Expression of pyrethroid metabolizing P450 enzymes characterizes highly resistant Anopheles vector species targeted by successful deployment of PBO-treated bednets in Tanzania

Johnson Matowo; David Weetman; Patricia Pignatelli; Alexandra Wright; Jacques D Charlwood; Robert Kaaya; Boniface Shirima; Oliva Moshi; Eliud Lukole; Jacklin Mosha; Alphaxard Manjurano; Franklin Mosha; Mark Rowland; Natacha Protopopoff

doi:10.1371/journal.pone.0249440

. 2022 Jan 24;17(1):e0249440. doi: 10.1371/journal.pone.0249440

Expression of pyrethroid metabolizing P450 enzymes characterizes highly resistant Anopheles vector species targeted by successful deployment of PBO-treated bednets in Tanzania

Johnson Matowo ^1,^*,^#, David Weetman ^2,^#, Patricia Pignatelli ², Alexandra Wright ³, Jacques D Charlwood ³, Robert Kaaya ¹, Boniface Shirima ¹, Oliva Moshi ¹, Eliud Lukole ⁴, Jacklin Mosha ⁴, Alphaxard Manjurano ⁴, Franklin Mosha ¹, Mark Rowland ³, Natacha Protopopoff ³

Editor: Nicholas C Manoukis⁵

PMCID: PMC8786186 PMID: 35073324

Abstract

Long lasting insecticidal nets (LLINs) are a proven tool to reduce malaria transmission, but in Africa efficacy is being reduced by pyrethroid resistance in the major vectors. A previous study that was conducted in Muleba district, Tanzania indicated possible involvement of cytochrome P450 monooxygenases in a pyrethroid resistance in An. gambiae population where pre-exposure to piperonyl butoxide (PBO) followed by permethrin exposure in CDC bottle bioassays led to partial restoration of susceptibility. PBO is a synergist that can block pyrethroid-metabolizing enzymes in a mosquito. Insecticide resistance profiles and underlying mechanisms were investigated in Anopheles gambiae and An. funestus from Muleba during a cluster randomized trial. Diagnostic dose bioassays using permethrin, together with intensity assays, suggest pyrethroid resistance that is both strong and very common, but not extreme. Transcriptomic analysis found multiple P450 genes over expressed including CYP6M2, CYP6Z3, CYP6P3, CYP6P4, CYP6AA1 and CYP9K1 in An. gambiae and CYP6N1, CYP6M7, CYP6M1 and CYP6Z1 in An. funestus. Indeed, very similar suites of P450 enzymes commonly associated with resistant populations elsewhere in Africa were detected as over expressed suggesting a convergence of mechanisms across Sub-Saharan African malaria vectors. The findings give insight into factors that may correlate with pyrethroid PBO LLIN success, broadly supporting model predictions, but revision to guidelines previously issued by the World Health Organization is warranted.

Introduction

The massive scale-up of insecticide treated bednets (ITNs) and in particular long-lasting insecticide-treated nets (LLINs) across sub-Saharan Africa has been the predominant factor in reducing malaria morbidity and deaths since the turn of the century [1]. Unfortunately, the number of malaria cases rose in several African countries in 2016 and 2017, and more widespread resurgence is possible [2]. Funding constraints in the most endemic countries is one factor holding back recent progress [3]. Although less easy to quantify, another key factor in this resurgence is resistance among the vectors to pyrethroids (used for all LLIN treatments [4]), which is now widespread. Although less common than pyrethroid resistance, resistance to other insecticide classes used in vector control is emerging in many regions of sub-Saharan Africa [5–8]. To combat resistance to insecticides, and to pyrethroids in particular, the WHO has developed The Global Plan for Insecticide Resistance Management (GPIRM) [9]. Despite the prevalence of strong pyrethroid-resistance, many malaria-endemic countries have yet to align their vector control strategies to those of the GPIRM, in part because of a continued dependence on pyrethroid-treated LLINs [5]. The advent of next generation LLINs—not solely treated with pyrethroids—has been urgently awaited. The first of these bi-treated nets combines a pyrethroid with a non-insecticidal synergist piperonyl butoxide (PBO-LLIN). The aim is to improve pyrethroid efficacy, primarily by inhibiting enzymes involved in insecticide detoxification processes [10].

The main mechanisms of pyrethroid resistance in An. gambiae involve mutations to the voltage-gated sodium channel (Vgsc) target-site and metabolic resistance [11].

In An. gambiae, over expression of a handful of P450 genes from the CYP6 and CYP9 subfamilies have been repeatedly associated with pyrethroid resistance in field populations of An. gambiae in West and West-Central Africa [11]. When multiple mutations combine, they may lead to high-levels of resistance and are likely to seriously threaten the efficacy of malaria control programs [12]. Fewer transcriptomic studies have been performed in East Africa and it is unclear whether a similar concentration of metabolic resistance on a few P450 genes occurs. Although resistance-conferring Vgsc mutations are absent in An. funestus, metabolic resistance alone seems capable of producing high levels of resistance, which has been associated with control failure [13]. As with An. gambiae, a limited suite of CYP6 and CYP9 pyrethroid-metabolizing cytochrome P450s are involved in pyrethroid resistance in An. funestus, although the relative importance of specific genes varies geographically [14]. Widespread dependence of high-level resistance on pyrethroid metabolizing P450 enzymes in the major malaria vectors is promising for the efficacy of PBO-LLINs.

A recent four-armed cluster randomized trial (RCT) conducted in Muleba district, in Tanzania [15] which compared the effect of a standard pyrethroid LLIN with PBO-LLINs, each with or without Indoor residual spraying (IRS). Study arms with IRS (using the organophosphate pirimiphos-methyl Actellic) or PBO-LLIN had a strong reduction in malaria transmission compared to the LLINs alone arm. Thus, the implementation of either PBO or the different insecticide class for IRS overcame pyrethroid resistance [15]. In Uganda, a recently published second trial supports the recommendations given to PBO-LLIN [16].

Following results from the Muleba trial the WHO issued a policy statement that the deployment of PBO-LLIN should be considered in areas where the main malaria vector(s) have pyrethroid resistance. This is when resistance is (a) confirmed (b) of intermediate level (10–80% mortality) in diagnostic dose bioassays, and (c) at least partially conferred by a (P450) monooxygenase-based resistance mechanism [17]. With higher costs and also limitations to supplies, the question of when and where to deploy PBO- LLINs at an operational scale for malaria control is a crucial consideration for international agencies and national malaria control programmes. Prior to the trial, An. gambiae was the predominant malaria vector in Muleba district with a high frequency of resistance to pyrethroids in diagnostic dose bioassays, attributed at least in part to near-fixation of the Vgsc1014S mutation [18]. Pyrethroid susceptibility in bioassays increased significantly if female mosquitoes were exposed to PBO indicating likely involvement of metabolic resistance mechanisms as well as the Vgsc mutation also referred to as kdr mutation. [19]. However, in Muleba, and in Tanzania generally, studies of specific genes involved in resistance have been limited to Vgsc mutations in An. gambiae [20] and have not been undertaken with An. funestus.

The present study, was aimed at characterizing molecular and metabolic resistance mechanisms present in intensely pyrethroid resistant populations of An. gambiae and An. funestus, and sought to describe the phenotypic and genetic insecticide resistance profiles of malaria vectors in Muleba. We hypothesize that the frequency of pyrethroid resistance in Muleba populations of An. gambiae s.s and An. funestus is high, accompanied by over expression of key candidate P450s genes.

Materials and methods

Consent and ethical clearance

Written consent was obtained from household heads before collecting mosquitoes inside the houses. This study was part of a cluster randomized trial that was conducted according to the Declaration of Helsinki and the International Guidelines for Ethical Review of Epidemiological Studies. Ethical clearance was obtained from the Medical Research Coordinating Committee (MRCC) of the National Institute for Medical Research (NIMR), London School of Hygiene and Tropical Medicine (LSHTM) and Kilimanjaro Christian Medical University College (KCMUCo).

Study area and mosquito collections

The study was conducted in Muleba district, on the western shore of Lake Victoria in Tanzania. The area is characterized by high malaria prevalence and the presence of the two major malaria vectors An. gambiae s.s. and An. funestus [15].

It was the site for a RCT that involved 40 villages each of which received one of the four possible treatments in February 2015; standard LLIN, PBO-LLIN, IRS and LLIN, IRS and PBO-LLIN. Olyset net, the standard LLIN (Sumitomo Chemicals, Japan) was treated with 2% permethrin while the PBO-LLIN, Olyset Plus (Sumitomo Chemicals, Japan) contained 2% permethrin and 1% PBO. For IRS, Actellic 300CS (Syngenta, Switzerland) a microencapsulated pirimiphos-methyl was applied at a dosage of 1 g/m² on the inside walls and ceiling of each house. Detailed information about the study site and interventions is published elsewhere [15].

One or two villages with high Anopheles density were selected, in each of the four RCT study arms (Fig 1). Kakoma received standard LLIN, Kishuro PBO-LLIN, Bweyenza received IRS and LLIN and the remaining two villages Kiteme & Kyamyorwa each received IRS and PBO-LLIN. Anopheles were sampled between November 2014 and January 2015 in all the villages at baseline, before intervention deployment in February 2015. Due to the reduction in mosquitoes observed in villages receiving PBO-LLIN and/or IRS, collections were discontinued and only Kakoma remained as a sentinel site for resistance throughout the trial. It was sampled in May and June 2016. Another village allocated to the LLIN arm, Kabirizi was selected in 2017 due to the high number of An. funestus found there.

Mosquito collection and identification

Wild mosquitoes

Indoor resting Anopheles mosquitoes were collected from different houses in the villages between 0600 and 0830 using mouth and/or prokopack aspirators. Blood fed female An. gambiae and An. funestus were kept for three days for blood digestion and used for all WHO diagnostic dose susceptibility and CDC synergist and intensity bottle assays. F1 progeny used for target site mutations and metabolic gene expression characterization were reared, in the PAMVERC accredited laboratory in Moshi, from adult An. gambiae s.s. collected from Kakoma and An. funestus from Kabirizi in 2017. Morphological identification of the field caught females Anopheles was done according to the key of Gillies and Coetzee [21].

The SINE-PCR method of Santolamazza et al. [22] was used to discriminate members of An. gambiae species complex tested during microarray, while TaqMan assays [23] were performed on a sub-sample exposed to CDC bottle and WHO bioassays. Member species of the An. funestus group were identified using a cocktail PCR described by Koekemoer et al. [24].

Laboratory susceptible strains

Three susceptible laboratory strains, namely An. gambiae s.s (Kisumu), An. coluzzii (Ngousso) and An. funestus (FANG) reared at the Liverpool School of Tropical Medicine were used for microarray and qPCR and used as reference strains for gene expression assays. The FANG strain that originated from Southern Angola, colonized at Liverpool since 2002 was used as a reference strain for An. funestus gene expression. For An. gambiae s.s gene expression, we used both Kisumu and Ngousso as reference strains to make analysis more stringent since the Kisumu strain has been colonized in laboratory for so long that it may not resemble a wild population very well.

Resistance assay with diagnostic concentration

To assess resistance status of malaria vectors in the study area (S1 Fig), wild caught female An. gambiae s.l. and An. funestus were exposed for one hour in WHO cylinders to papers procured from the WHO recommended supplier Universiti Sains Malaysia treated with diagnostic concentrations of either permethrin (0.75%) (pyrethroid), lambda-cyhalothrin (0.05%) (pyrethroid), bendiocarb (0.1%) (carbamate) or pirimiphos-methyl (0.25%) (organophosphate) [25]. These insecticides are currently used for LLIN and IRS treatment.

Mosquitoes were then transferred to a holding tube, provided with 10% sugar solution and their mortality was recorded 24 hours later. Approximately 100 mosquitoes (25 per replicate) were used per test.

Tests with control mortality exceeding 5% were excluded. This assessment was carried out to ascertain the frequency of insecticide resistance for each insecticide in Muleba populations of An. gambiae s.s and An. funestus.

Synergist bioassays

Synergist assays with piperonyl butoxide (PBO) were undertaken in 2017 to identify the potential role of elevated mixed-function oxidases in resistance in An. gambiae s.l. (Kakoma) and An. funestus (Kabirizi). According to treatment mosquitoes were pre-exposed for one hour, either to 50 μg/ml PBO treated or acetone coated bottles, and transferred for 30 minutes into bottles treated with 21.5μg/ml permethrin or acetone. Mortality was recorded 24 hours post-exposure [26].

Resistance intensity dose response assay

To establish the intensity of resistance, a dose response bioassay using modified Centers for Disease Control and prevention (CDC) bottle bioassays, [25, 26] were performed on female An. gambiae and An. funestus collected from Kakoma and Kabirizi villages in April-May 2016. Wheaton bottles were coated with concentrations of permethrin that gave between 5% and 95% mortality (5 μg/ml to 860 μg/ml for An. gambiae s.l., 21.5 μg/ml to 215 μg/ml for An. funestus and 1.6 μg/ml to 21.5 μg/ml for susceptible An. gambiae Kisumu strain). Approximately 12 mosquitoes were aspirated into each bottle and knock-down recorded at the start and after 15- and 30-minutes exposure.

Mosquitoes were transferred to paper cups, provided with 10% sugar solution, and mortality recorded after 24 hours. Five to eight replicates were performed for each concentration alongside with a control bottle (coated with acetone).

Genotyping of kdr and GSTe2 mutations

We genotyped kdr and GSTe2 mutations in F1 progeny from field-collected An. gambiae s.s. and An. funestus, respectively; each of these mutations have proven causative links with pyrethroid resistance [27, 28]. To genotype the nucleotide variants leading to kdr mutations in the An. gambiae VGSC (L1014F or S), hydrolysis probe assays were undertaken as described by Bass et al. (2007) [28]. These used TaqMan primers and minor groove binding (MGB) probes (Applied Biosystems, UK) and SensiMix DNA kit (Quantace).

The qPCR was run on an MxPRO3005 thermal cycler and analysed from endpoint scatter plots using MxPRO software (Aligent technologies, Stratagene, USA). The qPCR cycling conditions for both L1014F and L1014S were 95°C for 10 minutes, followed by 45 cycles of 95°C for 15s and 63°C for 45s.

A further TaqMan assay was used to assess the presence and role of the L119F-GSTe2 mutation, previously associated with DDT and pyrethroid resistance in An. funestus [29]. Reactions were run and analyzed as above with the following conditions. The final volume contained 1× SensiMix (Bioline, London, UK), 800 nM of each primer and 200nM of each probe and the PCR cycling conditions included an initial denaturation at 95°C for 10 minutes, followed by 40 cycles of 95°C for 10s and 60°C for 45s.

Transcriptome analyses

Transcriptome analyses were carried out to identify genes that were putatively involved in observed insecticide resistance in Muleba populations of An. gambiae s.s. and An. funestus. Both An. gambiae s.s. and An. funestus were collected in May-June 2017 from Kakoma and Kabirizi villages respectively.

F1 female and male An. gambiae s.s. and An. funestus were separated on the day of emergence and the males were discarded. Females were fed on 10% glucose solution until they were three days old. The mosquitoes were then killed instantly in ethanol and preserved in RNAlater, stored overnight at 4⁰C then transferred to -20⁰C for longer-term storage.

Fully-interwoven loop designs were used to compare transcriptome expression profiles of wild pyrethroid-resistant An. funestus from Kabirizi village to the insecticide susceptible An. funestus laboratory strain FANG. Wild, pyrethroid-resistant, An. gambiae from Kakoma village were compared to the insecticide susceptible laboratory strains Kisumu and Ngousso (S2 Fig). Each comparison in the two experiments consisted of four independent biological replicates of RNA from pools of ten females in a balanced design to mitigate any dye bias.

RNA was extracted from the four batches of ten female mosquitoes using the RNAqueous kit (Thermo Fisher) according to the manufacturer’s instructions and treated with DNase I (Qiagen). Quality and quantity of the RNA were checked using a Nanodrop spectrophotometer (Nanodrop Technologies, Wilmington, DE, USA) and a Bioanalyser 2100 (Agilent Technologies, USA). Each extracted pool of RNA was labeled separately with cy3 and cy5 dyes using the Low Input Quick Amp Labelling Kit (Agilent Technologies, USA) according to the manufacturer’s instructions.

Labeled samples were hybridized to a 60k-probe microarray for An. funestus (Agilent; A-MEXP-2374) [29], or, for An. gambiae, a 15k-probe microarray (Agilent; A-MEXP-2196 [14], using the Agilent gene expression hybridization kit (Agilent Technologies, USA). Slides were washed according to the manufacturer’s instructions and scanned on an Agilent G2565CA microarray scanner. Data was extracted using Feature Extraction 12.0 software (Agilent Technologies, USA).

Candidate gene expression analysis

Quantitative PCR analysis was performed on genes identified as candidates from the microarray experiments. Primers were designed using the NCBI primer BLAST [30]. Complementary DNA (cDNA) was synthesized from the same RNA samples used in the microarray experiments using oligo(dT)20 and SuperScript III (Invitrogen) according to the manufacturers’ instructions and purified through a DNA-binding column (Qiagen). The quality and quantity of cDNA was measured using a Nanodrop spectrophotometer (Nanodrop Technologies, Wilmington, DE, USA). To check the dissociation curve and estimate efficiencies, primer pairs were tested using one pool from the wild samples and one from a laboratory strain, for each species respectively, in a dilution series starting from approximately 20ng/μg of cDNA.

Primer pairs exhibiting a linear relationship between threshold cycle (Ct) values and template concentration in standard curves, and high PCR amplification efficiency were chosen for further analysis. The qPCR reactions were performed using the Agilent MXPro Real-Time PCR detection system (Agilent Technologies, Stratagene, USA). A total volume of 20μl contained10μl Brilliant III SYBR Green, 0.6ul of each primer (at 10nM) 300 nM of primers, 1μl of cDNA (at 2ng/ul) and 7.8 μl sterile-distilled water. The thermal profile was as follows: 1 cycle 95°C for 3 min, 40 cycles of 95⁰C for 10s then 60⁰C for 10s. Four biological replicates were run for each sample, with three technical replicates. Two endogenous normalizing genes, ribosomal S7 and elongation factor tau, were amplified for each sample to control for variation in cDNA quantity (primer pairs used for each species are shown in S1 and S2 Tables).

Data analysis

Diagnostic dose bioassay results were interpreted according to WHO criteria: A 24 hours mortality superior to 98% indicates susceptibility, mortality of 90 to 97% suspected resistance, and mortality of less than 90% confirmed resistance [25]. To assess resistance intensity, Diagnostic concentrations which killed 50% (LC₅₀) of wild An. gambiae and An. funestus were estimated by Probit analysis using Polo plus (version 1.0, Le Ora Software LLC). The LC₅₀ values were used to calculate resistance ratios between each wild population and the An. gambiae Kisumu susceptible reference strain for assessing resistance intensity. The An. gambiae Kisumu susceptible reference strain was used as a comparator for both species, owing to unavailability of a susceptible An. funestus strain in the testing laboratory in Muleba. A resistance ratio of 2 indicates potential resistance or suggestive of probable resistance while resistance ratio greater than 2 indicates resistance.

Loess normalization of microarray data was performed by LIMMA 2.4.1 [31], with analysis of expression using the MAANOVA package [32], with data processing using custom R scripts [14]. Two of the An. funestus arrays were excluded owing to damage to a slide, but the fully interwoven loop design used still provided robust results under such circumstances [33].

Statistical significance of probes was determined using strict criteria based on a multiple testing corrected probability (q-value) threshold (q<0.0001), effect size (fold change, FC >2 or FC <-2) and, for An. gambiae, cross-experiment replication criteria vs. both susceptible colonies. Gene expression for each target gene, was normalized using that of the endogenous genes and was then analysed relative to the susceptible strains of An. gambiae or An. coluzzii (Kisumu and Ngousso) or An. funestus (FANG) using the 2^-ΔΔCt method, correcting for PCR efficiency variation [34]. Differences in expression were tested in Microsoft Excel by comparing the delta Ct values between strains using either a Student’s t-test or, if an F-test indicated significant heterogeneity of variances between groups, a Welch’s t-test (t-test not assuming equal variances). For both F-tests and t-tests, a threshold of p < 0.05 was to used to assign a significant difference between treatments.

Results

Resistance assay with diagnostic concentration

In 2014, the number of mosquitoes exposed per insecticide and location varied between 89 and 171. The mortality rate of An. gambiae exposed to permethrin and lambda-cyhalothrin in WHO cylinder tests was low, with only one of the ten bioassays recording mortality above 10% (Fig 2). Mortality to bendiocarb, the active ingredient used previously for IRS, was much more variable ranging from around 90% in three villages to <35% in Kikagate village. All An. gambiae were fully susceptible to pirimiphos methyl, the active ingredient used for IRS in the trial. The number of An. funestus collected were too few to test at this time.

Mortality in An. gambiae s.l. collected from Kakoma in 2016, was 4% (95% CI: 0.8–7.9) similar to the baseline measurement for permethrin in 2014. Mortality in bendiocarb assays decreased from 94 to 45% (χ²₂ = 54.3, p<0.001) between 2014 and 2016, despite no operational exposure and despite the data coming from a mixture of two members of the An. gambiae complex. Pyrethroid and carbamate resistance was also observed in An. funestus from Kabirizi with 31% (95%CI: 24.9–37.1) mortality after exposure to permethrin and 80% (95%CI: 76.7–83.3) with bendiocarb.

In 2014, An. gambiae complex in Kakoma was composed of 93.5% (29/31) of An.gambiae s.s. (hereinafter called An. gambiae) in but in 2017 55.4% (46/79) with the remainder being An. arabiensis.

Synergist bioassays

Due to strong resistance observed against permethrin, PBO synergist bioassay test using the CDC bottle assay were conducted in the same villages in 2017. After exposure to permethrin, An. gambiae s.l. mortality was 1.4% (95%CI: 0.1–3.6%) and increased to 18.1% (95%CI: 9.5–26.7%) when pre-exposed to PBO and 6.5% (95%CI: 0–15.9%) which increased to 53.2% (95%CI: 26.0–80.4) in An. funestus. Mortality in the PBO-only bottle (of 50 μg) was 2.8% and 17.3% for An. gambiae s.l. and An. funestus respectively and mortality in the control less than 2%.

Resistance intensity dose response assay

In the 2016 collections done in Kakoma, a dose that was 40 times (860 μg/ml) the diagnostic dose of permethrin was required to produce a 24-hour mortality of 96.7% (88/91) in CDC bottle bioassays in An. gambiae s.l., and a dose that was 10 times the diagnostic concentration (215 μg/ml) was required to produce a mortality of 97.8% (87/89) in An. funestus (Fig 3). The Anopheles diagnostic dose in the CDC bottle bioassay for permethrin is 21.5 μg/ml.

Anopheles gambiae, An. arabiensis and An. funestus showed resistance ratios to permethrin of 63.2, 20.7 and 38.9, respectively compared to the susceptible An. gambiae colony (Kisumu). Although confidence intervals overlapped, this suggests a difference in mechanism or frequency of resistance between species, (Table 1).

Table 1. Lethal concentrations (LC₅₀ in μg/ml/bottle) and resistance ratios (RR₅₀) of permethrin against An. gambiae s.l. and An. funestus field population in intensity CDC bottle bioassays.

Species	Total exposed	LC₅₀^* (95%CI^**)	RR₅₀^_*** (95%CI)
Kisumu	233	1.8 (1.1–2.4)	ref
An. funestus	433	68.6 (59.2–79.4)	38.9 (30.1–50.1)
An. gambiae	195	111.5 (75.1–170.2)	63.2 (42.0–94.9)
An. arabiensis	51	36.6 (13.2–83.3)	20.7 (11.2–38.3)

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*LC₅₀ = lethal concentration required to kill 50% of the population

**CI = Confidence interval

***RR_{50 =} resistance ratio or measure of resistance in an insect population, calculated by dividing the LC₅₀ of the resistant population by the LC₅₀ of the susceptible population.

Molecular mechanisms

For An. gambiae, the 1014S kdr mutation was fixed (N = 227), whilst the 1014F mutation was rare, with only one homozygote detected with fewer than 10% F/S heterozygotes. No kdr mutations were detected in An. arabiensis (N = 245) [16]. The mutation L119F-GSTe2 potentially linked to resistance was not detected in An. funestus (N = 92).

Only An. funestus and An. gambiae were considered in the microarray experiment because An. arabiensis is a minor contributor to malaria transmission in the study area [35, 36]. Transcriptomic analysis of An. funestus from the village of Kabirizi, revealed 789 probes (out of approximately 60,000) as significant using stringent criteria, of which 375 were over-expressed relative to the FANG susceptible strain (Fig 4A; S3 Table). Of these, 48 could be identified as having a possible role in detoxification processes, with 47 of the probes coming from just five P450 genes (each represented by multiple probes).

Fig 4 — (a) Volcano plot of all probes significant in experimental comparison (b) Relative expression levels of four candidate genes in qPCR. Red circles show over expressed gene probes targeting P450 genes.

Two P450s, CYP6N1 and CYP6M7, were among the most statistically significant and highly expressed of all genes; expressed at levels 17 and 21-fold higher, respectively, than the FANG strain. The other significant genes represented by multiple significant probes were CYP6Z1 and CYP6M1 (each 4 to 5 times higher than FANG; S4 Table). Each of the genes was confirmed as being significantly over expressed by qPCR (S5 Table), and whilst fold-change values were lower than those in the microarray, CYP6N1 and CYP6M7 remained as the more highly expressed (Fig 4B).

In transcriptome analysis of An. gambiae from Kakoma village, 562 probes were consistently significantly differentially expressed in relation to both of the susceptible strains included (Fig 5A; S6 Table). Of these, 87 (65 of which were over expressed) were identifiable as possible detoxification-related genes, including members of the three major metabolic gene subfamilies P450s, GSTs and COEs, as well as transporter genes and alcohol dehydrogenases.

Fig 5 — (a) Volcano plot of all probes significant in all experimental comparisons (average of the two experiments). (b) Relative expression levels of candidate genes in qPCR. Note that CYP6M2 and CYP6Z2 are significant vs Kisumu despite lower fold changes than vs Ngousso.

From these significant detoxification genes, P450s were the most common class, with CYP6M2, CYP6Z3, CYP6P3, CYP6P4, CYP6AA1 and CYP9K1 being the most notable (expression range between 4 and 11 higher than the susceptible strains). These P450 genes, along with VATPase—the most over expressed gene (≈88-fold) and also two highly under-expressed detoxification genes GSTE2 and CYP9J5 were chosen for qPCR analysis, along with an additional P450, CYP6M1, that was not significantly over expressed and which was included as a negative control (S7 Table). Excluding the VATPase gene, which showed more than 20-fold lower expression in qPCR than the microarray results, there was a broad agreement between datasets (Pearson’s r = 0.58, N = 18). Most genes were expressed at similar or greater levels in qPCR than in the microarray (Fig 5A).

Moreover, all genes, barring the negative control CYP6M1, were significantly over-expressed in comparison with either of the colonies (S8 Table). The physically-neighboring genes CYP6P3 and CYP6P4 were most strongly and consistently over expressed, followed by CYP6M2 and CYP9K1 (Fig 5B). Each of these An. gambiae P450 genes are known to metabolize pyrethroids.

Discussion

At both baseline and after two years of interventions, An. gambiae showed an extremely high frequency of resistance to both permethrin and lambda-cyhalothrin, with only one instance of permethrin mortality being greater than 10%. In 2017, An. funestus were also tested and showed moderate resistance level (31% mortality). Based on resistance ratios, both An. gambiae s.s, An. arabiensis and An. funestus were highly resistant to insecticides tested.

WHO recommends PBO LLIN deployment in areas of intermediate resistance (10–80% mortality). The strength of resistance is not considered by the WHO recommendation because data were unavailable to populate the malaria model predictions on which the recommendation was based [37]. However, strength of resistance is potentially a more crucial metric because vectors that might just survive a diagnostic dose (but not a dose of greater concentration) are formally classed as resistant. Slight increases in dosage might kill them and they may represent little threat to the operational effectiveness of ITNs [38, 39]. Although resistance intensities may be estimated in different ways, in Muleba An. gambiae and An. funestus showed estimated resistance ratios (LC₅₀ dose points) of 63 and 39 respectively, similar to those reported for a resistant population from Uganda [38]. Although we did not use the practical method of 5× and 10× diagnostic concentrations for assessing resistance intensity, we were able to observe mortality rates at different doses of permethrin. An. funestus showed suspected resistance when the concentration was 10 times the diagnostic dose and would be interpreted as indicative of high resistance intensity [25]. For An. gambiae 20% survived the concentration that was slightly greater than 10x and 3% survived the concentration which was 40x the diagnostic dose.

With such a profile mosquitoes would be able to successfully feed through standard pyrethroid LLINs [40] which may explain the small impact of these nets in the Tanzania trial [15]. The addition of PBO in synergist assay resulted in a partial restoration of susceptibility to permethrin in both An. gambiae and An. funestus which indicates the involvement of P450. This was confirmed by the identification of multiple P450 genes over expressed in An. gambiae. CYP6M2, CYP6P3, CYP6P4, CYP9K1 are particularly notable because they have been frequently associated with resistance in transcriptomic studies [41, 42] and demonstrated to metabolize pyrethroids [43, 44]. Evidence that these genes appear key to resistance in An. gambiae has come from West and West Central Africa [11]. The P450s identified in these studies were also the key ones in Muleba, suggesting either convergent evolution or spread of mechanisms between both sides of the continent.

The most significantly over expressed genes in An. funestus were dominated by CYP6 subfamily P450s, most notably CYP6N1, CYP6M7, CYP6M1 and CYP6Z1, all of which have been previously associated with pyrethroid resistance [45, 46]. The two best-known pyrethroid-associated P450s in An. funestus, CYP6P9a and CYP6P9b [47] were, however, not over expressed in Muleba, which thus appears to be a population in which CYP6M7 acts in their stead and which metabolizes pyrethroids with equally high efficiency [14]. The gene expression data for the two important Muleba malaria vectors thus provides strong evidence to validate the third WHO criterion, for deployment.

Interestingly, carbamate resistance increased significantly in An. gambiae between 2014 and 2017, despite cessation of carbamate use for control prior to the baseline collections.

The presence of acetylcholinesterase (Ace1) target site mutation has been involved in resistance to organophosphates and/or carbamates in Anopheles populations [48]. Bendiocarb resistance was already observed in the study site in 2011 while Ace1 mutations was not detected at this time in local An. gambiae [18]. In the present study, Ace 1 was not investigated and could have contributed to the change in bendiocarb resistance. Pyrethroid-driven over expression of P450s may cause or perhaps combine with Ace 1 mutations to produce bendiocarb resistance, with the primary cross-resistance candidate genes CYP6M2 and CYP6P3 in An. gambiae’s sister species An. coluzzii [48], and CYP6Z1 in An. funestus [45] all significantly over expressed in Muleba populations.

In Muleba the mechanistic profile of both An. gambiae and, especially, An. funestus, which lacks pyrethroid target site mutations, appears dominated by over expression of key candidate P450s. A crucial point is that genes providing evidence for a P450-based resistance mechanism are not just those shown to be over expressed in the current or even previous studies but have been subject to functional validation to demonstrate their role in pyrethroid detoxification and/or resistance, which is the case for genes in both focal species of this study. Also, in this study, the frequency of pyrethroid resistance in Muleba was much greater than 90% in An. gambiae and in the cluster randomised trial PBO-LLINs were significantly more effective than standard LLINs [15]. PBO-LLINs could, therefore, still be recommended where resistance is greater than 80% and metabolic resistance is prevalent.

Conclusions

A posteriori resistance profiling shows that malaria vector populations in the study area had high resistance intensities yet malaria prevalence in the PBO-LLIN was reduced by 44% compared to standard LLIN [15]. Revision of the condition specified by the WHO for the deployment of PBO-LLIN should be considered as evidence on the efficacy of these nets accumulates.

Supporting information

S1 Fig. Testing timeline.

(TIF)

Click here for additional data file.^{(466.2KB, tif)}

S2 Fig. Interwoven microarray experimental loop design.

(TIF)

Click here for additional data file.^{(204.7KB, tif)}

S1 Table. Primers used in An. funestus quantitative real-time PCR.

(DOC)

Click here for additional data file.^{(35.5KB, doc)}

S2 Table. Primers used in An. gambiae quantitative real-time PCR.

(DOC)

Click here for additional data file.^{(46KB, doc)}

S3 Table. Full results from An. funestus microarray analyses.

(XLSX)

Click here for additional data file.^{(3.8MB, xlsx)}

S4 Table. Characteristics of genes from microarrays analysis that were carried forward for An. funestus qPCR.

(DOC)

Click here for additional data file.^{(29.5KB, doc)}

S5 Table. Quantitative PCR results for An. funestus.

(XLSX)

Click here for additional data file.^{(16.5KB, xlsx)}

S6 Table. Full results from An. gambiae microarray analyses.

(XLSX)

Click here for additional data file.^{(1.6MB, xlsx)}

S7 Table. Characteristics of genes from microarrays analysis that were carried forward for An. gambiae qPCR.

(DOC)

Click here for additional data file.^{(46.5KB, doc)}

S8 Table. Quantitative PCR results for An. gambiae.

(XLSX)

Click here for additional data file.^{(20.4KB, xlsx)}

Acknowledgments

We are greatly indebted to the PAMVERC field workers in Muleba for their active participation in mosquito collections, testing and processing. We express our sincere thanks to PAMVERC insectary and molecular laboratory staff in Moshi for rearing mosquitoes, processing and preserving mosquitoes in RNALater. The assistance from the community leaders and households from which mosquitoes were collected is highly appreciated. Last but not least, a lot of thanks are to Mr. Rabieth Shani and Mrs. Fridah Temba, the PAMVERC administrators in Muleba and Moshi respectively for settling logistics issues throughout the study.

Data Availability

The microarray data generated are deposited in Array Express with accession numbers E-MTAB-10579 and E-MTAB-10580. Microarray analysis results and quantitative PCR data and results are provided within the supplementary materials.

Funding Statement

The study was supported by the Welcome Trust through Malaria Capacity Development Consortium (MCDC), a Post Doctoral award to JM (grant No. ITDCBC9410) with additional support from the Joint Global Health Trials Scheme of the UK, Department for International Development, Medical Research Council, and Welcome Trust (MR/L004437/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS One. doi: 10.1371/journal.pone.0249440.r001

Decision Letter 0

John Vontas

26 Apr 2021

PONE-D-21-08461

Insecticide resistance characteristic of Anopheles vector species successfully controlled by deployment of pyrethroid and PBO long lasting insecticidal treated nets (LLINs) in Tanzania

PLOS ONE

Dear Dr. Johnson Matowo,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please clarify text, to clearly indicate mosquito species in each session

Please discuss the possible relevance of a number of additional insecticide resistance molecular markers not accessed in the study

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Reviewer #1: The research article by Matowo et al is a comprehensive study regarding the insecticide status and related mechanisms operating in a targeted area in Tanzania, where a permethrin/PBO co treated LLINs trial occured. It provides important and operationally relevant information regarding insecticide resistance status which are applicable to relevant trials and field settings. The manuscript is well written and well organized and I only have the following suggestions to make:

1. The relevance OPs/ carbamates bioassays performed in this study (otherwise focusing on pyrethroid resistance) could be more elaborate to introduce the reader to the concept of cross resistance. Since no molecular diagnostics for OPs/carabamates have been performed, target site mechanisms should be discussed as a possible mechanism. The authors mention that no ace mutations had been detected in the area based on data from 2013, but this could have changed in 5-10 years’ time.

2. PBO experiments show clear metabolic resistance, but this could be, as in many other cases, a synergistic phenomenon operating in parallel with other resistance mechanisms (e.g. target site mutations like N1575Y and cuticle resistance).

3. In some instances, it is difficult to distinguish to which mosquito species the authors refer to (An. gambiae ss, An. coluzzii, or hybrid forms).

4. It would be relevant to discuss why the newly defined CYP6P9a/9b SNPs associated with resistance in An. funestus were not assessed (i.e., no CYP6P9a overexpression detected).

5. The continued dependence on pyrethroid-treated LLINs is very relevant and could be discussed in more details (logistics: limited supplies of co-PBO treated nets, high cost, distribution issues, other factors?)

6. A supplementary Table with the list of primers used in this study would be useful.

Reviewer #2: The paper entitled "Insecticide resistance characteristic of Anopheles vector species successfully controlled by deployment of pyrethroid and PBO long lasting insecticidal treated nets in Tanzania" is an interesting piece of work from experts in the field of insecticide resistance and vector control. Cluster randomized trial demonstrated that permethrin LLINs co-treated with the mixed function oxidase inhibitor (PBO) was more efficient than the net treated only with pyrethroid. Bioassay data and molecular analysis undertaken in this study to determine the underlying mechanism of pyrethroid resistance in Anopheles gambiae and An. funestus. Both data were in agreement with LLINs efficacy data. The manuscript well written and the data nicely presented and support the final conclusion. I have no hesitation to recommend this work in its form for publication in PLOS ONE.

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PLoS One. 2022 Jan 24;17(1):e0249440. doi: 10.1371/journal.pone.0249440.r002

Author response to Decision Letter 0

1 Jul 2021

All specific reviewer and editor comments have been addressed accordingly in a letter on Response to reviewers

(attached)

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Submitted filename: Rebuttal letter_PLOS ONE.pdf

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PLoS One. doi: 10.1371/journal.pone.0249440.r003

Decision Letter 1

Nicholas C Manoukis

5 Oct 2021

PONE-D-21-08461R1Insecticide resistance characteristic of Anopheles vector species successfully controlled by deployment of pyrethroid and PBO long lasting insecticidal treated nets in TanzaniaPLOS ONE

Dear Dr. Matowo,

Please submit your revised manuscript by Nov 19 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

Additional Editor Comments (if provided):

Thank you for your resubmission. I was asked to take over as AE, and happy to do so. Please note carefully the comments from reviewer #3- the relation between the results in the paper and ultimate real world effectiveness of LLINs seems quite indirect - here the actual effectiveness is not measured in the field, rather resistance of mosquitoes from field populations is measured and quantified. To illustrate what I mean, note the sentence from the abstract starting on line 19:

"A cluster randomized trial in Muleba district, Tanzania demonstrated that permethrin LLINs co-treated with piperonyl butoxide (PBO), a synergist that can block pyrethroid-metabolizing enzymes in the mosquito, had much greater efficacy than pyrethroid-only nets."

This sentence implies more that what was measured in this study. Rather, the data show that "permethrin LLINs co-treated with piperonyl butoxide (PBO), a synergist that can block pyrethroid-metabolizing enzymes in the mosquito, was more effective in knocking down and killing field-derived populations of An. gambiae and An. funestus in laboratory assays than pyrethroid-only nets".

The current title ("Insecticide resistance characteristic of Anopheles vector species successfully controlled by deployment of pyrethroid and PBO long lasting insecticidal treated nets in Tanzania") is likewise misleading, reflecting some of the same issues- particularly the words "deployment", "control", and "in Tanaznia", all of which suggest overall effectiveness of an intervention in the field. As far as I can tell from the MS, nothing was deployed in the field and no control of malaria vectors in nature was measured. A more accurate title is needed, focusing on what was done: Increased mortality of field-derived populations of Anopheles mosquitoes from Tanzania when exposed to pyrethroid and PBO long lasting insecticidal nets.

I do not understand how the conclusion section follows from the results presented. Malaria prevalence was not measured in this study as far as I can tell.

To be absolutely clear as I can be, the issue comes down to this: The overall effectiveness of a LLIN is measured in the field- many factors besides the ability of resistant mosquitoes to evade death from the insecticide can affect effectiveness (e.g. frequency of resistant genotypes, relative use rates of treated bednets, predator assemblages, sub-lethal effects, etc), and many of these are not assessed in this study.

None of this is to say the study is not worth publishing. What you have submitted is research on the fine-scale mechanisms of insecticide resistance in some malaria vector populations in Tanzania- results that have relevance to treated bed net effectiveness, but are not the whole story. Please adjust the focus of your presentation accordingly to increase the clarify on what was actually done and its relation to the possible situation in the field.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

Reviewer #3: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: (No Response)

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

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6. Review Comments to the Author

Reviewer #1: (No Response)

Reviewer #2: The authors have responded to reviewers comments adequately. Since I have no further comments, I have no hesitation to recommend this work for publication.

Reviewer #3: Matowo et al. examined the incidence, extent, and management of pyrethroid resistance in Anopheles mosquitoes during 2014-2016 in five villages of the Muleba district in North Tanzania. As pyrethrioid resistance to permethrin treated insecticidal nets has reduced the efficacy of this approach, augmentation using piperonyl butoxide, a synergist that blocks pyrethroid metabolizing enzymatic activity, was investigated. Four villages were selected to receive 1 of 4 treatments: 1) long-lasting insecticide (permethrin) treated netting (LLIN), 2) LLIN + piperonyl butoxide (Py-PBO), 3) LLIN + and indoor residual spray (IRS) using an organophosphate product Actellic, 4) LLIN + Py PBO + IRS. They then conducted sampling to determine if the nets differentially affected mosquito populations in each village. Using flies from the collection the authors conducted a series of tests: a) a resistance assay using single diagnostic concentrations of permethrin, lambda-cyhalothrin, bendiocarb, and pirimiphos-methyl; b) a synergist bioassay aimed at determining how pre-exposure to piperonyl butoxide affected permethrin resistance values, c) a resistance intensity dose response assay aimed at establishing resistance curves for two mosquito species from two villages both treated with the permethrin netting LLIN treatment alone, Kakoma and Kabirizi. They also conducted molecular and genetic analyses of wild collected An. gambiae and An. Funestus to determine d) genotyping for kdr and GSTe2 mutations; e) transcriptome analysis of pyrethroid resistant mosquitoes; and f) candidate gene expression analysis.

Generally, the manuscript is well written and easy to read. The introduction fully introduces the concepts needed to understand the goals of the project and the methods are well written as far as what was provided. However, there are a number of problems with the manuscript that make evaluation of the claims difficult. Most importantly, while the focus of the paper is the efficacy of different netting treatments, the data on trapping efficacy is entirely missing. Even after review, it is unclear to me how the authors planned to assess treatment efficacy and there no data provided to show that the netting was effective at management mosquito populations at all. Rather, the authors devote the results to lab assessments of resistance values using flies caught from these villages. However, even with those data, sampling dates are not provided, and statistical comparisons between groups for the data that are presented are absent. Indeed, while there is a suppression of susceptibility to pyrethroids, in comparison to other chemical classes, between sites, the resistance values appear similar and without statistical comparison, there is no way to determine whether differential treatments affected resistance. In fact, the resistance of flies from the single LLIN treatment at Kakoma appeared similar to those that did include the PBO treatment at Kishuro and Kiteme. The authors could either, A) provide those missing data, if they are available and introduce new analyses, or B) the authors may want to change the wording of their claims and make their manuscript more focused on their explicit goals.

Please see my more detailed line comments below:

Ln 68: Generally, readers struggle to keep multiple acronyms straight. I would recommend writing out the insecticide treatments instead. It would really make the manuscript more accessible. However, if you feel that the acronyms are necessary, please consider simplifying them. Can you simplify Py-PBO to just PBO? Having such long acronyms makes deciphering the treatments tiring.

Ln 70: Please make sure to define IRS, Indoor residual spray, for the reader. I would also elaborate on this approach too. Why is it used? How does it compare to netting? Does combining approaches and insecticide classes affect resistance and resistance management?

I would also reiterate here that the pyrethroid used in the netting was permethrin.

Lns 91-94: At this stage it would be helpful describe in detail what you hypotheses were. What did you expect to learn from the deployment of the different treatments to the 5 villages in Muleba? Summarize in a few sentences what you did and why.

Ln 96: Why is this first section of the methods in quotes? Please remove. I would also give this section a heading of its own “Consent and ethical clearance” or something to that effect.

Ln 104-117: There is a lot of information missing from this section. Please include 1) the dates that each treatment were deployed, 2) how long they were deployed, 3) whether and when the treatments were reapplied or serviced, 4) the names of the pesticides used, 5) the manufacturer information of those pesticide products, 6) the netting information (mesh gauge, brand), 7) the concentrations and volume applied both to the netting and the indoor sprays.

Figure 1: Can you include the sampling location data on the map? How many sample sites were in each village? Just one or multiple?

Ln 119: Please reconsider this section organization. I think there this too much here and some of the information belongs in a different section altogether. Please only include sample collection and id info here. Move all the information in the middle paragraph to a new section on lab susceptible strains.

Ln 121: What how many samples were collected? For the data to be robust (fig2) there should be multiple collections from multiple sites in each village. Was this done? If so, please describe.

Ln 127 and going forward: Please refrain from referring to these strains by their village names. It makes keeping them straight nearly impossible for the reader. Instead, please refer to them as the susceptible strain for each species.

Ln 141: For each of these sections going forward I would consider giving a brief 1-2 sentence description of why these assessments were conducted. This helps the reader understand why you did what you did and better interpret the results later on. Including a clear description of your hypotheses in the introduction will help with this too.

Ln 144-145: Because you refer to the class of insecticides throughout the article, it would be helpful at this stage to include those class names here with each of the insecticides you tested. For instance, you could include in parentheses (pyrethroid) after permethrin, or (carbamate) after bendiocarb.

You also need to include the source of the chemicals you used here. Where did you purchase them? Who was the manufacturer? This is important for replication.

What are these concentrations in ug/ml values? This will help these data make sense given the concentration values reported later on in fig. 3.

I agree with one of the other reviewers too, that including information on why these insecticides were selected for analysis is important. Right now that information is absent. Is bendiocarb at risk for cross resistance? Are lambda-cyhalothrin and bendiocarb used in mosquito management and if so how? Water treatments? Fogging? Netting?

Ln 152: Why were PBO and permethrin administer separately rather than concomitantly? This method is not explained.

Ln 166: Please be sure to fully explain what the goals of each genetic analysis were. In other words, why do we care about these mutations?

Also please include the collection dates and location for the insects used in these analyses.

Ln 182: Same as the last comment. Please describe why you conducted this transcriptome analysis, what you attempted to learn, and why that is important.

Also please include collection dates and location.

Ln 246: Is there no trapping data you can include here? How many flies were recovered from each village during each sample? How did you evaluate the efficacy of each treatment?

Ln 251: Please refer to the treatments instead of or alongside the village names.

Ln 253: Please report how many flies were collected at each location, if possible.

Lns 257-265: These is a lot of information here. I could consider making a table instead and show the Lc50 values of each species at each location for each year.

Ln 277: What was the diagnostic dose? Providing this information is important for comparison.

Ln 289: Please consider adding an additional footnote to table 1. Please include how RR is calculated. I would also consider adding information to the methods and materials describing the significance of different RR values. The WHO describes that values less than 5 indicated susceptibility while values greater than 5 indicate resistance in Aedes mosquitoes. Is this the same for Anopheles?

Fig. 2. Please add statistical analysis between groups. Logistic regression and posthoc analysis among sites for each pesticide would help determine if these differences in mortality were in fact different.

I would also add the species label to the y-axis for clarity, and change the village names to treatment labels

Fig. 3. I would again, go back and use logistic regression to compare survival and report he LC50 values here on the figure. For good measure, you could also denote the diagnostic dose here on the figure for each species.

Fig 4. In figure captions, please refer to treatment at the Kabirizi village. Also include what year those samples were collected.

Can you conduct a comparison of the CT values for Kabarizi vs the lab susceptible population (FANG)? A t-test for each gene may suffice. Otherwise, we don’t know if these differences are statistically significant or not.

Fig. 5. What year were these samples collected? Refer to the lab susceptible populations rather than village names (Kisumu or Ngousso). Again, run a stats comparison for the village vs lab susceptible. Also, the DPI resolution of this figures is a little low, making the figure labels difficult to read, but that could just be on my end.

Ln 358: This sentence appears to have a typo. Change to “ The addition of PBO in the synergist assay…” ?

Ln 380: The authors state that the mechanism of resistance appears the same for the pyrethroids and carbamate because bendiocarb resistance was present in An. funestus. However, this may not be the case and the experiments reported here to do not evaluate this hypothesis. Be careful not to overextend on your claims.

Ln 389: Where are these data reported? Where does this 90% values come from?

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

PLoS One. 2022 Jan 24;17(1):e0249440. doi: 10.1371/journal.pone.0249440.r004

Author response to Decision Letter 1

24 Nov 2021

All comments from the editor and reviewer(s) have been well addressed

Attachment

Submitted filename: Response to Reviewers.pdf

Click here for additional data file.^{(270.3KB, pdf)}

PLoS One. doi: 10.1371/journal.pone.0249440.r005

Decision Letter 2

Nicholas C Manoukis

14 Dec 2021

PONE-D-21-08461R2Expression of pyrethroid metabolizing P450 enzymes characterizes highly resistant Anopheles vector species targeted by successful deployment of PBO-treated bednets in TanzaniaPLOS ONE

Dear Dr. Matowo,

Please submit your revised manuscript by Jan 28 2022 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Nicholas C. Manoukis

Academic Editor

PLOS ONE

Journal Requirements:

Additional Editor Comments (if provided):

Nice job addressing reviewer comments. Please address the last remaining issues with special attention to including stats and enough information on other variables already published to make the paper a stand-alone product. I look forward to seeing another revision.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #3: Matowo et al. has addressed most of the comments I made in the previous review round. The new title is good and is more descriptive of their current project. Adding a few sentences here and there in the methods to keep the reader focused on what they did and why is also a big improvement. It reads much better now. Good job with that. Just a few comments remain.

First, in the abstract, I would consider reworking line 32. The current manuscript reads “…had much greater efficacy than pyrethrioid-only nets.” This still sounds like you tested the efficacy of pesticides on reducing mosquito populations rather than defining resistance characteristics. Be more specific with what you are referring to when you say “ efficacy.” Efficacy of what? Please consider changing to something like this, to avoid confusion for the reader: “nets treated with PBO reduced the incidence of or severity of resistance more than pyrethroid only nets” or something to that effect.

Ln 93: removed comma after the word study

Lns 102-107: Please remove those quotation marks

Ln 110-124: While I appreciate that you already included the pesticide trial information in a previously published paper, you still need to include this information again as this is a separate paper. Please include the names of the pesticides and the rates they were applied. For more information related the trial, please explicitly refer the reader to Protopopoff 2018. I would also consider giving a brief 1-2 sentence summary of that project so the reader can follow how these are connected. It’s best not to assume the reader will be familiar with your other work. The current paper should be self-explanatory. The reader shouldn’t have to be familiar with your other projects to understand what you did here and at the very least, should some information be severely redundant to explain, them clearly indicate where the reader should go for that information.

Ln 140: Good job breaking out these sections in the methods. Reads much clearer now.

Ln 150: I really like this supplemental figure!

Ln 244-267: Maybe I am missing it, but in the rebuttal, the authors state that they used t-tests to analyze differences in CT values between groups and they refer to the stats section for that information. I still don’t see that here. Please include.

Ln 332 & ln 358: In both places the authors refer to significant differences. I assume this refers to the t-tests they ran? Where are the values for those stats? Please include.

**********

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Reviewer #3: No

PLoS One. 2022 Jan 24;17(1):e0249440. doi: 10.1371/journal.pone.0249440.r006

Author response to Decision Letter 2

17 Dec 2021

All issues that were raised by Editor and Reviewer #03 have been adequately addressed

Attachment

Submitted filename: Rebuttal letter_Dec. 2021.pdf

Click here for additional data file.^{(189.9KB, pdf)}

PLoS One. doi: 10.1371/journal.pone.0249440.r007

Decision Letter 3

Nicholas C Manoukis

21 Dec 2021

Expression of pyrethroid metabolizing P450 enzymes characterizes highly resistant Anopheles vector species targeted by successful deployment of PBO-treated bednets in Tanzania

PONE-D-21-08461R3

Dear Dr. Matowo,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Nicholas C. Manoukis

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Great job, and congratulations on a nice study!

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #3: Yes

**********

6. Review Comments to the Author

Reviewer #3: Great job on the revisions! This is a fine paper and will be a meaningful contribution to the field. Best of luck in the future and happy holidays.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Reviewer #3: No

PLoS One. doi: 10.1371/journal.pone.0249440.r008

Acceptance letter

Nicholas C Manoukis

13 Jan 2022

PONE-D-21-08461R3

Expression of pyrethroid metabolizing P450 enzymes characterizes highly resistant Anopheles vector species targeted by successful deployment of PBO-treated bednets in Tanzania

Dear Dr. Matowo:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

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on behalf of

Dr. Nicholas C. Manoukis

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. Testing timeline.

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S2 Fig. Interwoven microarray experimental loop design.

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S1 Table. Primers used in An. funestus quantitative real-time PCR.

(DOC)

Click here for additional data file.^{(35.5KB, doc)}

S2 Table. Primers used in An. gambiae quantitative real-time PCR.

(DOC)

Click here for additional data file.^{(46KB, doc)}

S3 Table. Full results from An. funestus microarray analyses.

(XLSX)

Click here for additional data file.^{(3.8MB, xlsx)}

S4 Table. Characteristics of genes from microarrays analysis that were carried forward for An. funestus qPCR.

(DOC)

Click here for additional data file.^{(29.5KB, doc)}

S5 Table. Quantitative PCR results for An. funestus.

(XLSX)

Click here for additional data file.^{(16.5KB, xlsx)}

S6 Table. Full results from An. gambiae microarray analyses.

(XLSX)

Click here for additional data file.^{(1.6MB, xlsx)}

S7 Table. Characteristics of genes from microarrays analysis that were carried forward for An. gambiae qPCR.

(DOC)

Click here for additional data file.^{(46.5KB, doc)}

S8 Table. Quantitative PCR results for An. gambiae.

(XLSX)

Click here for additional data file.^{(20.4KB, xlsx)}

Attachment

Submitted filename: Rebuttal letter_PLOS ONE.pdf

Click here for additional data file.^{(476.8KB, pdf)}

Attachment

Submitted filename: Response to Reviewers.pdf

Click here for additional data file.^{(270.3KB, pdf)}

Attachment

Submitted filename: Rebuttal letter_Dec. 2021.pdf

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Data Availability Statement

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PERMALINK

Expression of pyrethroid metabolizing P450 enzymes characterizes highly resistant Anopheles vector species targeted by successful deployment of PBO-treated bednets in Tanzania

Johnson Matowo

David Weetman

Patricia Pignatelli

Alexandra Wright

Jacques D Charlwood

Robert Kaaya

Boniface Shirima

Oliva Moshi

Eliud Lukole

Jacklin Mosha

Alphaxard Manjurano

Franklin Mosha

Mark Rowland

Natacha Protopopoff

Roles

Abstract

Introduction

Materials and methods

Consent and ethical clearance

Study area and mosquito collections

Fig 1. Map of Tanzania showing the location of Muleba district and the study villages.

Mosquito collection and identification

Wild mosquitoes

Laboratory susceptible strains

Resistance assay with diagnostic concentration

Synergist bioassays

Resistance intensity dose response assay

Genotyping of kdr and GSTe2 mutations

Transcriptome analyses

Candidate gene expression analysis

Data analysis

Results

Resistance assay with diagnostic concentration

Fig 2. Mortality of Anopheles gambiae s.l field populations exposed to permethrin, lambdacyhalothrin, bendiocarb and pirimiphos-methyl insecticides from five villages in 2014.

Synergist bioassays

Resistance intensity dose response assay

Fig 3. 24 hours mortality in An. gambiae s.l. and An. funestus field population after exposure to different concentration of permethrin in intensity CDC bottle bioassays.

Table 1. Lethal concentrations (LC50 in μg/ml/bottle) and resistance ratios (RR50) of permethrin against An. gambiae s.l. and An. funestus field population in intensity CDC bottle bioassays.

Molecular mechanisms

Fig 4. Genes significantly over expressed in An.funestus from Kabirizi vs FANG laboratory susceptible colony.

Fig 5. Genes significantly over expressed in An. gambiae from Kakoma vs Kisumu and Ngousso laboratory susceptible colonies.

Discussion

Conclusions

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

John Vontas

Roles

Author response to Decision Letter 0

Decision Letter 1

Nicholas C Manoukis

Roles

Author response to Decision Letter 1

Decision Letter 2

Nicholas C Manoukis

Roles

Author response to Decision Letter 2

Decision Letter 3

Nicholas C Manoukis

Roles

Acceptance letter

Nicholas C Manoukis

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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Table 1. Lethal concentrations (LC₅₀ in μg/ml/bottle) and resistance ratios (RR₅₀) of permethrin against An. gambiae s.l. and An. funestus field population in intensity CDC bottle bioassays.