4 hybrid (An. gambiae) mosquitoes displayed a moderate intensity of resistance to all pyrethroids tested. This was observed with mortality rates of 96.7 ± 2.1% and 100% for permethrin 5X and 10X, respectively, and 97.7 ± 2.3% for deltamethrin 5X and 99.3 ± 0.7% for deltamethrin 10X (Figure 2). Regarding the profile we observed for the MANGOUM_X_KISUMU hybrid mosquitoes, they were more resistant to permethrin when compared to deltamethrin. For this reason, a time-course exposure method was used to select highly permethrin-resistant (HR) and highly susceptible (HS) phenotypes. HR mosquitoes were selected with a 90 min exposure time (mortality rate = 91.6 ± 1.5%), whereas HS mosquitoes were selected at a 3 min exposure time (mortality rate = 24.5 ± 10.7%) (Figure 2).

3.2. Contribution of Cytochrome P450 Markers in the Escalation of Deltamethrin Resistance in An. funestus

In total, 309 DNA samples (Alive = 138, Dead = 140, Non-exposed = 31) were genotyped for CYP6P9a, CYP6P9b, and 6.5-kb insertion. The proportion of each genotype is presented in Figure 3 below.
A significant difference in the distribution of genotypes of each mutation was observed between dead and alive mosquitoes after exposure to 1X deltamethrin (CYP6P9a: χ2: 54.58, p < 0.0001; CYP6P9b: χ2: 60.32, p < 0.0001; 6.5 kb-SV: χ2: 52.82, p < 0.0001). The frequency of homozygote resistant (RR) and heterozygote resistant (RS) of each marker was higher in the alive group compared to the dead group. Assessment of the odds ratio (OR) revealed a stronger association between the resistant allele of each marker and the ability of the mosquitoes to survive exposure to deltamethrin, supporting the involvement of these alleles in the observed resistance (Table S2). Concerning the increased intensity of resistance, a significant difference was found in the distribution of genotypes between alive and dead mosquitoes exposed to 5X DC of deltamethrin (CYP6P9a/χ2: 39.81, p < 0.0001; CYP6P9b/χ2: 25.01, p < 0.0001; 6.5 kb/χ2: 38.72, p < 0.0001). The same pattern was observed with 10X the concentration (CYP6P9a/χ2: 42.27, p < 0.0001; CYP6P9b/χ2: 39.85%, p < 0.0001; 6.5 kb/χ2: 45.24, p < 0.0001). Mosquitoes possessing the resistant allele had a greater ability to survive exposure to 5X and 10X DC of deltamethrin compared to those with the susceptible allele, indicating that these markers are associated with the escalation of deltamethrin resistance in An. funestus (Table S2).
Looking at the cumulative impact of these markers, Figure 4 depicts the distribution of genotypes of two combined markers (CYP6P9a/CYP6P9b; CYP6P9a/6.5 kb; CYP6P9b/6.5 kb) and three markers (CYP6P9a/CYP6P9b/6.5 kb). We observed that mosquitoes harboring a combination of double- or triple homozygote-resistant genotypes (for example, CYP6P9a (RR)/CYP6P9b (RR) or CYP6P9a (RR)/CYP6P9b (RR)/6.5 kb (RR)) were significantly more likely to survive exposure to the different doses of deltamethrin compared to those completely lacking the mutations (for example, CYP6P9a (SS)/CYP6P9b (SS) or CYP6P9a (SS)/CYP6P9b (SS)/6.5 kb (SS)), as shown in the Table S2. Heterozygote mosquitoes were also more likely to survive exposure to this insecticide than their susceptible homozygote counterparts (Table S2). A significant association was found between the presence of the double and triple homozygote resistant genotypes and the ability of hybrid mosquitoes to survive exposure to 1X, 5X, and 10X deltamethrin, showing that these markers combine to exacerbate the resistance to deltamethrin (Table S2).

3.3. Impact of VGSC Mutations on the Escalation of Permethrin Resistance in An. gambiae

In total, 77 hybrid females (Alive 90 min = 42, Dead 03 min = 35, Non-exposed = 40) were genotyped for the L1014F and N1575Y mutations in HR and HS after exposure to permethrin 1X. A significant difference in genotype distribution was observed between the HR and HS groups for the L1014F (χ2: 52.2; p < 0.0001) and N1575Y (χ2: 13.7; p = 0.00021) mutations. The homozygote-resistant RR at the L1014F-VGSC locus was only present among the live mosquitoes and was completely absent in the dead group (Figure 5), supporting that this VGSC-resistant marker is associated with permethrin resistance (OR = 2793; p = 0.0001; CI = 53.4 to 146,077.1). Regarding the N1575Y mutation, homozygote RR was absent, and the frequency of the heterozygote genotype-RS was higher in the survivor group than in the dead group (χ2: 13.5; p = 0.0002). A greater proportion of the susceptible genotype-SS was in the dead group than in the alive group (Figure 5). A significant association was found between the ability of mosquitoes with the N1575Y heterozygote genotype to survive exposure to permethrin 1X compared to those with the susceptible genotype (OR = 6.2; p = 0.0004; CI = 2.3 to 16.9). When the two markers were combined, the proportion of RR/RS and RS/RS genotypes was higher in highly resistant than in susceptible mosquitoes (Figure 5). Overall, possessing the two VGSC markers confers a significant ability to survive exposure to permethrin compared to the double susceptible homozygotes (OR = 1763; p = 0.0002; CI = 33.3 to 93,077.7) (Table S2).

3.4. Contribution of Asaia spp. to the Escalation of Pyrethroid Insecticide Resistance in Malaria Vectors

3.4.1. Prevalence of Asaia spp. in Anopheles Strains

Overall, Asaia spp. was screened in 387 An. funestus and 197 An. gambiae, including parental and crossing mosquitoes. Prevalence rates of 77% (298/387) and 83.2% (163/196) were recorded in An. funestus and An. gambiae, respectively (Figure 6). Of the 20 PCR amplicons sent for sequencing, 18 samples with a sequence size of approximately 470 bp were subjected to a BLASTn search in GenBank (NCBI). All sequences were homologous to the reference sequences of Asaia spp. No significant difference in Asaia prevalence was observed between the two species (χ2: 2.9; p = 0.08). Focusing on An. funestus, the frequency of Asaia was almost similar between the laboratory-resistant strain FUMOZ (55%, 22/40) and the reference susceptible colony FANG (50%, 20/40). However, the FUMOZ_X_FANG hybrid line was significantly more infected with Asaia spp. (83.4%, 256/307) than FUMOZ (χ2: 17.8; p< 0.0001) and FANG (χ2: 24.1; p< 0.0001) (Figure 4). Concerning An. gambiae species, the prevalence of Asaia was higher in KISUMU (77.5%, 31/40) and the hybrid MANGOUM_X_KISUMU (100%, 116/116), but lower in the MANGOUM field strains (40%, 16/40). As noticed in An. funestus, the hybrid strain MANGOUM_X_KISUMU was also significantly more infected with the symbiont when compared to the pure lines MANGOUM (χ2: 81.7; p < 0.0001) and the susceptible strain KISUMU (χ2: 27.5; p < 0.0001) (Figure 6).

Assessment of the Link between the Prevalence of Asaia spp. and Insecticide Resistance in Hybrids FUMOZ_X_FANG

Almost all the alive mosquitoes after exposure to deltamethrin were more infected with Asaia spp. with a frequency of 98.5% (136/138), compared to the dead group, which registered a prevalence of 79.7% (110/138) (χ2 = 25.5, p < 0.0001). This was confirmed by the odds ratio, which showed that mosquitoes infected with Asaia had a greater chance of surviving exposure than uninfected mosquitoes (OR = 17.3, p = 0.0001, CI = 4 to 74.3). The same pattern was observed with different concentrations of insecticide, where resistant mosquitoes infected with the symbiont were more likely to survive 1X, 5X, and 10X concentrations of deltamethrin compared to the susceptible ones (Table 1). However, a significant association between the prevalence of Asaia and the resistance phenotype was found only at 5X concentrations of deltamethrin (OR = 25.8, p = 0.002, CI = 3.2 to 203.7).
Considering the genotypes, for all the mutations evaluated, a comparison of the Asaia proportion between genotypes showed that homozygous resistant-RR individuals were significantly more infected with the bacteria when compared to the other genotypes. Overall, harboring the resistance alleles CYP6P9a_R, CYP6P9b_R, and 6.5 kb-SV_R increased the likelihood of individuals being more infected with the symbiont compared to the susceptible allele (Figure 7). When the markers were evaluated together, the double- and triple-resistant genotypes (RR/RR and RR/RR/RR) were found to be much more infected with Asaia spp. compared to the double- and triple-susceptible or heterozygote genotypes. It would also be interesting to highlight an increase in the odds ratio when the markers were combined, thus demonstrating that the presence of more than two homozygous resistant genotypes in mosquitoes would further favour more infection with Asaia than with a single allele (Table S3).

Association between the Prevalence of Asaia spp. and Insecticide Resistance in Hybrids MANGOUM_X_KISUMU

All individuals of this strain (alive and dead) were infected by Asaia, hence, no correlation was observed between the phenotype and the infection by the symbiont. Similar to the L1014F and N1575Y VGSC markers, no significant association was found between the marker and Asaia.

3.4.2. Abundance of Asaia spp. in Anopheles Hybrids Strains

The qPCR assay for Asaia spp. was performed on 415 Anopheles hybrid mosquitoes after exposure to insecticides (An. funestus = 307, An. gambiae = 116) (Table S4). The relative abundance of Asaia spp. in An. funestus species ranges from 0.0 to 4392.4 copies, with a median of 11.5 [IQR = 3.2–33.8] and a mean of 47.1. An. gambiae crossing, on the other hand, presented a bacterial quantity between 1.8 and 106,619, with a median of 472.5 [IQR = 143.2–1282.4] and a mean of 2849.9. Using the Mann-Whitney test, we observed a significant difference in the abundance of Asaia between the two species (p < 0.0001) (Figure 6).

Assessment of the Link between the Quantity of Asaia spp. and Insecticide Resistance in Hybrids FUMOZ_X_FANG

A comparison of the bacterial load between alive (n = 135) and dead (n = 136) mosquitoes revealed that in resistant individuals, the density varied from 0.1 to 4392, with a median of 15.9 [IQR = 5.6–33.5] and a mean of 64.5. The susceptible group had a load range of 0.0–479.9, a median of 11.2 [IQR = 3.9–38.8], and a mean of 31.5. There was no significant difference in symbiont abundance between the two groups (p = 0.3; Mann-Whitney test). Considering the insecticide dose, we observed a significant difference in the amount of Asaia between alive and dead mosquitoes only at 1X (p = 0.02; Mann-Whitney test) (Figure 8).
The same analysis was performed using the previously identified resistance markers. Using the non-parametric ANOVA test (Kruskal-Wallis test), we found no significant association between any genotype of the different mutations and the abundance of the bacteria (CYP6P9a: p = 0.4726; CYP6P9b: p = 0.8231, 6.5 kb-SV: p = 0.3227). The same observation was made for the combined markers (CYP6P9a/CYP6P9b: p = 0.8384; CYP6P9a/6.5 kb-SV: p = 0.4912; CYP6P9b/6.5 kb-SV: p = 0.7517; CYP6P9a/CYP6P9b/6.5 kb-SV: p = 0.9527).

Association between Asaia spp. Load and Insecticide Resistance in Anopheles gambiae Hybrid Strains

Regarding the bacterial quantity, the Asaia load of the HR mosquitoes fluctuated from 1.83 to 15,990, with a median of 533.2 [IQR = 104.6–1264] and a mean of 1632. The HS strain had a bacterial load ranging from 27.3 to 106,619, with a median of 1045 [IQR = 381.6–2739] and a mean of 6.96. Susceptible mosquitoes were thus significantly more loaded with Asaia spp. than the resistant group, as shown in Figure 8 (p = 0.04; Mann-Whitney test). In addition, we observed that the symbiont was more abundant in the SS and SS/SS genotypes for all the VGSC markers tested compared to other genotypes. However, this was not significant, confirming the negative association between Asaia load and permethrin resistance in An. gambiae (Table 2).

4. Discussion

This study explored the possible association of the Asaia symbiont with the observed increased pyrethroid resistance in An. funestus and An. gambiae. These findings established the contribution of cytochrome P450 markers to the increasing resistance intensity and revealed a contrasting association of the Asaia symbiont with insecticide resistance in both Anopheles species.

4.1. High Level of Resistance to Pyrethroids in An. funestus and An. gambiae Strains

Here, we report a very low mortality rate of FUMOZ mosquitoes against discriminating doses of pyrethroids, showing that the selection for a resistance phenotype with deltamethrin over generations for this reference strain generated a relatively stable resistance to pyrethroids over time [30]. In addition, the results of the WHO bioassays conducted on the hybrid strain An. funestus (reared in the absence of insecticide selection) showed an escalation of resistance to deltamethrin. This high level of resistance might be due in part to the combined action of several cytochrome P450-associated loci (rp1) previously identified in the FUMOZ-R strain [41]. Indeed, previous studies have indicated the predominant role of metabolic genes, driven primarily by the duplicated cytochrome P450 genes CYP6P9a and CYP6P9b, which allow mosquitoes to withstand exposure to pyrethroids [9,42].
While focusing on the field population of An. gambiae collected from Mangoum, we registered a high level of resistance to pyrethroids. Similar results were previously obtained in the same locality, revealing a very low mortality rate of mosquitoes to discriminating doses of not only pyrethroids but also carbamates, organophosphates, and organochlorines [32]. This could be explained by the presence of VGSC mutation sites imposed by the massive use of insecticides in the locality, probably from both LLINs and agricultural activities, as recently described [32]. The MANGOUM_X_KISUMU mosquito crosses were more susceptible to pyrethroids than the parental lines, exhibiting low resistance intensity. Several cases of reversal insecticide resistance have been reported in An. gambiae reared under laboratory conditions [43,44,45]. This indicates that resistance in the field can significantly decrease over time if mosquitoes are not continuously subjected to insecticide pressure [44].

4.2. Cytochrome P450 Markers and VGSC Mutations Are Partially Associated with the Escalation of Pyrethroid Resistance in Mosquitoes

Genotyping of CYP6P9a, CYP6P9b, and 6.5 kb-SV in An. funestus revealed a strong association between these markers and the ability of mosquitoes to survive increasing doses of deltamethrin. This is in line with previous genomic studies, which suggested that metabolic detoxification of cytochrome P450 monooxygenases (CYP6P9a/b) appears to be one of the major mechanisms of pyrethroid resistance in both laboratory and field strains of An. funestus [35,42,46,47,48,49]. The increased expression of these genes, driven by polymorphisms in the cis-regulatory regions, coupled with allelic variation in the coding region with key amino acid changes [50], would produce stronger metabolic activity against both type I and II pyrethroids. The 6.5-kb SV, on the other hand, has been shown to act as an activator of the expression of the duplicated P450 genes [37]. Indeed, the near fixation of the three genetic elements has been shown to increase metabolic detoxification and escalate the resistance of vectors to pyrethroids [37]. However, their presence could not completely explain the aggravation of deltamethrin resistance observed in this hybrid strain, as our findings demonstrated a decrease in the association between the mutations and the resistance phenotype with high doses of insecticide. Thus, it suggests that other mechanisms besides the metabolic resistance loci could be involved.
Molecular detection of VGSC mutations in MANGOUM_X_KISUMU crossed mosquitoes revealed a high frequency of the L1014F resistant allele in highly resistant mosquitoes after 90 min of exposure to permethrin. Indeed, over the past decades, studies have associated this substitution of domain II of the voltage-gated sodium channel with DDT and pyrethroid resistance [51,52,53]. Similarly, a high proportion of the N1575Y allele was detected in surviving mosquitoes, further supporting its association with pyrethroid resistance, as it was found to compensate for the deleterious fitness effects of L1014F [54]. Nonetheless, these two mutations do not account for all the genetic variance of the super resistance to permethrin detected in this strain, and further research into other factors contributing to the escalation of pyrethroid resistance in this An. gambiae strain is required.
The significant correlation observed between both cytochrome P450 and VGSC alleles provided a suitable template for investigating the association between the presence/abundance of specific symbionts and the resistance phenotype and genotype.

4.3. Detection of Asaia spp. in Anopheles Strains

Our data revealed that Asaia spp. occurred in both An. funestus and An. gambiae strains, showing that the bacteria is tightly associated with several species of Anopheles mosquitoes [55]. This ability to colonize Anopheles populations is attributed to its potential for horizontal transmission (through pre-adult and adult mosquito oral feeding), as well as vertical transmission from mother to progeny via ovarian infection to eggs [56,57]. Furthermore, we observed that the offspring of the hybrids (An. funestus and An. gambiae) were much more infected by the symbiont than the parental lines, thus demonstrating that the crossing carried out would have favored the infection by Asaia. This could be explained by the fact that the physiological modifications engendered by the crossing, could have increased the prevalence of Asaia to compensate for the demand for essential nutrients and metabolic cofactors (such as carbon, nitrogen, and vitamins) provided by the symbiont [58].

4.4. Asaia spp. Is Associated with the Escalation of Pyrethroid Resistance in An. funestus

This study also demonstrated that the prevalence of Asaia was significantly higher in FUMOZ_X_FANG resistant hybrids than in susceptible hybrids at each concentration of insecticide tested accompanied by a significant association with the escalation of deltamethrin resistance at 5X. However, this association was reduced at 10X, probably because other factors play a greater role at this resistance level. The presence of the Asaia symbiont could alter or reduce the effects of an insecticide in mosquitoes through direct degradation of pyrethroids by the bacterial strain. This was demonstrated in an agricultural pest, the bean bug Riptortus pedestrians, for which Burkholderia bacteria were able to metabolize fenitrothion, an organophosphate pesticide [22]. Moreover, phylogenomic analysis of Asaia strains isolated from Ceratitis capitata (fruit fly) led to the detection of an ancestral hydrolase gene that can contribute to the degradation of pyrethroids [25]. Future genomic and transcriptomic studies of the Asaia strain from FUMOZ-R could help detect bacterial detoxification genes. Another mechanism through which Asaia could contribute to resistance in this strain is by indirectly increasing the expression of multiple detoxification enzymes capable of breaking down pyrethroids. This mechanism was described in An. stephensi, where midgut bacteria boost the activity of alpha-esterase and glutathione S-transferases, resulting in temephos resistance [59]. In addition, our findings also showed that homozygote-resistant genotypes for all mutations (6.5 kb, CYP6P9a, and CYP6P9b) or combined mutations were more infected compared to the susceptible genotypes. Despite the lack of information on the association between genetic factors and mosquito microbial variations, we hypothesized that selecting FUMOZ-R mosquitoes for deltamethrin resistance would result in the generation of a parallel resistant strain of Asaia to this insecticide, which could be transmitted to the progeny. It is possible that there was a tandem selection of a resistant Asaia strain with the cytochrome P450 alleles, which can explain why resistant homozygote genotypes are more infected with the symbiont. Therefore, it will be interesting to isolate and compare the Asaia strain from the resistant (FUMOZ) and susceptible (FANG) laboratory strains and field mosquitoes.
Regarding the bacterial load in mosquitoes, the results of this study showed a significant association between the quantity of Asaia and the resistant phenotype after exposure to the diagnostic concentration of deltamethrin (1X). This finding supports recent observations that selection pressure leads to the increase of resistance alleles against the effectiveness of insecticides. This could also have an evolutionary impact on the insect microbiota by competing with and altering factors that influence microbial load in the host [21]. Indeed, the abundance of symbionts and the overall composition of the microbiota can rapidly evolve in an insect population in response to natural and artificial selection pressures [21]. This ability has been clearly described in the experimental selection of laboratory strains of the aphid Aphis gossypii Glover with spirotetramat, where a significant induction of the relative abundance of several bacterial taxa in their host was detected [60]. Moreover, we also observed that the density/quantity of the Proteobacteria Asaia seems to be higher in homozygote-resistant genotypes than in other genotypes for all markers tested, although this was not significant. This is in line with the results obtained by Berticat et al. (2002), who observed that higher densities of Wolbachia correlate positively with the presence of insecticide resistance alleles in laboratory and natural populations of Culex pipiens mosquitoes [61]. They suggested that mosquitoes may be less efficient in controlling Wolbachia density when they carry ester- or ace-organophosphate resistant alleles because of the physiological cost of resistance. A similar immune deficiency associated with cytochrome P450-based resistance could have occurred and reduced the ability of resistant mosquitoes (FUMOZ_X_FANG) to control the density of Asaia.

4.5. Asaia Load Is Negatively Associated with the Pyrethroid Resistance in Anopheles gambiae

In contrast to An. funestus, all An. gambiae mosquitoes were infected by Asaia, suggesting that An. gambiae is more permissive to the symbiont. This pattern correlates with previous observations on the Afro-tropical vector sowing that Asaia was able to greatly colonize several tissues in An. gambiae [56]. Since all An. gambiae individuals were infected with the bacterium, no association could be established between the prevalence of Asaia and the resistance phenotype/genotype in this species.
Nevertheless, in terms of abundance, the quantity of Asaia was significantly greater in the susceptible phenotype. This result corroborates a study that suggested that Asaia and Serratia are overabundant in the susceptible field of Anopheles coluzzii mosquitoes exposed to deltamethrin [13]. Although the mechanism behind this phenomenon is not well understood, it could be similar to the case of Bacillus thuringiensis, which produces SmEnhancin, which perforates the midgut of Helicoverpa armigera [62]. Asaia could secrete some substances that increase the permeability of the internal target organs to pyrethroid in An. gambiae. Concerning the resistance markers, we observed a high abundance of the bacteria in the homozygous-SS genotype compared to the other genotypes. This pattern was different from that obtained for An. funestus, indicating a variable relationship between this symbiont and insecticide resistance in both species. This could be associated not only with the different resistance mechanisms at play, with P450-based metabolic resistance having a different interaction with symbionts than VGSC-based target-site resistance, but also with the different types of insecticides used. Further investigations are needed to understand the contrasting pattern of the effect of Asaia on pyrethroid resistance in both species and both resistance mechanisms.

5. Conclusions

Our findings demonstrate that in the An. funestus strain, the prevalence of the bacteria was mainly associated with the resistant phenotype at 5X and genotype, while for abundance, we detected a difference in the Asaia load between alive and dead at 1X. Contrarily, for An. gambiae, only the quantification of the bacteria allowed us to visualize that the infection was associated with a susceptible phenotype/genotype. This study provides further evidence for the possible role of Anopheles endosymbionts in insecticide resistance. Nevertheless, additional studies are required to better understand how Asaia could contribute to insecticide resistance and how this varies between different vector species.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/microorganisms11030644/s1, Table S1: List of primers and probes, Table S2: Association between markers and insecticide resistance, Table S3: Association between prevalence of Asaia and genotypes, Table S4: Relative abundance of Asaia in Anopheles species.

Author Contributions

Conceptualization, F.M.D.K., L.M.J.M. and C.S.W.; data curation, F.M.D.K., L.M.J.M. and M.T.; formal analysis, F.M.D.K., L.M.J.M., M.T. and M.M.S.; funding acquisition, C.S.W.; investigation, F.M.D.K., L.M.J.M., M.T. and C.S.W.; methodology, F.M.D.K., L.M.J.M., M.M.S., C.G.T.M. and C.S.W.; project administration, C.S.W.; resources, C.S.W.; software, F.M.D.K., L.M.J.M., M.T., M.M.S. and C.G.T.M.; supervision, L.M.J.M., M.T., M.A.N. and C.S.W.; visualization C.S.W.; writing—original draft, F.M.D.K.; writing—review and editing, F.M.D.K., L.M.J.M., M.T. and C.S.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by a Wellcome Trust Senior Research Fellowship in Biomedical Sciences awarded to C.S.W. (217188/Z/19/Z).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data generated or analysed during this study are included within the article and its additional files.

Acknowledgments

The authors are grateful to the research team members at CRID, especially Bertrand Mbakam for his support during the laboratory process. Nelly Manuella Tchatchoua, Tekoh Theofelix Anyerengue, and Carlos S. Djoko Tagne for their scientific inputs. The authors are also thanking Armel N. Tedjou and Arnaud Tepa for providing the Mangoum mosquito samples.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. World Health Organization. World Malaria Report 2021; World Health Organization: Geneva, Switzerland, 2021. [Google Scholar]
  2. World Health Organization. Malaria Vaccine Implementation, P. Full Evidence Report on the RTS,S/AS01 Malaria Vaccine; WHO: Geneva, Switzerland, 2021; p. 90. [Google Scholar]
  3. Bhatt, S.; Weiss, D.J.; Cameron, E.; Bisanzio, D.; Mappin, B.; Dalrymple, U.; Battle, K.E.; Moyes, C.L.; Henry, A.; Eckhoff, P.A.; et al. The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015. Nature 2015, 526, 207–211. [Google Scholar] [CrossRef] [Green Version]
  4. Hemingway, J. The way forward for vector control. Science 2017, 358, 998–999. [Google Scholar] [CrossRef]
  5. Menze, B.D.; Kouamo, M.F.; Wondji, M.J.; Tchapga, W.; Tchoupo, M.; Kusimo, M.O.; Mouhamadou, C.S.; Riveron, J.M.; Wondji, C.S. An Experimental Hut Evaluation of PBO-Based and Pyrethroid-Only Nets against the Malaria Vector Anopheles funestus Reveals a Loss of Bed Nets Efficacy Associated with GSTe2 Metabolic Resistance. Genes 2020, 11, 143. [Google Scholar] [CrossRef] [Green Version]
  6. Tchouakui, M.; Mugenzi, L.M.J.; Menze, B.D.; Khaukha, J.N.T.; Tchapga, W.; Tchoupo, M.; Wondji, M.J.; Wondji, C.S. Pyrethroid Resistance Aggravation in Ugandan Malaria Vectors Is Reducing Bednet Efficacy. Pathogens 2021, 10, 415. [Google Scholar] [CrossRef]
  7. Mugenzi, L.M.; Akosah-Brempong, G.; Tchouakui, M.; Menze, B.D.; Tekoh, T.A.; Tchoupo, M.; Nkemngo, F.N.; Wondji, M.J.; Nwaefuna, E.K.; Osae, M.; et al. Escalating pyrethroid resistance in two major malaria vectors Anopheles funestus and Anopheles gambiae (s.l.) in Atatam, Southern Ghana. BMC Infect. Dis. 2022, 22, 799. [Google Scholar] [CrossRef]
  8. Toé, K.H.; Jones, C.M.; N’Fale, S.; Ismail, H.M.; Dabiré, R.K.; Ranson, H. Increased Pyrethroid Resistance in Malaria Vectors and Decreased Bed Net Effectiveness, Burkina Faso. Emerg. Infect. Dis. 2014, 20, 1691. [Google Scholar] [CrossRef]
  9. Riveron, J.M.; Huijben, S.; Tchapga, W.; Tchouakui, M.; Wondji, M.J.; Tchoupo, M.; Irving, H.; Cuamba, N.; Maquina, M.; Paaijmans, K.; et al. Escalation of Pyrethroid Resistance in the Malaria Vector Anopheles funestus Induces a Loss of Efficacy of Piperonyl Butoxide–Based Insecticide-Treated Nets in Mozambique. J. Infect. Dis. 2019, 220, 467–475. [Google Scholar] [CrossRef] [Green Version]
  10. Corbel, V.; N’Guessan, R. Distribution, Mechanisms, Impact and Management of Insecticide Resistance in Malaria Vectors: A Pragmatic Review. In Anopheles Mosquitoes–New Insights into Malaria Vectors; Manguin, S., Ed.; InTech: Tokyo, Japan, 2013. [Google Scholar]
  11. Riveron, J.M.; Tchouakui, M.; Mugenzi, L.; Menze, B.D.; Chiang, M.-C.; Wondji, C.S. Insecticide Resistance in Malaria Vectors: An Update at a Global Scale. In Towards Malaria Elimination—A Leap Forward; Manguin, S., Dev, V., Eds.; InTech: Tokyo, Japan, 2018. [Google Scholar]
  12. Omoke, D.; Kipsum, M.; Otieno, S.; Esalimba, E.; Sheth, M.; Lenhart, A.; Njeru, E.M.; Ochomo, E.; Dada, N. Western Kenyan Anopheles gambiae showing intense permethrin resistance harbour distinct microbiota. Malar. J. 2021, 20, 77. [Google Scholar] [CrossRef]
  13. Pelloquin, B.; Kristan, M.; Edi, C.; Meiwald, A.; Clark, E.; Jeffries, C.L.; Walker, T.; Dada, N.; Messenger, L.A. Overabundance of Asaia and Serratia Bacteria Is Associated with Deltamethrin Insecticide Susceptibility in Anopheles coluzzii from Agboville, Côte d’Ivoire. Microbiol. Spectr. 2021, 9, e00157-21. [Google Scholar] [CrossRef]
  14. Dada, N.; Lol, J.C.; Benedict, A.C.; López, F.; Sheth, M.; Dzuris, N.; Padilla, N.; Lenhart, A. Pyrethroid exposure alters internal and cuticle surface bacterial communities in Anopheles albimanus. ISME J. 2019, 13, 2447–2464. [Google Scholar] [CrossRef] [Green Version]
  15. Ingham, V.A.; Tennessen, J.A.; Lucas, E.R.; Elg, S.; Yates, H.C.; Carson, J.; Guelbeogo, W.M.; Sagnon, N.F.; Hughes, G.L.; Heinz, E.; et al. Integration of whole genome sequencing and transcriptomics reveals a complex picture of the reestablishment of insecticide resistance in the major malaria vector Anopheles coluzzii. PLoS Genet. 2021, 17, e1009970. [Google Scholar] [CrossRef]
  16. Douglas, A.E. Multiorganismal Insects: Diversity and Function of Resident Microorganisms. Annu. Rev. Entomol. 2015, 60, 17–34. [Google Scholar] [CrossRef] [Green Version]
  17. Gendrin, M.; Christophides, G.K. The Anopheles Mosquito Microbiota and Their Impact on Pathogen Transmission. In Anopheles Mosquitoes—New Insights into Malaria Vectors; Manguin, S., Ed.; InTech: Tokyo, Japan, 2013. [Google Scholar]
  18. Bahia, A.C.; Dong, Y.; Blumberg, B.J.; Mlambo, G.; Tripathi, A.; BenMarzouk-Hidalgo, O.J.; Chandra, R.; Dimopoulos, G. Exploring Anopheles gut bacteria for Plasmodium blocking activity. Environ. Microbiol. 2014, 16, 2980–2994. [Google Scholar] [CrossRef] [Green Version]
  19. Cirimotich, C.M.; Dong, Y.; Clayton, A.M.; Sandiford, S.L.; Souza-Neto, J.A.; Mulenga, M.; Dimopoulos, G. Natural microbe-mediated refractoriness to Plasmodium infection in Anopheles gambiae. Science 2011, 332, 855–858. [Google Scholar] [CrossRef] [Green Version]
  20. Meister, S.; Agianian, B.; Turlure, F.; Relógio, A.; Morlais, I.; Kafatos, F.C.; Christophides, G.K. Anopheles gambiae PGRPLC-Mediated Defense against Bacteria Modulates Infections with Malaria Parasites. PLoS Pathog. 2009, 5, e1000542. [Google Scholar] [CrossRef] [Green Version]
  21. Pietri, J.E.; Liang, D. The Links Between Insect Symbionts and Insecticide Resistance: Causal Relationships and Physiological Tradeoffs. Ann. Entomol. Soc. Am. 2018, 111, 92–97. [Google Scholar] [CrossRef]
  22. Kikuchi, Y.; Hayatsu, M.; Hosokawa, T.; Nagayama, A.; Tago, K.; Fukatsu, T. Symbiont-mediated insecticide resistance. Proc. Natl. Acad. Sci. USA 2012, 109, 8618–8622. [Google Scholar] [CrossRef] [Green Version]
  23. Xia, X.; Sun, B.; Gurr, G.M.; Vasseur, L.; Xue, M.; You, M. Gut Microbiota Mediate Insecticide Resistance in the Diamondback Moth, Plutella xylostella (L.). Front. Microbiol. 2018, 9, 25. [Google Scholar] [CrossRef] [Green Version]
  24. Dada, N.; Sheth, M.; Liebman, K.; Pinto, J.; Lenhart, A. Whole metagenome sequencing reveals links between mosquito microbiota and insecticide resistance in malaria vectors. Sci. Rep. 2018, 8, 2084. [Google Scholar] [CrossRef] [Green Version]
  25. Comandatore, F.; Damiani, C.; Cappelli, A.; Ribolla, P.E.M.; Gasperi, G.; Gradoni, F.; Capelli, G.; Piazza, A.; Montarsi, F.; Mancini, M.V.; et al. Phylogenomics Reveals that Asaia Symbionts from Insects Underwent Convergent Genome Reduction, Preserving an Insecticide-Degrading Gene. mBio 2021, 12, e00106-21. [Google Scholar] [CrossRef]
  26. Favia, G.; Ricci, I.; Marzorati, M.; Negri, I.; Alma, A.; Sacchi, L.; Bandi, C.; Daffonchio, D. Bacteria of the Genus Asaia: A Potential Paratransgenic Weapon Against Malaria. In Transgenesis and the Management of Vector-Borne Disease; Aksoy, S., Ed.; Springer: New York, NY, USA, 2008; Volume 627, pp. 49–59. [Google Scholar]
  27. Moran, N.A.; Dunbar, H.E. Sexual acquisition of beneficial symbionts in aphids. Proc. Natl. Acad. Sci. USA 2006, 103, 12803–12806. [Google Scholar] [CrossRef] [Green Version]
  28. Bassene, H.; Niang, E.H.A.; Fenollar, F.; Doucoure, S.; Faye, O.; Raoult, D.; Sokhna, C.; Mediannikov, O. Role of plants in the transmission of Asaia sp., which potentially inhibit the Plasmodium sporogenic cycle in Anopheles mosquitoes. Sci. Rep. 2020, 10, 7144. [Google Scholar] [CrossRef]
  29. Hunt, R.H.; Brooke, B.D.; Pillay, C.; Koekemoer, L.L.; Coetzee, M. Laboratory selection for and characteristics of pyrethroid resistance in the malaria vector Anopheles funestus. Med. Vet. Entomol. 2005, 19, 271–275. [Google Scholar] [CrossRef]
  30. Hargreaves, K.; Koekemoer, L.L.; Brooke, B.D.; Hunt, R.H.; Mthembu, J.; Coetzee, M. Anopheles funestus resistant to pyrethroid insecticides in South Africa. Med. Vet. Entomol. 2000, 14, 181–189. [Google Scholar] [CrossRef]
  31. Besansky, N.J.; Stump, A.D.; Vulule, J.M.; Atieli, F.K. Dynamics of the Pyrethroid Knockdown Resistance Allele in Western Kenyan Populations of Anopheles Gambiae in Response to Insecticide-Treated Bed Net Trials. Am. J. Trop. Med. Hyg. 2004, 70, 591–596. [Google Scholar] [CrossRef]
  32. Tepa, A.; Kengne-Ouafo, J.A.; Djova, V.S.; Tchouakui, M.; Mugenzi, L.M.J.; Djouaka, R.; Pieme, C.A.; Wondji, C.S. Molecular Drivers of Multiple and Elevated Resistance to Insecticides in a Population of the Malaria Vector Anopheles gambiae in Agriculture Hotspot of West Cameroon. Genes 2022, 13, 1206. [Google Scholar] [CrossRef]
  33. World Health Organization; Food and Agriculture Organization of the United Nations. Global Situation of Pesticide Management in Agriculture and Public Health: Report of a 2018 WHO-FAO Survey; World Health Organization: Geneva, Switzerland, 2019. [Google Scholar]
  34. Livak, K.J. Organization and Mapping of A Sequence on the Drosophila Melanogaster X and Y Chromosomes That is Transcribed During Spermatogenesis. Genetics 1984, 107, 611–634. [Google Scholar] [CrossRef]
  35. Weedall, G.D.; Mugenzi, L.M.J.; Menze, B.D.; Tchouakui, M.; Ibrahim, S.S.; Amvongo-Adjia, N.; Irving, H.; Wondji, M.J.; Tchoupo, M.; Djouaka, R.; et al. A cytochrome P450 allele confers pyrethroid resistance on a major African malaria vector, reducing insecticide-treated bednet efficacy. Sci. Transl. Med. 2019, 11, eaat7386. [Google Scholar] [CrossRef] [Green Version]
  36. Mugenzi, L.M.J.; Menze, B.D.; Tchouakui, M.; Wondji, M.J.; Irving, H.; Tchoupo, M.; Hearn, J.; Weedall, G.D.; Riveron, J.M.; Wondji, C.S. Cis-regulatory CYP6P9b P450 variants associated with loss of insecticide-treated bed net efficacy against Anopheles funestus. Nat. Commun. 2019, 10, 4652. [Google Scholar] [CrossRef] [Green Version]
  37. Mugenzi, L.M.J.; Menze, B.D.; Tchouakui, M.; Wondji, M.J.; Irving, H.; Tchoupo, M.; Hearn, J.; Weedall, G.D.; Riveron, J.M.; Cho-Ngwa, F.; et al. A 6.5-kb intergenic structural variation enhances P450-mediated resistance to pyrethroids in malaria vectors lowering bed net efficacy. Mol. Ecol. 2020, 29, 4395–4411. [Google Scholar] [CrossRef]
  38. Bass, C.; Nikou, D.; Blagborough, A.M.; Vontas, J.; Sinden, R.E.; Williamson, M.S.; Field, L.M. PCR-based detection of Plasmodium in Anopheles mosquitoes: A comparison of a new high-throughput assay with existing methods. Malar. J. 2008, 7, 177. [Google Scholar] [CrossRef] [Green Version]
  39. Rami, A.; Raz, A.; Zakeri, S.; Dinparast Djadid, N. Isolation and identification of Asaia sp. in Anopheles spp. mosquitoes collected from Iranian malaria settings: Steps toward applying paratransgenic tools against malaria. Parasites Vectors 2018, 11, 367. [Google Scholar] [CrossRef] [Green Version]
  40. Jeffries, C.L.; Lawrence, G.G.; Golovko, G.; Kristan, M.; Orsborne, J.; Spence, K.; Hurn, E.; Bandibabone, J.; Tantely, M.L.; Raharimalala, F.N.; et al. Novel Wolbachia Strains in Anopheles Malaria Vectors from Sub-Saharan Africa. bioRxiv 2018. [Google Scholar] [CrossRef]
  41. Wondji, C.S.; Irving, H.; Morgan, J.; Lobo, N.F.; Collins, F.H.; Hunt, R.H.; Coetzee, M.; Hemingway, J.; Ranson, H. Two duplicated P450 genes are associated with pyrethroid resistance in Anopheles funestus, a major malaria vector. Genome Res. 2009, 19, 452–459. [Google Scholar] [CrossRef] [Green Version]
  42. Riveron, J.M.; Irving, H.; Ndula, M.; Barnes, K.G.; Ibrahim, S.S.; Paine, M.J.I.; Wondji, C.S. Directionally selected cytochrome P450 alleles are driving the spread of pyrethroid resistance in the major malaria vector Anopheles funestus. Proc. Natl. Acad. Sci. USA 2013, 110, 252–257. [Google Scholar] [CrossRef] [Green Version]
  43. Williams, J.; Flood, L.; Praulins, G.; Ingham, V.A.; Morgan, J.; Lees, R.S.; Ranson, H. Characterisation of Anopheles strains used for laboratory screening of new vector control products. Parasites Vectors 2019, 12, 522. [Google Scholar] [CrossRef] [Green Version]
  44. Machani, M.G.; Ochomo, E.; Zhong, D.; Zhou, G.; Wang, X.; Githeko, A.K.; Yan, G.; Afrane, Y.A. Phenotypic, genotypic and biochemical changes during pyrethroid resistance selection in Anopheles gambiae mosquitoes. Sci. Rep. 2020, 10, 19063. [Google Scholar] [CrossRef]
  45. Tchouakui, M.; Oruni, A.; Assatse, T.; Manyaka, C.R.; Tchoupo, M.; Kayondo, J.; Wondji, C.S. Fitness cost of target-site and metabolic resistance to pyrethroids drives restoration of susceptibility in a highly resistant Anopheles gambiae population from Uganda. PLoS ONE 2022, 17, e0271347. [Google Scholar] [CrossRef]
  46. Brooke, B.D.; Kloke, G.; Hunt, R.H.; Koekemoer, L.L.; Tem, E.A.; Taylor, M.E.; Small, G.; Hemingway, J.; Coetzee, M. Bioassay and biochemical analyses of insecticide resistance in southern African Anopheles funestus (Diptera: Culicidae). Bull. Entomol. Res. 2001, 91, 265–272. [Google Scholar] [CrossRef]
  47. Amenya, D.A.; Naguran, R.; Lo, T.C.M.; Ranson, H.; Spillings, B.L.; Wood, O.R.; Brooke, B.D.; Coetzee, M.; Koekemoer, L.L. Over expression of a Cytochrome P450 (CYP6P9) in a Major African Malaria Vector, Anopheles funestus, Resistant to Pyrethroids: CYP6P9 overexpressed in resistant An. funestus. Insect Mol. Biol. 2008, 17, 19–25. [Google Scholar] [CrossRef]
  48. Riveron, J.M.; Ibrahim, S.S.; Chanda, E.; Mzilahowa, T.; Cuamba, N.; Irving, H.; Barnes, K.G.; Ndula, M.; Wondji, C.S. The highly polymorphic CYP6M7 cytochrome P450 gene partners with the directionally selected CYP6P9a and CYP6P9b genes to expand the pyrethroid resistance front in the malaria vector Anopheles funestus in Africa. BMC Genom. 2014, 15, 817. [Google Scholar] [CrossRef] [Green Version]
  49. Riveron, J.M.; Chiumia, M.; Menze, B.D.; Barnes, K.G.; Irving, H.; Ibrahim, S.S.; Weedall, G.D.; Mzilahowa, T.; Wondji, C. S. Rise of multiple insecticide resistance in Anopheles funestus in Malawi: A major concern for malaria vector control. Malar. J. 2015, 14, 344. [Google Scholar] [CrossRef] [Green Version]
  50. Ibrahim, S.S.; Riveron, J.M.; Bibby, J.; Irving, H.; Yunta, C.; Paine, M.J.I.; Wondji, C.S. Allelic Variation of Cytochrome P450s Drives Resistance to Bednet Insecticides in a Major Malaria Vector. PLoS Genet 2015, 11, e1005618. [Google Scholar] [CrossRef] [Green Version]
  51. Martinez-Torres, D.; Chandre, F.; Williamson, M.S.; Darriet, F.; Berge, J.B.; Devonshire, A.L.; Guillet, P.; Pasteur, N.; Pauron, D. Molecular characterization of pyrethroid knockdown resistance (kdr) in the major malaria vector Anopheles gambiae s.s. Insect Mol. Biol. 1998, 7, 179–184. [Google Scholar] [CrossRef] [Green Version]
  52. O’Reilly, A.O.; Khambay, B.P.S.; Williamson, M.S.; Field, L.M.; Wallace, B.A.; Davies, T.G.E. Modelling insecticide-binding sites in the voltage-gated sodium channel. Biochem. J. 2006, 396, 255–263. [Google Scholar] [CrossRef] [Green Version]
  53. Verhaeghen, K.; Van Bortel, W.; Roelants, P.; Backeljau, T.; Coosemans, M. Detection of the East and West African kdr mutation in Anopheles gambiae and Anopheles arabiensis from Uganda using a new assay based on FRET/Melt Curve analysis. Malar. J. 2006, 5, 16. [Google Scholar] [CrossRef] [Green Version]
  54. Jones, C.M.; Liyanapathirana, M.; Agossa, F.R.; Weetman, D.; Ranson, H.; Donnelly, M.J.; Wilding, C.S. Footprints of positive selection associated with a mutation (N1575Y) in the voltage-gated sodium channel of Anopheles gambiae. Proc. Natl. Acad. Sci. USA 2012, 109, 6614–6619. [Google Scholar] [CrossRef] [Green Version]
  55. Chouaia, B.; Rossi, P.; Montagna, M.; Ricci, I.; Crotti, E.; Damiani, C.; Epis, S.; Faye, I.; Sagnon, N.F.; Alma, A.; et al. Molecular Evidence for Multiple Infections as Revealed by Typing of Asaia Bacterial Symbionts of Four Mosquito Species. Appl. Environ. Microbiol. 2010, 76, 7444–7450. [Google Scholar] [CrossRef] [Green Version]
  56. Damiani, C.; Ricci, I.; Crotti, E.; Rossi, P.; Rizzi, A.; Scuppa, P.; Capone, A.; Ulissi, U.; Epis, S.; Genchi, M.; et al. Mosquito-Bacteria Symbiosis: The Case of Anopheles gambiae and Asaia. Microb. Ecol. 2010, 60, 644–654. [Google Scholar] [CrossRef] [Green Version]
  57. Damiani, C.; Ricci, I.; Crotti, E.; Rossi, P.; Rizzi, A.; Scuppa, P.; Esposito, F.; Bandi, C.; Daffonchio, D.; Favia, G. Paternal transmission of symbiotic bacteria in malaria vectors. Curr. Biol. 2008, 18, R1087–R1088. [Google Scholar] [CrossRef] [Green Version]
  58. Ricci, I.; Damiani, C.; Rossi, P.; Capone, A.; Scuppa, P.; Cappelli, A.; Ulissi, U.; Mosca, M.; Valzano, M.; Epis, S.; et al. Mosquito symbioses: From basic research to the paratransgenic control of mosquito-borne diseases: Bacterial symbiosis in mosquito. J. Appl. Entomol. 2011, 135, 487–493. [Google Scholar] [CrossRef] [Green Version]
  59. Soltani, A.; Vatandoost, H.; Oshaghi, M.A.; Enayati, A.A.; Chavshin, A.R. The role of midgut symbiotic bacteria in resistance of Anopheles stephensi (Diptera: Culicidae) to organophosphate insecticides. Pathog. Glob. Health 2017, 111, 289–296. [Google Scholar] [CrossRef]
  60. Zhang, J.; Pan, Y.; Zheng, C.; Gao, X.; Wei, X.; Xi, J.; Peng, T.; Shang, Q. Rapid evolution of symbiotic bacteria populations in spirotetramat-resistant Aphis gossypii glover revealed by pyrosequencing. Comp. Biochem. Physiol. Part D Genom. Proteom. 2016, 20, 151–158. [Google Scholar] [CrossRef]
  61. Berticat, C.; Rousset, F.; Raymond, M.; Berthomieu, A.; Weill, M. High Wolbachia density in insecticide-resistant mosquitoes. Proc. R. Soc. London. Ser. B Biol. Sci. 2002, 269, 1413–1416. [Google Scholar] [CrossRef] [Green Version]
  62. Fang, S.; Wang, L.; Guo, W.; Zhang, X.; Peng, D.; Luo, C.; Yu, Z.; Sun, M. Bacillus thuringiensis bel protein enhances the toxicity of Cry1Ac protein to Helicoverpa armigera larvae by degrading insect intestinal mucin. Appl. Environ. Microbiol. 2009, 75, 5237–5243. [Google Scholar] [CrossRef] [Green Version]
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Figure 1. Susceptibility profile of An. funestus and An. gambiae strains to 1X DC of permethrin and deltamethrin. Results are the average of recorded mortalities following 60 min of exposure. Data are shown as mean ± SEM. *** p < 0.0001.
Figure 1. Susceptibility profile of An. funestus and An. gambiae strains to 1X DC of permethrin and deltamethrin. Results are the average of recorded mortalities following 60 min of exposure. Data are shown as mean ± SEM. *** p < 0.0001.
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Figure 2. Resistance intensity of the An. funestus and An. gambiae hybrid strains to pyrethroids. (a) Estimation of resistance intensity with 5X and 10X the diagnostic concentrations of permethrin and deltamethrin in both Anopheles mosquitoes. (b) Time-point mortality rates to permethrin 1X DC of An. gambiae hybrid mosquitoes to generate the highly resistant (HR: alive 90 min) and highly susceptible (HS: dead 03 min). Data are shown as mean ± SEM. *** p < 0.0001.
Figure 2. Resistance intensity of the An. funestus and An. gambiae hybrid strains to pyrethroids. (a) Estimation of resistance intensity with 5X and 10X the diagnostic concentrations of permethrin and deltamethrin in both Anopheles mosquitoes. (b) Time-point mortality rates to permethrin 1X DC of An. gambiae hybrid mosquitoes to generate the highly resistant (HR: alive 90 min) and highly susceptible (HS: dead 03 min). Data are shown as mean ± SEM. *** p < 0.0001.
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Figure 3. Distribution of the proportions of the cytochrome P450 genotypes between dead and alive in F4 of An. funestus hybrid mosquitoes after WHO bioassays with 1X, 5X, and 10X concentrations of deltamethrin. (a) distribution of the CYP6P9a genotypes, (b) repartition of the CYP6P9b genotypes, and (c). 6.5 kb insertion genotypes. RR represents the proportion of individuals harboring the homozygote-resistant mutation. SS corresponds to the proportion of individuals with the homozygote susceptible genotype, and RS represents the frequency of heterozygote mosquitoes. 1X: Diagnostic concentration of the insecticide; 5X and 10X correspond to 5 and 10 times the diagnostic concentration of insecticide, respectively.
Figure 3. Distribution of the proportions of the cytochrome P450 genotypes between dead and alive in F4 of An. funestus hybrid mosquitoes after WHO bioassays with 1X, 5X, and 10X concentrations of deltamethrin. (a) distribution of the CYP6P9a genotypes, (b) repartition of the CYP6P9b genotypes, and (c). 6.5 kb insertion genotypes. RR represents the proportion of individuals harboring the homozygote-resistant mutation. SS corresponds to the proportion of individuals with the homozygote susceptible genotype, and RS represents the frequency of heterozygote mosquitoes. 1X: Diagnostic concentration of the insecticide; 5X and 10X correspond to 5 and 10 times the diagnostic concentration of insecticide, respectively.
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Figure 4. Distribution of combined genotypes of cytochrome P450 mutations between alive and dead after exposure to pyrethroids. (a) CYP6P9a and CYP6P9b association; (b) 6.5 kb-SV and CYP6P9a; (c) 6.5 kb-SV and CYP6P9b combination; (d) triple combination: 6.5 kb-SV, CYP6P9a, and CYP6P9b.
Figure 4. Distribution of combined genotypes of cytochrome P450 mutations between alive and dead after exposure to pyrethroids. (a) CYP6P9a and CYP6P9b association; (b) 6.5 kb-SV and CYP6P9a; (c) 6.5 kb-SV and CYP6P9b combination; (d) triple combination: 6.5 kb-SV, CYP6P9a, and CYP6P9b.
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Figure 5. Contribution of VGSC mutations and their combinations in the escalation of pyrethroid resistance in An. gambiae hybrid strains. Distribution of genotypes for (a) L1014F, (b) N1575Y, and (c) a combination of L1014F and N1575Y, between alive and dead after pyrethroid exposure. HR: Alive after 90 min of exposure to permethrin 1X DC (Highly resistant; HS: Dead after 3 min of exposure to permethrin 1X DC (Highly susceptible).
Figure 5. Contribution of VGSC mutations and their combinations in the escalation of pyrethroid resistance in An. gambiae hybrid strains. Distribution of genotypes for (a) L1014F, (b) N1575Y, and (c) a combination of L1014F and N1575Y, between alive and dead after pyrethroid exposure. HR: Alive after 90 min of exposure to permethrin 1X DC (Highly resistant; HS: Dead after 3 min of exposure to permethrin 1X DC (Highly susceptible).
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Figure 6. Detection of the Asaia spp. symbiont in Anopheles samples. (a) An electrophoresis gel picture of the PCR products. (b) Prevalence of Asaia symbiont in An. funestus and An. gambiae (c) Prevalence of Asaia in different strains (parental lines and crossings). The prevalence was estimated as the proportion of infected mosquitoes with Asaia spp. (d) Estimation of the abundance of Asaia in overall An. funestus and An. gambiae mosquitoes tested. The Mann-Whitney test was used to evaluate the differences in Asaia loads between the two species.
Figure 6. Detection of the Asaia spp. symbiont in Anopheles samples. (a) An electrophoresis gel picture of the PCR products. (b) Prevalence of Asaia symbiont in An. funestus and An. gambiae (c) Prevalence of Asaia in different strains (parental lines and crossings). The prevalence was estimated as the proportion of infected mosquitoes with Asaia spp. (d) Estimation of the abundance of Asaia in overall An. funestus and An. gambiae mosquitoes tested. The Mann-Whitney test was used to evaluate the differences in Asaia loads between the two species.
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Figure 7. Prevalence of Asaia spp. in relation to resistance and susceptible alleles. (a) Association between CYP6P9a-R and CYP6P9a-S alleles and the prevalence of Asaia spp. (b) Association between CYP6P9b-R and CYP6P9b-S alleles and the prevalence of Asaia spp. (c) Association between the alleles of the structural variant 6.5 kb-SV and the prevalence of Asaia spp. bacteria.
Figure 7. Prevalence of Asaia spp. in relation to resistance and susceptible alleles. (a) Association between CYP6P9a-R and CYP6P9a-S alleles and the prevalence of Asaia spp. (b) Association between CYP6P9b-R and CYP6P9b-S alleles and the prevalence of Asaia spp. (c) Association between the alleles of the structural variant 6.5 kb-SV and the prevalence of Asaia spp. bacteria.
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Figure 8. Relationship between the abundance of Asaia spp. and insecticide resistance phenotype in hybrids An. funestus and An. gambiae after exposure to insecticide. HR: Alive mosquitoes after 90 min permethrin exposure to permethrin 1X DC (Highly resistant); HS: Dead 3 min after exposure to permethrin 1X DC (Highly susceptible).
Figure 8. Relationship between the abundance of Asaia spp. and insecticide resistance phenotype in hybrids An. funestus and An. gambiae after exposure to insecticide. HR: Alive mosquitoes after 90 min permethrin exposure to permethrin 1X DC (Highly resistant); HS: Dead 3 min after exposure to permethrin 1X DC (Highly susceptible).
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Table
Table 1. Association between the prevalence of Asaia spp. and the insecticide resistance phenotype in Anopheles funestus and Anopheles gambiae hybrid strains.
Table 1. Association between the prevalence of Asaia spp. and the insecticide resistance phenotype in Anopheles funestus and Anopheles gambiae hybrid strains.
SpeciesPhenotypesTestedInfectedPrevalence of Asaia spp. Comparison of the Prevalence of Asaia spp. between Alive and Dead
An. funestusAlive 1X424197.62χ2 = 4.91, p = 0.02; OR = 8.2 p = 0.05
Dead 1X423583.33
Alive 5X484797.92 χ2 = 16.93, p < 0.0001; OR = 25.8, p = 0.002
Dead 5X483164.58
Alive 10X4848100 χ2 = 4.11, p = 0.04; OR = 9.8, p = 0.12
Dead 10X484491.67
An. gambiaeHR4242100 /
HS3535100
OR: Odd ratio, χ2 = Chi-square, p = p value, HR = Highly resistant, HS = Highly susceptible, CI = Confidence interval.
Table
Table 2. Association between the abundance of Asaia spp. and resistance genotype in An. gambiae hybrid strains.
Table 2. Association between the abundance of Asaia spp. and resistance genotype in An. gambiae hybrid strains.
MarkersGenotypeTestedMedianMeanPercentiles (IQR)
25th75th
L1014FRR28569.161832.8142.191205.1
RS23484.321457.2145.241970.4
SS231281.79393.1432.85703.5
N1575YRS37587.572452276.092199.2
SS38873.935570.7120.41784.2
L1014F and N1575YRR/RS21550.762103.6229.511074.2
RS/RS121227.42354.1265.274033
SS/SS181281.710,407195.912887
RR = Homozygote resistant genotype, RR = Heterozygote resistant genotype, SS = Susceptible genotype, IQR = Interquartile range.
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Djondji Kamga, F.M.; Mugenzi, L.M.J.; Tchouakui, M.; Sandeu, M.M.; Maffo, C.G.T.; Nyegue, M.A.; Wondji, C.S. Contrasting Patterns of Asaia Association with Pyrethroid Resistance Escalation between the Malaria Vectors Anopheles funestus and Anopheles gambiae. Microorganisms 2023, 11, 644. https://doi.org/10.3390/microorganisms11030644

AMA Style

Djondji Kamga FM, Mugenzi LMJ, Tchouakui M, Sandeu MM, Maffo CGT, Nyegue MA, Wondji CS. Contrasting Patterns of Asaia Association with Pyrethroid Resistance Escalation between the Malaria Vectors Anopheles funestus and Anopheles gambiae. Microorganisms. 2023; 11(3):644. https://doi.org/10.3390/microorganisms11030644

Chicago/Turabian Style

Djondji Kamga, Fleuriane Metissa, Leon M. J. Mugenzi, Magellan Tchouakui, Maurice Marcel Sandeu, Claudine Grace Tatsinkou Maffo, Maximilienne Ascension Nyegue, and Charles S. Wondji. 2023. "Contrasting Patterns of Asaia Association with Pyrethroid Resistance Escalation between the Malaria Vectors Anopheles funestus and Anopheles gambiae" Microorganisms 11, no. 3: 644. https://doi.org/10.3390/microorganisms11030644

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