Molecular Characterization of Mosquito Species and Confirmation of First Record of Aedes aegypti in Buraydah City,Kingdom of Saudi Arabia

Abstract

Mosquitoes are a source of concern because they transmit many infectious diseases, including Zika virus, chikungunya, and malaria. Accurate and rapid identification of mosquitoes is essential for disease surveillance and control. Genetic diversity in mosquito species, resulting from adaptation to different environments, leads to many differences in morphological characteristics. Traditional identification methods relying on morphology can be time-consuming and unreliable. The study aimed to identify medically and veterinary significant adult mosquito species throughout 2021 in Buraydah City, Kingdom of Saudi Arabia (KSA). We collected adult mosquitoes using Black Hole light traps in the city. The mosquitoes were morphologically identified using traditional identification keys and characterized by using the mitochondrial cytochrome oxidase c subunit I (COI) barcode regions. Although the genetic sequences we discovered do not necessarily represent new records, they do represent species with a long history of evolutionary independence, at least among adult mosquito species in KSA, especially in Buraydah city. Both morphological and molecular data identified five mosquito species: Culex pipiens (Linnaeus, 1758), Cx. sitiens (Wiedemann, 1828), Aedes aegypti (Linnaeus, 1762), Ae. caspius (Pallas, 1771), and Anopheles dthali (Patton, 1905). These species correspond to those from Kenya, India, KSA, and Iran with genetic variation. Aedes aegypti was confirmed for the first time in Buraydah city. DNA barcoding is a useful tool that can overcome inefficiencies and difficulties and complement traditional taxonomy.

Keywords

molecular identification barcode gene Buraydah city genetic biodiversity

Introduction

The combination of scientific knowledge and field observations is important for effective mosquito control. The role of mosquitoes in disease transmission highlights the significance of developing control programs on a scientific basis (Sousa et al., 2022). The first step in the mosquito control program starts with the accurate identification of species. Traditionally, mosquito identification relied on morphological features and taxonomic keys, which have some advantages and disadvantages, as mentioned in Besansky et al. (2003), Pennisi (2003), and Beebe (2018). The use of DNA sequences for biological classification/identification was first introduced by Tautz and Arctander (2002,2003) and Hebert et al. (2003). Since mitochondrial genes are quicker and more accurate, they have been employed to identify mosquito species thus far (Mousson et al., 2005; Munawar et al., 2020). Mitochondrial genes, particularly cytochrome c oxidase subunit I (COI) and COII, are widely utilized DNA-based markers for investigating the evolution and historical population dynamics of mosquitoes (Bunmee et al., 2021; Helleman et al., 2025).

Records of Ae. aegypti in KSA date back to 1900, when it was first reported only in the southwestern part of the country (Mattingly and Knight, 1956). From this point onward, this species was reported from different regions of the country as mentioned in Table 1. These studies demonstrate how invasive Ae. aegypti has migrated from the western and southern parts of KSA to the central region. The spread of invasive mosquito species into new areas is usually troublesome due to the possibility of introducing disease pathogens such as dengue fever, chikungunya, yellow fever, and Zika virus.

Table 1.

Reports Indicate Migration of Ae. aegypti from the Western and Southern Regions of KSA to the Central Region

Region	Key collection sites/Provinces	Record history
Asir (southwestern)	Abha	Miller et al., 2002; Al Ahmad et al., 2011; Al Ashry et al., 2014
Makkah Al Mukarramah (western)	Makkah	Miller et al., 2002; Alahmed et al., 2009; Al Ahmad et al., 2011; Aziz et al., 2012; Khater et al., 2013; Mahyoub et al., 2015; Hassan et al., 2016
Makkah Al Mukarramah (western)	Jeddah	Al Ahmad et al., 2011; Al-Azab et al., 2013; Al-Ghamdi et al., 2014; Alikhan et al., 2014
Al-Madinah Al-Munawwarah (western)	Al-Madinah	El-Badry and Al-Ali, 2010; Al Ahmad et al., 2011; Sowilem et al., 2013; Al Ali et al., 2016; Hassan et al., 2016
Jazan (southwestern)	Jazan	Miller et al., 2002; Alahmed et al., 2010; Al Ahmad et al., 2011; Al Ahmed et al., 2013; Bakr et al., 2014
Al Bahah (southwestern)	Al Bahah	Al Ahmed et al., 2010a; Naeem et al., 2016
Najran (southwestern)	Najran	Al Ahmed et al., 2010b; Al Ahmad et al., 2011
Al-Qassim (central)	Al-Qassim	Kheir et al., 2011
Tabouk (northwestern)	Tabouk	Hassan et al., 2016
Riyadh (central)	Riyadh	Alzahrani et al., 2021

KSA, Kingdom of Saudi Arabia

To the best of our knowledge, this study is the first report on the molecular confirmation of Ae. aegypti in Buraydah as the leading vector for many diseases, including the dengue fever virus, in the world (Gloria-Soria et al., 2016). The other four studied species, i.e., Ae. caspius, Cx. pipiens, Cx. sitiens, and An. dthali, have been reported as disease vectors from various parts of the world, including KSA (Dawah et al., 2023). Moreover, all these species were reported before from different parts of the KSA (Alahmed et al., 2019; Dawah et al., 2023), including Buraydah (Al-Rashidi et al., 2025), but here we are reporting for the first time the molecular characterization and phylogenetic analysis of these five species from the area.

Materials and Methods

Adults mosquito collection and morphological identification

Adult mosquitoes were collected using Black Hole light traps in Buraydah city, KSA, throughout 2021 from the selected 10 areas (Table 2). Standard taxonomic keys were used for genus and species identification as described by Reinert (2000), Rueda (2004), Azari-Hamidian and Harbach (2009), and Soltani and Keshavarzi (2016). Forty-eight adult mosquitoes were preserved individually in 1.5 mL Eppendorf tubes and stored at −80°C until they were used for DNA isolation.

Table 2.

Coordinates of the Mosquito Study Regions in Buraydah City, KSA Using a GPS System

Regions	Coordinates
Regions	E	N
Buraydah city
El-Akhdar	43.977761	26.398561
Wasit	43.95404722	26.31702778
Al-Olaya	43.89066111	26.35491389
Southern Al Muntazah	44.021975	26.24311944
Al-Hassa	44.06951944	26.22025
El-Sarkia Nakea	43.99712778	26.36132778
Al-Rashidiyat	43.92418611	26.41840556
Al-Wurud	43.97576389	26.42403889
Al Iskan	43.93919444	26.37325278
Al-Subaiya	43.89698333	26.39586111

Molecular identification

DNA extraction

Genomic DNA was extracted from legs, thorax, and wings of individual adult mosquitoes using the Quick-DNATM Mini Pro-Plus kit (ZYMO R ESEARCH, Catalogue No. D4068, USA) according to the manufacturer’s protocol. The extracted DNA quality was excessed on agarose gel 1% with 1xTBE (1.1M Tris base, 900 mM Boric acid, and 25 mM EDTA pH = 8) buffer and stained with 0.5 µg/mL ethidium bromide. The quantity of DNA was checked by a NanoDrop 2000 UV-Vis Spectrophotometer (Thermo Scientific, USA).

Amplification of mtCOI gene fragment

The barcoding region of the mitochondrial cytochrome oxidase subunit I (mtCOI) was amplified using universal primers of Folmer et al. (1994) (Table 3).

Table 3.

Primer Pair Used for DNA Barcoding

mtCOI gene	Sequence of primer5′–3′
LCO1490 Forward primer	GGTCAACAAATCATAAAGATATTGG
HCO2198 Reverse primer	TAAACTTCAGGGTGACCAAAAAATC

PCR was performed in a 25 µL volume including 12.5 µL of 2X Dream Taq Green PCR Master Mix (Thermo Fisher Scientific, catalogue number: K1081, USA), 1 µL of each forward and reverse primers (10 pmol/µL), along with 4 µL of 1X bovine serum albumin (BSA) and 5 µL of template DNA (50 ng/µL). The remaining volume was made up of nuclease-free water to complete a total of 25 µL. The PCR was performed in a Veriti ^TM 96-well thermal cycler (Applied Biosystems, 2990218112). The thermal cycling conditions were denaturation at 94°C for 4 min, followed by 40 cycles of 94°C for 30 s, annealing at 50°C for 45 s, and extension at 72°C for 45 s with a final extension step at 72°C for 1 minute.

Agarose gel electrophoresis

The amplified PCR products were visualized on 1% agarose gel, prepared with 1xTBE buffer, and stained with ethidium bromide as mentioned before. The PCR products were kept at −20°C until sent for sequencing at the Macrogen Sequencing facility in Seoul, South Korea.

Sequence and phylogenetic analysis

The readable chromatograms of the amplified DNA sequences were cleaned and BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi) in the GenBank database to identify the related species. The sequences were analyzed using the Molecular Evolutionary Genetic Analysis MEGA11 version 11.1.3 software (Kumar et al., 2004; Tamura et al., 2021). The ClustalW tool of MEGA was used to perform multiple sequence alignment. A maximum likelihood (ML) pattern was used to construct the phylogenetic trees for the Culex, Aedes, and Anopheles genera. Bootstrap replications (1000) were performed to test the statistical significance of tree branching.

Results

Identification of adult species of mosquito in Buraydah city

A total of 23,347 adult mosquitoes were collected in 2021 from Buraydah city during this study as mentioned previously (Al-Rashidi et al., 2025). These mosquitoes belong to three genera: Culex 91%, Aedes 8%, and Anopheles 1%. Based on their morphological characteristics, these mosquito genera were further divided into five species: two species of Culex (Cx. pipiens and Cx. sitiens), two species of Aedes (Ae. caspius and Ae. aegypti), and one species of Anopheles (An. dthali).

Molecular identification

The COI gene fragment (700 bp) was amplified from 48 mosquito samples belonging to 5 species such as Ae. caspius (n = 22), Ae. aegypti (n = 10), Cx. pipiens (n = 9), An. dthali (n = 6), and Cx. sitiens (n = 1). Based on PCR profiles, no detectable intra or interspecific fragment length polymorphisms were found among any of the five mosquito species under investigation.

COXI gene sequencing and phylogenetic analysis

The studied COI fragment sequences of mosquitoes were BLAST in the GenBank database and compared with sequences from the GenBank (NCBI) database. The BLAST results showed five species: Cx. pipiens, Cx. sitiens, Ae. aegypti, Ae. caspius, and An. dthali (Table 4). The convergence and divergence between the COI sequence of mosquitoes of Buraydah province and GenBank sequences are shown in the form of a phylogenetic tree using MEGA11 software. Analysis was conducted using ML method and bootstrap test (1000 replications) in MEGA11.

Table 4.

Details of Comparison of the Studied Mosquito Samples with Species Identification from GenBank (NCBI) Databases

Buridah gen CO1 samples	GenBank acc. No.	Mosquito species description recorded in the gene bank	Gene definition^×	Identity (%) similar sequence recorded in NCBI gene bank	Gene length(bp)	Gene published date	Country	References
1,3,4,5,6,7,9,10	MK300250.1	Culex pipiens	isolate NEH12	100	709	Dec 14, 2018	Kenya	Makanda M, 2019
8	OK002044.1	Culex sitiens	isolate Saudi Arabia—jazan	98.40	626	Sep 2, 2021	Jazan	Noureldin, et al., 2022
11,12,13,14,15,16,17, 18,19,20	MK300227.1	Aedes aegypti	isolate NCH12	99.84	639	Dec 14, 2018	Kenya	Makanda et al., 2019
HF1, HF2, HF3, HF4, HF5, HS1, HS2, HS3, HS4, HS5, HS6, HS7, HS8, HS9, HS10, HS11, HS12, HS13, HS14, HS15, HS16, HS17	MH709109.1	Aedes caspius	strain B1 Bishmont Konarak	99.36–100	671	Aug 1, 2018	Iran	Nejati, 2018
A1, A2, A3, A4, A5, A6	KM389471.1	Anopheles dthali	strain SE24	99.84–99.51	633	Aug 25, 2014	Iran	Karimian et al., 2014

Gene definition: cytochrome oxidase subunit I (COI) gene, partial cds; mitochondrial.

Culex pipiens-COI diversity and phylogenetic analysis

The COI gene sequences of eight Cx. pipiens sequences from KSA were subjected to BLAST analysis. The results indicated that the top hits (100% sequence identity) were homologous COI sequences that were obtained from the GenBank of Cx. pipiens from Kenya (MK300250.1) and India (MK347224.1).

A total of 634 bp of multiple sequence alignment between Cx. pipiens from KSA and sequences of Cx. pipiens retrieved from the GenBank revealed no single nucleotide polymorphisms (SNPs).

The comparison of the sequences from KSA and the GenBank sequences using the ML method made it possible for the construction of a phylogenetic tree with one haplotype that contains all the Culex pipiens sequences from KSA and the sequences from India (MK347224.1), Turkey (MK713990.1), Thailand (OK413150.1), and Kenya (MK300250.1) (Fig. 1).

Culex sitiens-COI diversity and phylogenetic analysis

A comparative analysis was conducted on a COI gene sequence of Cx. sitiens sequence from KSA and GenBank sequences. Results show that the samples have a significant similarity of 98.40% with Cx. sitiens (OK002044.1) detected in Jazan.

A total of 634 bp of multiple sequence alignments revealed 19 SNPs, most of which were constant at the same base position between Saudi and New Caledonia Cx. sitiens (bp 6, 11, 24, 26, 27, 35, 177, 206, 266, 335, 338, 396, 521, 546, 584, 596, 614, 617, and 620) (Supplementary Fig. S1 and Table 1).

The comparison of the sequences from KSA and New Caledonia using ML method for the construction of phylogenetic trees revealed two haplotypes. The haplotype 1 contains Culex sitiens sequence from KSA along with sequence from Jazan, supported by 97% bootstrap value and the haplotype 2 contains the sequences from New Caledonia (MN733806 and MN733805), supported by 99% bootstrap value (Fig. 2).

Aedes aegypti-COI diversity and phylogenetic analysis

In this study, we compared 10 Ae. aegypti sequences from KSA with the GenBank sequences. The results indicated a high similarity of 99.84% to the Ae. aegypti from Kenya (MK300226).

A total of 639 bp of multiple sequence alignments between 10 Saudi Ae. aegypti samples and Ae. aegypti sequences samples from Kenya, Thailand and Malaysia retrieved from the GenBank revealed a total of 10 SNPs (bp 138, 204, 207, 216, 288, 438, 450, 465, 588, and 600 (Supplementary Fig. S2 and Table 2).

The ML tree was generated from COI sequences of 10 Aedes aegypti from KSA and 3 homologous sequences from GenBank. The tree topology identified two haplotypes based on 1000 replicates; haplotype H1 included 9 individual sequences from Buraydah along with Genbank sequence from Kenya, while haplotype H2 included one sequence from Buraydah along with sequences from Malaysia and Thailand supported by 41% bootstrap value (Fig. 3).

Aedes caspius-COI diversity and phylogenetic analysis

The 22 Ae. caspius samples from KSA were compared with GenBank sequence. The analysis revealed high similarity ranging from 99.36% to 100% with the type (Ae. caspius, MH709109) from Iran.

A total of 624 bp of multiple sequence alignments revealed 13 SNPs, most of which were constant at the same base position between Saudi and the GenBank Ae. caspius sequence at positions 2, 6, 11, 33, 194, 209, 227, 230, 302, 305, 326, 380, and 500 bp (Supplementary Fig. S3 and Table 3).

The ML tree was generated from COI sequences of 22 Ae. caspius from KSA and 3 homologous sequences (Iran: Sistan and Baluchestan) from GenBank. The tree topology identified 11 haplotypes based on 1000 replicates. Four of the Ae. caspius from KSA formed a single haplotype (singleton), i.e., haplotypes 3, 7, 9, and 10, respectively. This indicates that these Ae. caspius samples are different from those of other Saudi or Iranian samples. Sequence hits of Ae. caspius of Iran (MH709109, MH634425, and MH559350) clustered in haplotype 1 and 6 with Saudi samples which shows that these tested Saudi Ae. caspius samples are related to Iranian samples (Fig. 4).

Anopheles dthali-COI diversity and phylogenetic analysis

A comparative analysis was conducted with 6 An. dthali samples from KSA with GenBank samples. The results showed a significant similarity of 99.84–99.51% with the type (An. dthali, KM068084) detected in Jazan.

A total of 620 bp of multiple sequence alignments of An. dthali revealed 8 SNPs between Saudi sequences and sequences of An. dthali retrieved from GenBank from Iran (accession nos. KM389470 and KM389471). Most of the SNPs were constant at the same base positions (bp 16, 30, 38, 140, 230, 338, 544, and 554) (Supplementary Fig. S4 and Table 4).

The ML tree was generated from COI sequences of six An. dthali from KSA and four homologous sequences from GenBank (two from Iran and two from Jazan). The tree topology identified two haplotypes based on 1000 replicates; haplotype H1 included six individual sequences from Buraydah along with Genbank sequence from Iran supported by 100% bootstrap value while haplotype H2 included two sequences from Jazan supported by 50% bootstrap value. It is significant that An. dthali samples from Buraydah coexist with Iranian samples but not with the Jazan samples, which may be because Iran is geographically closer to Buraydah than Jazan (Fig. 5).

Molecular phylogenetic characterization of mosquito samples collected from Buraydah province, KSA

To assess the genetic relatedness among different mosquito samples collected from Buraydah province, KSA, in this study, a phylogenetic tree was constructed using the ML method and bootstrapping test (1000 replications) in MEGA 11 software.

A total of 48 mosquito COI sequences (22 Ae. caspius, 10 Ae. aegypti, 9 Cx. pipiens, 6 An. dthali, and 1 Cx. sitiens) were analyzed. Based on the COI region, the ML analysis clustered these sequences into five distinct clades representing their respective five species (Fig. 6).

Here, it is worth noting that the phylogenetic tree split into two distinct branches based on the COI region. One branch contains An. dthali (Myzomyia series: subfamily Anophelinae), while the other contains four species, Ae. caspius, Ae. aegypti, Cx. pipiens, and Cx. sitiens, which represent the Aedini and the Culicini tribes, respectively, of the subfamily Culicinae (Fig. 6).

Discussion

Culex pipiens, Cx. quinquefasciatus (Say, 1823), Cx. sitiens, and Cx. tritaeniorhynchus are the most common and noted mosquito species in various regions of KSA (Alsheikh, 2011; Bakr et al., 2014; Al Ashry et al., 2018; Alahmed et al., 2019). Culex tritaeniorhynchus appears to be the most common in the Jazan region (Al Ahmad et al., 2011; Alahmed et al., 2019). Furthermore, the high rate (more than 90%) of Culex species in Buraydah province may provide an increased risk of encephalitis, West Nile viruses, and Bancroftian filariasis transmission in the future (Michael, 2012; Tahmina et al., 2018). Our study found no genetic variation in Cx. pipiens sequences. The Cx. pipiens Saudi haplotype is also found in other regions, including Kenya (MK300223), Thailand (OK413150), Turkey (MK713990), and Colombia (MN299023). Similarly, one study shows low COI polymorphisms between Cx. pipiens ecotypes, where the mtCOI gene could not distinguish between the Cx. pipiens and Cx. molestus ecotypes (Francuski et al., 2019). Moreover, Cx. sitiens, the Saudi COI haplotype was clearly different from the New Caledonia Cx. sitiens. This showed a significant level of genetic variation between Cx. sitiens from KSA and New Caledonia. In contrast, Noureldin et al. (2022) used the COI gene to identify Cx. sitiens and Cx. tritaeniorhynchus (Giles, 1901) from Jazan, KSA. They found that the Jazan Cx. sitiens was closely related to samples from Vietnam, Guinea, and Singapore.

In this study, species within the genus Aedes were the second highest collection of mosquito samples from Buraydah province (8% of total collection). Two species of genus Aedes were morphologically identified as Ae. aegypti and Ae. caspius. Both species are the vectors of important diseases in humans and animals in the world. Aedes aegypti is the vector of human diseases such as dengue, yellow fever, chikungunya, and Zika virus all over the world (Lim et al., 2025). Nevertheless, Ae. caspius has been reported as the vector of Rift Valley fever in southern KSA (Jupp et al., 2002). Here we reported the first confirmation of Ae. aegypti in Buraydah province. This species was first reported in the province in 2025 (Al-Rashidi et al., 2025). For KSA Ae. aegypti COI sequences, the two identified haplotypes were indistinguishable from Ae. aegypti from Kenya (MK300226), Thailand (OP477052), and Malaysia (MF148269). Due to significant gene flow between these populations, these findings imply that there is minimal genetic difference between Ae. aegypti from the KSA and other countries. This supports the findings of Mashlawi et al. (2024), who hypothesised that Saudi and Thai Ae. aegypti has a mixed ancestry based on microsatellite research. Moreover, study from Iran shows the close relationship between Ae. aegypti from KSA, Pakistan, and Iran (Paksa et al., 2024). These studies clearly show high gene flow and low genetic diversity between the Ae. aegypti population of the Asian countries. Based on our results, the COI gene generates 11 haplotypes, showing a high level of genetic diversity in the Saudi Ae. caspius samples. However, Ae. caspius from Iran had a close relationship with haplotypes 1 and 6 found in the KSA. Doosti et al. (2018) found similar results in Iran, identifying 12 haplotypes using the COI gene, which indicates a high degree of variation within the species.

An. dthali was found in several areas of KSA (Alahmed et al., 2009; Waheed et al., 2018; Alahmed et al., 2019). In Iran, An. dthali was regarded as one of the main malaria vectors (Hanafi-Bojd et al., 2011). Although An. dthali has never been linked to the spread of malaria or other mosquito-borne diseases in KSA, it has been identified as a secondary malaria vector in the Jazan region (Waheed et al., 2018). Two haplotypes of An. dthali have been found in the present study based on the COI region. Interestingly, Saudi An. dthali produced two haplotypes: one with GenBank homologous samples and the other with Iranian samples. Munawar et al. (2020) had earlier suggested that there was no genetic variation between An. dthali from Iran and KSA based on COI and ITS2 genes analysis. Our finding was in accordance with Munawar et al. (2020) showing no genetic variation and a high level of gene flow between these populations based on COI sequences.

The comparison of current samples to those from GenBank showed a significant similarity. The slight differences can be explained by mutations between the samples. Climate change may play a role in promoting variation and creating genetic diversity in mosquitoes. The different ecosystems and weather conditions where the samples were collected contributed to the increase in species density. These differences also suggest that the genetic diversity of the samples may lead to different rates of infection.

Authors’ Contributions

Conceptualization and study design: H.M.A.-S. and J.A.M. Sample collection and methodology: H.S.A.-R., M.F.A. Data analysis: F.M.S., K.M., A.A.-F., and J.A.M. Writing—original draft preparation: F.M.S., J.A.M., M.R.F., and K.M. Technical supervision: M.A.A., J.A.M., and H.S.A. Study supervision and project management: H.M.A.-S., M.A.A., A.G.A., and J.A.M. All authors read and approved the final article.

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Footnotes

Acknowledgments

The authors, therefore, acknowledge with thanks DSR for technical and financial support.

Author Disclosure Statement

The authors declare that they have no competing interests.

Funding Information

This Project was funded by the Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, Saudi Arabia, under grant no. (IPP: 697-130–2025).

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