Larval breeding water drives differential selection pressures on genetic insecticide resistance and metabolic enzyme plasticity in Anopheles gambiae s.l

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Gyimah, Godwin K. Amlalo, Rebecca Pwalia, Samuel S. Akporh, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8493684/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract Background The control of mosquito-borne diseases is heavily reliant on insecticide-based interventions. The evolution of insecticide resistance is a complex process driven by both direct chemical exposure and indirect environmental pressures. While the larval environment is known to influence adult mosquito traits, its long-term impact on the evolution of multiple resistance mechanisms is poorly understood. This study used an experimental evolution approach to investigate how larval aquatic environments select for insecticide resistance profiles in An. gambiae s.l. over 10 successive generations. Methods Anopheles gambiae s.l. larvae were collected from a single site in Accra, Ghana, and colonized in the laboratory for 10 filial generations. The larvae were reared in three distinct water types: field-collected water (FW), dechlorinated tap water (TW), and distilled water (DW). At each generation, phenotypic susceptibility to four classes of insecticides was assessed using WHO bioassays, including synergist assays with piperonyl butoxide (PBO). The frequencies of the kdr-w ( L 995 F ) and ace-1 ( G 119 S ) target-site mutations were determined using molecular analysis. The activity of key metabolic enzymes, P450 monooxygenases, carboxylesterases (α and β), and insensitive acetylcholinesterase was quantified through biochemical assays. Selected physicochemical properties of the rearing waters were also characterized. Results kdr-w mutation rapidly increased to fixation by generation F 2 in mosquitoes reared in dechlorinated tap water, a trend not observed in the other two water types, suggesting a strong, water-mediated selective advantage provided by tap water chemistry. There was an overall significant decline in the frequency of the kdr-w mutation from 90–100% at F0 to ~ 63% by F 10 . Conversely, the frequency of the ace-1 mutation increased steadily from approximately 60% to 90% over the 10 generations. Mosquitoes reared in the nutrient and ion-rich field water consistently exhibited significantly elevated levels of detoxification enzymes, particularly ⍺-esterases and mixed-function oxidases (up to 32% for oxidases), compared to those reared in tap and distilled water indicating phenotypic plasticity induced by natural environmental co-factors. Conclusion The larval aquatic environment fundamentally shapes the genetic and biochemical basis of insecticide resistance in adult Anopheles gambiae s.l.. The physicochemical composition of breeding water induces metabolic detoxification systems and influences the rate of fixation of target-site mutations. These findings suggest that environmental co-factors play a critical role in the persistence of resistance genes, providing a new evolutionary framework for integrated vector management. Larval source management can serve not only to reduce vector populations but also be a critical tool for managing insecticide resistance by modifying the environmental pressures that select for resistant phenotypes. Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Biological sciences/Genetics Biological sciences/Molecular biology Biological sciences/Zoology Anopheles gambiae s.l. insecticide resistance larval environment kdr ace-1 metabolic resistance phenotypic plasticity larval source management experimental evolution Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Malaria remains a significant global health challenge, particularly in sub-Saharan Africa, where the primary vectors belong to the Anopheles gambiae sensu lato (s.l.) complex [ 1 ]–[ 4 ]. Vector control is the cornerstone of malaria prevention and relies heavily on insecticide-based interventions, namely long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) [ 5 ], [ 6 ]. Pyrethroids have been the principal class of insecticides used for these interventions due to their efficacy and low mammalian toxicity [ 1 ], [ 7 ]. The widespread use of these insecticides has, however, led to the emergence and rapid spread of insecticide resistance in Anopheles populations, which now threatens the effectiveness of malaria control programs worldwide [ 5 ], [ 6 ], [ 8 ]. Mosquitoes have evolved several mechanisms to survive insecticide exposure. Among these target-site modifications and enhanced metabolic detoxification are the most-studied [ 9 ], [ 10 ]. Target-site resistance involves genetic mutations in the protein targets of insecticides, reducing their binding affinity. A well-characterized mutation in An. gambiae s.l. include the L 995 F substitution (also known as kdr-w or knockdown resistance) in the voltage-gated sodium channel (vgsc) gene, which confers resistance to both pyrethroids and DDT [ 9 ], [ 11 ], [ 12 ]. Another critical mutation is the G 119 S substitution in the acetylcholinesterase gene ( ace-1 ), which reduces susceptibility to organophosphates and carbamates [ 5 ], [ 8 ], [ 13 ], [ 14 ]. The frequency of these mutations is a key indicator of resistance pressure in wild mosquito populations [ 15 ]–[ 17 ]. Metabolic resistance involves the upregulation of detoxification enzymes that metabolize and sequester insecticides before they can reach their intended target [ 18 ]–[ 20 ]. The primary enzyme families implicated are cytochrome P450 monooxygenases (P450s), glutathione S-transferases (GSTs), and carboxylesterases (α and β-esterases) [ 21 ]. The contribution of metabolic resistance, particularly P450s, can be assessed using the synergist piperonyl butoxide (PBO), which inhibits these enzymes and can restore susceptibility to pyrethroids in resistant mosquitoes [ 5 ], [ 18 ], [ 22 ], [ 23 ]. The presence of multiple resistance mechanisms within a single mosquito population complicates vector control efforts and necessitates a deeper understanding of the evolutionary factors driving their selection and maintenance [ 24 ]–[ 26 ]. The larval environment plays a critical role in shaping the evolutionary trajectory of physiological and biochemical traits of adult mosquitoes, including their insecticide susceptibility [ 27 ], [ 28 ]. Mosquito breeding habitats can be influenced by urban pollution and agricultural runoff, exposing larvae to a wide range of chemical contaminants, including pesticides, heavy metals, and high concentrations of organic matter [ 6 ], [ 28 ]. Physicochemical parameters of the water, such as pH, electrical conductivity (EC), nutrient levels, and biochemical oxygen demand (BOD), do not merely influence mosquito larval development and the composition of mosquito assemblages [ 29 ] but, could also act as selective filters that favour certain genotypes over others. Studies have demonstrated that larval exposure to pollutants can modulate adult longevity, reproductive fitness, and tolerance to insecticides [ 30 ], [ 31 ]. However, there is significant lack of longitudinal data on how these habitats influence the stability, fixation, or loss of resistance alleles over time. The current study used an experimental evolution approach to investigate the impact of rearing Anopheles gambiae s.l. larvae in three distinct water types: field-collected water, dechlorinated tap water, and distilled water on resistance to insecticides. The research tracks the frequency of the kdr-w and ace-1 target-site mutations and the activity of metabolic detoxification enzymes over 10 filial generations to elucidate the influence of the larval aquatic environment on the stability or otherwise of insecticide resistance. Methods Breeding water experimental set-up Anopheles gambiae s.l. mosquito larvae and pupae were collected from breeding ponds on a vegetable farm in Opeibea (5º35’56N; 0º10’59’W), a suburb within the Accra Metropolis, Ghana, between September and October 2021. In addition to collecting mosquitoes, samples of the field water were fetched into closed containers. All collected samples were returned to the Vestergaard-Noguchi Vector Laboratory, and the immature mosquitoes were divided into three breeding water types: dechlorinated tap water (TW), samples of the field water (FW), and distilled water (DW). They were raised to adults, transferred into 30cm x 30cm x 30cm netted cages and fed with a 10% sugar solution. Seven to ten-day-old adult female mosquitoes were fed on sheep blood through an artificial membrane feeder. An oviposition dish was prepared and placed in each cage 48–72 hours after blood-feeding. Eggs collected from adults emerging from the preceding generation of each experimental group were hatched in fresh aliquots of its designated breeding water type for 10 subsequent filial generations. Field water samples were fetched from the vegetable farm pond to wash eggs for hatching in the field water group. All mosquitoes were maintained under standard insectary conditions, i.e., relative humidity (RH) 75 ± 10% and temperature 27 ± 2℃. Four independent replicates were set-up for each water type at each filial generation. Insecticide susceptibility tests Insecticide susceptibility tests were performed on adult female An. gambiae s.l. mosquitoes at each filial generation according to World Health Organization standards (WHO) [ 32 ]. Representatives of the four classes of insecticides: pyrethroids (0.05% deltamethrin, 0.75% permethrin), organophosphate (0.25% pirimiphos-methyl), organochlorine (4% DDT), and carbamate (0.1% bendiocarb) were tested. A synergist assay with 4% piperonyl butoxide (PBO) with pyrethroids was conducted to assess the probable presence of metabolic enzyme activities within the colony. Twenty to twenty-five 3–5-day-old non-blood fed female Anopheles gambiae s.l. were exposed to the various discriminating doses of insecticides for an hour and moved to a holding tube. For the synergist assay, mosquitoes were pre-exposed to PBO for one hour before the pyrethroid insecticides. A control group for the synergist assay was exposed to only PBO. This served as a quality check for the assay since PBO are not insecticides. Mortality 20% invalidates the assay. Two replicates of silicon-impregnated paper per assay served as the control and were run in parallel with the various insecticides. Mortality was assessed in the holding tube after 24 hours. We fit a generalized linear mixed model (GLMM) to investigate insecticide, breeding water type and the filial generation as fixed effects on recorded mortality, using glmer function from the lme4 package in R. The replicates were set as random effect variables. The model was fit with a binomial distribution with a logit link function since the response variable was binary (dead or alive). The odds ratios and 95% confidence intervals (CI) were calculated from the summary estimates obtained from the model. Contrast analyses of mortality per generations were performed using F0 as the reference, and significant mortality was confirmed only when p -value < 0.05 and CI does not include 1. DDT and field water (FW) were also set as the reference insecticide and water type, respectively. Screening for knockdown resistance (kdr-w L995F) and acetylcholine esterase (Ace-1 G119S) gene mutations. For each water type, 30 mosquitoes from each filial generation were randomly selected from those tested (died or lived) in the WHO susceptibility test. DNA was extracted using 2% Cetyl trimethyl ammonium bromide (CTAB) protocol [ 33 ], [ 34 ]. The Anopheles gambiae vgsc- L 995 F alleles were characterized by PCR with primers AGD1 [5’-ATAGATTCCCCGACCATG-3’]; AGD2 [5’-AGACAAGGATGATGAACC-3’], AGD3 [5’-AATTTGCATTACTTACGACA-3’], and AGD4 [5’-CTGTAGTGATAGGAAATTTA-3’], and the ace-1 alleles with EX3AGdir [5’-GATCGTGGACACCGTGTTCG-3’] and EX3AGrev [5’-AGGATGGCCCGCTGGAACAG-3’], using established protocols [ 35 ], [ 36 ]. A generalized linear model (GLM) was used to analyse whether observed mutation frequencies were dependent on the filial generation, mutation type ( kdr-w , ace1) and water. The model was fit using a binomial distribution with a logit link function using the glm function in R. Odds ratio and 95% CI were calculated as earlier described. The frequencies were compared among filial generation in each water type, and between water types. Linear trends of mutation frequencies from F 0 to F 10 were also analysed and compared. The mortality and mutation frequency data was merged based on filial generation and water type to investigate correlation of the mutation frequencies with mortality observed following exposure to each insecticide. We performed Pearson's product-moment correlation for each unique combination of mutation type, insecticide, and water source. The correlation coefficient (r) and the corresponding p -value were calculated for each of these combinations to determine the strength and statistical significance of the relationship. Combinations with fewer than two data points were excluded from the correlation analysis. Biochemical assay for estimation of enzyme activity Fifty non-blood-fed, non-insecticide exposed female mosquitoes per filial generation from each breeding water type were assessed for enzyme activities using the techniques already outlined [ 37 ]. The evaluated enzymes were P450 monooxygenases (P450s), carboxylesterases (α and β-esterases), and Insensitive acetylcholine esterase (Ache). Individual mosquitoes were homogenized in 0.1 M potassium phosphate buffer (pH = 7.2), centrifuged, and the resulting supernatant was collected for use in the biochemical assays. Positive and negative controls were included on each microplate to ensure consistency, reliability, and accuracy of the experimental results. The nonspecific esterase activity was determined using either α-naphthyl acetate or β-naphthyl acetate as substrates. The reaction products were coupled with Fast Blue B salt to form a coloured complex whose intensity corresponded to enzyme activity. The absorbance of β-naphthyl and α-naphthyl reactions was recorded at 540 nm and 620 nm, respectively. This allowed for the quantification of esterase activity, which reflects the hydrolytic potential of the enzyme in metabolizing ester-containing insecticides. Oxidase activity was assessed using tetramethylbenzidine (TMBZ) and hydrogen peroxide as chromogenic reagents, with cytochrome C serving as the positive control. The reaction was allowed to proceed under standardized incubation conditions, after which absorbance was measured at 620 nm. The degree of color development was proportional to the level of oxidase activity, which is indicative of the mosquito’s capacity for oxidative detoxification of insecticides. Acetylcholinesterase (AChE) activity was evaluated using acetylthiocholine iodide and 5,5′-dithiobis-(2-nitrobenzoic acid) (DTNB) as reagents. The assay was conducted both in the absence and presence of the carbamate inhibitor propoxur to detect insensitive enzyme variants. The rate of colour formation, resulting from the reaction between thiocholine and DTNB to produce a yellow-coloured anion of 5-thio-2-nitrobenzoic acid, was measured at 414 nm. The change in absorbance indicated the presence of altered enzyme forms associated with target site insensitivity. Total protein content in each homogenate was determined using a microplate-based protein assay, and absorbance was measured at 620 nm. The protein concentration of each sample was used to normalize enzyme activity, which was expressed as absorbance per milligram of protein. Enzyme expression profiles were compared between samples from different breeding water types from the same filial generation and across the different filial generations using a series of one-way analyses of variance (ANOVA). When water type was detected by the ANOVA as a significant effect, we performed a Tukey's Honest Significant Difference (HSD) post-hoc test to identify which specific water type pairs had significant differences. Additionally, to assess the overall change in enzyme expression across all generations, we performed a series of independent samples Welch's t-tests. For each enzyme, we compared the expression levels in the FW (field water) control group to the DW (distilled water) and TW (tap water) groups separately. Physicochemical assessment of breeding water Physicochemical parameters, including biochemical oxygen demand (BOD), pH, electrical conductivity (EC), total dissolved solids (TDS), total alkalinity, chlorine, phosphate, total ammonia nitrogen, carbon dioxide, calcium, magnesium, and total hardness, were assessed in each type of breeding water at F0 and every other generation (a total of 5 times) across the 10 filial generations [ 38 ], [ 39 ]. Statistical analysis was performed using Stata/IC 64 software. The Shapiro-Wilk test was applied to assess the normality of the data, and since the physiochemical parameter values of the various breeding water types did not follow a normal distribution, the Bonferroni non-parametric test was used for pairwise comparisons between water types. Results Pyrethroid-PBO overcomes persistent phenotypic resistance across all water types We investigated changes in the An. gambiae s.l susceptibility phenotype against several insecticides following continual breeding in different water types for 10 filial generations. High levels of phenotypic resistance were sustained across all generations for most insecticides, with the notable exception of pyrethroid-PBO combinations (Fig. 1 ). Mortalities recorded in F 1 - F 10 , except for the distilled water (DW) colony which could not survive beyond the 5th generation, were compared to the reference population (F 0 ). The logistic regression analysis demonstrated that the baseline odds of mortality for the F 0 generation in FW with DDT exposure (reference insecticide) was significantly low (OR = 0.046, 95% CI= [0.014, 0.146], p < 0.0001) (Table S1 ), establishing a minimal mortality rate for the founding population. Mortality in FW increased by odds of 5.23 (95%CI= [1.36, 20.12], p = 0.016) only in F 8 compared to F 0 assuming reference levels for all tested variables. Insecticide treatments containing the synergist piperonyl butoxide (PBO) resulted in higher odds of mortality with deltamethrin + PBO (DM + PBO) dramatically increasing the odds of death by ~ 358 (95%CI= [77.08, 1663.24], p < 0.001) compared to the reference insecticide, DDT (Table S1 ). While the main effects highlight the overall potency of PBO-synergized insecticides, the analysis of interaction terms revealed a more complex relationship between the factors. Significantly increased mortality was identified with the pyrethroids (PM, DM) + PBO from as early as F 1 and at other specific generations (Fig. 1 , Table S1 ) as observed for DM + PBO in tap water at F 8 ( p = 0.025). Therefore, among the water types compared, tap water appears to increase susceptibility to pyrethroids + PBO insecticides, though this is not consistent over 10 generations. We investigated whether the generational mortality trends for each insecticide differed between the breeding water types. The analyses also allowed an assessment of which specific filial generations changed significantly from F 0 within each larval environment. The results revealed consistent and transient susceptibility patterns. Tap water (TW) reared mosquitoes showed relatively high mortality at F 1 for all insecticides, except PM, PM + PBO and DM + PBO (Fig. 2 ). This reverted at F 2 and stayed consistently similar to F0 ( p > 0.05) despite observed subtle changes in mean mortality throughout the remaining generations (Fig. 2 , Table S2 ). On the contrary, formulations containing PBO (DM + PBO, PM + PBO) were associated with significantly persistent lowered mortality from F 1 to F 10 regardless of water type. The odds for mortality were generally < 0.1, except F 6 (OR = 7.86, 95%CI= [2.57, 24.05], p < 0.0001) where there was a one timepoint increased mortality relative to F 0 in FW (Fig. 2 , Table S2 ). Divergent evolutionary trajectories of kdr-w and ace-1 mutations across water types We fitted a generalized linear model (GLM) to estimate the probability of a mosquito possessing a specific mutation at a given generation in a particular water type and then analysed trends in the changes (slopes) mutations across generations between water types. The single nucleotide mutations L 995 F ( kdr-w ) and G 119 S ( ace-1 ) of An. gambiae s.l. populations were observed across all generations (F 0 -F 10 ) for each breeding water. The estimated mutation frequencies across generations revealed contrasting temporal trends for the ace-1 and kdr-w . The frequency of kdr-w was consistently higher than ace-1 irrespective of the water type with ~ 12 times higher odds ( p < 0.0001, 95%CI= [4,23, 32.99]) of occurring compared to ace-1 (Table S3 ). Kdr-w frequency generally fluctuated between 90–100%, showing a strong fixation propensity (Fig. 3 A). Ace-1 mutation frequency changed from 63% at F 0 in TW to 93% at F 8 , indicating a progressive accumulation of this mutation over time. Except in TW where kdr-w rapidly rose to fixation after a decline at F 1 , this mutation generally showed a declining trend from an initial value of ~ 100% at F 0 in FW and DW to 76% at F 3 in DW (Fig. 3 B). In FW, the odds for the kdr-w mutation decreases by about 19% (OR = 0.81, 95%CI= [0.70, 0.94], p = 0.005) with each passing generation, while it increased significantly in mosquitoes bred in TW (Table S3 : gen* kdr-w *TW). Field water composition induces significant metabolic enzyme plasticity The expression levels of the enzymes tested; insensitive acetylcholinesterase (AChE), ⍺-esterase, β-esterase, and mixed function oxidase, varied significantly across generations (ANOVA: F = 6.669, p < 0.0001) and were influenced by water type (ANOVA: F = 4.609, p = 0.010). Considering F 0 -F 5— to enable inclusion of DW– we observed that TW and DW often had similar expression levels with instances where either one or both differed significantly from FW. For instance, the expression of ⍺-esterase at F 0 was similar for TW and DW, but at F 1 all three water types differed (Fig. 4 A). The differences, however, was not consistent for onward generations, but at least one water type (often FW) differed from the others. The expression of oxidase also showed similar patterns as described for ⍺-esterase and, Ache and β-esterase expressions were generally similar across water types (Fig. 4 A). From F 6 - F 10 where only FW and TW were compared, we observe similar ⍺ -esterase expression between these water types, while the other enzymes differed often at various generations. While breeding in DW appeared to reduce levels of ⍺- and β-esterases in the mosquitoes, TW did not result in significant changes in these enzymes. Ache was the least affected enzyme and was similarly reduced in DW and TW reared mosquitoes (Fig. 4 B). Marked differences in the physicochemical profiles of the three water types were observed over the experimental period, providing selective landscapes for the developing larvae (Fig. 5 , Fig S1 ). FW exhibited elevated levels of biochemical oxygen demand (BOD), electrical conductivity (EC) and total dissolved solids (TDS) peaking at 436 mg/L, 1,060 µS/cm and 805 mg/L, respectively, far exceeding the values recorded for TW and DW ( p < 0.05). Nutrient concentrations were also elevated in FW compared to TW and DW. Phosphate and ammonia nitrogen (NH₄–N) were exceptionally high in week 1 before declining in subsequent weeks ( p = 0.016). These values in exceeded WHO limits for….. Calcium (Ca) and magnesium (Mg) remained below the WHO guideline of 200 mg/L for all water types. pH values were generally within the WHO-recommended range (6.5–8.5) for all water types ( p > 0.05), though FW showed slight fluctuations between 6.91 and 7.76. Overall, larvae reared in nutrient-rich FW consistently exhibited significantly higher metabolic enzyme activity compared to TW and DW cohorts. This was most pronounced in oxidase levels, which were elevated by up to 32% (Fig. 4 B), indicating that FW induces a higher baseline of detoxification capacity. Discussion We have tracked phenotypic insecticide susceptibility, target-site mutation frequencies, and metabolic enzyme activity over 11 filial generations (including the founding population), to provide confirmatory evidence that the larval aquatic environment plays a crucial role in the evolution of insecticide resistance profiles of adult mosquitoes. Our key findings reveal a significant decline in the frequency of the kdr-w mutation, a concurrent rise in the ace-1 mutation, and a strong induction of detoxification enzymes by nutrient and ion-rich field water. These appear to sustain the effectiveness of PBO-synergized pyrethroids, indicating a strong metabolic influence while the underlying genetic and biochemical mechanisms are dynamic and environmentally modulated. There was evidence of potentially increasing susceptibility to other classes of insecticides including non-synergized pyrethroids during continuous mosquito maintenance in dechlorinated tap water (TW) and distilled water (DW), although this was not observed to be significant given the limits of the current study. We discuss implications for our selection of water source for laboratory colonization of Anopheles mosquitoes, and for mechanisms for insecticide resistance and vector related to the population studied. The most striking result of this study was the unexpected rapid increase to fixation of the kdr-w mutation by F 2 in mosquito populations reared in dechlorinated tap water (TW). This strong selection was unusual compared to field water (FW) and distilled water (DW) where the mutation frequency fluctuated and remained high but variable. Tap water often contains residual chlorine, heavy metals from pipes or specific mineral ions which can act as xenobiotics and select for individuals with more robust detoxification or stress-response systems, which are often genetically linked to resistance loci. This differential selection highlights the importance of water physicochemical factors in driving the evolution of target-site mediated pyrethroid resistance. In contrast to kdr-w , the frequency of ace-1 mutation, which confers resistance to organophosphates (OPs) and carbamates, remained lower and never reached fixation in any water type, despite an overall decline in the frequency of the kdr-w mutation over 10 generations. The lower frequency of ace-1 may suggest a fitness cost associated with the mechanism, or that the selection pressure that favours pyrethroid resistance was overwhelmingly dominant during our experiments [ 40 ], [ 41 ]. The generational decline in kdr-w frequencies supports the hypothesis of a fitness cost, a phenomenon described in other vector populations where resistance alleles decrease in frequency when selection pressure is removed [ 42 ]. For instance, a significant fitness cost associated with the L 1014 S - kdr mutation in a Ugandan An. gambiae population led to a restoration of susceptibility in an insecticide-free environment [ 42 ]. Our study provides further evidence for this phenomenon with the L995F allele during laboratory colonization. These results highlight that in the maintenance of mosquito populations in the laboratory the breeding water source should be carefully monitored especially when the mosquitoes will be used for investigating mechanisms of insecticide resistance. Even without active insecticide application, the genetic architecture of resistance within a population can evolve rapidly during colonization, potentially predisposing it to resistance against different insecticide classes. Our enzyme analyses showed dramatic effects of water type on detoxification capacity. Mosquitoes reared in field water, which was characterized by a high organic and ionic load, consistently showed elevated levels of detoxification enzymes, particularly ⍺-esterases and mixed-function oxidases (P450s). Oxidase activity showed the largest reduction of 32.1% in DW relative to FW. Similarly, ⍺-esterase activity significantly decreased in DW but was stable in TW. Oxidases and ⍺-esterases are crucial for metabolic resistance against multiple insecticide classes[ 43 ], hence their reduced activities in the artificial waters (DW, and to a lesser extent, TW) suggests that natural inducers present in the FW environment are essential for maintaining the high baseline levels of these key metabolic enzymes. Their absence in the laboratory waters may effectively reduce the mosquitoes' intrinsic detoxification capacity. β-esterases confer metabolic resistance by sequestering insecticides such as organophosphates, carbamates, and pyrethroids before these compounds reach their neural targets. Elevated β-esterase activity, often resulting from gene overexpression, enhances the breakdown of insecticides and consequently reduces their toxicity to mosquitoes [ 44 ]–[ 47 ]. Acetylcholinesterase (AChE), on the other hand, is an essential enzyme that hydrolyzes the neurotransmitter acetylcholine to terminate synaptic transmission. Organophosphate and carbamate insecticides specifically target AChE by irreversibly or reversibly inhibiting its activity, leading to the accumulation of acetylcholine at synaptic junctions, neural overstimulation, and ultimately, insect death [ 46 ], [ 48 ], [ 49 ]. All the laboratory water types (DW and TW) showed a significant decrease for β-esterase and AChE activity across generations. This suggests a mechanism of phenotypic plasticity, where exposure to environmental xenobiotics in the larval stage "primes" the adult's detoxification systems, potentially conferring enhanced tolerance to insecticides later in life. Our findings align with a growing body of evidence highlighting the link between the larval environment and adult insecticide susceptibility [ 27 ], [ 50 ]. Pollution and agricultural runoff in breeding sites contribute to increased insecticide resistance in Anopheles vectors [ 50 ], [ 51 ]. The physicochemical analysis of our field water, which revealed high levels of biochemical oxygen demand (BOD), electrical conductivity (EC), and nutrients, corresponds with characteristics of polluted and agricultural habitats known to select for resistance [ 39 ], [ 50 ], [ 52 ]. The central role of metabolic resistance, particularly mediated by P450 enzymes, is well-documented across Africa [ 19 ], [ 53 ], [ 54 ]. The restoration of susceptibility with PBO in our study is consistent with findings from Benin, Cameroon, and Nigeria, where P450s like CYP6M2 and CYP6P3 are major drivers of pyrethroid resistance [ 53 ]–[ 56 ]. The profound increase in mortality when mosquitoes were exposed to deltamethrin and permethrin in combination with the synergist PBO strongly implicates mixed-function oxidase enzymes as a primary mechanism of metabolic resistance in this population. The odds of death for deltamethrin with PBO were approximately 358 times higher than the baseline, confirming that inhibiting these enzymes can largely restore pyrethroid susceptibility. However, the observation that the efficacy of these synergized insecticides diminished in later generations suggests that the mosquito colony was adapting, possibly through the selection of alternative resistance mechanisms not fully inhibited by PBO. The insecticide resistance mechanisms in the mosquito population studied suggested by our results is that the complex chemical matrix of natural breeding sites induces a broad, non-specific upregulation of the mosquito's detoxification machinery. The higher organic and nutrient content in field water likely serves as an environmental stressor that selects for a more robust enzymatic defense system [ 21 ]. This has critical implications for vector control. It suggests that larval source management (LSM) is not merely a tool for population reduction but could also be a vital component of insecticide resistance management. By cleaning or modifying polluted breeding sites, control programs could potentially reduce the selection for metabolically resistant mosquitoes, thereby producing adult populations that are more susceptible to existing insecticides [ 57 ]. The observed shift from kdr-w based resistance towards ace-1 dominance in the laboratory colony underscores the evolutionary plasticity of An. gambiae . This implies that if vector control programs were to switch from pyrethroids to organophosphates or carbamates to manage kdr-w resistance, this population already possesses a high frequency of the corresponding ace-1 resistance allele, which could lead to rapid control failure. This highlights the necessity for integrated resistance management strategies that include rotational insecticide use, synergists, and non-chemical interventions like LSM. This study has several notable strengths. The longitudinal design, tracking a single mosquito colony for 10 filial generations, allowed for the observation of micro-evolutionary changes in resistance mechanisms over time, providing insights that cross-sectional studies cannot offer. The multi-pronged approach, integrating phenotypic bioassays, molecular genotyping, and biochemical enzyme analysis, provides a holistic and robust characterization of the resistance profile. Finally, the use of three distinct and well-characterized water types enabled a controlled comparison to isolate and understand the specific impact of breeding water quality on resistance dynamics. Despite these strengths, the study has limitations. First, laboratory colonization inherently differs from natural conditions. Factors such as predation, competition, and fluctuating environmental conditions are absent, which may alter the fitness costs and benefits of resistance alleles. Therefore, the observed decline in kdr-w frequency might be more pronounced in the laboratory than it would be in the field, where pyrethroid pressure persists. Second, the mosquito population originated from a single urban site in Accra, and the findings may not be generalizable to other An. gambiae populations in different ecological settings, such as rural agricultural areas. An alternative explanation for the steady increase in ace-1 frequency could be genetic drift, which can have a strong effect in laboratory colonies founded from a limited number of wild individuals, rather than an unmeasured selective pressure. Similarly, while the increased enzyme activity in field water reared mosquitoes is likely due to chemical induction, it cannot be entirely disconnected from potential nutritional benefits, as the rich microbial community and dissolved organic matter might produce healthier, larger adults with inherently more active metabolic systems. Lastly, the collapse of the distilled water colony after the fifth generation limited long-term comparisons for this control group. This study opens several avenues for future research. Transcriptomic (RNA-seq) analyses should be conducted on larvae and adults reared in different water types to identify upregulated detoxification genes more comprehensively. This would provide a more precise understanding than the broad enzyme activity assays used here. To confirm the fitness cost hypothesis, targeted studies measuring life-history traits (e.g., longevity, fecundity, mating competitiveness) should be performed on mosquitoes with different kdr-w and ace-1 genotypes from this population. Furthermore, replicating this longitudinal study with populations from different ecological zones, particularly rural agricultural areas with high pesticide use versus populations from fields without agricultural activities, would be crucial to determine the broader applicability of these findings. Finally, semi-field studies are needed to validate whether the trends observed in the laboratory, especially the decline of kdr-w , hold under more natural environmental conditions. Conclusions This research demonstrates that the larval aquatic environment is a powerful selective force that significantly shapes the genetic and biochemical basis of insecticide resistance in adult Anopheles gambiae s.l.. The quality of breeding water not only induces metabolic detoxification systems that can enhance insecticide tolerance but also influences the evolutionary trajectory of key target-site mutations over generations. These findings underscore that a comprehensive approach to malaria vector control must extend beyond targeting adult mosquitoes and incorporate larval source management as a strategic tool for mitigating the evolution and spread of insecticide resistance. The chemical ecology of mosquito breeding sites is a critical, and often overlooked, battleground in the fight against malaria. Abbreviations ace-1 acetylcholinesterase BOD biochemical oxygen demand CI confidence interval CTAB Cetyl trimethyl ammonium bromide DDT Dichlorodiphenyltrichloroethane DM deltamethrin DTNB 5,5′-dithiobis-(2-nitrobenzoic acid) DW distilled water EC electrical conductivity FW field water GLM generalized linear model GLMM generalized linear mixed model GST glutathione S-transferases kdr knockdown resistance Mg Magnesium PBO piperonyl butoxide PCR polymerase chain reaction PM permethrin TDS total dissolved solids TMBZ tetramethylbenzidine TW tap water vgsc voltage-gated sodium channel WHO World Health Organization Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials All data generated or analysed during this study are included in this published article and its supplementary information files. Competing interests The authors declare that they have no competing interests Funding No funding was received for this study. Authors’ contributions IKG conceived the idea for this study. JA, IKG, and GKA finalized the study design. IKG, GKA, SSA, AAL, DAB, SG, ABIA, JOJ, SOD, GAK, and AODY conducted the experiments. IKG, GKA, and JA complied and analysed the data. JA, SKD, and RP supervised the study. JA, DKA, RD, and SKD reviewed the manuscript. All authors read and approved the final manuscript. Acknowledgements The authors are grateful to staff of the Ecological Laboratory, University of Ghana, for water sample analyses. The support and insightful contributions from the faculty of the African Regional Postgraduate Programme in Insect Science (ARPPIS), University of Ghana, are also gratefully acknowledged. References F. 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TableS3glmcoefs.xlsx Tables S3: Results of general linear model (GLM) testing the association of filial generation, and water type with frequency of mutations. The fitted model: glm_mut= glm(cbind(mutated_count, non_mutated_count) ~ gen * mutation * water, family = binomial(link = "logit"), data = data) TableS4enzymeexpressiondifferences.xlsx Table S4: ANOVA results for comparison of enzyme quantities between water types at each filial generation. FigS1.docx Figure S1: The temporal variations of water physicochemical parameters across three larval environments. The estimates were made at Weeks 1, Week 7, Week 13, Week 19, and Week 25 during the 25-week experimental period. 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Points represent the mean mortality from four replicates at each generation.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8493684/v1/db6849547ff4b65a2de75c01.png"},{"id":99811657,"identity":"f072d8c5-d888-4673-8f04-3bf049ca6f30","added_by":"auto","created_at":"2026-01-08 14:34:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":141379,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of odds of\u003c/strong\u003e \u003cstrong\u003emortality for each generation relative to the parent filial generation\u003c/strong\u003e. The heatmap's colour intensity reflects the multiplicative change in the odds of death for a given generation compared to its F0 control. An odds ratio \u0026gt;2 (red) means the odds are more than twice as high as F\u003csub\u003e0\u003c/sub\u003e. A value of 1 (white) means the mortality is the same as F0 and blue squares are lower mortaility than F0. Statistical significance \u0026lt;0.05 is indicated as * (Table S2).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8493684/v1/135b66996c93304722ee46e9.png"},{"id":99811967,"identity":"8f95fa19-60f8-4232-908a-10f15309f063","added_by":"auto","created_at":"2026-01-08 14:35:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":132653,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMutation frequencies of insecticide resistance-associated gene across generations. \u003c/strong\u003eThe observed frequencies (A) are plotted as points at each filial generation. Estimated trends in the gene frequencies (B), obtained from GLM, compare decline or increase of the mutation across water types. FW= field water, TW= tap water, DW= distilled water\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8493684/v1/a077b566642b0f26116cf36d.png"},{"id":99811709,"identity":"77a103ae-d973-46f0-a428-a88ebe01f5cf","added_by":"auto","created_at":"2026-01-08 14:34:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":244182,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of mean estimated enzyme levels in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAn. gambiae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e s.l bred in different breeding water type for 5-10 generations. \u003c/strong\u003eEnzymes are in rows and filial generation are in columns (A). Different letters indicate a statistically significant difference, while common letters (e.g. \u003cem\u003ea\u003c/em\u003eand \u003cem\u003eab\u003c/em\u003e) indicate no statistically significant difference (Table S4). The overall change in enzyme levels for DW and TW relative to FW (B) depicts left-sides bar plot that indicate reduced expression. Red bars are significant (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05) while grey bars are not.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8493684/v1/86c720ac45be554064021957.png"},{"id":99811877,"identity":"7e565cd8-2c32-48e3-8560-32d7fc2e3957","added_by":"auto","created_at":"2026-01-08 14:34:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":70815,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of physicochemical parameters in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eAn. gambiae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e s.l bred in different breeding water types. \u003c/strong\u003eDifferent letters indicate a statistically significant difference, while common letters (e.g. \u003cem\u003ea\u003c/em\u003e and \u003cem\u003eab\u003c/em\u003e) indicate no statistically significant difference.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8493684/v1/c5fa6bc5d097d9a76a28a50d.png"},{"id":99814906,"identity":"794e5de2-1139-4ead-b38b-c09efaed1b32","added_by":"auto","created_at":"2026-01-08 14:43:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1810728,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8493684/v1/5934ed83-759e-4092-939c-21700a452f9a.pdf"},{"id":99811802,"identity":"5d94658a-dc48-44fd-8174-983460d0c673","added_by":"auto","created_at":"2026-01-08 14:34:49","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":27784,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable S1: Detailed results from generalized linear mixed model (GLMM) fit to test dependency of mortality on variables including insecticide, water type and filial generation. \u003c/strong\u003eThe model fitted was as follows: glmm_full= glmer(cbind(dead, total - dead) ~ insecticide * water * gen + (1 | rep), data = data, family = binomial(link = \"logit\")). Significant estimates are shown in red fonts.\u003c/p\u003e","description":"","filename":"TableS1glmmcoefs.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8493684/v1/14070389d51d6dc7188e4fc7.xlsx"},{"id":99811878,"identity":"59f0618d-750a-4a82-ad46-31453ee5b2d9","added_by":"auto","created_at":"2026-01-08 14:34:57","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":31371,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable S2: Results from comparing odds of mortality of each filial generation with the reference F0.\u003c/strong\u003e The contrast was made for each insecticide and water type. Significant contrasts are highlighted in green.\u003c/p\u003e","description":"","filename":"TableS2heatmapsig.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8493684/v1/209be0bcc12277a2b4b5c302.xlsx"},{"id":99811887,"identity":"748216f3-d637-4034-a62a-98569d953e2a","added_by":"auto","created_at":"2026-01-08 14:35:05","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":11935,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTables S3: Results of general linear model (GLM) testing the association of filial generation, and water type with frequency of mutations.\u003c/strong\u003e The fitted model: glm_mut= glm(cbind(mutated_count, non_mutated_count) ~ gen * mutation * water, family = binomial(link = \"logit\"), data = data)\u003c/p\u003e","description":"","filename":"TableS3glmcoefs.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8493684/v1/b633a1b6612aa1c0255f2480.xlsx"},{"id":99811654,"identity":"9ae5f179-9295-42a0-abbd-a36b9a8a3a67","added_by":"auto","created_at":"2026-01-08 14:34:29","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":13729,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable S4: ANOVA results for comparison of enzyme quantities between water types at each filial generation.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"TableS4enzymeexpressiondifferences.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8493684/v1/be6496f98dd7fe4f3f108075.xlsx"},{"id":99811610,"identity":"006b3e26-0680-46be-b30f-bb597ad48fb8","added_by":"auto","created_at":"2026-01-08 14:34:16","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":470534,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure S1: The temporal variations of water physicochemical parameters across three larval environments. \u003c/strong\u003eThe estimates were made at Weeks 1, Week 7, Week 13, Week 19, and Week 25 during the 25-week experimental period.\u003c/p\u003e","description":"","filename":"FigS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8493684/v1/e683817b8a410fa614f9f92a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Larval breeding water drives differential selection pressures on genetic insecticide resistance and metabolic enzyme plasticity in Anopheles gambiae s.l","fulltext":[{"header":"Background","content":"\u003cp\u003eMalaria remains a significant global health challenge, particularly in sub-Saharan Africa, where the primary vectors belong to the \u003cem\u003eAnopheles gambiae sensu lato\u003c/em\u003e (s.l.) complex [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u0026ndash;[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Vector control is the cornerstone of malaria prevention and relies heavily on insecticide-based interventions, namely long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Pyrethroids have been the principal class of insecticides used for these interventions due to their efficacy and low mammalian toxicity [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The widespread use of these insecticides has, however, led to the emergence and rapid spread of insecticide resistance in \u003cem\u003eAnopheles\u003c/em\u003e populations, which now threatens the effectiveness of malaria control programs worldwide [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMosquitoes have evolved several mechanisms to survive insecticide exposure. Among these target-site modifications and enhanced metabolic detoxification are the most-studied [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Target-site resistance involves genetic mutations in the protein targets of insecticides, reducing their binding affinity. A well-characterized mutation in \u003cem\u003eAn. gambiae\u003c/em\u003e s.l. include the \u003cem\u003eL\u003c/em\u003e995\u003cem\u003eF\u003c/em\u003e substitution (also known as \u003cem\u003ekdr-w\u003c/em\u003e or knockdown resistance) in the voltage-gated sodium channel (vgsc) gene, which confers resistance to both pyrethroids and DDT [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Another critical mutation is the \u003cem\u003eG\u003c/em\u003e119\u003cem\u003eS\u003c/em\u003e substitution in the acetylcholinesterase gene (\u003cem\u003eace-1\u003c/em\u003e), which reduces susceptibility to organophosphates and carbamates [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The frequency of these mutations is a key indicator of resistance pressure in wild mosquito populations [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u0026ndash;[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Metabolic resistance involves the upregulation of detoxification enzymes that metabolize and sequester insecticides before they can reach their intended target [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u0026ndash;[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The primary enzyme families implicated are cytochrome P450 monooxygenases (P450s), glutathione S-transferases (GSTs), and carboxylesterases (α and β-esterases) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The contribution of metabolic resistance, particularly P450s, can be assessed using the synergist piperonyl butoxide (PBO), which inhibits these enzymes and can restore susceptibility to pyrethroids in resistant mosquitoes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The presence of multiple resistance mechanisms within a single mosquito population complicates vector control efforts and necessitates a deeper understanding of the evolutionary factors driving their selection and maintenance [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u0026ndash;[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe larval environment plays a critical role in shaping the evolutionary trajectory of physiological and biochemical traits of adult mosquitoes, including their insecticide susceptibility [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Mosquito breeding habitats can be influenced by urban pollution and agricultural runoff, exposing larvae to a wide range of chemical contaminants, including pesticides, heavy metals, and high concentrations of organic matter [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Physicochemical parameters of the water, such as pH, electrical conductivity (EC), nutrient levels, and biochemical oxygen demand (BOD), do not merely influence mosquito larval development and the composition of mosquito assemblages [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] but, could also act as selective filters that favour certain genotypes over others. Studies have demonstrated that larval exposure to pollutants can modulate adult longevity, reproductive fitness, and tolerance to insecticides [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, there is significant lack of longitudinal data on how these habitats influence the stability, fixation, or loss of resistance alleles over time.\u003c/p\u003e \u003cp\u003eThe current study used an experimental evolution approach to investigate the impact of rearing \u003cem\u003eAnopheles gambiae\u003c/em\u003e s.l. larvae in three distinct water types: field-collected water, dechlorinated tap water, and distilled water on resistance to insecticides. The research tracks the frequency of the \u003cem\u003ekdr-w\u003c/em\u003e and \u003cem\u003eace-1\u003c/em\u003e target-site mutations and the activity of metabolic detoxification enzymes over 10 filial generations to elucidate the influence of the larval aquatic environment on the stability or otherwise of insecticide resistance.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eBreeding water experimental set-up\u003c/h2\u003e \u003cp\u003e \u003cem\u003eAnopheles gambiae\u003c/em\u003e s.l. mosquito larvae and pupae were collected from breeding ponds on a vegetable farm in Opeibea (5\u0026ordm;35\u0026rsquo;56N; 0\u0026ordm;10\u0026rsquo;59\u0026rsquo;W), a suburb within the Accra Metropolis, Ghana, between September and October 2021. In addition to collecting mosquitoes, samples of the field water were fetched into closed containers. All collected samples were returned to the Vestergaard-Noguchi Vector Laboratory, and the immature mosquitoes were divided into three breeding water types: dechlorinated tap water (TW), samples of the field water (FW), and distilled water (DW). They were raised to adults, transferred into 30cm x 30cm x 30cm netted cages and fed with a 10% sugar solution. Seven to ten-day-old adult female mosquitoes were fed on sheep blood through an artificial membrane feeder. An oviposition dish was prepared and placed in each cage 48\u0026ndash;72 hours after blood-feeding. Eggs collected from adults emerging from the preceding generation of each experimental group were hatched in fresh aliquots of its designated breeding water type for 10 subsequent filial generations. Field water samples were fetched from the vegetable farm pond to wash eggs for hatching in the field water group. All mosquitoes were maintained under standard insectary conditions, i.e., relative humidity (RH) 75\u0026thinsp;\u0026plusmn;\u0026thinsp;10% and temperature 27\u0026thinsp;\u0026plusmn;\u0026thinsp;2℃. Four independent replicates were set-up for each water type at each filial generation.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInsecticide susceptibility tests\u003c/h3\u003e\n\u003cp\u003eInsecticide susceptibility tests were performed on adult female \u003cem\u003eAn. gambiae\u003c/em\u003e s.l. mosquitoes at each filial generation according to World Health Organization standards (WHO) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Representatives of the four classes of insecticides: pyrethroids (0.05% deltamethrin, 0.75% permethrin), organophosphate (0.25% pirimiphos-methyl), organochlorine (4% DDT), and carbamate (0.1% bendiocarb) were tested. A synergist assay with 4% piperonyl butoxide (PBO) with pyrethroids was conducted to assess the probable presence of metabolic enzyme activities within the colony. Twenty to twenty-five 3\u0026ndash;5-day-old non-blood fed female \u003cem\u003eAnopheles gambiae\u003c/em\u003e s.l. were exposed to the various discriminating doses of insecticides for an hour and moved to a holding tube. For the synergist assay, mosquitoes were pre-exposed to PBO for one hour before the pyrethroid insecticides. A control group for the synergist assay was exposed to only PBO. This served as a quality check for the assay since PBO are not insecticides. Mortality\u0026thinsp;\u0026lt;\u0026thinsp;5% after PBO exposure makes the assay valid, between 5% and 20% is corrected with the Abbott formula, and \u0026gt;\u0026thinsp;20% invalidates the assay. Two replicates of silicon-impregnated paper per assay served as the control and were run in parallel with the various insecticides. Mortality was assessed in the holding tube after 24 hours.\u003c/p\u003e \u003cp\u003eWe fit a generalized linear mixed model (GLMM) to investigate insecticide, breeding water type and the filial generation as fixed effects on recorded mortality, using \u003cem\u003eglmer\u003c/em\u003e function from the \u003cem\u003elme4\u003c/em\u003e package in R. The replicates were set as random effect variables. The model was fit with a binomial distribution with a logit link function since the response variable was binary (dead or alive). The odds ratios and 95% confidence intervals (CI) were calculated from the summary estimates obtained from the model. Contrast analyses of mortality per generations were performed using F0 as the reference, and significant mortality was confirmed only when \u003cem\u003ep\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and CI does not include 1. DDT and field water (FW) were also set as the reference insecticide and water type, respectively.\u003c/p\u003e \u003cp\u003e \u003cem\u003eScreening for knockdown resistance (kdr-w L995F) and acetylcholine esterase (Ace-1 G119S) gene mutations.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eFor each water type, 30 mosquitoes from each filial generation were randomly selected from those tested (died or lived) in the WHO susceptibility test. DNA was extracted using 2% Cetyl trimethyl ammonium bromide (CTAB) protocol [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The \u003cem\u003eAnopheles gambiae\u003c/em\u003e vgsc-\u003cem\u003eL\u003c/em\u003e995\u003cem\u003eF\u003c/em\u003e alleles were characterized by PCR with primers AGD1 [5\u0026rsquo;-ATAGATTCCCCGACCATG-3\u0026rsquo;]; AGD2 [5\u0026rsquo;-AGACAAGGATGATGAACC-3\u0026rsquo;], AGD3 [5\u0026rsquo;-AATTTGCATTACTTACGACA-3\u0026rsquo;], and AGD4 [5\u0026rsquo;-CTGTAGTGATAGGAAATTTA-3\u0026rsquo;], and the \u003cem\u003eace-1\u003c/em\u003e alleles with EX3AGdir [5\u0026rsquo;-GATCGTGGACACCGTGTTCG-3\u0026rsquo;] and EX3AGrev [5\u0026rsquo;-AGGATGGCCCGCTGGAACAG-3\u0026rsquo;], using established protocols [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA generalized linear model (GLM) was used to analyse whether observed mutation frequencies were dependent on the filial generation, mutation type (\u003cem\u003ekdr-w\u003c/em\u003e, ace1) and water. The model was fit using a binomial distribution with a logit link function using the \u003cem\u003eglm\u003c/em\u003e function in R. Odds ratio and 95% CI were calculated as earlier described. The frequencies were compared among filial generation in each water type, and between water types. Linear trends of mutation frequencies from F\u003csub\u003e0\u003c/sub\u003e to F\u003csub\u003e10\u003c/sub\u003e were also analysed and compared.\u003c/p\u003e \u003cp\u003eThe mortality and mutation frequency data was merged based on filial generation and water type to investigate correlation of the mutation frequencies with mortality observed following exposure to each insecticide. We performed Pearson's product-moment correlation for each unique combination of mutation type, insecticide, and water source. The correlation coefficient (r) and the corresponding \u003cem\u003ep\u003c/em\u003e-value were calculated for each of these combinations to determine the strength and statistical significance of the relationship. Combinations with fewer than two data points were excluded from the correlation analysis.\u003c/p\u003e\n\u003ch3\u003eBiochemical assay for estimation of enzyme activity\u003c/h3\u003e\n\u003cp\u003eFifty non-blood-fed, non-insecticide exposed female mosquitoes per filial generation from each breeding water type were assessed for enzyme activities using the techniques already outlined [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The evaluated enzymes were P450 monooxygenases (P450s), carboxylesterases (α and β-esterases), and Insensitive acetylcholine esterase (Ache). Individual mosquitoes were homogenized in 0.1 M potassium phosphate buffer (pH\u0026thinsp;=\u0026thinsp;7.2), centrifuged, and the resulting supernatant was collected for use in the biochemical assays. Positive and negative controls were included on each microplate to ensure consistency, reliability, and accuracy of the experimental results.\u003c/p\u003e \u003cp\u003eThe nonspecific esterase activity was determined using either α-naphthyl acetate or β-naphthyl acetate as substrates. The reaction products were coupled with Fast Blue B salt to form a coloured complex whose intensity corresponded to enzyme activity. The absorbance of β-naphthyl and α-naphthyl reactions was recorded at 540 nm and 620 nm, respectively. This allowed for the quantification of esterase activity, which reflects the hydrolytic potential of the enzyme in metabolizing ester-containing insecticides.\u003c/p\u003e \u003cp\u003eOxidase activity was assessed using tetramethylbenzidine (TMBZ) and hydrogen peroxide as chromogenic reagents, with cytochrome C serving as the positive control. The reaction was allowed to proceed under standardized incubation conditions, after which absorbance was measured at 620 nm. The degree of color development was proportional to the level of oxidase activity, which is indicative of the mosquito\u0026rsquo;s capacity for oxidative detoxification of insecticides.\u003c/p\u003e \u003cp\u003eAcetylcholinesterase (AChE) activity was evaluated using acetylthiocholine iodide and 5,5\u0026prime;-dithiobis-(2-nitrobenzoic acid) (DTNB) as reagents. The assay was conducted both in the absence and presence of the carbamate inhibitor propoxur to detect insensitive enzyme variants. The rate of colour formation, resulting from the reaction between thiocholine and DTNB to produce a yellow-coloured anion of 5-thio-2-nitrobenzoic acid, was measured at 414 nm. The change in absorbance indicated the presence of altered enzyme forms associated with target site insensitivity.\u003c/p\u003e \u003cp\u003eTotal protein content in each homogenate was determined using a microplate-based protein assay, and absorbance was measured at 620 nm. The protein concentration of each sample was used to normalize enzyme activity, which was expressed as absorbance per milligram of protein.\u003c/p\u003e \u003cp\u003eEnzyme expression profiles were compared between samples from different breeding water types from the same filial generation and across the different filial generations using a series of one-way analyses of variance (ANOVA). When water type was detected by the ANOVA as a significant effect, we performed a Tukey's Honest Significant Difference (HSD) post-hoc test to identify which specific water type pairs had significant differences. Additionally, to assess the overall change in enzyme expression across all generations, we performed a series of independent samples Welch's t-tests. For each enzyme, we compared the expression levels in the FW (field water) control group to the DW (distilled water) and TW (tap water) groups separately.\u003c/p\u003e\n\u003ch3\u003ePhysicochemical assessment of breeding water\u003c/h3\u003e\n\u003cp\u003ePhysicochemical parameters, including biochemical oxygen demand (BOD), pH, electrical conductivity (EC), total dissolved solids (TDS), total alkalinity, chlorine, phosphate, total ammonia nitrogen, carbon dioxide, calcium, magnesium, and total hardness, were assessed in each type of breeding water at F0 and every other generation (a total of 5 times) across the 10 filial generations [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStatistical analysis was performed using Stata/IC 64 software. The Shapiro-Wilk test was applied to assess the normality of the data, and since the physiochemical parameter values of the various breeding water types did not follow a normal distribution, the Bonferroni non-parametric test was used for pairwise comparisons between water types.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePyrethroid-PBO overcomes persistent phenotypic resistance across all water types\u003c/h2\u003e \u003cp\u003eWe investigated changes in the \u003cem\u003eAn. gambiae\u003c/em\u003e s.l susceptibility phenotype against several insecticides following continual breeding in different water types for 10 filial generations. High levels of phenotypic resistance were sustained across all generations for most insecticides, with the notable exception of pyrethroid-PBO combinations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Mortalities recorded in F\u003csub\u003e1\u003c/sub\u003e- F\u003csub\u003e10\u003c/sub\u003e, except for the distilled water (DW) colony which could not survive beyond the 5th generation, were compared to the reference population (F\u003csub\u003e0\u003c/sub\u003e). The logistic regression analysis demonstrated that the baseline odds of mortality for the F\u003csub\u003e0\u003c/sub\u003e generation in FW with DDT exposure (reference insecticide) was significantly low (OR\u0026thinsp;=\u0026thinsp;0.046, 95% CI= [0.014, 0.146], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e), establishing a minimal mortality rate for the founding population. Mortality in FW increased by odds of 5.23 (95%CI= [1.36, 20.12], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016) only in F\u003csub\u003e8\u003c/sub\u003e compared to F\u003csub\u003e0\u003c/sub\u003e assuming reference levels for all tested variables. Insecticide treatments containing the synergist piperonyl butoxide (PBO) resulted in higher odds of mortality with deltamethrin\u0026thinsp;+\u0026thinsp;PBO (DM\u0026thinsp;+\u0026thinsp;PBO) dramatically increasing the odds of death by ~\u0026thinsp;358 (95%CI= [77.08, 1663.24], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to the reference insecticide, DDT (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). While the main effects highlight the overall potency of PBO-synergized insecticides, the analysis of interaction terms revealed a more complex relationship between the factors. Significantly increased mortality was identified with the pyrethroids (PM, DM)\u0026thinsp;+\u0026thinsp;PBO from as early as F\u003csub\u003e1\u003c/sub\u003e and at other specific generations (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e) as observed for DM\u0026thinsp;+\u0026thinsp;PBO in tap water at F\u003csub\u003e8\u003c/sub\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.025). Therefore, among the water types compared, tap water appears to increase susceptibility to pyrethroids\u0026thinsp;+\u0026thinsp;PBO insecticides, though this is not consistent over 10 generations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe investigated whether the generational mortality trends for each insecticide differed between the breeding water types. The analyses also allowed an assessment of which specific filial generations changed significantly from F\u003csub\u003e0\u003c/sub\u003e within each larval environment. The results revealed consistent and transient susceptibility patterns. Tap water (TW) reared mosquitoes showed relatively high mortality at F\u003csub\u003e1\u003c/sub\u003e for all insecticides, except PM, PM\u0026thinsp;+\u0026thinsp;PBO and DM\u0026thinsp;+\u0026thinsp;PBO (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This reverted at F\u003csub\u003e2\u003c/sub\u003e and stayed consistently similar to F0 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) despite observed subtle changes in mean mortality throughout the remaining generations (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). On the contrary, formulations containing PBO (DM\u0026thinsp;+\u0026thinsp;PBO, PM\u0026thinsp;+\u0026thinsp;PBO) were associated with significantly persistent lowered mortality from F\u003csub\u003e1\u003c/sub\u003e to F\u003csub\u003e10\u003c/sub\u003e regardless of water type. The odds for mortality were generally\u0026thinsp;\u0026lt;\u0026thinsp;0.1, except F\u003csub\u003e6\u003c/sub\u003e (OR\u0026thinsp;=\u0026thinsp;7.86, 95%CI= [2.57, 24.05], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) where there was a one timepoint increased mortality relative to F\u003csub\u003e0\u003c/sub\u003e in FW (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDivergent evolutionary trajectories of kdr-w and ace-1 mutations across water types\u003c/h3\u003e\n\u003cp\u003eWe fitted a generalized linear model (GLM) to estimate the probability of a mosquito possessing a specific mutation at a given generation in a particular water type and then analysed trends in the changes (slopes) mutations across generations between water types. The single nucleotide mutations \u003cem\u003eL\u003c/em\u003e995\u003cem\u003eF\u003c/em\u003e (\u003cem\u003ekdr-w\u003c/em\u003e) and \u003cem\u003eG\u003c/em\u003e119\u003cem\u003eS\u003c/em\u003e (\u003cem\u003eace-1\u003c/em\u003e) of \u003cem\u003eAn. gambiae\u003c/em\u003e s.l. populations were observed across all generations (F\u003csub\u003e0\u003c/sub\u003e-F\u003csub\u003e10\u003c/sub\u003e) for each breeding water. The estimated mutation frequencies across generations revealed contrasting temporal trends for the \u003cem\u003eace-1\u003c/em\u003e and \u003cem\u003ekdr-w\u003c/em\u003e. The frequency of \u003cem\u003ekdr-w\u003c/em\u003e was consistently higher than \u003cem\u003eace-1\u003c/em\u003e irrespective of the water type with ~\u0026thinsp;12 times higher odds (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, 95%CI= [4,23, 32.99]) of occurring compared to \u003cem\u003eace-1\u003c/em\u003e (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e). \u003cem\u003eKdr-w\u003c/em\u003e frequency generally fluctuated between 90\u0026ndash;100%, showing a strong fixation propensity (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). \u003cem\u003eAce-1\u003c/em\u003e mutation frequency changed from 63% at F\u003csub\u003e0\u003c/sub\u003e in TW to 93% at F\u003csub\u003e8\u003c/sub\u003e, indicating a progressive accumulation of this mutation over time. Except in TW where \u003cem\u003ekdr-w\u003c/em\u003e rapidly rose to fixation after a decline at F\u003csub\u003e1\u003c/sub\u003e, this mutation generally showed a declining trend from an initial value of ~\u0026thinsp;100% at F\u003csub\u003e0\u003c/sub\u003e in FW and DW to 76% at F\u003csub\u003e3\u003c/sub\u003e in DW (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). In FW, the odds for the \u003cem\u003ekdr-w\u003c/em\u003e mutation decreases by about 19% (OR\u0026thinsp;=\u0026thinsp;0.81, 95%CI= [0.70, 0.94], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005) with each passing generation, while it increased significantly in mosquitoes bred in TW (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e: gen*\u003cem\u003ekdr-w\u003c/em\u003e*TW).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eField water composition induces significant metabolic enzyme plasticity\u003c/h3\u003e\n\u003cp\u003eThe expression levels of the enzymes tested; insensitive acetylcholinesterase (AChE), ⍺-esterase, β-esterase, and mixed function oxidase, varied significantly across generations (ANOVA: F\u0026thinsp;=\u0026thinsp;6.669, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and were influenced by water type (ANOVA: F\u0026thinsp;=\u0026thinsp;4.609, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010). Considering F\u003csub\u003e0\u003c/sub\u003e-F\u003csub\u003e5\u0026mdash;\u003c/sub\u003e to enable inclusion of DW\u0026ndash; we observed that TW and DW often had similar expression levels with instances where either one or both differed significantly from FW. For instance, the expression of ⍺-esterase at F\u003csub\u003e0\u003c/sub\u003e was similar for TW and DW, but at F\u003csub\u003e1\u003c/sub\u003e all three water types differed (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). The differences, however, was not consistent for onward generations, but at least one water type (often FW) differed from the others. The expression of oxidase also showed similar patterns as described for ⍺-esterase and, Ache and β-esterase expressions were generally similar across water types (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eFrom F\u003csub\u003e6\u003c/sub\u003e - F\u003csub\u003e10\u003c/sub\u003e where only FW and TW were compared, we observe similar ⍺ -esterase expression between these water types, while the other enzymes differed often at various generations. While breeding in DW appeared to reduce levels of ⍺- and β-esterases in the mosquitoes, TW did not result in significant changes in these enzymes. Ache was the least affected enzyme and was similarly reduced in DW and TW reared mosquitoes (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eMarked differences in the physicochemical profiles of the three water types were observed over the experimental period, providing selective landscapes for the developing larvae (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Fig \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). FW exhibited elevated levels of biochemical oxygen demand (BOD), electrical conductivity (EC) and total dissolved solids (TDS) peaking at 436 mg/L, 1,060 \u0026micro;S/cm and 805 mg/L, respectively, far exceeding the values recorded for TW and DW (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Nutrient concentrations were also elevated in FW compared to TW and DW. Phosphate and ammonia nitrogen (NH₄\u0026ndash;N) were exceptionally high in week 1 before declining in subsequent weeks (\u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.016). These values in exceeded WHO limits for\u0026hellip;.. Calcium (Ca) and magnesium (Mg) remained below the WHO guideline of 200 mg/L for all water types. pH values were generally within the WHO-recommended range (6.5\u0026ndash;8.5) for all water types (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05), though FW showed slight fluctuations between 6.91 and 7.76.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOverall, larvae reared in nutrient-rich FW consistently exhibited significantly higher metabolic enzyme activity compared to TW and DW cohorts. This was most pronounced in oxidase levels, which were elevated by up to 32% (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), indicating that FW induces a higher baseline of detoxification capacity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe have tracked phenotypic insecticide susceptibility, target-site mutation frequencies, and metabolic enzyme activity over 11 filial generations (including the founding population), to provide confirmatory evidence that the larval aquatic environment plays a crucial role in the evolution of insecticide resistance profiles of adult mosquitoes. Our key findings reveal a significant decline in the frequency of the \u003cem\u003ekdr-w\u003c/em\u003e mutation, a concurrent rise in the \u003cem\u003eace-1\u003c/em\u003e mutation, and a strong induction of detoxification enzymes by nutrient and ion-rich field water. These appear to sustain the effectiveness of PBO-synergized pyrethroids, indicating a strong metabolic influence while the underlying genetic and biochemical mechanisms are dynamic and environmentally modulated. There was evidence of potentially increasing susceptibility to other classes of insecticides including non-synergized pyrethroids during continuous mosquito maintenance in dechlorinated tap water (TW) and distilled water (DW), although this was not observed to be significant given the limits of the current study. We discuss implications for our selection of water source for laboratory colonization of \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes, and for mechanisms for insecticide resistance and vector related to the population studied.\u003c/p\u003e \u003cp\u003eThe most striking result of this study was the unexpected rapid increase to fixation of the \u003cem\u003ekdr-w\u003c/em\u003e mutation by F\u003csub\u003e2\u003c/sub\u003e in mosquito populations reared in dechlorinated tap water (TW). This strong selection was unusual compared to field water (FW) and distilled water (DW) where the mutation frequency fluctuated and remained high but variable. Tap water often contains residual chlorine, heavy metals from pipes or specific mineral ions which can act as xenobiotics and select for individuals with more robust detoxification or stress-response systems, which are often genetically linked to resistance loci. This differential selection highlights the importance of water physicochemical factors in driving the evolution of target-site mediated pyrethroid resistance. In contrast to \u003cem\u003ekdr-w\u003c/em\u003e, the frequency of \u003cem\u003eace-1\u003c/em\u003e mutation, which confers resistance to organophosphates (OPs) and carbamates, remained lower and never reached fixation in any water type, despite an overall decline in the frequency of the \u003cem\u003ekdr-w\u003c/em\u003e mutation over 10 generations. The lower frequency of \u003cem\u003eace-1\u003c/em\u003e may suggest a fitness cost associated with the mechanism, or that the selection pressure that favours pyrethroid resistance was overwhelmingly dominant during our experiments [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. The generational decline in \u003cem\u003ekdr-w\u003c/em\u003e frequencies supports the hypothesis of a fitness cost, a phenomenon described in other vector populations where resistance alleles decrease in frequency when selection pressure is removed [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. For instance, a significant fitness cost associated with the \u003cem\u003eL\u003c/em\u003e1014\u003cem\u003eS\u003c/em\u003e-\u003cem\u003ekdr\u003c/em\u003e mutation in a Ugandan \u003cem\u003eAn. gambiae\u003c/em\u003e population led to a restoration of susceptibility in an insecticide-free environment [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Our study provides further evidence for this phenomenon with the L995F allele during laboratory colonization. These results highlight that in the maintenance of mosquito populations in the laboratory the breeding water source should be carefully monitored especially when the mosquitoes will be used for investigating mechanisms of insecticide resistance. Even without active insecticide application, the genetic architecture of resistance within a population can evolve rapidly during colonization, potentially predisposing it to resistance against different insecticide classes.\u003c/p\u003e \u003cp\u003eOur enzyme analyses showed dramatic effects of water type on detoxification capacity. Mosquitoes reared in field water, which was characterized by a high organic and ionic load, consistently showed elevated levels of detoxification enzymes, particularly ⍺-esterases and mixed-function oxidases (P450s). Oxidase activity showed the largest reduction of 32.1% in DW relative to FW. Similarly, ⍺-esterase activity significantly decreased in DW but was stable in TW. Oxidases and ⍺-esterases are crucial for metabolic resistance against multiple insecticide classes[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], hence their reduced activities in the artificial waters (DW, and to a lesser extent, TW) suggests that natural inducers present in the FW environment are essential for maintaining the high baseline levels of these key metabolic enzymes. Their absence in the laboratory waters may effectively reduce the mosquitoes' intrinsic detoxification capacity. β-esterases confer metabolic resistance by sequestering insecticides such as organophosphates, carbamates, and pyrethroids before these compounds reach their neural targets. Elevated β-esterase activity, often resulting from gene overexpression, enhances the breakdown of insecticides and consequently reduces their toxicity to mosquitoes [\u003cspan additionalcitationids=\"CR45 CR46\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u0026ndash;[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Acetylcholinesterase (AChE), on the other hand, is an essential enzyme that hydrolyzes the neurotransmitter acetylcholine to terminate synaptic transmission. Organophosphate and carbamate insecticides specifically target AChE by irreversibly or reversibly inhibiting its activity, leading to the accumulation of acetylcholine at synaptic junctions, neural overstimulation, and ultimately, insect death [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. All the laboratory water types (DW and TW) showed a significant decrease for β-esterase and AChE activity across generations. This suggests a mechanism of phenotypic plasticity, where exposure to environmental xenobiotics in the larval stage \"primes\" the adult's detoxification systems, potentially conferring enhanced tolerance to insecticides later in life. Our findings align with a growing body of evidence highlighting the link between the larval environment and adult insecticide susceptibility [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Pollution and agricultural runoff in breeding sites contribute to increased insecticide resistance in \u003cem\u003eAnopheles\u003c/em\u003e vectors [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The physicochemical analysis of our field water, which revealed high levels of biochemical oxygen demand (BOD), electrical conductivity (EC), and nutrients, corresponds with characteristics of polluted and agricultural habitats known to select for resistance [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe central role of metabolic resistance, particularly mediated by P450 enzymes, is well-documented across Africa [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. The restoration of susceptibility with PBO in our study is consistent with findings from Benin, Cameroon, and Nigeria, where P450s like CYP6M2 and CYP6P3 are major drivers of pyrethroid resistance [\u003cspan additionalcitationids=\"CR54 CR55\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]\u0026ndash;[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. The profound increase in mortality when mosquitoes were exposed to deltamethrin and permethrin in combination with the synergist PBO strongly implicates mixed-function oxidase enzymes as a primary mechanism of metabolic resistance in this population. The odds of death for deltamethrin with PBO were approximately 358 times higher than the baseline, confirming that inhibiting these enzymes can largely restore pyrethroid susceptibility. However, the observation that the efficacy of these synergized insecticides diminished in later generations suggests that the mosquito colony was adapting, possibly through the selection of alternative resistance mechanisms not fully inhibited by PBO.\u003c/p\u003e \u003cp\u003eThe insecticide resistance mechanisms in the mosquito population studied suggested by our results is that the complex chemical matrix of natural breeding sites induces a broad, non-specific upregulation of the mosquito's detoxification machinery. The higher organic and nutrient content in field water likely serves as an environmental stressor that selects for a more robust enzymatic defense system [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This has critical implications for vector control. It suggests that larval source management (LSM) is not merely a tool for population reduction but could also be a vital component of insecticide resistance management. By cleaning or modifying polluted breeding sites, control programs could potentially reduce the selection for metabolically resistant mosquitoes, thereby producing adult populations that are more susceptible to existing insecticides [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. The observed shift from \u003cem\u003ekdr-w\u003c/em\u003e based resistance towards \u003cem\u003eace-1\u003c/em\u003e dominance in the laboratory colony underscores the evolutionary plasticity of \u003cem\u003eAn. gambiae\u003c/em\u003e. This implies that if vector control programs were to switch from pyrethroids to organophosphates or carbamates to manage \u003cem\u003ekdr-w\u003c/em\u003e resistance, this population already possesses a high frequency of the corresponding \u003cem\u003eace-1\u003c/em\u003e resistance allele, which could lead to rapid control failure. This highlights the necessity for integrated resistance management strategies that include rotational insecticide use, synergists, and non-chemical interventions like LSM.\u003c/p\u003e \u003cp\u003eThis study has several notable strengths. The longitudinal design, tracking a single mosquito colony for 10 filial generations, allowed for the observation of micro-evolutionary changes in resistance mechanisms over time, providing insights that cross-sectional studies cannot offer. The multi-pronged approach, integrating phenotypic bioassays, molecular genotyping, and biochemical enzyme analysis, provides a holistic and robust characterization of the resistance profile. Finally, the use of three distinct and well-characterized water types enabled a controlled comparison to isolate and understand the specific impact of breeding water quality on resistance dynamics. Despite these strengths, the study has limitations. First, laboratory colonization inherently differs from natural conditions. Factors such as predation, competition, and fluctuating environmental conditions are absent, which may alter the fitness costs and benefits of resistance alleles. Therefore, the observed decline in \u003cem\u003ekdr-w\u003c/em\u003e frequency might be more pronounced in the laboratory than it would be in the field, where pyrethroid pressure persists. Second, the mosquito population originated from a single urban site in Accra, and the findings may not be generalizable to other \u003cem\u003eAn. gambiae\u003c/em\u003e populations in different ecological settings, such as rural agricultural areas.\u003c/p\u003e \u003cp\u003eAn alternative explanation for the steady increase in \u003cem\u003eace-1\u003c/em\u003e frequency could be genetic drift, which can have a strong effect in laboratory colonies founded from a limited number of wild individuals, rather than an unmeasured selective pressure. Similarly, while the increased enzyme activity in field water reared mosquitoes is likely due to chemical induction, it cannot be entirely disconnected from potential nutritional benefits, as the rich microbial community and dissolved organic matter might produce healthier, larger adults with inherently more active metabolic systems. Lastly, the collapse of the distilled water colony after the fifth generation limited long-term comparisons for this control group.\u003c/p\u003e \u003cp\u003eThis study opens several avenues for future research. Transcriptomic (RNA-seq) analyses should be conducted on larvae and adults reared in different water types to identify upregulated detoxification genes more comprehensively. This would provide a more precise understanding than the broad enzyme activity assays used here. To confirm the fitness cost hypothesis, targeted studies measuring life-history traits (e.g., longevity, fecundity, mating competitiveness) should be performed on mosquitoes with different \u003cem\u003ekdr-w\u003c/em\u003e and \u003cem\u003eace-1\u003c/em\u003e genotypes from this population. Furthermore, replicating this longitudinal study with populations from different ecological zones, particularly rural agricultural areas with high pesticide use versus populations from fields without agricultural activities, would be crucial to determine the broader applicability of these findings. Finally, semi-field studies are needed to validate whether the trends observed in the laboratory, especially the decline of \u003cem\u003ekdr-w\u003c/em\u003e, hold under more natural environmental conditions.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis research demonstrates that the larval aquatic environment is a powerful selective force that significantly shapes the genetic and biochemical basis of insecticide resistance in adult \u003cem\u003eAnopheles gambiae\u003c/em\u003e s.l.. The quality of breeding water not only induces metabolic detoxification systems that can enhance insecticide tolerance but also influences the evolutionary trajectory of key target-site mutations over generations. These findings underscore that a comprehensive approach to malaria vector control must extend beyond targeting adult mosquitoes and incorporate larval source management as a strategic tool for mitigating the evolution and spread of insecticide resistance. The chemical ecology of mosquito breeding sites is a critical, and often overlooked, battleground in the fight against malaria.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eace-1\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;acetylcholinesterase\u003c/p\u003e\n\u003cp\u003eBOD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;biochemical oxygen demand\u003c/p\u003e\n\u003cp\u003eCI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;confidence interval\u003c/p\u003e\n\u003cp\u003eCTAB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Cetyl trimethyl ammonium bromide\u003c/p\u003e\n\u003cp\u003eDDT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Dichlorodiphenyltrichloroethane\u003c/p\u003e\n\u003cp\u003eDM \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;deltamethrin\u003c/p\u003e\n\u003cp\u003eDTNB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;5,5′-dithiobis-(2-nitrobenzoic acid)\u003c/p\u003e\n\u003cp\u003eDW\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;distilled water\u003c/p\u003e\n\u003cp\u003eEC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;electrical conductivity\u003c/p\u003e\n\u003cp\u003eFW\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;field water\u003c/p\u003e\n\u003cp\u003eGLM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;generalized linear model\u003c/p\u003e\n\u003cp\u003eGLMM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;generalized linear mixed model\u003c/p\u003e\n\u003cp\u003eGST\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;glutathione S-transferases\u003c/p\u003e\n\u003cp\u003ekdr \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;knockdown resistance\u003c/p\u003e\n\u003cp\u003eMg\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Magnesium\u003c/p\u003e\n\u003cp\u003ePBO\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;piperonyl butoxide\u003c/p\u003e\n\u003cp\u003ePCR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;polymerase chain reaction\u003c/p\u003e\n\u003cp\u003ePM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;permethrin\u003c/p\u003e\n\u003cp\u003eTDS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;total dissolved solids\u003c/p\u003e\n\u003cp\u003eTMBZ\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;tetramethylbenzidine\u003c/p\u003e\n\u003cp\u003eTW\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;tap water\u003c/p\u003e\n\u003cp\u003evgsc\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;voltage-gated sodium channel\u003c/p\u003e\n\u003cp\u003eWHO\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article and its supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIKG conceived the idea for this study. JA, IKG, and GKA finalized the study design. IKG, GKA, SSA, AAL, DAB, SG, ABIA, JOJ, SOD, GAK, and AODY conducted the experiments. IKG, GKA, and JA complied and analysed the data. JA, SKD, and RP supervised the study. JA, DKA, RD, and SKD reviewed the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to staff of the Ecological Laboratory, University of Ghana, for water sample analyses. The support and insightful contributions from the faculty of the African Regional Postgraduate Programme in Insect Science (ARPPIS), University of Ghana, are also gratefully acknowledged.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eF. 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Jin, \u003cem\u003eNew and Future Development in Biopesticide Research: Biotechnological Exploration\u003c/em\u003e. 2022. doi: 10.1007/978-981-16-3989-0.\u003c/li\u003e\n\u003cli\u003eF. Cui \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Carboxylesterase-mediated insecticide resistance: Quantitative increase induces broader metabolic resistance than qualitative change,\u0026rdquo; \u003cem\u003ePestic. Biochem. Physiol.\u003c/em\u003e, vol. 121, pp. 88\u0026ndash;96, 2015, doi: 10.1016/j.pestbp.2014.12.016.\u003c/li\u003e\n\u003cli\u003eV. L. Low \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Enzymatic characterization of insecticide resistance mechanisms in field populations of Malaysian Culex quinquefasciatus say (Diptera: Culicidae),\u0026rdquo; \u003cem\u003ePLoS One\u003c/em\u003e, vol. 8, no. 11, pp. 1\u0026ndash;8, 2013, doi: 10.1371/journal.pone.0079928.\u003c/li\u003e\n\u003cli\u003eS. H. 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Endocrinol.\u003c/em\u003e, vol. 108, no. 1, pp. 19\u0026ndash;31, May 1994, doi: 10.1016/1367-8280(94)90084-1.\u003c/li\u003e\n\u003cli\u003eR. R. Samal, K. Panmei, P. Lanbiliu, and S. Kumar, \u0026ldquo;Metabolic detoxification and \u003cem\u003eace-1\u003c/em\u003e target site mutations associated with acetamiprid resistance in Aedes aegypti L,\u0026rdquo; \u003cem\u003eFront. Physiol.\u003c/em\u003e, vol. 13, p. 988907, Aug. 2022, doi: 10.3389/FPHYS.2022.988907/BIBTEX.\u003c/li\u003e\n\u003cli\u003eC. Antonio-Nkondjio \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Anopheles gambiae distribution and insecticide resistance in the cities of Douala and Yaound\u0026eacute; (Cameroon): influence of urban agriculture and pollution,\u0026rdquo; \u003cem\u003eSpringerC Antonio-Nkondjio, BT Fossog, C Ndo, BM Djantio, SZ Togouet, P Awono-AmbeneMalaria Journal, 2011\u0026bull;Springer\u003c/em\u003e, vol. 10, 2011, doi: 10.1186/1475-2875-10-154.\u003c/li\u003e\n\u003cli\u003eT. E. 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Dj\u0026egrave;gb\u0026egrave; \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Molecular characterization of DDT resistance in Anopheles gambiae from Benin,\u0026rdquo; \u003cem\u003eSpringerI Dj\u0026egrave;gb\u0026egrave;, FR Agossa, C. Jones, R Poupardin, S Cornelie, M Akogb\u0026eacute;to, H Ranson, V CorbelParasites vectors, 2014\u0026bull;Springer\u003c/em\u003e, vol. 7, no. 1, Aug. 2014, doi: 10.1186/1756-3305-7-409.\u003c/li\u003e\n\u003cli\u003eI. Fagbohun, E. Idowu, O. Otubanjo, T. A.-S. Reports, and undefined 2020, \u0026ldquo;First report of AChE1 (G119S) mutation and multiple resistance mechanisms in Anopheles gambiae ss in Nigeria,\u0026rdquo; \u003cem\u003enature.comIK Fagbohun, Idowu, OA Otubanjo, TS AwololaScientific Reports, 2020\u0026bull;nature.com\u003c/em\u003e, doi: 10.1038/s41598-020-64412-7.\u003c/li\u003e\n\u003cli\u003eN. A. Kala-Chouakeu \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Pyrethroid Resistance Situation across Different Eco-Epidemiological Settings in Cameroon,\u0026rdquo; \u003cem\u003eMolecules\u003c/em\u003e, vol. 27, no. 19, p. 6343, Oct. 2022, doi: 10.3390/MOLECULES27196343/S1.\u003c/li\u003e\n\u003cli\u003eY. Fotso-Toguem \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Genetic Diversity of Cytochrome P450s CYP6M2 and CYP6P4 Associated with Pyrethroid Resistance in the Major Malaria Vectors Anopheles coluzzii and Anopheles gambiae from Yaound\u0026eacute;, Cameroon,\u0026rdquo; \u003cem\u003eGenes (Basel).\u003c/em\u003e, vol. 14, no. 1, p. 52, Jan. 2023, doi: 10.3390/GENES14010052/S1.\u003c/li\u003e\n\u003cli\u003eM. Avramov, A. Thaivalappil, \u0026hellip; A. L.-J. of M., and undefined 2024, \u0026ldquo;Relationships between water quality and mosquito presence and abundance: a systematic review and meta-analysis,\u0026rdquo; \u003cem\u003eAcad. Avramov, A Thaivalappil, A Ludwig, L Miner, CI Cullingham, L Waddell, DR LapenJournal Med. Entomol. 2024\u0026bull;academic.oup.com\u003c/em\u003e, Accessed: Aug. 26, 2025. [Online]. Available: https://academic.oup.com/jme/article-abstract/61/1/1/7313562\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Anopheles gambiae s.l., insecticide resistance, larval environment, kdr, ace-1, metabolic resistance, phenotypic plasticity, larval source management, experimental evolution","lastPublishedDoi":"10.21203/rs.3.rs-8493684/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8493684/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe control of mosquito-borne diseases is heavily reliant on insecticide-based interventions. The evolution of insecticide resistance is a complex process driven by both direct chemical exposure and indirect environmental pressures. While the larval environment is known to influence adult mosquito traits, its long-term impact on the evolution of multiple resistance mechanisms is poorly understood. This study used an experimental evolution approach to investigate how larval aquatic environments select for insecticide resistance profiles in \u003cem\u003eAn. gambiae\u003c/em\u003e s.l. over 10 successive generations.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e \u003cem\u003eAnopheles gambiae\u003c/em\u003e s.l. larvae were collected from a single site in Accra, Ghana, and colonized in the laboratory for 10 filial generations. The larvae were reared in three distinct water types: field-collected water (FW), dechlorinated tap water (TW), and distilled water (DW). At each generation, phenotypic susceptibility to four classes of insecticides was assessed using WHO bioassays, including synergist assays with piperonyl butoxide (PBO). The frequencies of the \u003cem\u003ekdr-w\u003c/em\u003e (\u003cem\u003eL\u003c/em\u003e995\u003cem\u003eF\u003c/em\u003e) and \u003cem\u003eace-1\u003c/em\u003e (\u003cem\u003eG\u003c/em\u003e119\u003cem\u003eS\u003c/em\u003e) target-site mutations were determined using molecular analysis. The activity of key metabolic enzymes, P450 monooxygenases, carboxylesterases (α and β), and insensitive acetylcholinesterase was quantified through biochemical assays. Selected physicochemical properties of the rearing waters were also characterized.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e \u003cem\u003ekdr-w\u003c/em\u003e mutation rapidly increased to fixation by generation F\u003csub\u003e2\u003c/sub\u003e in mosquitoes reared in dechlorinated tap water, a trend not observed in the other two water types, suggesting a strong, water-mediated selective advantage provided by tap water chemistry. There was an overall significant decline in the frequency of the \u003cem\u003ekdr-w\u003c/em\u003e mutation from 90\u0026ndash;100% at F0 to ~\u0026thinsp;63% by F\u003csub\u003e10\u003c/sub\u003e. Conversely, the frequency of the \u003cem\u003eace-1\u003c/em\u003e mutation increased steadily from approximately 60% to 90% over the 10 generations. Mosquitoes reared in the nutrient and ion-rich field water consistently exhibited significantly elevated levels of detoxification enzymes, particularly ⍺-esterases and mixed-function oxidases (up to 32% for oxidases), compared to those reared in tap and distilled water indicating phenotypic plasticity induced by natural environmental co-factors.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe larval aquatic environment fundamentally shapes the genetic and biochemical basis of insecticide resistance in adult \u003cem\u003eAnopheles gambiae\u003c/em\u003e s.l.. The physicochemical composition of breeding water induces metabolic detoxification systems and influences the rate of fixation of target-site mutations. These findings suggest that environmental co-factors play a critical role in the persistence of resistance genes, providing a new evolutionary framework for integrated vector management. Larval source management can serve not only to reduce vector populations but also be a critical tool for managing insecticide resistance by modifying the environmental pressures that select for resistant phenotypes.\u003c/p\u003e","manuscriptTitle":"Larval breeding water drives differential selection pressures on genetic insecticide resistance and metabolic enzyme plasticity in Anopheles gambiae s.l","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-08 13:53:01","doi":"10.21203/rs.3.rs-8493684/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-03T05:31:24+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-28T23:49:28+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-27T08:04:24+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-20T18:05:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"328900450941705049902085013452680814243","date":"2026-01-15T22:14:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"309812829608790695156485534508968205037","date":"2026-01-13T07:59:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8134050057662097668400316679689303267","date":"2026-01-06T15:39:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-06T15:03:47+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-05T10:40:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-02T12:13:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-02T12:11:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-01-01T07:08:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ddca5e13-6e90-44b6-8143-c1505ba4d1a3","owner":[],"postedDate":"January 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":60731300,"name":"Biological sciences/Ecology"},{"id":60731301,"name":"Earth and environmental sciences/Ecology"},{"id":60731302,"name":"Earth and environmental sciences/Environmental sciences"},{"id":60731303,"name":"Biological sciences/Genetics"},{"id":60731304,"name":"Biological sciences/Molecular biology"},{"id":60731305,"name":"Biological sciences/Zoology"}],"tags":[],"updatedAt":"2026-05-14T06:24:32+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-08 13:53:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8493684","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8493684","identity":"rs-8493684","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}