Molecular Identification and phylogenetic analysis of mosquito vectors from Mananthavady Taluk, Wayanad, Kerala, India

Abstract

Background & objectives: 

Every year more than one billion people are infected and about one million people die from vector-borne diseases; of which mosquito-borne diseases remain as the world’s most severe insect-borne diseases with excessive rates of morbidity and mortality. This study aimed to examine the mosquito vectors and the possible diseases transmitted by them in the Mananthavady Taluk of Wayanad, Kerala.

Methods: 

The area selected for the present study was Mananthavady Taluk of Wayanad district, Kerala, during 2019–2021. The collected specimen were subjected for morphological identification using taxonomic keys and were confirmed by DNA barcoding. Molecular phylogeny assessment was done for the collected species of vector mosquitoes.

Results: 

A total of 17 mosquito species belonging to 5 genera, Anopheles, Aedes, Culex, Mansonia and Armigereswere identified. The mitochondrial COI gene sequences generated for molecular identification of these species were submitted to NCBI GenBank.

Interpretation & conclusion: 

Overall, this study extends our understanding of the molecular evolution of mosquito vectors of medical and veterinary concern, which could aid in developing biotechnological approaches used in Culicidae control programs.

INTRODUCTION

Mosquitoes are the most ubiquitous arthropod vectors of human diseases, spreading malaria, lymphatic filariasis, and arboviruses including dengue and Zika virus around the world. Among them, vectors of public health relevance are generally confined to the genera Anopheles, Aedesand Culex,that have been implicated in the transmission of a spectrum of vector-borne diseases with significant morbidity and mortality among humans[^1,2,3,4].

The family Culicidae(Diptera) has approximately 3600 valid and described species, which are widely distributed throughout most environments on the planet[⁵]. In India, about 410 species have already been reported[⁶]. These include, Anopheles stephensi, an important vector of malaria, Aedes aegypti, a vector of dengue, and Culex quinquefasciatus, a vector of bancroftian filariasis besides other species involved in the transmission of arboviruses[⁷]. These diseases are more prevalent in tropical and subtropical regions, and they preferentially afflict the poorest people. Dengue, malaria, Chikungunya, yellow fever and Zika outbreaks have plagued communities, taken lives and overwhelmed health systems across many areas since 2014. Correct vector identification is very important to design strategies for managing vector-borne diseases[⁸]. During routine taxonomic sample collection, standard taxonomic identification is difficult due to the loss of some features like wings and legs. In addition, existence of sibling species has further complicated the species identification of mosquitoes[⁹]. One of the most significant disadvantages of relying solely on physical characteristics for species identification and phylogenetic studies is that some traits or attributes are only visible at specific life cycle stages or in one gender. Furthermore, phenotypic changes may or may not be related to genotypic variants, making accurate correlations difficult to establish[¹⁰]. The results of more recent morphological studies, where the developing life stages of mosquitoes (pupae and larvae) have been analysed, are sometimes inconsistent with the traditional classification[¹¹]. Hence DNA barcoding provides an important tool for the identifications of mosquito species and may enable description of species biodiversity of this important group of vectors. It could be achieved using the entire mosquito specimen[⁹], legs[¹²], or any other insect body part.

In the present study, we have collected and sequenced approximately 700bp fragment of COI gene of 17 mosquito species from five genera including Anopheles, Culex, Aedes, Mansonia and Armigeres that are common in India and are important vectors of medical and veterinary importance. The unambiguous identification of these selected mosquito species was done with the use of mitochondrial marker gene sequence information and the molecular phylogenetic analyses were performed with genetic divergence to understand the distance between the genus of mosquitoes and to evaluate the evolutionary relationship among them. The study was conducted in Mananthavady Taluk of Wayanad, Kerala, India where the climate, with its abundance of water bodies and intermittent rain, is optimal for mosquitoes to thrive and transmit disease-causing pathogens to humans.

MATERIAL & METHODS

Mosquito specimens used in the study were collected from different sites of the study area from 2019 to 2021. Preliminary identification was done using authentic taxonomic keys with the help of experts from ICMR-Vector Control Research Centre, Puducherry and the assorted specimens were subjected to molecular taxonomic studies. The total genomic DNA was isolated from single whole mosquito sample using a DNA extraction kit (Macherey-Nagel Inc.) according to the manufacturer’s instructions. For DNA barcode analysis, the 700 bp region of mitochondrial COI gene was targeted and amplified with the primers: forward 5’ - GGA TTT GGA AAT TGA TTA GTT CCT T - 3’ and reverse 5’ - AAA AAT TTT AAT TCC AGT TGG AAC AGC - 3^’9. The gel purified PCR products were sequenced using Sanger’s dideoxy chain termination method[¹³] using an ABI 3730XL automated sequencer. The consensus obtained from forward and reverse sequences was taken for searching similarity with other sequences in NCBI database using the BLAST tool.

For the selection of the model to be implemented for phylogenetic analysis, the best fit model test was used to determine the optimum substitution models. The GTR+G model was selected from 24 different nucleotide substitution models for the 17 original sequences of the selected species in the present study based on the lowest AIC and BIC values. The robustness of the clades of the tree was determined using bootstrap analysis of 1000 replications with the elimination of all the codons having gaps and missing data, and the maximum likelihood (ML) tree was generated with the outgroup Musca domestica.

Ethical statement: Not applicable

RESULTS

The 17 mosquito species under five genera namely Aedes, Culex, Anopheles, Mansonia and Armigeres were collected randomly from selected sites [Table 1]. Aedes albopictus and Ae. vittatus are the secondary vectors of dengue, Chikungunya and yellow fever. Ae. albopictus is also a Zika virus carrier. Japanese encephalitis (JE) vectors outnumbered all other vectors collected from the area with twelve species [Figure 1]. Armigeressubal- batus is an incriminated vector of JE[^14,15,16] and this species outnumbered every other species in the collection, regardless of season or location. All the vectors identified in India for lymphatic filariasis viz; Culex quinquefasciatus, Mansonia indiana, M. uniformis and Aedes niveus were collected from the area. The sole malaria vector found in this area was Anopheles stephensi.

Figure 1: The pie-chart showing the vectoral status of mosquitoes from MananthavadyTaluk of Wayanad district, Kerala. JE; Japanese encephalitis

Table 1: List of vector mosquitoes and their vectoral status from Mananthavady Taluk of Wayanad district, Kerala, India

Genomic DNA extracted from the whole insect sample had appreciable quality of >10 kb which yielded the amplified PCR product size of approximately 700 bp. All the sequences had an accurate match with their own haplotypes in the NCBI with significant percentage of identities. These were submitted and authenticated in the NCBI GenBank with respective accession numbers (Table 2). All DNA sequences of the present study showed 98 to 100 percent similarity with the sequences in the BLAST, which shows the accuracy of the identification. The Maximum Likelihood tree was constructed using the species in this study and resulted in monophyletic clades with discrete clusters [Figure 2].

Figure 2: Phylogenetic tree (Maximum-Likelihood method) representing the mosquito vectors on partial COI gene sequences with Musca domesticaas outgroup.

Table 2: the GenBank Accession numbers of mosquito vectors collected from Mananthavady Taluk of Wayanad district, Kerala

The genus Culex, Mansonia and Anopheles formed separate clades and species belonging to the same genera clustered together. Pairwise cluster was shown between the species Cx. vishnui and Cx. pseudovishnui, Cx. infulaand Cx. bitaeniorhyncus, Cx. gelidus and Cx. pallidothorax, Cx. fuscocephala and Cx. quinquefasciatus, An. stephensiand An. barbirostris, Ae. vittatus and Ae. niveus and M. indiana and M. uniformis. The lowest genetic difference was shown for species Cx. infulaand Cx. bitaeniorhyncusfollowed by Cx. vishnui and Cx. pseudovishnui with the bootstrap value of 100 and 98 respectively. Out of the three Aedes species, Ae. vittatus and Ae. niveus formed a single clade whereas Ae. albopictus was clustered along with Armigeres sabalbatus species as they show more similarity. The mean distances of COI gene sequence by Kimura 2 parameter was also assessed (Table 3).

Table 3: The COI gene sequence distance (K2P) of mosquitoes

DISCUSSION

The ability of DNA barcodes to identify species reliably, quickly and cost effectively has particular importance in medical entomology, where molecular approaches to species diagnoses are often of great benefit in the identification of all life stages, from eggs to adults. The mitochondrial cytochrome c oxidase subunit I (COI) gene region of the mitochondrial genome is the gold standard for barcode identification of species[¹⁸] and has proved invaluable for distinguishing between mosquito species[^19,20,21]. The COI gene sequences was generated and compared with haplotypes retrieved from NCBI and all the sequences generated in the study contained no indels and the alignments were straightforward. The sequences lacked nonsense or stop codons, which is the characteristic feature of the mitochondrial gene. Codon positions included were 1^st + 2^nd + 3^rd. All positions containing gaps and missing data were eliminated. There were 639 positions in the final dataset.

The GTR+G model was selected for ML analysis of the seventeen sequences representing the partial COI gene sequence. The estimated Transition/Transversion bias (R) is 0.80. Substitution pattern and rates were estimated under the Kimura 2-parameter model[²²]. The nucleotide frequencies are A = 25.00%, T/U = 25.00%, C = 25.00%, and G = 25.00%. The maximum log likelihood for this computation was -3872.171. The sequences were highly AT rich, which ranged from 39.6 to 28.9 and GC content of 16.3 to 15.2.

Transitional substitution rates were found to be higher between T and C (21.8) and lower between G and A (4.48). T/A and T/G (10.5 each) showed more transversional substitution than G/T and G/C. (4.43 each). The shape parameter for the discrete Gamma Distribution had an estimated value of 0.2046. The Tamura-Nei[²³] model (+G) was used to estimate the substitution pattern and rates. To describe evolutionary rate variations among sites (5 categories, [+G]), a discrete Gamma distribution was utilised. The mean evolutionary rates per site in these categories were 0.00, 0.01, 0.13, 0.68, and 4.18 respectively. The nucleotide frequencies were A = 29.20%, T/U = 38.82%, C = 16.38%, and G = 15.60%. For estimating ML values, a tree topology was automatically computed. The maximum log likelihood for this computation was -2932.556. The overall mean distance by Kimura 2 parameter is 0.14. The maximum pairwise distance was shown by Mansonia indianafrom all other species except M. uniformis. Within-group distance is 0.13 and between-group distance is 0.177. Culex(0.09) had a greater distance within the group than Anopheles (0.13). Mansonia and Culexhad the greatest mean distance (0.181), whereas Aedesand Culexhave the least (0.128). Within a subpopulation, mean diversity was 0.11, while overall population diversity was 0.13. The coefficient of differentiation was 0.14.

As morphological characterization is stage specific, morphological identification of mosquitoes becomes difficult. Even though differences in the abdominal terga and supra-alar of adult mosquitos can easily separate them[²⁴], their larval stages are physically similar. Adults of Cx. vishnui and Cx. pseudovishnui, on the other hand, have numerous outward traits that make them difficult to distinguish. They can be distinguished during the larval stage. However, growing larvae into adults, which is required for taxonomic classification of some species, is time and resource consuming^[25]. Our findings showed close congruence of lowest genetic divergence (0.1 %) between the two species of Culex (Cx. vishnuiand Cx. pseudovishnui). As a result, it is clear that supplementing traditional taxonomy with DNA-based molecular approaches has the potential to enhance vector surveillance.

CONCLUSION

Overall, this research adds to our understanding of the molecular evolution of mosquito vectors of medical and veterinary value, which could help us to better biotechnological technologies used in Culicidaecontrol programmes. The current study created COI barcodes for several major mosquito vectors collected in India, demonstrating the utility of the DNA barcode in identifying species despite prior taxonomic studies and phylogenetic tree was created to understand the evolutionary relationship among them. To summarise, the current findings clearly demonstrate that single gene sequences (COI) can be used to identify mosquitoes as COI has the highest genus-wide resolution among the evaluated markers. As a result, we recommend launching DNA barcodes for all mosquito species found in southern India in the near future to aid in the identification and quarantine of mosquito vectors, as well as the monitoring of mosquito-borne illness epidemics.

Conflict of interest: None

Acknowledgements

The financial support and infrastructure facilities provided by the University of Calicut for this work is gratefully acknowledged. Thanks are due to Dr. Natarajan and co-workers, ICMR-Vector Control Research Centre (ICMR-VCRC), Puducherry for their valuable suggestions on the proper identification and taxonomy of mosquitoes.