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Article

Spatial Distribution of Microsporidia MB Along Clinal Gradient and the Impact of Its Infection on Pyrethroid Resistance in Anopheles gambiae s.l. Mosquitoes from Nigeria and Niger Republic

by
Lamine M. Moustapha
1,*,
Muhammad M. Mukhtar
2,
Abdoul-Nasser H. Sanda
1,
Shuaibu Adamu
2,
Yusuf Y. Aliyu
2,
Hadizat K. Einoi
2,
Maryam U. Maigari
3,
Peter C. Okeke
4,
David E. Nwele
5,
Abiodun Obembe
6,
Udoka C. Nwangwu
7,
Jeremy K. Herren
8 and
Sulaiman S. Ibrahim
1,2,*
1
Department of Biological Sciences, Université André Salifou, Zinder P.O. Box 565, Niger
2
Department of Biochemistry, Bayero University, Kano PMB 3011, Nigeria
3
Integrated Science Department, Federal College of Education (Technical), Ashaka Road, Gombe PMB 60, Nigeria
4
Department of Zoology and Environmental Biology, University of Nigeria, Nsukka, Enugu P.O. Box 3146, Nigeria
5
Department of Biology/Biotechnology, David Umahi Federal University of Health Science, Uburu PMB 211, Nigeria
6
Department of Zoology, Kwara State University, Ilorin PMB 1530, Nigeria
7
Entomology Unit, National Arbovirus and Vectors Research Centre (NAVRC), 4 Park Ln, GRA, Enugu 400102, Nigeria
8
International Centre of Insect Physiology and Ecology (ICIPE), Kasarani, Nairobi P.O. Box 30772-00100, Kenya
*
Authors to whom correspondence should be addressed.
Parasitologia 2025, 5(3), 31; https://doi.org/10.3390/parasitologia5030031
Submission received: 4 April 2025 / Revised: 19 June 2025 / Accepted: 23 June 2025 / Published: 28 June 2025
(This article belongs to the Topic The Complexity of Parasites in Animals: Impacts, Innovation, and Interventions)
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Abstract

Microsporidia MB (MB), a promising biological control agent, suppresses Plasmodium falciparum transmission in Anopheles mosquitoes. This study examined the spatial distribution of MB infection in natural populations of An. gambiae s.l. mosquitoes collected in Nigeria and Niger Republic, and its association with insecticide susceptibility in the mosquitoes. Microsporidia MB has wide geographic distribution across Nigeria and Niger Republic. The overall prevalence of MB in F0 mosquitoes was 12.25% (95% CI: 7.76–16.75%); 25 mosquitoes out of 204 were positive. Geographic variation was observed, with a higher prevalence (5/15 mosquitoes) in Ebonyi State (33.33%, CI: 9.48–57.19%, Fisher’s exact test, p = 0.008). Infection rates were higher in An. coluzzii mosquitoes (21/133 mosquitoes), estimated at 15.79% (CI: 9.59–21.99%) compared to An. gambiae s.s. mosquitoes (4/71), with approximately 5.63% (CI: 0.27–11.00%, χ2 = 4.44; df = 1, p = 0.035). Resistant mosquitoes had a significantly higher prevalence of MB infection than susceptible mosquitos at 28.57% (CI: 16.74–40.40%) with an odds ratio of 3.33 (CI: 1.23–9.03, p = 0.017). These findings suggests that MB can be exploited as an alternative for vector control in Nigeria and Niger, but its possible association with pyrethroid resistance suggests that it should be taken into account as a potential confounder when designing insecticide resistance management strategies.

Graphical Abstract

1. Introduction

Malaria remains a significant global public health issue, particularly in Africa, where over 94% of infection/cases and 95% of malaria-related deaths occur [1]. Nigeria has the highest burden of malaria in the world, accounting for ~26% of malaria cases and ~30% of malaria-related deaths globally. The neighbouring country of Niger also faces significant malaria challenges, contributing 5.9% of malaria-related deaths globally, ranking third [1].
The major malaria vectors found in Nigeria and Niger Republic (hereafter Niger) belong to the Anopheles gambiae complex (principally An. gambiae s.s., An. coluzzii, and An. arabiensis) and secondarily the Anopheles funestus s.s. [2,3,4,5,6,7]. These species exhibit considerable ecological diversity and wide distribution patterns across different habitats [8,9,10]. Studies conducted in Nigeria and Niger have highlighted the abundance and broad distribution of species within the Anopheles gambiae complex and Anopheles funestus group along various ecological zones [3,6,11].
Vector control is the cornerstone of the fight against malaria, with the major control tools being insecticide-treated bed nets and indoor residual spraying [12,13,14,15]. Unfortunately, the use of insecticides has led to the development of resistance to nearly all classes of public health insecticides, with pyrethroids, the key ingredients in insecticide-treated bed nets (ITNs), affected disproportionately [16]. In Niger, pyrethroid resistance towards alpha-cypermethrin, deltamethrin, and permethrin has been documented [11,12,17]. In Nigeria, widespread pyrethroid resistance has been reported in Anopheles mosquitoes. Studies have shown high resistance levels in southern and northern Nigeria, with significant operational implications for ITN effectiveness [3,18,19]. In both countries, high pyrethroid resistance in Anopheles gambiae is associated with increased activities of metabolic enzymes (e.g., P450s and GSTs) and the West African knockdown resistance (kdr-w) mutation [12,20,21,22,23].
The bulk of research on resistance mechanisms has focused on the role of metabolic genes and target site mutations [24,25,26,27], with alternative mechanisms such as the role of the gut microbiome in mediating resistance receiving little attention. However, Dada and colleagues have demonstrated that variations in the Anopheles gut microbiome can influence pyrethroid resistance, suggesting an additional layer of complexity to resistance management [28].
In the face of the resistance challenges associated with synthetic insecticides, efforts are being increasingly invested towards alternative, more eco-friendly control measures, such as Wolbachia [29,30,31] and Bacillus thuringiensis (Bti) [32,33]. The discovery of Microsporidia MB, an intracellular symbiont in Anopheles mosquitoes, has sparked interest due to its potential for malaria control. The presence of MB in Anopheles mosquitoes negatively impacts their ability to transmit Plasmodium [34]. MB accumulates in mosquito tissues, with sexual and vertical transmission ensuring its persistence and transmission [34,35,36]. The presence of MB has been confirmed in several Anopheles species across Africa, including Kenya, Ghana, Niger, and Benin [6,34,37,38]. Studies have shown that its prevalence varies by geographic region, habitat type, and climatic conditions. For instance, in Kenya, MB prevalence in An. gambiae complex mosquitoes was higher in low-altitude areas with warm temperatures and high rainfall compared to high-altitude areas with cooler temperatures and lower rainfall [34]. Similarly, in Ghana, MB prevalence in An. gambiae s.l. was higher in forest zones compared to savanna zones [38]. Recently, a variation in MB infection was reported in two geographical localities of Benin republic [39]. The above findings underscore the significant role of environmental conditions in shaping the geographic distribution of MB.
While MB shows promise as a biological control agent [40], its effectiveness may be influenced by environmental conditions and inherent variability in transmission rates, complicating its use. Moreover, its potential to influence mosquito phenotypes, particularly insecticide resistance, remains largely unexplored. Understanding interspecies and intraspecies variations in MB infection between Anopheles populations and the potential role of MB resistance is essential for informing malaria control strategies. This study investigated the spatial distribution of MB and assessed its association with insecticide resistance phenotypes in Anopheles gambiae s.l. mosquitoes from Nigeria and Niger.

2. Materials and Methods

2.1. Collection of Anopheles Mosquitoes

Mosquitoes were collected across twelve sites, spanning contrasting ecological settings: one site in Niger and eleven in Nigeria (Figure 1). These sites cover mangrove swamp, tropical rainforest, Guinea savanna, Sudan savannah, and the Sahel (Table 1). Blood-fed female Anopheles mosquitoes (F0) resting indoors were collected using Prokopack electric aspirators (John W. Hook, Gainesville, FL, USA) early in the morning, between 05:00 and 06:00 a.m. The mosquitoes were transferred to Bayero University Kano in paper cups (using cooling boxes) and maintained under standard insectarium conditions (25 °C and 75% relative humidity, with 12 h:12 h light/dark cycles), fed with 10% sugar. Collections were conducted in Nigeria between June and September and in Niger in September 2024. Gravid females were forced to lay eggs individually and, following oviposition, identified to species level using PCR, before eggs from identical species were pooled and reared to adulthood for insecticide bioassays.

2.2. Morphological and Molecular Identification of Anopheles Mosquitoes to Species Level

Gravid F0 female mosquitoes (4–5 d old after blood meal) were forced to lay eggs inside 1.5 mL Eppendorf tubes. They were morphologically identified to species complex level using keys described by Gillies and Coetzee [41] based on traits such as palpus length, wing spots pattern, and leg banding. Molecular identification was conducted using SINE200 PCR [42]. Genomic DNA (gDNA) was extracted using the LIVAK protocol [43]. Each gDNA premix of 14 µL comprised 1.5 µL of 10x Taq A buffer, 0.75 µL of MgCl2, 0.12 µL of 10 mM dNTP mixes, 0.51 µL (0.34 µM) each of the SINE200 F and R primers, 0.12 µL of 5 U/µL KapaTaq Polymerase (Kapa Biosciences, Wilmington, MA, USA), and 10.49 µL of ddH20, to which 1 µL of gDNA was added. The thermal cycling conditions were an initial denaturation at 95 °C for 5 min, followed by 35 cycles each of denaturation at 95 °C for 30 s, annealing at 54 °C for 30 s, and extension at 72 °C for 1 min. A final extension step was performed at 72 °C for 5 min. PCR products were separated on 1.5% agarose gel stained with pEqGREEN, and visualised using InGenius 3 GelDoc, (Syngene, Cambridge, UK) with expected band sizes of 479 bp, 245 bp, and 220 bp, respectively, for An. coluzzii, An. gambiae s.s., and An. arabiensis. Genomic DNA samples from previously PCR-confirmed An. coluzzii, An. gambiae s.s., and arabiensis were used for positive controls, and for a negative control, nuclease-free water was used.

2.3. Insecticide Susceptibility Bioassays

Tube bioassays were conducted using the World Health Organization (WHO) protocol [44,45]. Briefly, for each test, 4 replicates of 20 to 25 non-blood-fed adult female mosquitoes (3–4 d old) were exposed to papers impregnated with either 0.05% deltamethrin or 0.75% permethrin. The test papers were purchased from Universiti Sains Malaysia (Penang, Malaysia). The mosquitoes were exposed for 1 h, transferred to holding tubes, and supplied with sugar. Mortalities were recorded at 24 h and mosquitoes alive at 24 h were separated from those which died.

2.4. Investigation of Spatial Distribution of MB Infection in Anopheles Mosquitoes

Subsets of gDNA extracted from the F0 females mentioned above (Table 1) were used for the PCR identification of MB infection. Amplification of the 18S rRNA gene was performed using MB18SF and MB18SR primers according to a previously published protocol [28]. Briefly, 3 μL of 5x master mix (Solis Biodyne, Tartu, Estonia), comprising 7.5 mM of MgCl2, 2 mM of each dNTP mix, and HOT FIREPol® DNA polymerase was mixed with 0.75 μL (0.5 μM) each of F and R primer, 3 μL of DNA template, and 7.5 μL of nuclease-free water. The thermal cycling conditions included an initial denaturation at 95 °C for 15 min, followed by 35 cycles each of denaturation at 95 °C for 30 s, annealing at 59 °C for 45 s, and extension at 72 °C for 45 s. The PCR products were separated on 1.5% agarose gel stained with pEqGREEN, and visualised using GelDoc for the expected band size of approximately 500 bp characteristic of MB. Genomic DNA from previously confirmed MB-positive An. coluzzii [6] was used as a positive control. Nuclease-free water was used as a negative control.

2.5. Investigation of the Association of Insecticide Resistance and MB Infection

The F1 mosquitoes from six sites in Nigeria, which were phenotyped with pyrethroid insecticides, were selected to screen MB infection (Table 1). From each site, an equal number of mosquitoes from the contrasting phenotypes [alive (resistant, R) and dead (susceptible, S)] were randomly selected and screened for infection.

2.6. Data Analysis

Data were analysed using XLSTAT BASIC 2024.4.2 [46] to investigate the relationships between MB infection status, Anopheles species, locality, and insecticide resistance. To establish the relationships between variables, a Chi-square test or a Fisher’s exact test of independence was applied to determine whether MB infection status is associated with species, locality, and insecticide susceptibility. The odds ratio (OR) was determined to measure the strength of association between variables. p-values < 0.05 were considered statistically significant. For each site, 95% confidence intervals (CIs) for the prevalence of MB infection were calculated using the exact binomial method, based on the number of infected mosquitoes out of the total number tested per site.
Multiple Correspondence Analysis (MCA) was conducted using XLSTAT’s “Factor Analysis” package, a multivariate approach designed for categorical data. The MCA was applied to explore key relationships, including the association between MB infection status and Anopheles species, the relationship between infection status and mosquito insecticide susceptibility (resistant vs. susceptible), and the spatial distribution of MB across sampled localities. MCA was conducted using the following categorical variables: Microsporidia MB infection status (MB+ and MB−) for infected and non-infected mosquitoes, respectively; mosquito species (An. coluzzii, An. gambiae s.s.); and insecticide susceptibility phenotype (Resistant/Susceptible). A breakdown of the number of Anopheles species used for MCA is provided in Table S1 in Supplementary File S2.

3. Results

3.1. Microsporidia MB Infects Anopheles Mosquitoes from Contrasting Ecological Settings

A total of 204 adult female F0 mosquitoes were analysed for MB infection, of which 25 were infected (gel pictures in File S1), with 12.25% prevalence (95% CI: 7.76–16.75%). Microsporidia MB was found to be widespread across sites with only 2 out of the 12 sites being negative (Figure 2). The prevalence of infection varied, ranging from of 0% to 33% (Table S2, File S2). For F0 females, the infection rate was highest in Ebonyi State, where 5 out of 15 mosquitoes were infected (33.33%, 95% CI: 9.48–57.19%), followed by Rivers State, where 7 out of 24 mosquitoes were positive for infection (29.17%, 95% CI: 10.98–47.35%). However, mosquitoes from Kwara and Gombe States were not infected. A Fisher’s exact test confirmed a statistically significant association between MB infection status and locality (p = 0.008).
Infection varied across Anopheles species with An. coluzzii exhibiting a higher infection rate. A total of 21 out of 133 An. coluzzii mosquitoes were infected, translating into prevalence of 15.79% (95% CI: 9.59–21.99%), compared to only 4 out of 71 for An. gambiae s.s. (prevalence = 5.63%, 95% CI: 0.27–11.00%) (Table S1, File S2). A statistically significant association was observed between MB infection status and mosquito species (χ2 = 4.44; df = 1, p = 0.035). Furthermore, when comparing the likelihood of infection between species, An. coluzzii had significantly higher odds of being infected with MB (odds ratio = 3.14, 95% CI: 1.03–9.54, p = 0.035), whereas An. gambiae s.s. was predicted to be likely not infected (odds ratio = 0.32, 95% CI: 0.11–0.91). The relationship between MB infection status and Anopheles species was also analysed using Multiple Correspondence Analysis (Figure 3).
The MCA plot illustrates the association between MB infection status and Anopheles species by clustering variable categories with similar profiles on the factor map. The two dimensions (F1 and F2) together explain 100% of the variability in the dataset, with F1 accounting for 57% and F2 explaining 43% of the variance. On the map, An. coluzzii and MB+ variables clustered together in the right-hand-side quadrant of dimension F1. This clustering indicates that these categories share similar profiles, consistent with the significantly higher prevalence of MB infection observed in An. coluzzii. Conversely, the MB-negative (MB infection status—No) variable and An. gambiae s.s. clustered in the left-hand-side quadrant of dimension F2. This separation possibly reflects the lower prevalence of infection in An. gambiae s.s. This clear spatial differentiation on the MCA plot corroborates the statistical findings, where An. coluzzii exhibited a significantly higher MB infection compared to An. gambiae s.s.

3.2. Microsporidia MB Infection Probably Correlates with Pyrethroid Resistance

Bioassays revealed resistance in all populations towards pyrethroid insecticides, with the lowest mortalities observed in the An. coluzzii populations from Gadau in Bauchi State (deltamethrin mortality = 18.75%), followed by Obio/Akpor in Bauchi State (permethrin mortality = 29.46%) (Figure 4). The lowest resistance was observed for the An. gambiae s.s. population from Zariagi, Kogi State (deltamethrin mortality = 85%).
To test the hypothesis that MB infection may be associated with insecticide resistance, a subset of F1 female mosquitoes previously exposed to pyrethroids were PCR-screened to detect MB infection. Of the 112 females tested with pyrethroid, an equal proportion of 50% susceptible (S) and 50% resistant (R) mosquitoes were utilised. Overall, 16 of 56 resistant (R) mosquitoes (28.57%, 95% CI: 16.74–40.40%) were infected with MB, compared to 6 of 56 susceptible (S) mosquitoes (10.71%, 95% CI: 2.61–18.82%). These differences in infection were statistically significant (χ2 = 5.65, df = 1, p = 0.017). The odds ratio of the likelihood of surviving pyrethroid exposure (R phenotype) when MB-infected was significant (OR = 3.33, 95% CI: 1.23–9.03, p = 0.017), compared with the non-significant odds ratio of 0.30 (95% CI: 0.11–0.81) observed in susceptible mosquitoes. The MCA plot in Figure 5 depicts the association between MB infection status and phenotypes (resistant vs. susceptible) by clustering variable categories with similar profiles. The two dimensions (F1 and F2) explain 100% of the variability, with F1 accounting for 61% and F2 explaining 39% of the variance.
The variables Resistant (R) and MB+ (positive infection status) cluster closely in the positive quadrant of F1. This indicates an association between the resistance phenotype and MB infection status. In contrast, the Susceptible (S) phenotype and MB− (negative infection status) cluster in the negative and positive quadrants of F2, respectively. This suggests an association between low MB infection and pyrethroid susceptibility.

4. Discussion

The threat of insecticide resistance spurs efforts for alternative control measures, including using biological agents such as Wolbachia and B. thuringiensis. The discovery of MB and the recent description of its ability to reduce Plasmodium infection in malaria mosquitoes [34] has catalysed new efforts to understand the bionomics of this promising fungus.
This primary study generates information about the distribution of MB in Anopheles mosquitoes from contrasting ecological settings and its association with insecticide resistance. MB is relatively well established in mosquito populations from Nigeria and Niger, with ten populations testing positive. However, it was not detected in two populations. This observation needs to be confirmed with a larger sample size. Indeed, previous studies have suggested that local and ecological variations influence the presence of MB [38,39,47]. Our results show that the differences in MB prevalence between mosquito species and geographic locations are possibly shaped by the underlying ecological origins of the mosquitoes. Indeed, humidity, temperature, breeding site characteristics, vegetation cover, and urbanisation can influence mosquito abundance, microbiota composition, and insecticide resistance phenotype [39,48,49,50,51]. For instance, the states of Ebonyi and Rivers, where MB prevalence was highest, are located in humid, vegetated zones that may support higher microbial diversity. Future studies should integrate detailed ecological and environmental data to disentangle these potential confounding effects.
Across Africa, MB appears to be well established in the main malaria vectors. The 12.25% MB infection prevalence observed in this study was double the 6.8% (17/251) prevalence reported in An. coluzzii in a study in which no infection was observed in An. gambiae s.s. from Zinder city in Niger [6]. However, it is lower than the 53.4% prevalence previously reported in Benin [37]. The MB prevalence observed in Ghana (1.8%) [38] and Kenya (1.7%) [47] was much lower than our findings (though fewer mosquito samples were screened in our study).
This study demonstrated a significantly higher prevalence of MB in An. coluzzii compared to An. gambiae s.s. A similar pattern has been described in a previous study from Benin, with a prevalence of 41.0% in An. gambiae s.s. versus 57.0% in An. coluzzii [37]. Most studies in East Africa indicate that MB infects An. arabiensis [34,35,47], while in West Africa it primarily infects An. coluzzii [6,37,38].
The MB infection rates varied significantly across the study sites, reflecting a likely influence of geographic and ecological factors. The highest infection rates were observed in Ebonyi State (a tropical rainforest site) and Rivers State (mangrove swamp) in the wild-caught mosquitoes, possibly because these localities offer particularly favourable conditions for optimal MB growth, including high humidity, conducive temperatures, and suitable habitats for optimal development in mosquito vectors. These findings are consistent with a previous study that reported that MB prevalence is influenced by species-specific and ecological factors [34]. Similarly, other studies [39,47,52] have documented geographic variation in MB prevalence, with higher rates in humid environments.
The higher prevalence of MB in pyrethroid-resistant mosquitoes raises important questions about its potential role in insecticide resistance. However, variations in insecticide exposure history between the different populations used in this study could also shape resistance phenotypes independent of MB infection. It is also important to acknowledge that the mosquitoes utilised for the bioassays were disproportionately An. coluzzii, with a limited number of An. gambiae s.s. (only 24 mosquitoes from one population out of the 112 F1 mosquitoes screened). Future studies should explore within-species variability in MB infection between resistant and susceptible mosquitoes, using a stratified approach to confirm the potential association between the infection and resistance phenotype. Several studies have linked the microbiome with insecticide resistance, showing that pyrethroid-resistant mosquitoes harbour distinct microbiota compared to the pyrethroid-susceptible strains [28,53]. For example, in the major malaria vector An. coluzzii, an abundance of Asaia and Serratia bacteria has been associated with deltamethrin resistance [54]. Resistant mosquitoes have been found to be enriched with bacteria and enzymes that can degrade insecticides, suggesting that the microbiota may play a role in resistance [28]. It has also been shown that MB infection can influence the phenotype of Anopheles such as adaptation to varying dietary conditions [55], faster larval development, and higher adult emergence rates [56], all which suggest an impact on various phenotypes. Although few samples were utilised, our finding of a possible association between pyrethroid resistance and MB infection highlights the need for further research into its roles in insecticide resistance, particularly towards key malaria control tools, such as long-lasting insecticidal bed nets and the ingredients used for indoor residual spraying. Understanding these may strengthen the management of resistance and improve malaria control efforts, and could lead to novel strategies that use insecticide resistance to facilitate the spread of MB through mosquito populations for sustainable malaria control.

5. Conclusions

Microsporidia MB is detected across multiple eco-geographic settings in Anopheles mosquitoes across Nigeria, and predominantly in An. coluzzii in both Nigeria and Niger. The detection of MB in multiple localities and its strong association with An. coluzzii, a major vector in West Africa, highlight its potential for biological control. However, more screening of mosquitoes should be conducted with larger sample sizes to confirm this pattern. The finding of a possible association between MB infection and the ability to survive insecticide exposure in Anopheles mosquitoes in this study is of interest to control programmes. However, there is a need to conduct further studies, ideally longitudinally, with higher mosquito numbers to confirm this observation. Future research should also incorporate environmental and entomological variables, and explore the functional role of MB in insecticide resistance. Such investigations will be essential to assess the feasibility of harnessing MB as a biological tool for integrated malaria vector management programmes.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/parasitologia5030031/s1; File S1: Agarose gel of MB PCR identification; File S2: Prevalence of MB infection across geographical sites and in mosquito species.

Author Contributions

Conceptualisation, S.S.I., J.K.H. and L.M.M.; methodology, L.M.M., A.-N.H.S., M.M.M., Y.Y.A., S.A., U.C.N., P.C.O., D.E.N., A.O., M.U.M. and H.K.E.; software, S.S.I. and L.M.M.; validation, S.S.I. and J.K.H.; formal analysis, L.M.M., S.S.I. and M.M.M.; resources, S.S.I.; data curation, S.S.I. and L.M.M.; writing—original draft preparation, L.M.M. and S.S.I.; writing—review and editing, J.K.H., P.C.O., D.E.N. and U.C.N.; visualisation, L.M.M. and S.S.I.; supervision, S.S.I.; project administration, S.S.I. and M.M.M.; funding acquisition, S.S.I. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding. This study was privately funded by S.S.I. and L.M.M.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The raw data generated from this study are available in the Supplementary Materials.

Acknowledgments

We thank the technicians of the Biochemistry laboratory of Bayero University of Kano and Sahelo-Saharan Ecology and Biodiversity Laboratory of Université André Salifou who provided technical support for the study both in the field and laboratory.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. WHO. World Malaria Report 2024: Addressing Inequity in the Global Malaria Response; WHO: Geneva, Switzerland, 2024. [Google Scholar]
  2. Ibrahim, S.S.; Manu, Y.A.; Tukur, Z.; Irving, H.; Wondji, C.S. High Frequency of Kdr L1014F Is Associated with Pyrethroid Resistance in Anopheles coluzzii in Sudan Savannah of Northern Nigeria. BMC Infect. Dis. 2014, 14, 441. [Google Scholar] [CrossRef] [PubMed]
  3. Ibrahim, S.S.; Mukhtar, M.M.; Datti, J.A.; Irving, H.; Kusimo, M.O.; Tchapga, W.; Lawal, N.; Sambo, F.I.; Wondji, C.S. Temporal Escalation of Pyrethroid Resistance in the Major Malaria Vector Anopheles coluzzii from Sahelo-Sudanian Region of Northern Nigeria. Sci. Rep. 2019, 9, 7395. [Google Scholar] [CrossRef]
  4. Ibrahim, S.S.; Mukhtar, M.M.; Irving, H.; Riveron, J.M.; Fadel, A.N.; Tchapga, W.; Hearn, J.; Muhammad, A.; Sarkinfada, F.; Wondji, C.S. Exploring the Mechanisms of Multiple Insecticide Resistance in a Highly Plasmodium-Infected Malaria Vector Anopheles funestus Sensu Stricto from Sahel of Northern Nigeria. Genes 2020, 11, 454. [Google Scholar] [CrossRef]
  5. Lamidi, T.B.; Alo, E.B.; Naphtali, R. Distribution and Abundance of Anopheles Mosquito Species in Three Selected Areas of Taraba State, North-Eastern Nigeria. Anim. Res. Int. 2017, 14, 2730–2740. [Google Scholar]
  6. Moustapha, L.M.; Sadou, I.M.; Arzika, I.I.; Maman, L.I.; Gomgnimbou, M.K.; Konkobo, M.; Diabate, A.; Bilgo, E. First Identification of Microsporidia MB in Anopheles coluzzii from Zinder City, Niger. Parasit. Vectors 2024, 17, 39. [Google Scholar] [CrossRef]
  7. Oduola, A.O.; Adelaja, O.J.; Aiyegbusi, Z.O.; Tola, M.; Obembe, A.; Ande, A.T.; Awolola, S. Dynamics of Anopheline Vector Species Composition and Reported Malaria Cases during Rain and Dry Seasons in Two Selected Communities of Kwara State. Niger. J. Parasitol. 2016, 37, 157. [Google Scholar] [CrossRef]
  8. Adeogun, A.; Babalola, A.S.; Okoko, O.O.; Oyeniyi, T.; Omotayo, A.; Izekor, R.T.; Adetunji, O.; Olakiigbe, A.; Olagundoye, O.; Adeleke, M.; et al. Spatial Distribution and Ecological Niche Modeling of Geographical Spread of Anopheles gambiae Complex in Nigeria Using Real Time Data. Sci. Rep. 2023, 13, 13679. [Google Scholar] [CrossRef]
  9. Ebenezer, A.; Okiwelu, S.; Agi, P.; Noutcha, M.E.; Awolola, T.; Oduola, A. Species Composition of the Anopheles gambiae Complex across Eco-Vegetational Zones in Bayelsa State, Niger Delta Region, Nigeria. J. Vector Borne Dis. 2012, 49, 164. [Google Scholar] [CrossRef]
  10. Thabet, H.S.; TagEldin, R.A.; Fahmy, N.T.; Diclaro, J.W.; Alaribe, A.A.; Ezedinachi, E.; Nwachuku, N.S.; Odey, F.O.; Arimoto, H. Spatial Distribution of PCR-Identified Species of Anopheles Gambiae senu lato (Diptera: Culicidae) Across Three Eco-Vegetational Zones in Cross River State, Nigeria. J. Med. Entomol. 2022, 59, 576–584. [Google Scholar] [CrossRef]
  11. Ibrahim, S.S.; Mukhtar, M.M.; Irving, H.; Labbo, R.; Kusimo, M.O.; Mahamadou, I.; Wondji, C.S. High Plasmodium Infection and Multiple Insecticide Resistance in a Major Malaria Vector Anopheles coluzzii from Sahel of Niger Republic. Malar. J. 2019, 18, 181. [Google Scholar] [CrossRef]
  12. Soumaila, H.; Hamani, B.; Arzika, I.I.; Soumana, A.; Daouda, A.; Daouda, F.A.; Iro, S.M.; Gouro, S.; Zaman-Allah, M.S.; Mahamadou, I.; et al. Countrywide Insecticide Resistance Monitoring and First Report of the Presence of the L1014S Knock down Resistance in Niger, West Africa. Malar. J. 2022, 21, 385. [Google Scholar] [CrossRef] [PubMed]
  13. Tchouakui, M.; Assatse, T.; Tazokong, H.R.; Oruni, A.; Menze, B.D.; Nguiffo-Nguete, D.; Mugenzi, L.M.J.; Kayondo, J.; Watsenga, F.; Mzilahowa, T.; et al. Detection of a Reduced Susceptibility to Chlorfenapyr in the Malaria Vector Anopheles gambiae Contrasts with Full Susceptibility in Anopheles funestus across Africa. Sci. Rep. 2023, 13, 2363. [Google Scholar] [CrossRef] [PubMed]
  14. Kouassi, B.L.; Edi, C.; Tia, E.; Konan, L.Y.; Akré, M.A.; Koffi, A.A.; Ouattara, A.F.; Tanoh, A.M.; Zinzindohoue, P.; Kouadio, B.; et al. Susceptibility of Anopheles gambiae from Côte d’Ivoire to Insecticides Used on Insecticide-Treated Nets: Evaluating the Additional Entomological Impact of Piperonyl Butoxide and Chlorfenapyr. Malar. J. 2020, 19, 454. [Google Scholar] [CrossRef] [PubMed]
  15. Fouet, C.; Ashu, F.A.; Ambadiang, M.M.; Tchapga, W.; Wondji, C.S.; Kamdem, C. Clothianidin-Resistant Anopheles gambiae Adult Mosquitoes from Yaoundé, Cameroon, Display Reduced Susceptibility to SumiShield® 50WG, a Neonicotinoid Formulation for Indoor Residual Spraying. BMC Infect. Dis. 2024, 24, 133. [Google Scholar] [CrossRef]
  16. Ranson, H.; Lissenden, N. Insecticide Resistance in African Anopheles Mosquitoes: A Worsening Situation That Needs Urgent Action to Maintain Malaria Control. Trends Parasitol. 2016, 32, 187–196. [Google Scholar] [CrossRef]
  17. Maiga, A.-A.; Sombié, A.; Zanré, N.; Yaméogo, F.; Iro, S.; Testa, J.; Sanon, A.; Koita, O.; Kanuka, H.; McCall, P.J.; et al. First Report of V1016I, F1534C and V410L Kdr Mutations Associated with Pyrethroid Resistance in Aedes aegypti Populations from Niamey, Niger. PLoS ONE 2024, 19, e0304550. [Google Scholar] [CrossRef]
  18. Busari, L.O.; Raheem, H.O.; Iwalewa, Z.O.; Fasasi, K.A.; Adeleke, M.A. Investigating Insecticide Susceptibility Status of Adult Mosquitoes against Some Class of Insecticides in Osogbo Metropolis, Osun State, Nigeria. PLoS ONE 2023, 18, e0285605. [Google Scholar] [CrossRef]
  19. Omotayo, A.I.; Ande, A.T.; Oduola, A.O.; Adelaja, O.J.; Adesalu, O.; Jimoh, T.R.; Ghazali, A.I.; Awolola, S.T. Multiple Insecticide Resistance Mechanisms in Urban Population of Anopheles coluzzii (Diptera: Culicidae) from Lagos, South-West Nigeria. Acta Trop. 2022, 227, 106291. [Google Scholar] [CrossRef]
  20. Awolola, T.S.; Adeogun, A.; Olakiigbe, A.K.; Oyeniyi, T.; Olukosi, Y.A.; Okoh, H.; Arowolo, T.; Akila, J.; Oduola, A.; Amajoh, C.N. Pyrethroids Resistance Intensity and Resistance Mechanisms in Anopheles gambiae from Malaria Vector Surveillance Sites in Nigeria. PLoS ONE 2018, 13, e0205230. [Google Scholar] [CrossRef]
  21. Ibrahim, S.S.; Muhammad, A.; Hearn, J.; Weedall, G.D.; Nagi, S.C.; Mukhtar, M.M.; Fadel, A.N.; Mugenzi, L.J.; Patterson, E.I.; Irving, H.; et al. Molecular Drivers of Insecticide Resistance in the Sahelo-Sudanian Populations of a Major Malaria Vector Anopheles coluzzii. BMC Biol. 2023, 21, 125. [Google Scholar] [CrossRef]
  22. Muhammad, A.; Ibrahim, S.S.; Mukhtar, M.M.; Irving, H.; Abajue, M.C.; Edith, N.M.A.; Da’u, S.S.; Paine, M.J.I.; Wondji, C.S. High Pyrethroid/DDT Resistance in Major Malaria Vector Anopheles coluzzii from Niger-Delta of Nigeria Is Probably Driven by Metabolic Resistance Mechanisms. PLoS ONE 2021, 16, e0247944. [Google Scholar] [CrossRef] [PubMed]
  23. Soumaila, H.; Idrissa, M.; Akgobeto, M.; Habi, G.; Jackou, H.; Sabiti, I.; Abdoulaye, A.; Daouda, A.; Souleymane, I.; Osse, R. Multiple Mechanisms of Resistance to Pyrethroids in Anopheles gambiae s.l Populations in Niger. Méd. Mal. Infect. 2017, 47, 415–423. [Google Scholar] [CrossRef]
  24. Mitchell, S.N.; Rigden, D.J.; Dowd, A.J.; Lu, F.; Wilding, C.S.; Weetman, D.; Dadzie, S.; Jenkins, A.M.; Regna, K.; Boko, P.; et al. Metabolic and Target-Site Mechanisms Combine to Confer Strong DDT Resistance in Anopheles gambiae. PLoS ONE 2014, 9, e92662. [Google Scholar] [CrossRef]
  25. Djouaka, R.F.; Bakare, A.A.; Coulibaly, O.N.; Akogbeto, M.C.; Ranson, H.; Hemingway, J.; Strode, C. Expression of the Cytochrome P450s, CYP6P3 and CYP6M2 Are Significantly Elevated in Multiple Pyrethroid Resistant Populations of Anopheles gambiae s.s. from Southern Benin and Nigeria. BMC Genom. 2008, 9, 538. [Google Scholar] [CrossRef] [PubMed]
  26. Weetman, D.; Wilding, C.S.; Neafsey, D.E.; Müller, P.; Ochomo, E.; Isaacs, A.T.; Steen, K.; Rippon, E.J.; Morgan, J.C.; Mawejje, H.D.; et al. Candidate-Gene Based GWAS Identifies Reproducible DNA Markers for Metabolic Pyrethroid Resistance from Standing Genetic Variation in East African Anopheles Gambiae. Sci. Rep. 2018, 8, 2920. [Google Scholar] [CrossRef] [PubMed]
  27. Zhong, D.; Chang, X.; Zhou, G.; He, Z.; Fu, F.; Yan, Z.; Zhu, G.; Xu, T.; Bonizzoni, M.; Wang, M.-H.; et al. Relationship between Knockdown Resistance, Metabolic Detoxification and Organismal Resistance to Pyrethroids in Anopheles sinensis. PLoS ONE 2013, 8, e55475. [Google Scholar] [CrossRef]
  28. Dada, N.; Sheth, M.; Liebman, K.; Pinto, J.; Lenhart, A. Whole Metagenome Sequencing Reveals Links between Mosquito Microbiota and Insecticide Resistance in Malaria Vectors. Sci. Rep. 2018, 8, 2084. [Google Scholar] [CrossRef]
  29. Hughes, G.L.; Koga, R.; Xue, P.; Fukatsu, T.; Rasgon, J.L. Wolbachia Infections Are Virulent and Inhibit the Human Malaria Parasite Plasmodium Falciparum in Anopheles gambiae. PLoS Pathog. 2011, 7, e1002043. [Google Scholar] [CrossRef]
  30. Gomes, F.M.; Barillas-Mury, C. Infection of Anopheline Mosquitoes with Wolbachia: Implications for Malaria Control. PLoS Pathog. 2018, 14, e1007333. [Google Scholar] [CrossRef]
  31. Walker, T.; Quek, S.; Jeffries, C.L.; Bandibabone, J.; Dhokiya, V.; Bamou, R.; Kristan, M.; Messenger, L.A.; Gidley, A.; Hornett, E.A.; et al. Stable High-Density and Maternally Inherited Wolbachia Infections in Anopheles moucheti and Anopheles demeilloni Mosquitoes. Curr. Biol. CB 2021, 31, 2310–2320.e5. [Google Scholar] [CrossRef]
  32. Almeida, J.; Mohanty, A.; Kerkar, S.; Hoti, S.; Kumar, A. Current Status and Future Prospects of Bacilli-Based Vector Control. Asian Pac. J. Trop. Med. 2020, 13, 525. [Google Scholar] [CrossRef]
  33. Boyce, R.; Lenhart, A.; Kroeger, A.; Velayudhan, R.; Roberts, B.; Horstick, O. Bacillus thuringiensis israelensis (Bti) for the Control of Dengue Vectors: Systematic Literature Review. Trop. Med. Int. Health 2013, 18, 564–577. [Google Scholar] [CrossRef] [PubMed]
  34. Herren, J.K.; Mbaisi, L.; Mararo, E.; Makhulu, E.E.; Mobegi, V.A.; Butungi, H.; Mancini, M.V.; Oundo, J.W.; Teal, E.T.; Pinaud, S.; et al. A Microsporidian Impairs Plasmodium falciparum Transmission in Anopheles arabiensis Mosquitoes. Nat. Commun. 2020, 11, 2187. [Google Scholar] [CrossRef]
  35. Makhulu, E.E.; Onchuru, T.O.; Gichuhi, J.; Otieno, F.G.; Wairimu, A.W.; Muthoni, J.N.; Koekemoer, L.; Herren, J.K. Localization and Tissue Tropism of the Symbiont Microsporidia MB in the Germ Line and Somatic Tissues of Anopheles Arabiensis. mBio 2024, 15, e02192-23. [Google Scholar] [CrossRef]
  36. Nattoh, G.; Maina, T.; Makhulu, E.E.; Mbaisi, L.; Mararo, E.; Otieno, F.G.; Bukhari, T.; Onchuru, T.O.; Teal, E.; Paredes, J.; et al. Horizontal Transmission of the Symbiont Microsporidia MB in Anopheles arabiensis. Front. Microbiol. 2021, 12, 647183. [Google Scholar] [CrossRef]
  37. Ahouandjinou, M.J.; Sovi, A.; Sidick, A.; Sewadé, W.; Koukpo, C.Z.; Chitou, S.; Towakinou, L.; Adjottin, B.; Hougbe, S.; Tokponnon, F.; et al. First Report of Natural Infection of Anopheles gambiae s.s. and Anopheles coluzzii by Wolbachia and Microsporidia in Benin: A Cross-Sectional Study. Malar. J. 2024, 23, 72. [Google Scholar] [CrossRef]
  38. Akorli, J.; Akorli, E.A.; Tetteh, S.N.A.; Amlalo, G.K.; Opoku, M.; Pwalia, R.; Adimazoya, M.; Atibilla, D.; Pi-Bansa, S.; Chabi, J.; et al. Microsporidia MB Is Found Predominantly Associated with Anopheles gambiae s.s and Anopheles coluzzii in Ghana. Sci. Rep. 2021, 11, 18658. [Google Scholar] [CrossRef]
  39. Tchigossou, G.; Lontsi-Demano, M.; Tossou, E.; Sovegnon, P.-M.; Akoton, R.; Adanzounon, D.; Dossou, C.; Koto, M.; Ogbon, A.; Gouété, M.; et al. Seasonal Variation of Microsporidia MB Infection in Anopheles gambiae and Anopheles coluzzii in Two Different Geographical Localities in Benin. Malar. J. 2025, 24, 95. [Google Scholar] [CrossRef]
  40. Bukhari, T.; Pevsner, R.; Herren, J.K. Microsporidia: A Promising Vector Control Tool for Residual Malaria Transmission. Front. Trop. Dis. 2022, 3, 957109. [Google Scholar] [CrossRef]
  41. Coetzee, M. Key to the Females of Afrotropical Anopheles Mosquitoes (Diptera: Culicidae). Malar. J. 2020, 19, 70. [Google Scholar] [CrossRef]
  42. Santolamazza, F.; Mancini, E.; Simard, F.; Qi, Y.; Tu, Z.; della Torre, A. Insertion Polymorphisms of SINE200 Retrotransposons within Speciation Islands of Anopheles gambiae Molecular Forms. Malar. J. 2008, 7, 163. [Google Scholar] [CrossRef] [PubMed]
  43. Livak, K.J. Organization and Mapping of a Sequence on the DROSOPHILA MELANOGASTER X and Y Chromosomes That Is Transcribed during Spermatogenesis. Genetics 1984, 107, 611–634. [Google Scholar] [CrossRef] [PubMed]
  44. World Health Organization. Test Procedures for Insecticide Resistance Monitoring in Malaria Vector Mosquitoes, 2nd ed.; World Health Organization: Geneva, Switzerland, 2016. [Google Scholar]
  45. WHO. Standard Operating Procedure for Testing Insecticide Susceptibility of Adult Mosquitoes in WHO Tube Tests; WHO: Geneva, Switzerland, 2022. [Google Scholar]
  46. Lumivero. XLSTAT|Logiciel Statistique Pour Excel. Available online: https://www.xlstat.com (accessed on 16 October 2024).
  47. Nattoh, G.; Onyango, B.; Makhulu, E.E.; Omoke, D.; Ang’ang’o, L.M.; Kamau, L.; Gesuge, M.M.; Ochomo, E.; Herren, J.K. Microsporidia MB in the Primary Malaria Vector Anopheles gambiae Sensu Stricto Is Avirulent and Undergoes Maternal and Horizontal Transmission. Parasit. Vectors 2023, 16, 335. [Google Scholar] [CrossRef] [PubMed]
  48. Agyekum, T.P.; Botwe, P.K.; Arko-Mensah, J.; Issah, I.; Acquah, A.A.; Hogarh, J.N.; Dwomoh, D.; Robins, T.G.; Fobil, J.N. A Systematic Review of the Effects of Temperature on Anopheles Mosquito Development and Survival: Implications for Malaria Control in a Future Warmer Climate. Int. J. Environ. Res. Public Health 2021, 18, 7255. [Google Scholar] [CrossRef]
  49. Saab, S.A.; Dohna, H.Z.; Nilsson, L.K.J.; Onorati, P.; Nakhleh, J.; Terenius, O.; Osta, M.A. The Environment and Species Affect Gut Bacteria Composition in Laboratory Co-Cultured Anopheles gambiae and Aedes albopictus Mosquitoes. Sci. Rep. 2020, 10, 3352. [Google Scholar] [CrossRef]
  50. Cuesta, E.B.; Coulibaly, B.; Bukhari, T.; Eiglmeier, K.; Kone, R.; Coulibaly, M.B.; Zongo, S.; Barry, M.; Gneme, A.; Guelbeogo, W.M.; et al. Comprehensive Ecological and Geographic Characterization of Eukaryotic and Prokaryotic Microbiomes in African Anopheles. Front. Microbiol. 2021, 12, 635772. [Google Scholar] [CrossRef]
  51. Machani, M.G.; Nzioki, I.; Onyango, S.A.; Onyango, B.; Githure, J.; Atieli, H.; Wang, C.; Lee, M.-C.; Githeko, A.K.; Afrane, Y.A.; et al. Insecticide Resistance and Its Intensity in Urban Anopheles arabiensis in Kisumu City, Western Kenya: Implications for Malaria Control in Urban Areas. PLoS ONE 2024, 19, e0303921. [Google Scholar] [CrossRef]
  52. Akorli, E.A.; Efua, A.N.; Egyirifa, R.K.; Dorcoo, C.; Otoo, S.; Tetteh, S.N.A.; Pul, R.M.; Derrick, B.S.; Oware, S.K.D.; Samuel, K.D.; et al. Mosquito breeding water parameters are important determinants for Microsporidia MB in the aquatic stages of Anopheles species. Parasites Vectors 2024, 17, 509. [Google Scholar] [CrossRef]
  53. Omoke, D.; Kipsum, M.; Otieno, S.; Esalimba, E.; Sheth, M.; Lenhart, A.; Njeru, E.M.; Ochomo, E.; Dada, N. Western Kenyan Anopheles gambiae Showing Intense Permethrin Resistance Harbour Distinct Microbiota. Malar. J. 2021, 20, 77. [Google Scholar] [CrossRef]
  54. Pelloquin, B.; Kristan, M.; Edi, C.; Meiwald, A.; Clark, E.; Jeffries, C.L.; Walker, T.; Dada, N.; Messenger, L.A. Overabundance of Asaia and Serratia Bacteria Is Associated with Deltamethrin Insecticide Susceptibility in Anopheles coluzzii from Agboville, Côte d’Ivoire. Microbiol. Spectr. 2021, 9, e00157-21. [Google Scholar] [CrossRef]
  55. Boanyah, G.Y.; Koekemoer, L.L.; Herren, J.K.; Bukhari, T. Effect of Microsporidia MB Infection on the Development and Fitness of Anopheles arabiensis under Different Diet Regimes. Parasit. Vectors 2024, 17, 294. [Google Scholar] [CrossRef]
  56. Otieno, F.G.; Barreaux, P.; Belvinos, A.S.; Makhulu, E.E.; Onchuru, T.O.; Wairimu, A.W.; Omboye, S.M.; King’ori, C.N.; Mawuko, S.B.; Kebira, A.N.; et al. Temperature Modulates the Dissemination Potential of Microsporidia MB, a Malaria-Blocking Endosymbiont of Anopheles Mosquitoes. bioRxiv 2024. bioRxiv: 2024.11.15.623820. [Google Scholar] [CrossRef]
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Figure 1. Map of sampling locations in Nigeria and Niger.
Figure 1. Map of sampling locations in Nigeria and Niger.
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Figure 2. Spatial distribution of MB along clinal gradient of aridity spanning Nigeria and Niger.
Figure 2. Spatial distribution of MB along clinal gradient of aridity spanning Nigeria and Niger.
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Figure 3. Spatial association between MB infection status and Anopheles species. MB infection status—No = MB-negative and MB infection status—Yes = MB-positive phenotypes.
Figure 3. Spatial association between MB infection status and Anopheles species. MB infection status—No = MB-negative and MB infection status—Yes = MB-positive phenotypes.
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Figure 4. Pyrethroid resistance profiles of F1 Anopheles mosquitoes from contrasting ecological settings. Results are the average of percentage mortalities from four or five replicates of 20–25 mosquitoes each ± standard error of mean (SEM). Blue bars are for deltamethrin and red bars for permethrin.
Figure 4. Pyrethroid resistance profiles of F1 Anopheles mosquitoes from contrasting ecological settings. Results are the average of percentage mortalities from four or five replicates of 20–25 mosquitoes each ± standard error of mean (SEM). Blue bars are for deltamethrin and red bars for permethrin.
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Figure 5. Spatial depiction of potential association between MB infection and pyrethroid resistance. MB infection status—No = MB-negative and MB infection status—Yes = MB-positive phenotypes.
Figure 5. Spatial depiction of potential association between MB infection and pyrethroid resistance. MB infection status—No = MB-negative and MB infection status—Yes = MB-positive phenotypes.
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Table 1. Sampling design and localities for Anopheles mosquito collection and bioassays.
Table 1. Sampling design and localities for Anopheles mosquito collection and bioassays.
LocalitynSpeciesBioassayEcological Setting
F0 parents caught indoor using Prokopack aspirators
Gayi Niger, Magaria 32An. coluzzii-Sahel
Gajerar Giwa, Katsina State32An. coluzzii Sahel
Gaa-Bolorunduro, Kwara State15An. gambiae s.s.-Guinea Savanna
Zariagi, Lokoja, Kogi State32An. gambiae s.s.-Guinea Savanna
Gotomo, Kebbi State15An. coluzzii-Sudan Savanna
Tsunami, Gusau, Zamfara State15An. coluzzii-Sudan Savanna
Ugalaba, Ezza North, Ebonyi State15An. coluzzii-Tropical Rainforest
Obio/Akpor LGA, Rivers State24An. coluzzii-Mangrove Swamp
Badagry, Lagos State24An. gambiae s.s.-Mangrove Swamp
F1 progenies used for bioassays
Gajerar Giwa, Katsina State16An. coluzziiPermethrinSahel
Dadin Kowa, Gombe State16An. coluzziiDeltamethrinGuinea Savanna
Zariagi, Lokoja, Kogi State24An. gambiae s.s.DeltamethrinGuinea Savana
Gamjin Bappa, Karaye, Kano State16An. coluzziiDeltamethrinGuinea Savana
Gadau, Bauchi State16An. coluzziiDeltamethrinSudan Savanna
Obio/Akpor LGA, Rivers State24An. coluzziiPermethrinMangrove Swamp
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Moustapha, L.M.; Mukhtar, M.M.; Sanda, A.-N.H.; Adamu, S.; Aliyu, Y.Y.; Einoi, H.K.; Maigari, M.U.; Okeke, P.C.; Nwele, D.E.; Obembe, A.; et al. Spatial Distribution of Microsporidia MB Along Clinal Gradient and the Impact of Its Infection on Pyrethroid Resistance in Anopheles gambiae s.l. Mosquitoes from Nigeria and Niger Republic. Parasitologia 2025, 5, 31. https://doi.org/10.3390/parasitologia5030031

AMA Style

Moustapha LM, Mukhtar MM, Sanda A-NH, Adamu S, Aliyu YY, Einoi HK, Maigari MU, Okeke PC, Nwele DE, Obembe A, et al. Spatial Distribution of Microsporidia MB Along Clinal Gradient and the Impact of Its Infection on Pyrethroid Resistance in Anopheles gambiae s.l. Mosquitoes from Nigeria and Niger Republic. Parasitologia. 2025; 5(3):31. https://doi.org/10.3390/parasitologia5030031

Chicago/Turabian Style

Moustapha, Lamine M., Muhammad M. Mukhtar, Abdoul-Nasser H. Sanda, Shuaibu Adamu, Yusuf Y. Aliyu, Hadizat K. Einoi, Maryam U. Maigari, Peter C. Okeke, David E. Nwele, Abiodun Obembe, and et al. 2025. "Spatial Distribution of Microsporidia MB Along Clinal Gradient and the Impact of Its Infection on Pyrethroid Resistance in Anopheles gambiae s.l. Mosquitoes from Nigeria and Niger Republic" Parasitologia 5, no. 3: 31. https://doi.org/10.3390/parasitologia5030031

APA Style

Moustapha, L. M., Mukhtar, M. M., Sanda, A.-N. H., Adamu, S., Aliyu, Y. Y., Einoi, H. K., Maigari, M. U., Okeke, P. C., Nwele, D. E., Obembe, A., Nwangwu, U. C., Herren, J. K., & Ibrahim, S. S. (2025). Spatial Distribution of Microsporidia MB Along Clinal Gradient and the Impact of Its Infection on Pyrethroid Resistance in Anopheles gambiae s.l. Mosquitoes from Nigeria and Niger Republic. Parasitologia, 5(3), 31. https://doi.org/10.3390/parasitologia5030031

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