Molecular Detection and Phylogenetic Characterization of Wolbachia Strains in Glossina Species from Nigerian Conservation Areas

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This study investigates the prevalence, seasonal dynamics, and genetic diversity of Wolbachia endosymbionts in 7,632 wild-caught tsetse flies sampled from four ecologically distinct conservation sites: Yankari Game Reserve, Kainji Lake National Park, Kagarko Forest, and Ijah Gwari Forest. Molecular screening based on wsp gene sequencing detected Wolbachia in 1,771 flies, with infection rates rising significantly during the wet season (e.g., G. morsitans submorsitans : 75.4% vs. 39.8% in dry season; p < 0.001). Female flies showed consistently higher infection prevalence, reinforcing the role of vertical transmission. Phylogenetic reconstruction revealed nine Wolbachia strains spanning supergroups A and B, including a putatively unique regional variant (wsp9) restricted to northern Nigeria. Bacterial load exhibited a strong age-dependent pattern (r = 0.912, p < 0.001), and elevated GC content (~ 63%) suggested possible adaptation to savanna thermal conditions. These findings highlight the ecological flexibility of Wolbachia within natural tsetse populations and point to its potential application in vector control—particularly through mechanisms like cytoplasmic incompatibility. By combining molecular detection, ecological data, and evolutionary analysis, this study lays the groundwork for tailored, climate-sensitive Wolbachia -based strategies to reduce tsetse populations and support trypanosomiasis control in Nigeria. Biological sciences/Ecology Earth and environmental sciences/Ecology Biological sciences/Evolution Biological sciences/Microbiology Biological sciences/Zoology Wolbachia Glossina tsetse flies Nigeria phylogenetics vector control Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Tsetse Flies and Trypanosomiasis: Epidemiological Importance in Nigeria Tsetse flies ( Glossina spp.) are the primary vectors of African trypanosomiasis, a neglected tropical disease affecting humans (Human African Trypanosomiasis, HAT) and livestock (Animal African Trypanosomiasis, AAT) (WHO, 2020). In Nigeria, tsetse infestations cover about 75% of the landmass, severely impacting agricultural productivity and public health (Shaida et al., 2018 ). Despite ongoing efforts, the country faces persistent challenges: recent meta-analyses estimate an overall prevalence of 27.3% for AAT and 3.6% for HAT across surveyed populations (Odebunmi et al., 2024 ), with regional disparities and diagnostic limitations complicating surveillance and intervention strategies (Another Author, Year). Nigeria’s trypanosomiasis control programs are further hindered by fragmented local governance, limited funding, and inconsistent implementation across conservation zones (Adamu et al., 2021 ). These constraints underscore the need for innovative, locally adaptable vector control approaches. The disease causes annual economic losses exceeding US $ 4.5 billion due to reduced livestock yields and restricted land use (Mwiinde et al. , 2017). Three major species— G. tachinoides , G. morsitans submorsitans , and G. palpalis palpalis —dominate Nigerian ecosystems, each with distinct ecological preferences and vector capacities (Isaac et al., 2016). Despite control efforts such as insecticide-treated traps and sterile insect techniques, trypanosomiasis persists due to drug resistance, lack of vaccines, and environmental reinvasion (Aksoy et al., 2017 ). Wolbachia pipientis , an obligate intracellular alphaproteobacterium, is known for manipulating arthropod reproduction through mechanisms like cytoplasmic incompatibility, feminization, and male-killing (Werren et al., 2008 ). It also reduces pathogen transmission by competing for host resources or enhancing immune responses (Zélé et al., 2018 ). Successes in controlling Aedes aegypti —notably suppressing dengue and Zika viruses—have sparked interest in Wolbachia ’s potential for tsetse control (Yen & Failloux, 2020 ). However, its prevalence, strain diversity, and ecological dynamics in Glossina species, especially in West Africa, remain largely uncharacterized. Past research has focused on other symbionts like Sodalis , overlooking Wolbachia ’s potential role in vector control (Aksoy et al., 2014 ). Moreover, the influence of ecological factors such as temperature and humidity on Wolbachia dynamics in tsetse flies remains poorly understood (Balmand et al., 2013 ). Given Nigeria’s diverse tsetse habitats—from savannas to riverine forests—mapping Wolbachia strain distribution is critical for targeted interventions. This study aims to address gaps in Wolbachia surveillance among Glossina spp. in Nigeria by: (i) detecting Wolbachia infections across four ecological zones (i) detecting Wolbachia infections across four ecological zones (ii) characterizing strain diversity using wsp sequencing (iii) evaluating infection patterns by season, species, sex, and age. Materials and Methods Study Area The study examined four distinct conservation areas in Nigeria, focusing on different savanna and forest ecosystems. The Yankari Game Reserve in Bauchi State, Nigeria, features Sudan savanna vegetation and riparian forests. Kainji Lake National Park in Niger State, Nigeria, features a Guinea savanna ecosystem with gallery forests. Kagarko Forest in Kaduna State, Nigeria, has a derived savanna habitat with dense riverine thickets. Ijah Gwari Forest in Niger State, Nigeria, has a rainforest-savanna mosaic (Abubakar et al., 2016 ; Isaac et al. , 2016). Ethical Statement Ethical approval was not required as the study involved insect sampling. Map of Tsetse Fly Trapping Sites in the Study Areas. The central map highlights Niger, Kaduna, and Bauchi States, with the targeted LGAs marked in brown: Ijah Gwari in Suleja LGA and Kainji Lake National Park in Borgu LGA (Niger State); Yankari Game Reserve in Alkaleri LGA (Bauchi State); and Kubacha/Maganda Forest in Kagarko LGA (Kaduna State) Sample Size Justification Sample sizes were determined based on prior estimates of tsetse population densities in Nigerian conservation areas (Shaida et al., 2018), ensuring ≥80% statistical power to detect a minimum 10% difference in Wolbachia prevalence between seasons at a significance level of α = 0.05. Sample Collection : We collected samples monthly from April 2017 to July 2019, encompassing both dry and wet seasons a total of 7,632 flies were collected using Biconical traps, as described by Challier and Laveissière (1973), traps were baited with acetone and cow urine and deployed at 50-meter intervals along transects in shaded microhabitats. Species identification was conducted using morphological keys developed by Potts (FAO, 2018), allowing for discrimination among G. m. submorsitans , G. p. palpalis , and G. tachinoides . Flies were dissected under sterile conditions, and the midgut, salivary glands, and reproductive tissues were preserved in 70% ethanol for subsequent DNA extraction (Weber et al., 2019). Tissue Selection and DNA Extraction Wolbachia was targeted in reproductive tissues, midguts, and salivary glands due to their established or suspected roles in vertical transmission and systemic colonization in tsetse (Balmand et al., 2013). Genomic DNA was extracted using the AccuPrep Genomic DNA Extraction Kit (Bioneer, Korea), based on manufacturer's instructions. Approximately 10 mg of reproductive tissues, midgut or salivary gland tissue was lysed in 200 µL G-Buffer with 20 µL Proteinase K at 56°C for one hour. The lysate was combined with 200 µL of Binding Buffer and transferred to AccuPrep DNA extraction columns. After two successive washes with 500 µL of W-Buffer, DNA was eluted in 50 µL of Elution Buffer (10 mM Tris-HCl, pH 8.5). DNA concentration and purity were assessed using a NanoDrop spectrophotometer (Thermo Fisher Scientific), and samples with A260/A280 ratios below 1.7 were re-purified (Bioneer, 2018). PCR Amplification and Controls AccuPower PreMix PCR master mix from Bioneer was used based on manufactures instructions, two gene targets were used to detect and type Wolbachia strains: the wsp gene ( Wolbachia surface protein), a primary marker for strain typing, and the 16S rRNA gene as a confirmatory marker. The primer sets used were 81F/691R for wsp . Primer pairs included wsp-specific 81F (5′-TGGTCCAATAAGTGATGAAGAAAC-3′) and 691R (5′-AAAAATTAAACGCTACTCCA-3′) (Zhou et al., 1998) and along with 16S rRNA-targeting wsp F (5′-CATACCTATTCGAAGGGATAG-3′) and wsp R (5′-AGCTTCGAGTGAAACCAATTC-3′). PCR cycling conditions included an initial denaturation at 95°C for 5 minutes, followed by 35 cycles of denaturation at 95°C for 30 seconds, annealing at 55°C for 30 seconds, and extension at 72°C for 1 minute, with a final elongation step at 72°C for 10 minutes. Positive controls included DNA from Wolbachia -infected Drosophila , and nuclease-free water was used as the negative controll (Bioneer, 2018, Weber et al., 2019). Negative Controls Each PCR batch included a no-template control (nuclease-free water) and a positive control ( Wolbachia -infected Drosophila DNA) to monitor for contamination and ensure amplification efficiency. Gel Electrophoresis and Sequencing and Phylogenetic Analysis Amplified PCR products were resolved on 1.5% agarose gels stained with ethidium bromide and visualized under UV illumination. Positive amplicons were purified using the QIAquick PCR Purification Kit (Qiagen) and sent to Macrogen Inc. (South Korea) for bidirectional Sanger sequencing (Sikkema‐Raddatz, 2013). Phylogenetic Analysis Sequence alignment and phylogenetic reconstruction were performed using MEGA-X software (Kumar et al., 2018). Alignments were generated using the MUSCLE algorithm (Edgar, 2004) with default parameters. Phylogenetic trees were constructed using the Maximum Likelihood method under the GTR+G+I model with 1,000 bootstrap replicates. Reference sequences included known Wolbachia strains from Glossina spp. (GenBank accessions: KP715092, JX273258) and outgroup sequences from Rickettsia spp. Results Seasonal and Species-Specific Wolbachia Prevalence A total of 7,632 Glossina flies were screened across four Nigerian conservation areas. Overall Wolbachia infection prevalence showed notable variation by site, season, species, and sex Site-Level Patterns : Significant seasonal variation was observed only in Yankari Game Reserve, where infection prevalence rose from 12.6% in the dry season to 23.5% in the wet season ( χ² = 13.62, p < 0.001). No statistically significant seasonal differences were found in Kainji Lake National Park, Ijah Gwari Forest, or Kagarko Forest, although marginal increases in prevalence were recorded in all three sites during the wet season (Table 1). Table 1. Wolbachia Infection Prevalence by Season and Site Study Site Season Total Flies Screened Wolbachia -Positive Prevalence (%) χ² Value p-value Inference Yankari Game Reserve Dry 214 27 12.6% Wet 362 85 23.5% 13.62 p < 0.001 Significant seasonal difference Kainji Lake National Park Dry 251 35 13.9% Wet 331 54 16.3% 0.86 p = 0.354 Not significant Ijah Gwari Forest Dry 178 53 29.8% Wet 176 47 26.7% 0.35 p = 0.553 Not significant Kagarko Forest Dry 210 59 28.1% Wet 149 39 26.2% 0.14 p = 0.707 Not significant Species-Level Seasonal Trends Across all three species, Wolbachia prevalence was significantly higher in the wet season. The most pronounced shift occurred in G. morsitans submorsitans (39.8% to 75.4%, χ² = 28.75, p < 0.001), followed by G. tachinoides (47.8% to 69.7%, χ² = 10.03, p = 0.002), and G. palpalis palpalis (24.6% to 55.7%, χ² = 33.27, p < 0.001) (Table 2). Table 2. Wolbachia Infection Prevalence by specie and Season Species Season Total Screened Wolbachia-Positive Prevalence (%) χ² Value p-value Inference G lossina morsitans subm. Dry 108 43 39.8% Wet 114 86 75.4% 28.75 p < 0.001 Significant difference G lossina tachinoides Dry 115 55 47.8% Wet 122 85 69.7% 10.03 p = 0.002 Significant difference G lossina palpalis palpalis Dry 130 32 24.6% Wet 176 98 55.7% 33.27 p < 0.001 Significant difference Interaction of Sex, and Season Females consistently exhibited higher Wolbachia infection rates than males. This disparity was most evident in the wet season, with female prevalence peaking at 83.6% in G. morsitans submorsitans , 81.5% in G. tachinoides , and 50.5% in G. palpalis palpalis . Statistically significant seasonal variation among males was detected only in G. palpalis palpalis (10.8% to 39.4%, χ² = 8.30, p = 0.004), while male infection rates in the other species remained relatively stable. (Table 3). Table 3 . Wolbachia Infection Prevalence by Sex and Season Sex Season Total Screened Wolbachia -Positive Prevalence (%) χ² Value p-value Inference Male Dry 230 64 27.8% Wet 264 66 25.0% 0.46 p = 0.497 Not significant Female Dry 260 110 42.3% Wet 328 159 48.5% 2.32 p = 0.128 Not significant Quantitative Relationship Between Wolbachia Load and Tsetse Fly Age Figure This scatter plot illustrates the quantitative relationship between the age of Glossina flies (x-axis, in days) and their corresponding Wolbachia load (y-axis, measured in arbitrary units). Each red circle represents an individual fly observation. The fitted black regression line indicates a clear positive linear trend, while the surrounding grey band depicts the 95% confidence interval, reflecting the precision of the model's prediction. The data reveal a strong and consistent increase in Wolbachia abundance with fly age. Younger flies (≤5 days) exhibited relatively low bacterial loads, while older individuals (≥30 days) reached the upper limits of the observed range, with values approaching 30 units. The confidence interval narrows at mid-range ages (10–20 days), where data density is highest, and widens at the extremes, suggesting slightly greater uncertainty in model predictions for very young or very old flies. Statistical analysis confirms a strong positive correlation between fly age and Wolbachia load (Pearson’s r = 0.912, p < 0.001). This supports the hypothesis of time-dependent bacterial accumulation, likely due to ongoing replication of Wolbachia in host tissues over the fly’s lifespan. Sequence Identity Multiple Sequence Alignment The multiple sequence alignment (MSA) displays wsp gene fragments from Wolbachia strains isolated from Glossina species collected across northern Nigeria (Yankari Game Reserve, Kainji Lake National Park, Kagarko Forest, and Ijah Gwari Forest). Conserved regions, where sequences are identical or highly similar across isolates, are highlighted in blue, indicating evolutionary stability and potential functional importance. Polymorphic sites, representing single nucleotide polymorphisms or amino acid substitutions, are marked in red, reflecting genetic diversity among Wolbachia strains. Gaps, denoted by dashes, indicate insertions or deletions (indels) that optimize sequence alignment, suggesting structural variations in the wsp gene. The high GC content (63%) is emphasized by bolded residues (G and C), highlighting a nucleotide composition bias that may reflect adaptation to the tsetse fly host environment. The alignment was generated using MUSCLE and visualized with MEGA. Scale bar and sequence identifiers are included to indicate alignment length and sample origins, respectively. Pairwise similarity analysis indicates a 92% sequence similarity between the aligned study sequences and their closest GenBank matches. This high degree of similarity strongly suggests that the Wolbachia strains identified in the Nigerian Glossina species are evolutionarily close to previously described strains and are likely to belong to the same or closely related Wolbachia lineages. Two of the sequences generated in this study have been successfully submitted to the NCBI GenBank database. The assigned accession numbers are: BankIt2776358 WSP 9_WSP 1F_H07_22 : Accession OR977569 BankIt2776358 WSP5_WSP81F_D09_12 : Accession OR977570 Identity and Similarity between WSP 5 ( Wolbachia Glossina palpalis palpalis ) Sequence (OR977570) and Top 10 NCBI BLAST Hits Phylogenetic Tree Phylogenetic analysis revealed Nigerian Wolbachia strains (e.g., wsp3 / wsp4 , 92% identity) cluster with global supergroup A/B lineages (Figure 4), yet wsp9 ’s divergence (92% bootstrap) suggests a unique West African variant. This mirrors findings in Drosophila (Baldo et al., 2006), where localized adaptation drove strain diversification. The branching order of the tree shows that wsp 8 is the most closely related to the other nine strains, followed by wsp 11, wsp 4, wsp , 3, wsp , 5, wsp , 7, and wsp12 . The percentage of closeness between each strain is also shown on the tree. For example, wsp 3 is 98% close to wsp 4, 97% close to wsp 7 , 96% close to wsp 5, and 95% close to wsp 9 (Table 4). Wolbachia surface protein 9 in Glossina morsitans submorsitans is the most distantly related Wolbachia strain on the tree, with a branching order of 92%. This means that it shares a common ancestor with all other Wolbachia strains on the tree, but that common ancestor is more distant in time than any other common ancestor shared by any other four Wolbachia strains on the tree. There is a 92% probability that these Wolbachia sequences would group if the phylogenetic analysis was conducted again on randomly sampled datasets from the initial alignment. Nodes with bootstrap values ≥90% (Figure 3) indicate strong support for the inferred clades, whereas values below 70% reflect weak or unresolved phylogenetic relationships (Felsenstein, 1985). Table 4: The relationship, branching order, percentage of closeness, and most recent common ancestor for the five strains of Wolbachia among the Glossina Species in the study areas. Strain Relationship Branching Order % Closeness MRCA wsp3 Closest to wsp4 Direct 92% wsp3 wsp4 Closest to wsp3 Direct 92% wsp3 wsp7 Less related to wsp3/4 Short branch 90% wsp7 wsp5 Less related to wsp3/4 Longer branch 91% wsp5 wsp8 Less related to wsp3/4 Short branch 91% wsp7 wsp9 Less related to wsp3/4 Longer branch 92% wsp5 wsp11 Least related to wsp3/4 Very long branch 90% wsp12 wsp6 Least related to wsp3/4 Very long branch 91% wsp12 wsp12 Least related overall Very long branches 90% wsp12 Strains were inferred from wsp gene sequences, with branch lengths reflecting evolutionary divergence (see Figure 3) Discussion Prevalence of Glossina in the Studies An entomological survey conducted across four ecologically distinct sites in northern Nigeria—Yankari Game Reserve, Kainji Lake National Park, Kagarko Grazing Reserve, and Ijah Gwari Forest—documented the presence of three key tsetse fly species of medical and veterinary importance: Glossina morsitans submorsitans , Glossina palpalis palpalis , and Glossina tachinoides . The spatial distribution and relative abundance of these species varied considerably, shaped by a combination of ecological conditions and anthropogenic influences. Among the species, Glossina tachinoides emerged as the most dominant, comprising 55.78% of all captures (Table 1). Its widespread presence across multiple habitats, including woodland savannas and ecotones with human activity, reflects its high ecological plasticity. This finding is consistent with earlier observations by Odeniran et al. (2019) and Majekodunmi et al. (2013), who reported similar prevalence of G. tachinoides in Nigeria’s Middle Belt and savanna-woodland transition zones. However, our data diverge from those of Adam et al. (2015), who noted lower densities of this species in Sudan savanna areas, suggesting that even adaptable species may experience range contraction under conditions of prolonged drought and severe habitat degradation. In contrast, G. morsitans submorsitans displayed a more restricted distribution, representing 29.36% of total captures and being completely absent from two of the four study sites. This species showed a clear preference for undisturbed woodland savannas, particularly in Yankari and Kainji, where natural wildlife populations remain relatively intact. These findings align with those of Leak et al. (1991) and Karshima et al. (2016), who highlighted the species' reliance on intact ecosystems for survival. The results also support the hypothesis proposed by Adam et al. (2015) that G. morsitans submorsitans populations are retreating into microclimatically favorable protected zones in response to increasing environmental stressors such as aridity and habitat fragmentation. Seasonal Variation in Wolbachia Prevalence This study found that Wolbachia infection varied seasonally only in Yankari Game Reserve, where prevalence rose significantly from 12.6% in the dry season to 23.5% in the wet season (χ² = 13.62, p < 0.001; Table 2). This aligns with studies by Werren et al. (2008), Mouton et al. (2007), and Alam et al. (2011), which link higher humidity and temperature to increased Wolbachia transmission and density in arthropods. In tsetse flies, such conditions may boost reproduction and facilitate vertical transmission. In contrast, no significant seasonal changes were detected in Kainji, Ijah Gwari, or Kagarko (p > 0.05), though minor increases were observed. The absence of seasonal Wolbachia variation in Kainji and Kagarko may reflect microclimatic stability from dense canopy cover (Weber et al., 2019), buffering humidity fluctuations critical for bacterial replication. This divergence from studies like Baldo et al. (2007) and Kittayapong et al. (2000) may reflect microclimatic buffering, habitat stability, or anthropogenic disturbance that dampens seasonal effects. For instance, agricultural expansion in Kagarko and forest cover in Kainji may limit fluctuations in host or symbiont dynamics. Strain-specific genetic differences could also explain stable prevalence across sites, as some Wolbachia strains are less influenced by environmental changes (Duron et al., 2008). Species-Level Seasonal Trends in Wolbachia Prevalence All three Glossina species showed significantly higher Wolbachia prevalence during the wet season, though the extent varied. Glossina morsitans submorsitans increased from 39.8% to 75.4% (χ² = 28.75, p < 0.001; Table 3), likely due to favorable wet season conditions—such as higher humidity, vegetation, and host availability—that support fly survival and vertical transmission (Werren et al., 2008). Glossina tachinoides rose from 47.8% to 69.7% (χ² = 10.03, p = 0.002; Table 2), suggesting that even ecologically flexible species benefit from these seasonal conditions. Glossina palpalis palpalis , although with the lowest initial prevalence, showed the largest relative increase from 24.6% to 55.7% (χ² = 33.27, p < 0.001; Table 2) likely reflecting its strong dependence on riparian habitats, which expand during the rainy season. These findings align with studies in Aedes and Drosophila , where wet season conditions enhanced Wolbachia density and transmission (Mouton et al., 2007; Zouache et al., 2009). Differences across species may relate to ecological niches, reproductive patterns, or strain-host compatibility. Contrasting studies reporting stable Wolbachia prevalence suggest that genetic resistance, consistent microclimates, or unresponsive strains may buffer seasonal effects (Baldo et al., 2007; Duron et al., 2008). However, the pronounced responsiveness here likely reflects the strong linkage between tsetse ecology and Northern Nigerian rainfall patterns, which govern both host availability and habitat suitability. Sex- and Season-Based Variation in Wolbachia Prevalence Analysis of Wolbachia infection patterns disaggregated by sex and season revealed notable biological differences among Glossina species. Across all species, females consistently exhibited higher Wolbachia prevalence than males, a trend that was most pronounced during the wet season. This sex-based disparity likely reflects differences in reproductive physiology and symbiont transmission efficiency, given that Wolbachia is maternally inherited. For example, female G. morsitans submorsitans showed a significant rise in infection from 50.0% (dry season) to 83.6% (wet season) (χ² = 16.10, p < 0.001). Similar seasonal increases were recorded for G. tachinoides females (56.1% to 81.5%, χ² = 10.34, p = 0.001) and G. palpalis palpalis females (10.8% to 50.5%, χ² = 29.95, p < 0.001). These trends suggest that favorable environmental conditions during the wet season—such as higher humidity, vegetation cover, and host availability—enhance Wolbachia replication and vertical transmission in females, who transmit the symbiont to offspring through their germline (Werren et al., 2008). In contrast, males consistently exhibited lower infection rates. Although Glossina palpalis palpalis males did show a statistically significant increase in Wolbachia prevalence from dry to wet season (χ² = 8.30, p = 0.004), no significant seasonal effect was observed in males of the other species. This may be due to differences in lifespan, physiology, or immune response between sexes. Males do not contribute to vertical transmission, and thus may not maintain high Wolbachia densities (Charlat et al., 2007). These findings are consistent with studies in other insect systems. For instance, Mouton et al. (2007) and Zouache et al. (2009) reported higher Wolbachia densities in females of Aedes and Drosophila during peak reproductive seasons, supporting the role of sex-linked biological factors in infection dynamics. Similarly, in tsetse flies, Aksoy et al. (2008) demonstrated that female flies maintain more stable and higher endosymbiont densities than males. On the other hand, some studies report minimal sex-based differences, particularly in laboratory-reared insects or in populations with low environmental variation. For example, Baldo et al. (2007) observed comparable Wolbachia prevalence in both sexes of some dipterans, possibly due to uniform rearing conditions or strain differences that buffer sex-specific effects. The lack of statistically significant seasonal variation among male flies in this study, except for G. palpalis palpalis , might be influenced by lower baseline infection levels, smaller sample sizes, or strain-host dynamics unfavoring high bacterial loads in non-reproductive individuals, though these factors require further investigation. The age-dependent Wolbachia load (Figure 1) parallels findings in Aedes, where older hosts exhibit stronger immune modulation (Zouache et al., 2009), suggesting a similar mechanism in tsetse flies. Wolbachia Strain Diversity in Nigerian Glossina Species: A Molecular and Phylogenetic Perspective Molecular analysis of the wsp ( Wolbachia surface protein) gene in Glossina species collected from Nigerian conservation areas revealed a complex but evolutionarily coherent profile of Wolbachia strain diversity. Multiple sequence alignment of the wsp gene demonstrated strong conservation—particularly in the core and flanking areas—across both newly sequenced samples and GenBank reference sequences (Figure 1). However, localized polymorphisms, including insertions and deletions, were also observed. These mutations reflect inter-strain divergence consistent with patterns previously reported across Wolbachia lineages (Baldo et al., 2006). The final alignment spanned 1,183 base pairs, slightly longer than the raw sequences due to computational gap insertions that account for evolutionary events such as indels. Pairwise similarity analysis showed up to 92% identity with GenBank sequences, suggesting that the Nigerian Wolbachia strains are closely related to globally circulating lineages, while still retaining unique genetic features likely shaped by local ecological conditions or host interactions. One of the key genomic features was the elevated GC content of 63%, which may support thermal adaptation hypotheses, as GC-rich DNA is proposed to resist denaturation in tropical climates (Gomes BLAST analysis corroborated the phylogenetic groupings. For instance, wsp5 (GenBank accession OR977570) showed 100% identity and full query coverage with sequence AJ585380.1 (Table 4), supporting the idea of trans-regional strain circulation. Similar findings were reported by Glowska et al. (2015), who demonstrated that Wolbachia strains can be shared across insect species and continents, likely due to horizontal transmission or co-dispersal via mobile hosts. Statistical validation of the tree structure using both the likelihood ratio test (p < 0.001) and Kishino-Hasegawa test (p = 0.02) confirmed that the phylogeny is robust and unlikely to be an artifact of random sampling. These results align well with earlier global studies. For example, Baldo et al. (2006), through the Multilocus Sequence Typing (MLST) framework, highlighted global conservation alongside local polymorphisms within Wolbachia genomes. Likewise, Zhou et al. (1998) confirmed that the wsp gene is a reliable marker for assessing strain-level diversity, especially where environmental and ecological pressures drive host-symbiont evolution. The discovery of identical matches like that between wsp5 and AJ585380.1 parallels findings by Glowska et al. (2015), who described broad Wolbachia distribution facilitated by both vertical and horizontal transmission routes. This supports the view that Wolbachia combines heritable stability with ecological adaptability, allowing it to colonize diverse hosts and habitats. On the other hand, this study diverges from patterns seen in East African and South American populations, where researchers have documented more highly divergent Wolbachia strains (2015), though experimental validation in Nigerian Wolbachia strains is required. This feature is especially relevant in the warm, humid climates of Northern Nigeria’s savanna and riparian zones. Phylogenetic reconstruction further clarified the evolutionary relationships among the nine Wolbachia strains. Most sequences clustered into strongly supported sub-clades (bootstrap values >90%; Tables 4.), indicating high reliability. The closest relationship was observed between wsp3 and wsp4 (92% identity), while wsp9, derived from Glossina morsitans submorsitans , appeared the most divergent. Moderate divergence patterns, such as the 91% identity between wsp5 and wsp8, could reflect host-specific interactions or geographic isolation, though additional data on host associations and spatial distribution are needed to elucidate these drivers. Relevance to Vector Competence, Control Strategies, and Symbiosis Although Wolbachia ’s role in trypanosome interference remains uncharacterized in Glossina , its age-dependent density (Figure 1) and maternal transmission suggest parallels to Aedes , where immune activation (e.g., Toll pathway upregulation) reduces viral transmission (Moreira et al., 2009). Two control strategies emerge: (1) Population suppression via cytoplasmic incompatibility (CI), where Wolbachia -infected males sterilize wild females (Bourtzis et al., 2014), and (2) Pathogen blocking, leveraging Wolbachia -mediated trypanosome inhibition—a mechanism requiring validation in tsetse flies. The high GC content (63%) and stability of Nigerian strains (e.g., wsp5 = 100% match to AJ585380.1) highlight their potential for field deployment. Wolbachia is known to influence the ability of insect vectors to acquire and transmit pathogens. In mosquitoes, for example, Wolbachia has been shown to activate host immune pathways such as Toll and Imd, which reduce susceptibility to viral infections (Moreira et al., 2009). Although the precise role of Wolbachia in modulating trypanosome development within tsetse flies is not yet fully understood, the patterns observed in this study—particularly the increasing Wolbachia load with fly age—suggest that older flies may exhibit different levels of vector competence. This aligns with findings in Drosophila and Aedes where Wolbachia densities increase with age, affecting both immune response and pathogen interference (Mouton et al., 2007; Zouache et al., 2009). Several factors can influence Wolbachia density in insects, including age, tissue type, host genotype, and viral infections (Kaur et al., 2020). Such age-related variation may be critical, considering that older female flies are more likely to contribute to transmission cycles. The observed strain diversity and stability of Wolbachia in Glossina species also provide a foundation for Wolbachia -based biological control approaches. One such method involves cytoplasmic incompatibility (CI), where the release of Wolbachia -infected male flies into wild populations results in non-viable offspring when they mate with uninfected females, leading to population suppression (Bourtzis et al., 2014). Another approach leverages Wolbachia ’s capacity to interfere with pathogen development, as demonstrated in Aedes aegypti , where Wolbachia infection blocks the transmission of arboviruses (Walker et al., 2011). The discovery of high GC content and genetic similarity to known strains—such as the 100% identity match of wsp5 to GenBank reference AJ585380.1—suggests that the Wolbachia strains identified in Nigerian tsetse flies are robust and may be suitable candidates for field deployment under local environmental conditions. Tsetse flies are obligate hosts of multiple endosymbionts, including Wigglesworthia , Sodalis , and Wolbachia , which together shape various aspects of host biology such as immunity, metabolism, and reproduction (Aksoy et al., 2008). The consistent maternal inheritance and high prevalence of Wolbachia observed in this study reinforce its role as a stable and possibly co-evolved symbiont. Furthermore, the strain-specific patterns revealed by the phylogenetic analysis—particularly the divergence of wsp9—suggest possible functional differences that could influence reproductive fitness, thermal tolerance, or competition with other symbionts (Baldo et al., 2006). The elevated GC content may also support more efficient gene expression and genomic resilience under high-temperature conditions common in West African savanna habitats (Gomes et al., 2015). The Wolbachia strains identified in this study are not only relevant from an evolutionary perspective but also hold substantial promise for application in vector control. Their prevalence, genetic stability, and ecological adaptability make them potential assets for integrated disease management strategies aimed at controlling human African trypanosomiasis. Conclusion This study provides critical insights into the ecological and seasonal dynamics of Glossina species and their Wolbachia endosymbionts across four ecologically diverse sites in northern Nigeria—Yankari Game Reserve, Kainji Lake National Park, Kagarko Grazing Reserve, and Ijah Gwari Forest. The entomological survey revealed Glossina tachinoides as the most prevalent species (55.78%), exhibiting high ecological plasticity, while Glossina morsitans submorsitans (29.36%) and Glossina palpalis palpalis (14.86%) showed more restricted distributions, influenced by habitat integrity and moisture availability, respectively. Seasonal variation in Wolbachia prevalence was significant only in Yankari, increasing from 12.6% to 23.5% during the wet season, with species-specific trends highlighting the role of humidity and host availability in enhancing infection rates (e.g., G. morsitans submorsitans from 39.8% to 75.4%). Sex-based differences underscored higher female prevalence, particularly in the wet season, likely due to maternal transmission efficiency. Molecular analysis of the wsp gene revealed a diverse yet coherent Wolbachia strain profile, with a high GC content (63%) suggesting potential thermal adaptation and pairwise similarities up to 92% with global lineages. Phylogenetic reconstruction identified stable clusters (e.g., wsp3 and wsp4 at 92% identity) and divergent strains (e.g., wsp9), supported by robust bootstrap values (>90%). BLAST analysis confirmed trans-regional strain circulation, with wsp5 showing 100% identity to GenBank sequence AJ585380.1. These findings underscore the ecological and genetic factors shaping tsetse-endosymbiont interactions, with implications for vector competence and disease transmission. The stability and diversity of Wolbachia strains, coupled with their age-dependent density, position them as promising candidates for integrated vector control strategies, including cytoplasmic incompatibility and pathogen blocking, pending further validation of trypanosome interference in tsetse flies. Recommendations Based on the study’s findings, the following recommendations are proposed to enhance tsetse control and mitigate African trypanosomiasis (AT) in northern Nigeria: Targeted Habitat Management: Prioritize conservation of woodland savannas and riparian zones, particularly in Yankari and Kainji, to sustain G. morsitans submorsitans and G. palpalis palpalis populations while minimizing habitat degradation in Kagarko and Ijah Gwari through regulated agricultural practices. Seasonal Control Interventions: Implement vector control measures, such as insecticide-treated targets or traps, during the dry season in Yankari, where Wolbachia prevalence is lower, to reduce tsetse populations before wet season peaks. Wolbachia -Based Strategies: Explore paratransgenic approaches using stable Wolbachia strains (e.g., wsp3 and wsp4) for cytoplasmic incompatibility or pathogen blocking. Field trials should assess strain efficacy under local climatic conditions, leveraging the high GC content for thermal resilience. Integrated Disease Management: Combine ecological monitoring with molecular surveillance of Wolbachia strains to adapt control strategies to seasonal and species-specific dynamics, enhancing collaboration between wildlife conservation and public health sectors. Further Research: Conduct longitudinal studies to correlate Wolbachia strain diversity with environmental stressors (e.g., temperature, humidity) and validate trypanosome interference mechanisms. Additional genetic markers (e.g., MLST) and functional assays are needed to confirm strain-specific adaptations, such as the potential uniqueness of wsp9. Limitations Several limitations constrain the interpretation and generalizability of this study: The analysis was confined to four sites in northern Nigeria, limiting its representativeness across the country’s diverse ecological zones, such as southern rainforest areas where tsetse dynamics may differ. The study relied on variable sample sizes across sites and seasons, with potential underrepresentation of males, which may have influenced the detection of seasonal Wolbachia variation in some species. The role of Wolbachia in trypanosome interference remains untested in tsetse flies, relying on inferences from other systems (e.g., Aedes ). Without experimental evidence, control strategy proposals are preliminary. The phylogenetic analysis was based solely on the wsp gene, which may not fully capture Wolbachia strain diversity. Additional markers or whole-genome sequencing could refine strain relationships and evolutionary histories. Declarations Acknowledgments We gratefully acknowledge the support of the park authorities in Yankari Game Reserve, Kainji Lake National Park, Kagarko Grazing Reserve, and Ijah Gwari Forest for facilitating field data collection. We thank the technical staff at Molecular Biology Unit of Nigerian Institute for Trypanosomiasis Research for their assistance with molecular analyses and phylogenetic reconstructions. Special gratitude is extended to Dr S. Shaida for valuable insights during manuscript preparation. This work benefited from discussions with Prof Muhammad Mamman, and Prof Isa Jatau whose expertise in vector ecology enriched the study. Funding No external funding was received for this research. This study was conducted as part of the author’s PhD thesis at Ahmadu Bello University Zaria. Conflict of Interest The author declares no conflicts of interest. There are no financial or personal relationships that could inappropriately influence or bias the content of this manuscript. Authors' Contributions Attahir Abubakar: Conceptualization, methodology design, supervision, and manuscript drafting. Ramatu Ado Abdullahi: Data collection, literature review, and manuscript editing. Usman Baba Musa: Statistical analysis, data interpretation, and visualization. Rukayya Garba Anchau: Fieldwork coordination, data validation, and critical revisions. Jabiru Garba: Software support, technical validation, and contributed to data analysis. Zainab Tamba: Assisted in literature review, formatting, and reference management. Saminu Sabiu: Contributed to methodology refinement, proofreading, and final approval of the manuscript. All authors read and approved the final manuscript. Data Availability Statement The dataset supporting the findings of this study has been deposited in the Dryad Digital Repository and is publicly available under the DOI: DOI 10.5281/zenodo.16875929 GenBank has been assigned accession numbers, BankIt2776358 WSP 9_ WSP 1F _H07_22 OR977569 and BankIt2776358 WSP5_WSP81F_D09_12 OR977570 References Abubakar, A., Ibrahim, M. & Ojo, O. Ecological characterization of Nigerian conservation areas. J. Afr. Ecol. 54 (3), 112–125 (2016). Adam, Y. et al. Population dynamics of Glossina tachinoides in Sudan savanna zones. Med. Vet. Entomol. 29 (2), 156–167. https://doi.org/10.1111/mve.12100 (2015). Adamu, U. O. et al. Control of African trypanosomiasis in Nigeria: Time to strengthen integrated approaches. Int. J. Anim. Veterinary Adv. 3 (3), 138–143 (2021). https://maxwellsci.com/print/ijava/v3-138-143.pdf Aksoy, S., Weiss, B. & Attardo, G. Paratransgenesis applied for control of tsetse transmitted sleeping sickness. Adv. Exp. Med. 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Kugu","email":"","orcid":"","institution":"Nigerian Institute for Trypanosomiasis Research","correspondingAuthor":false,"prefix":"","firstName":"Basheer","middleName":"A.","lastName":"Kugu","suffix":""},{"id":512506355,"identity":"1497e22e-a44d-47d8-9a41-0d629e331ad7","order_by":7,"name":"Saminu Sabiu","email":"","orcid":"","institution":"Nigerian Institute for Trypanosomiasis Research","correspondingAuthor":false,"prefix":"","firstName":"Saminu","middleName":"","lastName":"Sabiu","suffix":""}],"badges":[],"createdAt":"2025-08-06 14:08:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7310521/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7310521/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91020932,"identity":"d2da4c1b-3268-4ac4-a389-e9f8342bf8d5","added_by":"auto","created_at":"2025-09-10 18:33:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":258814,"visible":true,"origin":"","legend":"\u003cp\u003eUnnumbered image in the \u003cstrong\u003eMaterials and Methods \u003c/strong\u003esection.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7310521/v1/32427cdd1f35bc001d2d86ef.png"},{"id":91020928,"identity":"41665861-f978-4625-b294-1d23577d6a31","added_by":"auto","created_at":"2025-09-10 18:33:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":104287,"visible":true,"origin":"","legend":"\u003cp\u003eAge-Dependent Accumulation of \u003cem\u003eWolbachia\u003c/em\u003ein \u003cem\u003eGlossina\u003c/em\u003e Flies with 95% Confidence Interval r = 0.912, p \u0026lt; 0.001).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7310521/v1/2c5a3eeb3c56faaa07200046.png"},{"id":91020929,"identity":"3b595ecb-786c-4ce8-b066-6346ee55faf9","added_by":"auto","created_at":"2025-09-10 18:33:38","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":247585,"visible":true,"origin":"","legend":"\u003cp\u003eMultiple sequence alignment of wsp gene fragments. Conserved regions (blue) and polymorphic sites (red) are highlighted. Gaps (dashes) reflect indels. The high GC content (63%) is denoted by bolded residues\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7310521/v1/0939f631f6a4fa4c0bc60c77.jpeg"},{"id":91021543,"identity":"43fcec27-d644-4721-8460-145494fc9704","added_by":"auto","created_at":"2025-09-10 18:41:38","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":143913,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree of \u003cem\u003eWolbachia\u003c/em\u003e strains inferred from \u003cem\u003ewsp\u003c/em\u003e sequences. Supergroups A/B are annotated. Node labels show bootstrap values (≥90% = strong support, 70–89% = moderate, \u0026lt;70% = weak). Scale bar indicates substitutions per site\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7310521/v1/c3cb7edf2c2c9ec0b5309283.jpeg"},{"id":91021735,"identity":"93f2cd96-b665-4068-b417-f10471c73bd1","added_by":"auto","created_at":"2025-09-10 18:49:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2198639,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7310521/v1/011282dd-639a-4914-bbbe-6ff4b427ca35.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Molecular Detection and Phylogenetic Characterization of Wolbachia Strains in Glossina Species from Nigerian Conservation Areas","fulltext":[{"header":"Introduction","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e\u003ch2\u003eTsetse Flies and Trypanosomiasis: Epidemiological Importance in Nigeria\u003c/h2\u003e\u003cp\u003eTsetse flies (\u003cem\u003eGlossina\u003c/em\u003e spp.) are the primary vectors of African trypanosomiasis, a neglected tropical disease affecting humans (Human African Trypanosomiasis, HAT) and livestock (Animal African Trypanosomiasis, AAT) (WHO, 2020). In Nigeria, tsetse infestations cover about 75% of the landmass, severely impacting agricultural productivity and public health (Shaida et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Despite ongoing efforts, the country faces persistent challenges: recent meta-analyses estimate an overall prevalence of 27.3% for AAT and 3.6% for HAT across surveyed populations (Odebunmi et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), with regional disparities and diagnostic limitations complicating surveillance and intervention strategies (Another Author, Year). Nigeria\u0026rsquo;s trypanosomiasis control programs are further hindered by fragmented local governance, limited funding, and inconsistent implementation across conservation zones (Adamu et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). These constraints underscore the need for innovative, locally adaptable vector control approaches.\u003c/p\u003e\u003cp\u003eThe disease causes annual economic losses exceeding US\u003cspan\u003e$\u003c/span\u003e4.5\u0026nbsp;billion due to reduced livestock yields and restricted land use (Mwiinde \u003cem\u003eet al.\u003c/em\u003e, 2017). Three major species\u0026mdash;\u003cem\u003eG. tachinoides\u003c/em\u003e, \u003cem\u003eG. morsitans submorsitans\u003c/em\u003e, and \u003cem\u003eG. palpalis palpalis\u003c/em\u003e\u0026mdash;dominate Nigerian ecosystems, each with distinct ecological preferences and vector capacities (Isaac et al., 2016). Despite control efforts such as insecticide-treated traps and sterile insect techniques, trypanosomiasis persists due to drug resistance, lack of vaccines, and environmental reinvasion (Aksoy et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). \u003cem\u003eWolbachia pipientis\u003c/em\u003e, an obligate intracellular alphaproteobacterium, is known for manipulating arthropod reproduction through mechanisms like cytoplasmic incompatibility, feminization, and male-killing (Werren et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). It also reduces pathogen transmission by competing for host resources or enhancing immune responses (Z\u0026eacute;l\u0026eacute; et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Successes in controlling \u003cem\u003eAedes aegypti\u003c/em\u003e\u0026mdash;notably suppressing dengue and Zika viruses\u0026mdash;have sparked interest in \u003cem\u003eWolbachia\u003c/em\u003e\u0026rsquo;s potential for tsetse control (Yen \u0026amp; Failloux, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, its prevalence, strain diversity, and ecological dynamics in \u003cem\u003eGlossina\u003c/em\u003e species, especially in West Africa, remain largely uncharacterized. Past research has focused on other symbionts like \u003cem\u003eSodalis\u003c/em\u003e, overlooking \u003cem\u003eWolbachia\u003c/em\u003e\u0026rsquo;s potential role in vector control (Aksoy et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Moreover, the influence of ecological factors such as temperature and humidity on \u003cem\u003eWolbachia\u003c/em\u003e dynamics in tsetse flies remains poorly understood (Balmand et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Given Nigeria\u0026rsquo;s diverse tsetse habitats\u0026mdash;from savannas to riverine forests\u0026mdash;mapping \u003cem\u003eWolbachia\u003c/em\u003e strain distribution is critical for targeted interventions.\u003c/p\u003e\u003cp\u003eThis study aims to address gaps in \u003cem\u003eWolbachia\u003c/em\u003e surveillance among \u003cem\u003eGlossina\u003c/em\u003e spp. in Nigeria by: (i) detecting \u003cem\u003eWolbachia\u003c/em\u003e infections across four ecological zones\u003c/p\u003e\u003cp\u003e(i) detecting \u003cem\u003eWolbachia\u003c/em\u003e infections across four ecological zones\u003c/p\u003e\n\u003cp\u003e(ii) characterizing strain diversity using \u003cem\u003ewsp\u003c/em\u003e sequencing\u003c/p\u003e\n\u003cp\u003e(iii) evaluating infection patterns by season, species, sex, and age.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Area\u003c/strong\u003e\u003cp\u003eThe study examined four distinct conservation areas in Nigeria, focusing on different savanna and forest ecosystems. The Yankari Game Reserve in Bauchi State, Nigeria, features Sudan savanna vegetation and riparian forests. Kainji Lake National Park in Niger State, Nigeria, features a Guinea savanna ecosystem with gallery forests. Kagarko Forest in Kaduna State, Nigeria, has a derived savanna habitat with dense riverine thickets. Ijah Gwari Forest in Niger State, Nigeria, has a rainforest-savanna mosaic (Abubakar et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Isaac \u003cem\u003eet al.\u003c/em\u003e, 2016).\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthical Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was not required as the study involved insect sampling.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMap of Tsetse Fly Trapping Sites in the Study Areas.\u003c/em\u003e The central map highlights Niger, Kaduna, and Bauchi States, with the targeted LGAs marked in brown: Ijah Gwari in Suleja LGA and Kainji Lake National Park in Borgu LGA (Niger State); Yankari Game Reserve in Alkaleri LGA (Bauchi State); and Kubacha/Maganda Forest in Kagarko LGA (Kaduna State)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample Size Justification\u003c/strong\u003e\u003cbr\u003e Sample sizes were determined based on prior estimates of tsetse population densities in Nigerian conservation areas (Shaida \u003cem\u003eet al.,\u003c/em\u003e 2018), ensuring \u0026ge;80% statistical power to detect a minimum 10% difference in \u003cem\u003eWolbachia\u003c/em\u003e prevalence between seasons at a significance level of \u0026alpha; = 0.05.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample Collection\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e We collected samples monthly from April 2017 to July 2019, encompassing both dry and wet seasons\u0026nbsp;a total of\u0026nbsp;7,632\u0026nbsp;flies were collected using Biconical traps, as described by Challier and Laveissi\u0026egrave;re (1973),\u0026nbsp;traps\u0026nbsp;were baited with acetone and cow urine and deployed at 50-meter intervals along transects in shaded microhabitats. Species identification was conducted using morphological keys developed by Potts (FAO, 2018), allowing for discrimination among \u003cem\u003eG. m. submorsitans\u003c/em\u003e, \u003cem\u003eG. p. palpalis\u003c/em\u003e, and \u003cem\u003eG. tachinoides\u003c/em\u003e. Flies were dissected under sterile conditions, and the midgut, salivary glands, and reproductive tissues were preserved in 70% ethanol for subsequent DNA extraction\u0026nbsp;(Weber\u003cem\u003e\u0026nbsp;et al.,\u003c/em\u003e 2019).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTissue Selection and DNA Extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eWolbachia\u003c/em\u003e was targeted in reproductive tissues, midguts, and salivary glands due to their established or suspected roles in vertical transmission and systemic colonization in tsetse (Balmand \u003cem\u003eet al.,\u003c/em\u003e 2013).\u0026nbsp;Genomic DNA was extracted using the AccuPrep Genomic DNA Extraction Kit (Bioneer, Korea), based on manufacturer\u0026apos;s instructions.\u0026nbsp;Approximately 10 mg of reproductive tissues,\u0026nbsp;midgut or salivary gland tissue was lysed in 200 \u0026micro;L G-Buffer with 20 \u0026micro;L Proteinase K at 56\u0026deg;C for one hour. The lysate was combined with 200 \u0026micro;L of Binding Buffer and transferred to AccuPrep DNA extraction columns. After two successive washes with 500 \u0026micro;L of W-Buffer, DNA was eluted in 50 \u0026micro;L of Elution Buffer (10 mM Tris-HCl, pH 8.5). DNA concentration and purity were assessed using a NanoDrop spectrophotometer (Thermo Fisher Scientific), and samples with A260/A280 ratios below 1.7 were re-purified\u0026nbsp;(Bioneer, 2018).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePCR Amplification and Controls\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAccuPower\u003c/em\u003e PreMix PCR master mix\u0026nbsp;from Bioneer\u0026nbsp;was used based on manufactures instructions, two\u0026nbsp;gene targets were used to detect and type \u003cem\u003eWolbachia\u003c/em\u003e strains: the \u003cem\u003ewsp\u003c/em\u003e gene (\u003cem\u003eWolbachia\u003c/em\u003e surface protein), a primary marker for strain typing, and the 16S rRNA gene as a confirmatory marker. The primer sets used were 81F/691R for \u003cem\u003ewsp\u003c/em\u003e. Primer pairs included wsp-specific 81F (5\u0026prime;-TGGTCCAATAAGTGATGAAGAAAC-3\u0026prime;) and 691R (5\u0026prime;-AAAAATTAAACGCTACTCCA-3\u0026prime;) (Zhou \u003cem\u003eet al.,\u003c/em\u003e 1998) and along with 16S rRNA-targeting\u0026nbsp;wsp\u0026nbsp;F (5\u0026prime;-CATACCTATTCGAAGGGATAG-3\u0026prime;) and\u0026nbsp;wsp\u0026nbsp;R (5\u0026prime;-AGCTTCGAGTGAAACCAATTC-3\u0026prime;). PCR cycling conditions included an initial denaturation at 95\u0026deg;C for 5 minutes, followed by 35 cycles of denaturation at 95\u0026deg;C for 30 seconds, annealing at 55\u0026deg;C for 30 seconds, and extension at 72\u0026deg;C for 1 minute, with a final elongation step at 72\u0026deg;C for 10 minutes. Positive controls included DNA from \u003cem\u003eWolbachia\u003c/em\u003e-infected \u003cem\u003eDrosophila\u003c/em\u003e, and nuclease-free water was used as the negative controll (Bioneer, 2018, Weber\u003cem\u003e\u0026nbsp;et al.,\u003c/em\u003e 2019).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNegative Controls\u003c/strong\u003e\u003cbr\u003eEach PCR batch included a no-template control (nuclease-free water) and a positive control (\u003cem\u003eWolbachia\u003c/em\u003e-infected \u003cem\u003eDrosophila\u003c/em\u003e DNA) to monitor for contamination and ensure amplification efficiency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGel Electrophoresis and Sequencing and Phylogenetic Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmplified PCR products were resolved on 1.5% agarose gels stained with ethidium bromide and visualized under UV illumination. Positive amplicons were purified using the QIAquick PCR Purification Kit (Qiagen) and sent to Macrogen Inc. (South Korea) for bidirectional Sanger sequencing\u0026nbsp;(Sikkema‐Raddatz, 2013).\u0026nbsp;\u0026nbsp;Phylogenetic Analysis Sequence alignment and phylogenetic reconstruction were performed using MEGA-X software (Kumar \u003cem\u003eet al.,\u003c/em\u003e 2018). Alignments were generated using the MUSCLE algorithm (Edgar, 2004) with default parameters. Phylogenetic trees were constructed using the Maximum Likelihood method under the GTR+G+I model with 1,000 bootstrap replicates. Reference sequences included known \u003cem\u003eWolbachia\u003c/em\u003e strains from \u003cem\u003eGlossina\u003c/em\u003e spp. (GenBank accessions: KP715092, JX273258) and outgroup sequences from \u003cem\u003eRickettsia\u003c/em\u003e spp.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSeasonal and Species-Specific \u003cem\u003eWolbachia\u003c/em\u003e Prevalence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 7,632 \u003cem\u003eGlossina\u003c/em\u003e flies were screened across four Nigerian conservation areas. Overall \u003cem\u003eWolbachia\u003c/em\u003e infection prevalence showed notable variation by site, season, species, and sex\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSite-Level Patterns\u003c/strong\u003e:\u003cbr\u003eSignificant seasonal variation was observed only in Yankari Game Reserve, where infection prevalence rose from 12.6% in the dry season to 23.5% in the wet season (\u003cem\u003e\u0026chi;\u0026sup2;\u003c/em\u003e = 13.62, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). No statistically significant seasonal differences were found in Kainji Lake National Park, Ijah Gwari Forest, or Kagarko Forest, although marginal increases in prevalence were recorded in all three sites during the wet season (Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1. \u003cem\u003eWolbachia\u003c/em\u003e Infection Prevalence by Season and Site\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"636\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy Site\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeason\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Flies Screened\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eWolbachia\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-Positive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u0026sup2; Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 51px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eYankari Game Reserve\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003eDry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e12.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 140px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003eWet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e23.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e13.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003ep \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 140px;\"\u003e\n \u003cp\u003eSignificant seasonal difference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eKainji Lake National Park\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003eDry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e251\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e13.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 140px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003eWet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e16.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003ep = 0.354\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 140px;\"\u003e\n \u003cp\u003eNot significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eIjah Gwari Forest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003eDry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e29.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 140px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003eWet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e26.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003ep = 0.553\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 140px;\"\u003e\n \u003cp\u003eNot significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003eKagarko Forest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003eDry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e28.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 140px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 55px;\"\u003e\n \u003cp\u003eWet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 68px;\"\u003e\n \u003cp\u003e149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 78px;\"\u003e\n \u003cp\u003e26.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 51px;\"\u003e\n \u003cp\u003ep = 0.707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 140px;\"\u003e\n \u003cp\u003eNot significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eSpecies-Level Seasonal Trends\u003c/strong\u003e\u003cbr\u003eAcross all three species, \u003cem\u003eWolbachia\u003c/em\u003e prevalence was significantly higher in the wet season. The most pronounced shift occurred in \u003cem\u003eG. morsitans submorsitans\u003c/em\u003e (39.8% to 75.4%, \u003cem\u003e\u0026chi;\u0026sup2;\u003c/em\u003e = 28.75, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), followed by \u003cem\u003eG. tachinoides\u003c/em\u003e (47.8% to 69.7%, \u003cem\u003e\u0026chi;\u0026sup2;\u003c/em\u003e = 10.03, \u003cem\u003ep\u003c/em\u003e = 0.002), and \u003cem\u003eG. palpalis palpalis\u003c/em\u003e (24.6% to 55.7%, \u003cem\u003e\u0026chi;\u0026sup2;\u003c/em\u003e = 33.27, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001) (Table 2).\u003c/p\u003e\n\u003cp\u003eTable 2. \u003cem\u003eWolbachia\u003c/em\u003e Infection Prevalence by specie and Season\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeason\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Screened\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWolbachia-Positive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u0026sup2; Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cem\u003eG\u003c/em\u003e\u003cem\u003elossina\u003c/em\u003e\u003cem\u003e\u0026nbsp;morsitans subm.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003eDry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003e39.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003eWet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003e75.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e28.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003ep \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eSignificant difference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cem\u003eG\u003c/em\u003e\u003cem\u003elossina\u003c/em\u003e\u003cem\u003e\u0026nbsp;tachinoides\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003eDry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003e47.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003eWet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e122\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003e69.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e10.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003ep = 0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eSignificant difference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cem\u003eG\u003c/em\u003e\u003cem\u003elossina\u003c/em\u003e\u003cem\u003e\u0026nbsp;palpalis palpalis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003eDry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003e24.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 114px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003eWet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e176\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 67px;\"\u003e\n \u003cp\u003e55.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003e33.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 62px;\"\u003e\n \u003cp\u003ep \u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eSignificant difference\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eInteraction of Sex, and Season\u003c/strong\u003e\u003cbr\u003eFemales consistently exhibited higher \u003cem\u003eWolbachia\u003c/em\u003e infection rates than males. This disparity was most evident in the wet season, with female prevalence peaking at 83.6% in \u003cem\u003eG. morsitans submorsitans\u003c/em\u003e, 81.5% in \u003cem\u003eG. tachinoides\u003c/em\u003e, and 50.5% in \u003cem\u003eG. palpalis palpalis\u003c/em\u003e. Statistically significant seasonal variation among males was detected only in \u003cem\u003eG. palpalis palpalis\u003c/em\u003e (10.8% to 39.4%, \u003cem\u003e\u0026chi;\u0026sup2;\u003c/em\u003e = 8.30, \u003cem\u003ep\u003c/em\u003e = 0.004), while male infection rates in the other species remained relatively stable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003cstrong\u003e. \u003cem\u003eWolbachia\u003c/em\u003e Infection Prevalence by Sex and Season\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"548\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeason\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Screened\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eWolbachia\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-Positive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u0026sup2; Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003eDry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003e27.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003eWet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003e25.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003ep = 0.497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003eNot significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003eDry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003e42.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003eWet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 69px;\"\u003e\n \u003cp\u003e48.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003ep = 0.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 88px;\"\u003e\n \u003cp\u003eNot significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative Relationship Between \u003cem\u003eWolbachia\u003c/em\u003e Load and Tsetse Fly Age\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure This scatter plot illustrates the quantitative relationship between the age of \u003cem\u003eGlossina\u003c/em\u003e flies (x-axis, in days) and their corresponding \u003cem\u003eWolbachia\u003c/em\u003e load (y-axis, measured in arbitrary units). Each red circle represents an individual fly observation. The fitted black regression line indicates a clear positive linear trend, while the surrounding grey band depicts the 95% confidence interval, reflecting the precision of the model\u0026apos;s prediction.\u003c/p\u003e\n\u003cp\u003eThe data reveal a strong and consistent increase in \u003cem\u003eWolbachia\u003c/em\u003e abundance with fly age. Younger flies (\u0026le;5 days) exhibited relatively low bacterial loads, while older individuals (\u0026ge;30 days) reached the upper limits of the observed range, with values approaching 30 units. The confidence interval narrows at mid-range ages (10\u0026ndash;20 days), where data density is highest, and widens at the extremes, suggesting slightly greater uncertainty in model predictions for very young or very old flies. Statistical analysis confirms a strong positive correlation between fly age and \u003cem\u003eWolbachia\u003c/em\u003e load (Pearson\u0026rsquo;s r = 0.912, p \u0026lt; 0.001). This supports the hypothesis of time-dependent bacterial accumulation, likely due to ongoing replication of \u003cem\u003eWolbachia\u003c/em\u003e in host tissues over the fly\u0026rsquo;s lifespan.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSequence Identity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultiple Sequence Alignment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe multiple sequence alignment (MSA) displays wsp gene fragments from Wolbachia strains isolated from \u003cem\u003eGlossina\u003c/em\u003e species collected across northern Nigeria (Yankari Game Reserve, Kainji Lake National Park, Kagarko Forest, and Ijah Gwari Forest). Conserved regions, where sequences are identical or highly similar across isolates, are highlighted in blue, indicating evolutionary stability and potential functional importance. Polymorphic sites, representing single nucleotide polymorphisms or amino acid substitutions, are marked in red, reflecting genetic diversity among \u003cem\u003eWolbachia\u003c/em\u003e strains. Gaps, denoted by dashes, indicate insertions or deletions (indels) that optimize sequence alignment, suggesting structural variations in the wsp gene. The high GC content (63%) is emphasized by bolded residues (G and C), highlighting a nucleotide composition bias that may reflect adaptation to the tsetse fly host environment. The alignment was generated using MUSCLE and visualized with MEGA. Scale bar and sequence identifiers are included to indicate alignment length and sample origins, respectively.\u003c/p\u003e\n\u003cp\u003ePairwise similarity analysis indicates a 92% sequence similarity between the aligned study sequences and their closest GenBank matches. This high degree of similarity strongly suggests that the \u003cem\u003eWolbachia\u003c/em\u003e strains identified in the Nigerian \u003cem\u003eGlossina\u003c/em\u003e species are evolutionarily close to previously described strains and are likely to belong to the same or closely related \u003cem\u003eWolbachia\u003c/em\u003e lineages. Two of the sequences generated in this study have been successfully submitted to the NCBI GenBank database. The assigned accession numbers are:\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eBankIt2776358 WSP 9_WSP 1F_H07_22\u003c/strong\u003e: Accession \u003cstrong\u003eOR977569\u003c/strong\u003e\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eBankIt2776358 WSP5_WSP81F_D09_12\u003c/strong\u003e: Accession \u003cstrong\u003eOR977570\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eIdentity and Similarity between WSP 5 (\u003cem\u003eWolbachia Glossina palpalis palpalis\u003c/em\u003e) Sequence (OR977570) and Top 10 NCBI BLAST Hits\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhylogenetic Tree\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePhylogenetic analysis revealed Nigerian \u003cem\u003eWolbachia\u003c/em\u003e strains (e.g., \u003cem\u003ewsp3\u003c/em\u003e/\u003cem\u003ewsp4\u003c/em\u003e, 92% identity) cluster with global supergroup A/B lineages (Figure 4), yet \u003cem\u003ewsp9\u003c/em\u003e\u0026rsquo;s divergence (92% bootstrap) suggests a unique West African variant. This mirrors findings in \u003cem\u003eDrosophila\u003c/em\u003e (Baldo \u003cem\u003eet al.,\u003c/em\u003e 2006), where localized adaptation drove strain diversification. The branching order of the tree shows that \u003cem\u003ewsp\u003c/em\u003e 8 is the most closely related to the other nine strains, followed by \u003cem\u003ewsp\u003c/em\u003e 11, \u003cem\u003ewsp\u003c/em\u003e 4, \u003cem\u003ewsp\u003c/em\u003e, 3, \u003cem\u003ewsp\u003c/em\u003e, 5, \u003cem\u003ewsp\u003c/em\u003e, 7, and \u003cem\u003ewsp12\u003c/em\u003e. The percentage of closeness between each strain is also shown on the tree. For example, \u003cem\u003ewsp 3\u003c/em\u003e is 98% close to \u003cem\u003ewsp\u003c/em\u003e 4, 97% close to \u003cem\u003ewsp 7\u003c/em\u003e, 96% close to \u003cem\u003ewsp\u003c/em\u003e 5, and 95% close to \u003cem\u003ewsp\u0026nbsp;\u003c/em\u003e9 (Table 4). \u003cem\u003eWolbachia\u003c/em\u003e surface protein 9 in \u003cem\u003eGlossina morsitans submorsitans\u003c/em\u003e is the most distantly related \u003cem\u003eWolbachia\u003c/em\u003e strain on the tree, with a branching order of 92%. This means that it shares a common ancestor with all other \u003cem\u003eWolbachia\u003c/em\u003e strains on the tree, but that common ancestor is more distant in time than any other common ancestor shared by any other four \u003cem\u003eWolbachia\u003c/em\u003e strains on the tree. There is a 92% probability that these \u003cem\u003eWolbachia\u003c/em\u003e sequences would group if the phylogenetic analysis was conducted again on randomly sampled datasets from the initial alignment. Nodes with bootstrap values \u0026ge;90% (Figure 3) indicate strong support for the inferred clades, whereas values below 70% reflect weak or unresolved phylogenetic relationships (Felsenstein, 1985).\u003c/p\u003e\n\u003cp id=\"_Toc194930762\"\u003eTable 4: \u0026nbsp; \u0026nbsp;The relationship, branching order, percentage of closeness, and most recent common ancestor for the five strains of \u003cem\u003eWolbachia\u003c/em\u003e among the \u003cem\u003eGlossina\u003c/em\u003e Species in the study areas.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eStrain\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eRelationship\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBranching Order\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e% Closeness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMRCA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eClosest to wsp4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDirect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eClosest to wsp3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDirect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLess related to wsp3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eShort branch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLess related to wsp3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLonger branch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e91%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLess related to wsp3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eShort branch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e91%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLess related to wsp3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLonger branch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e92%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLeast related to wsp3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eVery long branch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLeast related to wsp3/4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eVery long branch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e91%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLeast related overall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eVery long branches\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ewsp12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eStrains were inferred from wsp gene sequences, with branch lengths reflecting evolutionary divergence (see Figure 3)\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003ePrevalence of Glossina in the Studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn entomological survey conducted across four ecologically distinct sites in northern Nigeria—Yankari Game Reserve, Kainji Lake National Park, Kagarko Grazing Reserve, and Ijah Gwari Forest—documented the presence of three key tsetse fly species of medical and veterinary importance: \u003cem\u003eGlossina morsitans submorsitans\u003c/em\u003e, \u003cem\u003eGlossina palpalis palpalis\u003c/em\u003e, and \u003cem\u003eGlossina tachinoides\u003c/em\u003e. The spatial distribution and relative abundance of these species varied considerably, shaped by a combination of ecological conditions and anthropogenic influences.\u003c/p\u003e\n\u003cp\u003eAmong the species, Glossina tachinoides emerged as the most dominant, comprising 55.78% of all captures (Table 1). Its widespread presence across multiple habitats, including woodland savannas and ecotones with human activity, reflects its high ecological plasticity. This finding is consistent with earlier observations by Odeniran \u003cem\u003eet al.\u003c/em\u003e (2019) and Majekodunmi \u003cem\u003eet al.\u003c/em\u003e (2013), who reported similar prevalence of \u003cem\u003eG. tachinoides\u003c/em\u003e in Nigeria’s Middle Belt and savanna-woodland transition zones. However, our data diverge from those of Adam \u003cem\u003eet al.\u003c/em\u003e (2015), who noted lower densities of this species in Sudan savanna areas, suggesting that even adaptable species may experience range contraction under conditions of prolonged drought and severe habitat degradation. In contrast, \u003cem\u003eG. morsitans submorsitans\u003c/em\u003e displayed a more restricted distribution, representing 29.36% of total captures and being completely absent from two of the four study sites. This species showed a clear preference for undisturbed woodland savannas, particularly in Yankari and Kainji, where natural wildlife populations remain relatively intact. These findings align with those of Leak \u003cem\u003eet al.\u003c/em\u003e (1991) and Karshima \u003cem\u003eet al.\u0026nbsp;\u003c/em\u003e(2016), who highlighted the species' reliance on intact ecosystems for survival. The results also support the hypothesis proposed by Adam \u003cem\u003eet al.\u003c/em\u003e (2015) that \u003cem\u003eG. morsitans submorsitans\u003c/em\u003e populations are retreating into microclimatically favorable protected zones in response to increasing environmental stressors such as aridity and habitat fragmentation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSeasonal Variation in \u003cem\u003eWolbachia\u003c/em\u003e Prevalence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study found that \u003cem\u003eWolbachia\u003c/em\u003e infection varied seasonally only in Yankari Game Reserve, where prevalence rose significantly from 12.6% in the dry season to 23.5% in the wet season (χ² = 13.62, p \u0026lt; 0.001; Table 2). This aligns with studies by Werren \u003cem\u003eet al.\u003c/em\u003e (2008), Mouton \u003cem\u003eet al.\u003c/em\u003e (2007), and Alam \u003cem\u003eet al.\u003c/em\u003e (2011), which link higher humidity and temperature to increased \u003cem\u003eWolbachia\u003c/em\u003e transmission and density in arthropods. In tsetse flies, such conditions may boost reproduction and facilitate vertical transmission. In contrast, no significant seasonal changes were detected in Kainji, Ijah Gwari, or Kagarko (p \u0026gt; 0.05), though minor increases were observed. The absence of seasonal \u003cem\u003eWolbachia\u003c/em\u003e variation in Kainji and Kagarko may reflect microclimatic stability from dense canopy cover (Weber \u003cem\u003eet al.,\u003c/em\u003e 2019), buffering humidity fluctuations critical for bacterial replication. This divergence from studies like Baldo \u003cem\u003eet al.\u003c/em\u003e (2007) and Kittayapong \u003cem\u003eet al.\u003c/em\u003e (2000) may reflect microclimatic buffering, habitat stability, or anthropogenic disturbance that dampens seasonal effects. For instance, agricultural expansion in Kagarko and forest cover in Kainji may limit fluctuations in host or symbiont dynamics. Strain-specific genetic differences could also explain stable prevalence across sites, as some \u003cem\u003eWolbachia\u003c/em\u003e strains are less influenced by environmental changes (Duron \u003cem\u003eet al.,\u003c/em\u003e 2008).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSpecies-Level Seasonal Trends in \u003cem\u003eWolbachia\u003c/em\u003e Prevalence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll three \u003cem\u003eGlossina\u003c/em\u003e species showed significantly higher \u003cem\u003eWolbachia\u003c/em\u003e prevalence during the wet season, though the extent varied. \u003cem\u003eGlossina morsitans submorsitans\u003c/em\u003e increased from 39.8% to 75.4% (χ² = 28.75, p \u0026lt; 0.001; Table\u0026nbsp;3), likely due to favorable wet season conditions—such as higher humidity, vegetation, and host availability—that support fly survival and vertical transmission (Werren \u003cem\u003eet al.,\u003c/em\u003e 2008). \u003cem\u003eGlossina tachinoides\u003c/em\u003e rose from 47.8% to 69.7% (χ² = 10.03, p = 0.002; Table\u0026nbsp;2), suggesting that even ecologically flexible species benefit from these seasonal conditions. \u003cem\u003eGlossina palpalis palpalis\u003c/em\u003e, although with the lowest initial prevalence, showed the largest relative increase\u0026nbsp;from 24.6% to 55.7% (χ² = 33.27, p \u0026lt; 0.001; Table 2)\u0026nbsp;likely reflecting its strong dependence on riparian habitats, which expand during the rainy season. These findings align with studies in \u003cem\u003eAedes\u003c/em\u003e and \u003cem\u003eDrosophila\u003c/em\u003e, where wet season conditions enhanced \u003cem\u003eWolbachia\u003c/em\u003e density and transmission (Mouton \u003cem\u003eet al.,\u003c/em\u003e 2007; Zouache \u003cem\u003eet al.,\u0026nbsp;\u003c/em\u003e2009). Differences across species may relate to ecological niches, reproductive patterns, or strain-host compatibility. Contrasting studies reporting stable \u003cem\u003eWolbachia\u003c/em\u003e prevalence suggest that genetic resistance, consistent microclimates, or unresponsive strains may buffer seasonal effects (Baldo \u003cem\u003eet al.,\u003c/em\u003e 2007; Duron \u003cem\u003eet al.,\u003c/em\u003e 2008). However, the pronounced responsiveness here likely reflects the strong linkage between tsetse ecology and Northern Nigerian rainfall patterns, which govern both host availability and habitat suitability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSex- and Season-Based Variation in \u003cem\u003eWolbachia\u003c/em\u003e Prevalence\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalysis of \u003cem\u003eWolbachia\u003c/em\u003e infection patterns disaggregated by sex and season revealed notable biological differences among \u003cem\u003eGlossina\u003c/em\u003e species. Across all species, females consistently exhibited higher \u003cem\u003eWolbachia\u003c/em\u003e prevalence than males, a trend that was most pronounced during the wet season. This sex-based disparity likely reflects differences in reproductive physiology and symbiont transmission efficiency, given that \u003cem\u003eWolbachia\u003c/em\u003e is maternally inherited. For example, female \u003cem\u003eG. morsitans submorsitans\u003c/em\u003e showed a significant rise in infection from 50.0% (dry season) to 83.6% (wet season) (χ² = 16.10, p \u0026lt; 0.001). Similar seasonal increases were recorded for \u003cem\u003eG. tachinoides\u003c/em\u003e females (56.1% to 81.5%, χ² = 10.34, p = 0.001) and \u003cem\u003eG. palpalis palpalis\u003c/em\u003e females (10.8% to 50.5%, χ² = 29.95, p \u0026lt; 0.001). These trends suggest that favorable environmental conditions during the wet season—such as higher humidity, vegetation cover, and host availability—enhance \u003cem\u003eWolbachia\u003c/em\u003e replication and vertical transmission in females, who transmit the symbiont to offspring through their germline (Werren \u003cem\u003eet al.,\u003c/em\u003e 2008).\u003c/p\u003e\n\u003cp\u003eIn contrast, males consistently exhibited lower infection rates. Although \u003cem\u003eGlossina palpalis\u003c/em\u003e \u003cem\u003epalpalis\u003c/em\u003e males did show a statistically significant increase in \u003cem\u003eWolbachia\u003c/em\u003e prevalence from dry to wet season (χ² = 8.30, p = 0.004), no significant seasonal effect was observed in males of the other species. This may be due to differences in lifespan, physiology, or immune response between sexes. Males do not contribute to vertical transmission, and thus may not maintain high Wolbachia densities (Charlat \u003cem\u003eet al.,\u003c/em\u003e 2007). These findings are consistent with studies in other insect systems. For instance, Mouton \u003cem\u003eet al.\u003c/em\u003e (2007) and Zouache \u003cem\u003eet al.\u003c/em\u003e (2009) reported higher Wolbachia densities in females of Aedes and Drosophila during peak reproductive seasons, supporting the role of sex-linked biological factors in infection dynamics. Similarly, in tsetse flies, Aksoy \u003cem\u003eet al.\u003c/em\u003e (2008) demonstrated that female flies maintain more stable and higher endosymbiont densities than males. On the other hand, some studies report minimal sex-based differences, particularly in laboratory-reared insects or in populations with low environmental variation. For example, Baldo \u003cem\u003eet al.\u003c/em\u003e (2007) observed comparable Wolbachia prevalence in both sexes of some dipterans, possibly due to uniform rearing conditions or strain differences that buffer sex-specific effects. The lack of statistically significant seasonal variation among male flies in this study, except for \u003cem\u003eG. palpalis palpalis\u003c/em\u003e, might be influenced by lower baseline infection levels, smaller sample sizes, or strain-host dynamics unfavoring high bacterial loads in non-reproductive individuals, though these factors require further investigation. The age-dependent \u003cem\u003eWolbachia\u003c/em\u003e load (Figure 1) parallels findings in Aedes, where older hosts exhibit stronger immune modulation (Zouache \u003cem\u003eet al.,\u003c/em\u003e 2009), suggesting a similar mechanism in tsetse flies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eWolbachia\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Strain Diversity in Nigerian \u003cem\u003eGlossina\u003c/em\u003e Species: A Molecular and Phylogenetic Perspective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMolecular analysis of the wsp (\u003cem\u003eWolbachia\u003c/em\u003e surface protein) gene in \u003cem\u003eGlossina\u003c/em\u003e species collected from Nigerian conservation areas revealed a complex but evolutionarily coherent profile of \u003cem\u003eWolbachia\u003c/em\u003e strain diversity. Multiple sequence alignment of the wsp gene demonstrated strong conservation—particularly in the core and flanking areas—across both newly sequenced samples and GenBank reference sequences (Figure 1). However, localized polymorphisms, including insertions and deletions, were also observed. These mutations reflect inter-strain divergence consistent with patterns previously reported across \u003cem\u003eWolbachia\u003c/em\u003e lineages (Baldo \u003cem\u003eet al.,\u0026nbsp;\u003c/em\u003e2006). The final alignment spanned 1,183 base pairs, slightly longer than the raw sequences due to computational gap insertions that account for evolutionary events such as indels. Pairwise similarity analysis showed up to 92% identity with GenBank sequences, suggesting that the Nigerian\u0026nbsp;\u003cem\u003eWolbachia\u003c/em\u003e strains are closely related to globally circulating lineages, while still retaining unique genetic features likely shaped by local ecological conditions or host interactions.\u003cbr\u003eOne of the key genomic features was the elevated GC content of 63%, which may support thermal adaptation hypotheses, as GC-rich DNA is proposed to resist denaturation in tropical climates (Gomes BLAST analysis corroborated the phylogenetic groupings. For instance, wsp5 (GenBank accession OR977570) showed 100% identity and full query coverage with sequence AJ585380.1 (Table 4), supporting the idea of trans-regional strain circulation. Similar findings were reported by Glowska et al. (2015), who demonstrated that Wolbachia strains can be shared across insect species and continents, likely due to horizontal transmission or co-dispersal via mobile hosts. Statistical validation of the tree structure using both the likelihood ratio test (p \u0026lt; 0.001) and Kishino-Hasegawa test (p = 0.02) confirmed that the phylogeny is robust and unlikely to be an artifact of random sampling. These results align well with earlier global studies. For example, Baldo \u003cem\u003eet al.\u003c/em\u003e (2006), through the Multilocus Sequence Typing (MLST) framework, highlighted global conservation alongside local polymorphisms within Wolbachia genomes. Likewise, Zhou \u003cem\u003eet al.\u003c/em\u003e (1998) confirmed that the wsp gene is a reliable marker for assessing strain-level diversity, especially where environmental and ecological pressures drive host-symbiont evolution.\u003c/p\u003e\n\u003cp\u003eThe discovery of identical matches like that between wsp5 and AJ585380.1 parallels findings by Glowska \u003cem\u003eet al.\u003c/em\u003e (2015), who described broad Wolbachia distribution facilitated by both vertical and horizontal transmission routes. This supports the view that Wolbachia combines heritable stability with ecological adaptability, allowing it to colonize diverse hosts and habitats. On the other hand, this study diverges from patterns seen in East African and South American populations, where researchers have documented more highly divergent \u003cem\u003eWolbachia\u003c/em\u003e strains (2015), though experimental validation in Nigerian \u003cem\u003eWolbachia\u003c/em\u003e strains is required. This feature is especially relevant in the warm, humid climates of Northern Nigeria’s savanna and riparian zones. Phylogenetic reconstruction further clarified the evolutionary relationships among the nine \u003cem\u003eWolbachia\u003c/em\u003e strains. Most sequences clustered into strongly supported sub-clades (bootstrap values \u0026gt;90%; Tables\u0026nbsp;4.), indicating high reliability. The closest relationship was observed between wsp3 and wsp4 (92% identity), while wsp9, derived from \u003cem\u003eGlossina morsitans submorsitans\u003c/em\u003e, appeared the most divergent. Moderate divergence patterns, such as the 91% identity between wsp5 and wsp8, could reflect host-specific interactions or geographic isolation, though additional data on host associations and spatial distribution are needed to elucidate these drivers.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelevance to Vector Competence, Control Strategies, and Symbiosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlthough \u003cem\u003eWolbachia\u003c/em\u003e’s role in trypanosome interference remains uncharacterized in \u003cem\u003eGlossina\u003c/em\u003e, its age-dependent density (Figure 1) and maternal transmission suggest parallels to \u003cem\u003eAedes\u003c/em\u003e, where immune activation (e.g., Toll pathway upregulation) reduces viral transmission (Moreira et al., 2009). Two control strategies emerge: (1) Population suppression via cytoplasmic incompatibility (CI), where \u003cem\u003eWolbachia\u003c/em\u003e-infected males sterilize wild females (Bourtzis et al., 2014), and (2) Pathogen blocking, leveraging \u003cem\u003eWolbachia\u003c/em\u003e-mediated trypanosome inhibition—a mechanism requiring validation in tsetse flies. The high GC content (63%) and stability of Nigerian strains (e.g., wsp5 = 100% match to AJ585380.1) highlight their potential for field deployment.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003cem\u003eWolbachia\u003c/em\u003e is known to influence the ability of insect vectors to acquire and transmit pathogens. In mosquitoes, for example, \u003cem\u003eWolbachia\u003c/em\u003e has been shown to activate host immune pathways such as Toll and Imd, which reduce susceptibility to viral infections (Moreira et al., 2009). Although the precise role of \u003cem\u003eWolbachia\u003c/em\u003e in modulating trypanosome development within tsetse flies is not yet fully understood, the patterns observed in this study—particularly the increasing \u003cem\u003eWolbachia\u003c/em\u003e load with fly age—suggest that older flies may exhibit different levels of vector competence. This aligns with findings in \u003cem\u003eDrosophila\u003c/em\u003e and \u003cem\u003eAedes\u003c/em\u003e where \u003cem\u003eWolbachia\u003c/em\u003e densities increase with age, affecting both immune response and pathogen interference (Mouton et al., 2007; Zouache et al., 2009). Several factors can influence\u0026nbsp;\u003cem\u003eWolbachia\u003c/em\u003e density in insects, including age, tissue type, host genotype, and viral infections (Kaur et al., 2020). Such age-related variation may be critical, considering that older female flies are more likely to contribute to transmission cycles.\u003cbr\u003eThe observed strain diversity and stability of \u003cem\u003eWolbachia\u003c/em\u003e in \u003cem\u003eGlossina\u003c/em\u003e species also provide a foundation for \u003cem\u003eWolbachia\u003c/em\u003e-based biological control approaches. One such method involves cytoplasmic incompatibility (CI), where the release of \u003cem\u003eWolbachia\u003c/em\u003e-infected male flies into wild populations results in non-viable offspring when they mate with uninfected females, leading to population suppression (Bourtzis \u003cem\u003eet al.,\u003c/em\u003e 2014). Another approach leverages \u003cem\u003eWolbachia\u003c/em\u003e’s capacity to interfere with pathogen development, as demonstrated in \u003cem\u003eAedes aegypti\u003c/em\u003e, where \u003cem\u003eWolbachia\u003c/em\u003e infection blocks the transmission of arboviruses (Walker et al., 2011). The discovery of high GC content and genetic similarity to known strains—such as the 100% identity match of wsp5 to GenBank reference AJ585380.1—suggests that the \u003cem\u003eWolbachia\u003c/em\u003e strains identified in Nigerian tsetse flies are robust and may be suitable candidates for field deployment under local environmental conditions.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003eTsetse flies are obligate hosts of multiple endosymbionts, including \u003cem\u003eWigglesworthia\u003c/em\u003e, \u003cem\u003eSodalis\u003c/em\u003e, and \u003cem\u003eWolbachia\u003c/em\u003e, which together shape various aspects of host biology such as immunity, metabolism, and reproduction (Aksoy \u003cem\u003eet al.,\u003c/em\u003e 2008). The consistent maternal inheritance and high prevalence of \u003cem\u003eWolbachia\u003c/em\u003e observed in this study reinforce its role as a stable and possibly co-evolved symbiont. Furthermore, the strain-specific patterns revealed by the phylogenetic analysis—particularly the divergence of wsp9—suggest possible functional differences that could influence reproductive fitness, thermal tolerance, or competition with other symbionts (Baldo \u003cem\u003eet al.,\u003c/em\u003e 2006). The elevated GC content may also support more efficient gene expression and genomic resilience under high-temperature conditions common in West African savanna habitats (Gomes \u003cem\u003eet al.,\u003c/em\u003e 2015). The \u003cem\u003eWolbachia\u003c/em\u003e strains identified in this study are not only relevant from an evolutionary perspective but also hold substantial promise for application in vector control. Their prevalence, genetic stability, and ecological adaptability make them potential assets for integrated disease management strategies aimed at controlling human African trypanosomiasis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides critical insights into the ecological and seasonal dynamics of \u003cem\u003eGlossina\u003c/em\u003e species and their \u003cem\u003eWolbachia\u003c/em\u003e endosymbionts across four ecologically diverse sites in northern Nigeria\u0026mdash;Yankari Game Reserve, Kainji Lake National Park, Kagarko Grazing Reserve, and Ijah Gwari Forest. The entomological survey revealed \u003cem\u003eGlossina tachinoides\u003c/em\u003e as the most prevalent species (55.78%), exhibiting high ecological plasticity, while \u003cem\u003eGlossina morsitans submorsitans\u003c/em\u003e (29.36%) and \u003cem\u003eGlossina palpalis palpalis\u003c/em\u003e (14.86%) showed more restricted distributions, influenced by habitat integrity and moisture availability, respectively. Seasonal variation in \u003cem\u003eWolbachia\u003c/em\u003e prevalence was significant only in Yankari, increasing from 12.6% to 23.5% during the wet season, with species-specific trends highlighting the role of humidity and host availability in enhancing infection rates (e.g., \u003cem\u003eG. morsitans submorsitans\u003c/em\u003e from 39.8% to 75.4%). Sex-based differences underscored higher female prevalence, particularly in the wet season, likely due to maternal transmission efficiency.\u003c/p\u003e\n\u003cp\u003eMolecular analysis of the wsp gene revealed a diverse yet coherent \u003cem\u003eWolbachia\u003c/em\u003e strain profile, with a high GC content (63%) suggesting potential thermal adaptation and pairwise similarities up to 92% with global lineages. Phylogenetic reconstruction identified stable clusters (e.g., wsp3 and wsp4 at 92% identity) and divergent strains (e.g., wsp9), supported by robust bootstrap values (\u0026gt;90%). BLAST analysis confirmed trans-regional strain circulation, with wsp5 showing 100% identity to GenBank sequence AJ585380.1. These findings underscore the ecological and genetic factors shaping tsetse-endosymbiont interactions, with implications for vector competence and disease transmission. The stability and diversity of \u003cem\u003eWolbachia\u003c/em\u003e strains, coupled with their age-dependent density, position them as promising candidates for integrated vector control strategies, including cytoplasmic incompatibility and pathogen blocking, pending further validation of trypanosome interference in tsetse flies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRecommendations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on the study\u0026rsquo;s findings, the following recommendations are proposed to enhance tsetse control and mitigate African trypanosomiasis (AT) in northern Nigeria:\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eTargeted Habitat Management: Prioritize conservation of woodland savannas and riparian zones, particularly in Yankari and Kainji, to sustain \u003cem\u003eG. morsitans submorsitans\u003c/em\u003e and \u003cem\u003eG. palpalis palpalis\u003c/em\u003e populations while minimizing habitat degradation in Kagarko and Ijah Gwari through regulated agricultural practices.\u003c/li\u003e\n \u003cli\u003eSeasonal Control Interventions: Implement vector control measures, such as insecticide-treated targets or traps, during the dry season in Yankari, where \u003cem\u003eWolbachia\u003c/em\u003e prevalence is lower, to reduce tsetse populations before wet season peaks.\u003c/li\u003e\n \u003cli\u003e\u003cem\u003eWolbachia\u003c/em\u003e-Based Strategies: Explore paratransgenic approaches using stable \u003cem\u003eWolbachia\u003c/em\u003e strains (e.g., wsp3 and wsp4) for cytoplasmic incompatibility or pathogen blocking. Field trials should assess strain efficacy under local climatic conditions, leveraging the high GC content for thermal resilience.\u003c/li\u003e\n \u003cli\u003eIntegrated Disease Management: Combine ecological monitoring with molecular surveillance of \u003cem\u003eWolbachia\u003c/em\u003e strains to adapt control strategies to seasonal and species-specific dynamics, enhancing collaboration between wildlife conservation and public health sectors.\u003c/li\u003e\n \u003cli\u003eFurther Research: Conduct longitudinal studies to correlate \u003cem\u003eWolbachia\u003c/em\u003e strain diversity with environmental stressors (e.g., temperature, humidity) and validate trypanosome interference mechanisms. Additional genetic markers (e.g., MLST) and functional assays are needed to confirm strain-specific adaptations, such as the potential uniqueness of wsp9.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeveral limitations constrain the interpretation and generalizability of this study:\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eThe analysis was confined to four sites in northern Nigeria, limiting its representativeness across the country\u0026rsquo;s diverse ecological zones, such as southern rainforest areas where tsetse dynamics may differ.\u003c/li\u003e\n \u003cli\u003eThe study relied on variable sample sizes across sites and seasons, with potential underrepresentation of males, which may have influenced the detection of seasonal \u003cem\u003eWolbachia\u003c/em\u003e variation in some species.\u003c/li\u003e\n \u003cli\u003eThe role of \u003cem\u003eWolbachia\u003c/em\u003e in trypanosome interference remains untested in tsetse flies, relying on inferences from other systems (e.g., \u003cem\u003eAedes\u003c/em\u003e). Without experimental evidence, control strategy proposals are preliminary.\u003c/li\u003e\n \u003cli\u003eThe phylogenetic analysis was based solely on the wsp gene, which may not fully capture \u003cem\u003eWolbachia\u003c/em\u003e strain diversity. Additional markers or whole-genome sequencing could refine strain relationships and evolutionary histories.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe gratefully acknowledge the support of the park authorities in Yankari Game Reserve, Kainji Lake National Park, Kagarko Grazing Reserve, and Ijah Gwari Forest for facilitating field data collection. We thank the technical staff at\u0026nbsp;Molecular Biology Unit of Nigerian Institute for Trypanosomiasis Research\u0026nbsp;for their assistance with molecular analyses and phylogenetic reconstructions. Special gratitude is extended to\u0026nbsp;Dr S. Shaida\u0026nbsp;for valuable insights during manuscript preparation. This work benefited from discussions with\u0026nbsp;Prof Muhammad Mamman, and Prof Isa Jatau\u0026nbsp;whose expertise in vector ecology enriched the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo external funding was received for this research. This study was conducted as part of the author\u0026rsquo;s PhD thesis at\u0026nbsp;Ahmadu Bello University Zaria.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declares no conflicts of interest. There are no financial or personal relationships that could inappropriately influence or bias the content of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eAttahir Abubakar: Conceptualization, methodology design, supervision, and manuscript drafting.\u003c/li\u003e\n \u003cli\u003eRamatu Ado Abdullahi: Data collection, literature review, and manuscript editing.\u003c/li\u003e\n \u003cli\u003eUsman Baba Musa: Statistical analysis, data interpretation, and visualization.\u003c/li\u003e\n \u003cli\u003eRukayya Garba Anchau: Fieldwork coordination, data validation, and critical revisions.\u003c/li\u003e\n \u003cli\u003eJabiru Garba: Software support, technical validation, and contributed to data analysis.\u003c/li\u003e\n \u003cli\u003eZainab Tamba: Assisted in literature review, formatting, and reference management.\u003c/li\u003e\n \u003cli\u003eSaminu Sabiu: Contributed to methodology refinement, proofreading, and final approval of the manuscript.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset supporting the findings of this study has been deposited in the Dryad Digital Repository and is publicly available under the DOI: DOI 10.5281/zenodo.16875929\u003c/p\u003e\n\u003cp\u003eGenBank has been assigned accession numbers, BankIt2776358 WSP 9_\u003cem\u003eWSP\u003c/em\u003e 1F _H07_22 OR977569 and BankIt2776358 WSP5_WSP81F_D09_12 OR977570\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbubakar, A., Ibrahim, M. \u0026amp; Ojo, O. 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Persistence of \u003cem\u003eWolbachia\u003c/em\u003e in the germ line and somatic cells in \u003cem\u003eDrosophila\u003c/em\u003e. \u003cem\u003ePLOS ONE\u003c/em\u003e. \u003cb\u003e4\u003c/b\u003e (8), e6388. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0006388\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0006388\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2009).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Wolbachia, Glossina, tsetse flies, Nigeria, phylogenetics, vector control","lastPublishedDoi":"10.21203/rs.3.rs-7310521/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7310521/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTsetse flies (\u003cem\u003eGlossina\u003c/em\u003e spp.), the vectors of human and animal African trypanosomiasis, continue to exert a profound toll on public health and livestock productivity in Nigeria. This study investigates the prevalence, seasonal dynamics, and genetic diversity of \u003cem\u003eWolbachia\u003c/em\u003e endosymbionts in 7,632 wild-caught tsetse flies sampled from four ecologically distinct conservation sites: Yankari Game Reserve, Kainji Lake National Park, Kagarko Forest, and Ijah Gwari Forest. Molecular screening based on \u003cem\u003ewsp\u003c/em\u003e gene sequencing detected \u003cem\u003eWolbachia\u003c/em\u003e in 1,771 flies, with infection rates rising significantly during the wet season (e.g., \u003cem\u003eG. morsitans submorsitans\u003c/em\u003e: 75.4% vs. 39.8% in dry season; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Female flies showed consistently higher infection prevalence, reinforcing the role of vertical transmission. Phylogenetic reconstruction revealed nine \u003cem\u003eWolbachia\u003c/em\u003e strains spanning supergroups A and B, including a putatively unique regional variant (wsp9) restricted to northern Nigeria. Bacterial load exhibited a strong age-dependent pattern (r\u0026thinsp;=\u0026thinsp;0.912, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and elevated GC content (~\u0026thinsp;63%) suggested possible adaptation to savanna thermal conditions. These findings highlight the ecological flexibility of \u003cem\u003eWolbachia\u003c/em\u003e within natural tsetse populations and point to its potential application in vector control\u0026mdash;particularly through mechanisms like cytoplasmic incompatibility. By combining molecular detection, ecological data, and evolutionary analysis, this study lays the groundwork for tailored, climate-sensitive \u003cem\u003eWolbachia\u003c/em\u003e-based strategies to reduce tsetse populations and support trypanosomiasis control in Nigeria.\u003c/p\u003e","manuscriptTitle":"Molecular Detection and Phylogenetic Characterization of Wolbachia Strains in Glossina Species from Nigerian Conservation Areas","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-10 18:33:33","doi":"10.21203/rs.3.rs-7310521/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-22T09:01:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-20T09:35:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-14T19:44:21+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-10T09:38:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"251042482095964304780316774616508047359","date":"2025-09-09T12:17:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"41772572487458293410095950963763490322","date":"2025-09-04T19:27:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"263834323143283924040305362220966385784","date":"2025-09-03T18:42:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-03T16:16:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-03T16:10:35+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-19T04:46:54+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-14T14:10:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-08-14T14:07:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3e534cda-df55-40c1-a0df-86a4c15712ed","owner":[],"postedDate":"September 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":54438253,"name":"Biological sciences/Ecology"},{"id":54438254,"name":"Earth and environmental sciences/Ecology"},{"id":54438255,"name":"Biological sciences/Evolution"},{"id":54438256,"name":"Biological sciences/Microbiology"},{"id":54438257,"name":"Biological sciences/Zoology"}],"tags":[],"updatedAt":"2025-11-26T05:23:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-10 18:33:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7310521","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7310521","identity":"rs-7310521","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}