# Mitochondrial and microbial diversity of the invasive mosquito vector species Culex tritaeniorhynchus across its extensive inter-continental geographic range

Claire L Jeffries, Luciano M Tantely, Perparim Kadriaj, Marcus S C Blagrove, Ioanna Lytra, James Orsborne, Hasan Mohammad Al-Amin, Abdul Rahim Mohammed, Mohammad Shafiul Alam, Romain Girod, et al.

<figure><img src="image_1.png" /></figure>

## ► To cite this version:

Claire L Jeffries, Luciano M Tantely, Perparim Kadriaj, Marcus S C Blagrove, Ioanna Lytra, et al.. Mitochondrial and microbial diversity of the invasive mosquito vector species Culex tritaeniorhynchus across its extensive inter-continental geographic range. Wellcome Open Research, 2024, 9 (18), 10.12688/wellcomeopenres.20761.1. hal-05131008

HAL Id: hal-05131008

https://hal.science/hal-05131008v1

Submitted on 26 Jun 2025

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

<figure><img src="image_2.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
<figure><img src="image_3.png" /></figure>

Check for updates

RESEARCH ARTICLE

# Mitochondrial and microbial diversity of the invasive mosquito vector species *Culex tritaeniorhynchus* across its extensive inter-continental geographic range [version 1; peer review: awaiting peer review]

Claire L. Jeffries<fnref n="1" />, Luciano M Tantely<fnref n="1" /> ID<fnref n="2" />, Perparim Kadriaj<fnref n="3" />, Marcus S C Blagrove ID<fnref n="4" />,<fnref n="5" />, Joanna Lytra<fnref n="6" />, James Orsborne<fnref n="1" />, Hasan Mohammad Al-Amin<fnref n="7" />,<fnref n="8" />, Abdul Rahim Mohammed ID<fnref n="9" />, Mohammad Shafiul Alam ID<fnref n="7" />, Romain Girod<fnref n="2" />, Yaw A Afrane ID<fnref n="9" />, Silvia Bino<fnref n="3" />, Vincent Robert<fnref n="10" />, Sebastien Boyer<fnref n="2" />,<fnref n="11" />, Matthew Baylis<fnref n="5" />,<fnref n="12" />, Enkelejda Velo ID<fnref n="3" />, Grant L Hughes ID<fnref n="13" />, Thomas Walker ID<fnref n="1" />,<fnref n="14" />

**V1** First published: 12 Jan 2024, 9:18
https://doi.org/10.12688/wellcomeopenres.20761.1

Latest published: 12 Jan 2024, 9:18
https://doi.org/10.12688/wellcomeopenres.20761.1

**Open Peer Review**

**Approval Status** AWAITING PEER REVIEW

Any reports and responses or comments on the article can be found at the end of the article.

## Abstract

## Background

*Culex (Cx.) tritaeniorhynchus* is an invasive mosquito species with an

<footnote n="1">¹Department of Disease Control, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK</footnote>

<footnote n="2">²Unite d'entomologie medicale, Institute Pasteur de Madagascar, Antanarivo, Madagascar</footnote>

<footnote n="3">³Vector Control Unit, Control of Infectious Diseases Department, Institute of Public Health, Tirana, Albania</footnote>

<footnote n="4">⁴Department of Evolution, Ecology and Behaviour, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, England, UK</footnote>

<footnote n="5">⁵Health Protection Research Unit on Emerging and Zoonotic Infections, University of Liverpool, Liverpool, England, UK</footnote>

<footnote n="6">⁶Department of Entomology and Agricultural Zoology, Benaki Phytopathological Institute, Athens, Greece</footnote>

<footnote n="7">⁷Infectious Diseases Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh</footnote>

<footnote n="8">⁸Berghofer Medical Research Institute, Queensland Institute of Medical Research, Brisbane, Australia</footnote>

<footnote n="9">⁹Department of Medical Microbiology, University of Ghana Medical School, University of Ghana, Accra, Greater Accra Region, Ghana</footnote>

<footnote n="10">¹⁰MIVEGEC, CNRS, Institute of Research for Development (IRD), University of Montpellier, Montpellier, France</footnote>

<footnote n="11">¹¹Medical and Veterinary Entomology Unit, Institut Pasteur du Cambodge, Phnom Penh, Cambodia</footnote>

<footnote n="12">¹²Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, England, UK</footnote>

<footnote n="13">¹³Departments of Vector Biology and Tropical Disease Biology, Centre for Neglected Tropical Disease, University of Liverpool, Liverpool, England, UK</footnote>

<footnote n="14">¹⁴School of Life Sciences, University of Warwick, Coventry, England, UK</footnote>
extensive and expanding inter-continental distribution, currently reported across Asia, Africa, the Middle East, Europe and now Australia. It is an important vector of medical and veterinary pathogens which cause significant morbidity and mortality in human and animal populations. Across regions endemic for Japanese encephalitis virus (JEV), *Cx. tritaeniorhynchus* is considered the major vector and has also been shown to contribute to the transmission of several other zoonotic arboviruses including Rift Valley fever virus (RVFV) and West Nile virus (WNV).

## Methods

In this study, we used laboratory vector competence experiments to determine if *Cx. tritaeniorhynchus* from a Southern European population were competent JEV vectors. We also obtained samples from multiple geographically dispersed *Cx. tritaeniorhynchus* populations from countries within Europe, Africa, Eurasia and Asia to perform phylogenetic analysis to measure the level of mitochondrial divergence using the *cytochrome oxidase subunit 1 (CO1)* gene. We also undertook bacterial 16S rRNA gene amplicon sequencing to determine microbial diversity and used multi-locus sequence typing (MLST) to determine any evidence for the presence of strains of the naturally occurring endosymbiotic bacterium *Wolbachia*.

## Results

*Cx. tritaeniorhynchus* from a Greek population were shown to be competent vectors of JEV with high levels of virus present in saliva. We found a significant level of mitochondrial genetic diversity using the mosquito *CO1* gene between geographically dispersed populations. Furthermore, we report diverse microbiomes identified by 16S rRNA gene amplicon sequencing within and between geographical populations. Evidence for the detection of the endosymbiotic bacteria *Wolbachia* was confirmed using *Wolbachia*-specific PCR and MLST.

## Conclusions

This study enhances our understanding of the diversity of *Cx. tritaeniorhynchus* and the associated microbiome across its inter-continental range and highlights the need for greater surveillance of this invasive vector species in Europe.

## Plain Language Summary

The mosquito species *Culex* (*Cx.*) *tritaeniorhynchus* is expanding its range and is now present in over 50 countries across Asia, Africa, the Middle East, Europe and now Australasia. It can transmit human and animal pathogens, resulting in significant morbidity and mortality. This species transmits Japanese encephalitis virus in endemic areas of
Asia, and it has also been shown to contribute to the transmission of
several other viruses that can infect humans, including Rift Valley
fever virus and West Nile virus. In this study, we firstly undertook
some lab experiments to show that *Cx. tritaeniorhynchus* from a
Southern European population are competent vectors of Japanese
encephalitis virus. We also obtained field mosquitoes from countries
within Europe, Africa, Eurasia and Asia and used phylogenetic analysis
to demonstrate a high level of mitochondrial divergence within and
between populations. In addition, we analysed the bacteria present
within mosquitoes and found a high level of microbial diversity.
Finally, we present evidence for the presence of *Wolbachia*
endosymbiotic bacteria in some populations of this mosquito species.
This study highlights the need for greater surveillance of this invasive
vector species – particularly in Europe.

Keywords

mosquitoes, Wolbachia, arboviruses, microbiome

**Corresponding author:** Thomas Walker (thomas.walker.1@warwick.ac.uk)

**Author roles:** **Jeffries CL:** Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing; **Tantely LM:** Investigation, Methodology, Writing – Review & Editing; **Kadriaj P:** Investigation, Methodology, Writing – Review & Editing; **Blagrove MSC:** Investigation, Methodology, Writing – Review & Editing; **Lytra I:** Investigation, Methodology, Writing – Review & Editing; **Orsborne J:** Investigation, Methodology, Writing – Review & Editing; **Al-Amin HM:** Investigation, Methodology, Writing – Review & Editing; **Mohammed AR:** Investigation, Methodology, Writing – Review & Editing; **Alam MS:** Investigation, Methodology, Writing – Review & Editing; **Girod R:** Investigation, Methodology, Writing – Review & Editing; **Afrane YA:** Investigation, Methodology, Writing – Review & Editing; **Bino S:** Investigation, Methodology, Writing – Review & Editing; **Robert V:** Investigation, Methodology, Writing – Review & Editing; **Boyer S:** Investigation, Methodology, Writing – Review & Editing; **Baylis M:** Investigation, Methodology, Writing – Review & Editing; **Velo E:** Investigation, Methodology, Supervision, Writing – Review & Editing; **Hughes GL:** Formal Analysis, Investigation, Methodology, Project Administration, Supervision, Writing – Review & Editing; **Walker T:** Conceptualization, Data Curation, Formal Analysis, Funding Acquisition, Investigation, Methodology, Project Administration, Resources, Supervision, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

**Competing interests:** No competing interests were disclosed.

**Grant information:** This study was supported by grants from Wellcome (101285); the European Food Safety Authority (EFSA) and the European Centre for Disease Control (ECDC); the Medical Research Council (ZK/16-041); the BBSRC/DEFRA (BB/W002906/1); the BBSRC (BB/T001240/1, BB/K018507/1, BB/V011278/1; BB/X018024/1; BB/W018446/1); Royal Society Wolfson Fellowship (RSWF\R1\180013); UK Research and Innovation (20197, 85336); and the National Institute for Health Research (NIHR2000907).

*The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.*

**Copyright:** © 2024 Jeffries CL et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**How to cite this article:** Jeffries CL, Tantely LM, Kadriaj P *et al.* Mitochondrial and microbial diversity of the invasive mosquito vector species *Culex tritaeniorhynchus* across its extensive inter-continental geographic range [version 1; peer review: awaiting peer review] Wellcome Open Research 2024, **9**:18 https://doi.org/10.12688/wellcomeopenres.20761.1

**First published:** 12 Jan 2024, **9**:18 https://doi.org/10.12688/wellcomeopenres.20761.1
## Introduction

The invasive mosquito vector species *Culex* (*Cx.*) *tritaeniorhynchus* has a wide and expansive distribution which includes populations in over 50 countries. Ranging across Asia, the Middle East and Africa (*Jeffries & Walker, 2015*), in recent decades it has been reported in Europe (*Samanidou & Harbach, 2003*), Eurasia (*Gugushvili, 2002*), Cape Verde off western Africa (*Alves et al., 2014*) and was recently recorded for the first time in Australia (*Lessard et al., 2021*). *Cx. tritaeniorhynchus* is the major vector of Japanese encephalitis virus (JEV) in Asia and the Pacific (*Jeffries & Walker, 2015*) and resulting JEV transmission leads to an estimated 50,000 – 175,000 cases of human disease annually (*Campbell et al., 2011; Erlanger et al., 2009*). Estimates suggest JE clinical disease presentations account for only 1% of total viral infections, indicating over-all occurrence of human JEV infections could be in the region of 5 – 17.5 million each year, with almost four billion people living in 24 endemic countries at risk (*Jeffries & Walker, 2015; Weaver & Reisen, 2010*). There have also been recent cases of JEV detection in mosquitoes and birds in Italy (*Platonov et al., 2012; Ravanini et al., 2012*) and an autochthonous human case in Angola, Africa (*Simon-Loriere et al., 2017*), in addition to the recent JEV outbreak in Australia, highlighting the possibilities of future viral spread and establishment in novel regions and naïve populations (*Gao et al., 2019; Lord, 2021; Weaver & Reisen, 2010*). *Cx. tritaeniorhynchus* is also capable of transmitting several other significant zoonotic arboviruses including RVFV (*Jupp et al., 2002*) and WNV (*Akhter et al., 1982; Fontenille, 1989; Reisen et al., 1982; Turell et al., 2006*) with viral geographic distributions extensively overlapping with the current range of *Cx. tritaeniorhynchus*.

The widespread presence of this invasive species warrants further investigation to determine if outbreaks could occur beyond the current arboviral transmission zones. *Cx. tritaeniorhynchus* is well established in Southern European countries such as Greece and Albania but the capacity to transmit JEV has not been assessed to date. Although laboratory vector competence studies can measure the capability and efficiency of a mosquito vector population to transmit arboviruses under experimental conditions, the vectorial capacity in wild populations is influenced by multiple factors, including genetic diversity and the composition of the microbiota (*Bolling et al., 2015; Cansado-Utrilla et al., 2021; Franz et al., 2015; Jupatanakul et al., 2014; Kilpatrick et al., 2010; Takken & Verhulst, 2013*). Although several studies have investigated genetic diversity and vector competency in *Cx. tritaeniorhynchus*, they were mostly confined to populations within the same region or country - largely within the Asian continent (*Ashfaq et al., 2014; Hayes et al., 1984; Luo et al., 2016; Philip Samuel et al., 2010; Sakai & Baker, 1972; Takahashi, 1980; Turell et al., 2006; Xie et al., 2021*).

Mosquito vectors have associations with a wide diversity of microbes (*Jupatanakul et al., 2014*), including bacteria such as *Wolbachia*, *Asaia*, *Serratia* and *Pseudomonas*, which can affect vectorial capacity (*Bolling et al., 2015; Minard et al., 2013*). Some studies on the native microbiome or associated

bacteria have been carried out in *Cx. tritaeniorhynchus* (*Guo et al., 2016; Kittayapong et al., 2000; Tsai et al., 2004*), but cross population microbiome composition studies comparing within and between geographically disperded populations has not been extenstive studied. In this study, we undertook laboratory vector competence experiments using an early generation colony of *Cx. tritaeniorhynchus* originating from Greece to demonstrate that European populations are competent vectors of JEV. We also obtained geographically dispersed *Cx. tritaeniorhynchus* from multiple populations (spanning four continents) to examine the mitochondrial and microbial diversity of this invasive and medically important vector species. Our results show evidence for mitochondrial divergence, a high level of microbial diversity and the presence of the endosymbiotic bacterium *Wolbachia* at only low prevalence and in only some geographic populations.

## Methods

### European population colonisation and JEV vector competence experiments

Field-collected *Cx. tritaeniorhynchus* larvae (~500) from Messolonghi, Greece were transported to the London School of Hygiene and Tropical Medicine for initiation of a colony. A range of techniques were employed to optimise insectary conditions for all mosquito life stages including large rearing cages (110 × 55 × 55 cm), light cycles with dusk/dawn simulation and swarm markers. JEV vector competence was assessed on the fourth generation at the Liverpool School of Tropical Medicine. Blood meals (heparinised human blood, NHS transfusion service, Speke) containing JEV (strain CNS138-11), to a final concentration of 6 log 10 plaque-forming units/mL, were provided for three hours, using a Hemotek membrane feeding system and an odourised feeding membrane, to 5-7-day-old adult females from which sugar sources had been withheld for 24 hours. Blood-fed females were incubated at 27°C, 70% humidity, for 14 days prior to collection of saliva using a forced salivation technique (*Moreira et al., 2009*). The head/thorax and abdomen were separated for surviving females after the 14-day incubation and the dissected body parts were stored for RNA preservation. RNA was extracted using Qiagen RNeasy kits from all saliva and body-part samples and tested by JEV-specific quantitative RT-PCR analysis (*Yang et al., 2004*) to determine infection rates. qPCR reactions were prepared using 5 µL of FastStart SYBR Green Master mix (Roche Diagnostics) with a final concentration of 1µM of each primer, 1 µL of PCR grade water and 2 µL template DNA, to a final reaction volume of 10 µL. Prepared reactions were run on a Roche LightCycler 96 System and amplification was followed by a dissociation curve (95°C for 10 s, 65°C for 60 s and 97°C for 1 s) to ensure the correct target sequence in addition to the inclusion of positive controls (RNA extracted from JEV strain CNS138-11) and no template controls (NTCs).

### Mosquito field collections

*Culex tritaeniorhynchus* specimens were obtained from field-collections in Albania, Greece, Georgia, Ghana, Madagascar and Bangladesh (*Figure 1*). The locations, year, GPS co-ordinates and number of specimens obtained are shown in Table 1. Specimens were collected in Albania during country-wide
<figure><img src="image_4.png" /></figure>

**Figure 1.** Locations of collection sites for *Cx. tritaeniorhynchus* samples analysed in this study. Yellow dots represent estimated collection locations within the six countries in our study (GPS co-ordinates, collection methods and number of specimens are shown in Table 1). Maps were produced using Mapchart licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

<table><caption>**Table 1.** *Cx. tritaeniorhynchus* collection locations and samples collected. Latitude and longitude coordinates are in decimal degrees. NBFF = non-blood-fed females, BFF = blood-fed females, \*denotes from field-collected larvae.</caption><thead><tr><th rowspan="2">Country</th><th rowspan="2">Year, Location (latitude, longitude)</th><th colspan="6">Cx. tritaeniorhynchus samples</th></tr><tr><th>Larvae</th><th>Adults*</th><th>NBFF</th><th>BFF</th><th>Males</th><th>Total</th></tr></thead><tbody><tr><td rowspan="7">Albania</td><td>2015, Fier (40.724,19.556)</td><td>-</td><td>-</td><td>263</td><td>6</td><td>-</td><td>269</td></tr><tr><td>2016, Fier (40.724,19.556)</td><td>-</td><td>30</td><td>546</td><td>28</td><td>1</td><td>605</td></tr><tr><td>2017, Fier (40.724,19.556)</td><td>613</td><td>24</td><td>675</td><td>288</td><td>28</td><td>1628</td></tr><tr><td>2015, Lezhe (41.784,19.644)</td><td>-</td><td>16</td><td>2</td><td>4</td><td>-</td><td>22</td></tr><tr><td>2016, Lezhe (41.784,19.529)</td><td>-</td><td>-</td><td>4</td><td>-</td><td>-</td><td>4</td></tr><tr><td>2016, Lushnje (40.997,19.529)</td><td>-</td><td>-</td><td>1</td><td>-</td><td>-</td><td>1</td></tr><tr><td>2015, Sarande (39.876,20.005)</td><td>-</td><td>-</td><td>2</td><td>1</td><td>1</td><td>4</td></tr><tr><td rowspan="5"></td><td>2016, Sarande (39.876,20.005)</td><td>-</td><td>-</td><td>1</td><td>-</td><td>-</td><td>1</td></tr><tr><td>2016, Shkoder (42.068,19.513)</td><td>-</td><td>-</td><td>2</td><td>-</td><td>-</td><td>2</td></tr><tr><td>2015, Vlore (40.467,19.490)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>3</td><td>3</td></tr><tr><td>2016, Vlore (40.467,19.490)</td><td>-</td><td>-</td><td>16</td><td>-</td><td>-</td><td>16</td></tr></tbody></table>
<table><thead><tr><th rowspan="2">Country</th><th rowspan="2">Year, Location (latitude, longitude)</th><th colspan="6">Cx. tritaeniorhynchus samples</th></tr><tr><th>Larvae</th><th>Adults*</th><th>NBFF</th><th>BFF</th><th>Males</th><th>Total</th></tr></thead><tbody><tr><td rowspan="2">Greece</td><td>2014, Messolonghi (38.339,21.252)</td><td>500</td><td>60</td><td>-</td><td>-</td><td>-</td><td>560</td></tr><tr><td>2015, Tsereteli (41.423, 44.824)</td><td>2</td><td>-</td><td>-</td><td>-</td><td>-</td><td>2</td></tr><tr><td rowspan="2">Georgia</td><td>2015, Gordabani (41.464, 45.099)</td><td>5</td><td>-</td><td>-</td><td>-</td><td>-</td><td>5</td></tr><tr><td>2015, Mzianeti (41.474, 45.165)</td><td>3</td><td>-</td><td>-</td><td>-</td><td>-</td><td>3</td></tr><tr><td rowspan="6">Bangladesh</td><td>2013, Paba (24.378, 88.533)</td><td>-</td><td>-</td><td>10</td><td>1</td><td>-</td><td>11</td></tr><tr><td>2013, Puthia (24.405, 88.888)</td><td>-</td><td>-</td><td>1</td><td>2</td><td>-</td><td>3</td></tr><tr><td>2013, Bagmara (24.602, 88.900)</td><td>-</td><td>-</td><td>7</td><td>7</td><td>-</td><td>14</td></tr><tr><td>2013, Mohadevpur (24.939, 88.718)</td><td>-</td><td>-</td><td>-</td><td>8</td><td>-</td><td>8</td></tr><tr><td>2013, Manda (24.801, 88.749)</td><td>-</td><td>-</td><td>2</td><td>5</td><td>-</td><td>7</td></tr><tr><td>2015, Brickaville (-18.824, 49.077)</td><td>-</td><td>-</td><td>10</td><td>-</td><td>-</td><td>10</td></tr><tr><td rowspan="8">Madagascar</td><td>2015, Farafangana (-22.821, 47.819)</td><td>-</td><td>-</td><td>9</td><td>1</td><td>-</td><td>10</td></tr><tr><td>2015, Ihosy (-22.412, 46.129)</td><td>-</td><td>-</td><td>10</td><td>-</td><td>-</td><td>10</td></tr><tr><td>2015, Maevatanana (-17.027, 46.767)</td><td>-</td><td>-</td><td>9</td><td>1</td><td>-</td><td>10</td></tr><tr><td>2015, Mampikony (-16.100, 47.632)</td><td>-</td><td>-</td><td>1</td><td>29</td><td>-</td><td>30</td></tr><tr><td>2015, Miandrivazo (-19.533, 45.449)</td><td>-</td><td>-</td><td>9</td><td>1</td><td>-</td><td>10</td></tr><tr><td>2015, Toamasina (-18.148, 49.404)</td><td>-</td><td>-</td><td>10</td><td>-</td><td>-</td><td>10</td></tr><tr><td>2015, Tulear (-23.387, 43.717)</td><td>-</td><td>-</td><td>-</td><td>32</td><td>11</td><td>43</td></tr><tr><td>2016, Tsaramandroso (-16.367, 46.993)</td><td>-</td><td>-</td><td>14</td><td>23</td><td>6</td><td>43</td></tr><tr><td>Ghana</td><td>2017, Dogo (5.874, 0.560)</td><td>-</td><td>-</td><td>7</td><td>-</td><td>-</td><td>7</td></tr></tbody></table>

entomological surveys in 2015–2016, in addition to focused field-work collections in 2017, including in the rural village of Sop in the Fier district, south-western Albania. A variety of adult trapping techniques and larval dipping were used. Specimens were preserved in Invitrogen RNAlater at -20°C followed by -70°C long-term storage. Field-collected fourth instar larvae were obtained from three sites in south-eastern Georgia in September 2015; using larval dipping in semi-permanent water bodies with vegetation, then stored in 70% ethanol. In Ghana, specimens were collected as adults from Dogo village in the Greater Accra region in June 2017 (Orsborne et al., 2019). Adult specimens were preserved in Invitrogen RNAlater with cold storage. Collections in Madagascar were carried out in 2015–2016, from locations spanning various bioclimatic eco-type zones (Jeffries et al., 2018b), and specimens were preserved in RNAlater with cold storage to prevent RNA degradation. Adult collections in Bangladesh were carried out in Sept–Nov 2013 from five sites within two districts in the Rajshahi Division in western Bangladesh. Within the district of Rajshahi, mosquitoes were collected from the upazilas (sub-districts) of Paba, Puthia and Bagmara, and within the Naogaon district, specimens were obtained from the upazilas of Manda and Mohadevpur. Samples were stored dry with silica gel desiccant to prevent microbial growth.

## Morphological identification

Adult specimens were morphologically identified using keys appropriate for the geographic region (Günay et al., 2017; Lytra & Emmanuel, 2014b; Reuben et al., 1994; Robert et al., 2019; Samanidou & Harbach, 2003; Tantely et al., 2016), observing distinctive morphological features, including the presence of a clear white band on the proboscis, entirely dark wings and ringed tarsi (Samanidou & Harbach, 2003). Adult female mosquito physiological status was recorded and if wild-caught blood-fed, then the stage of digestion and time since blood-feeding was approximated using the Sella score method (Detinova, 1962; Martínez-de la Puente et al., 2013).

## Nucleic acid extraction and molecular species confirmation

Dependent upon the collection location, techniques and preservation methods, the relevant nucleic acid extraction methods were undertaken. All specimens were homogenised using a Qiagen Tissue Lyser II and Qiagen 3mm stainless steel beads. DNA was extracted from specimens using a Qiagen DNeasy Blood and Tissue kit according to the manufacturer's instructions. Some samples where subject to RNA extraction alone, or a modified method for simultaneous RNA and DNA co-extraction utilising Trizol reagent extraction protocol,
prior to column-based extraction of the relevant phase using Qiagen DNeasy or RNeasy kits. RNA eluates were converted to cDNA using Applied Biosystems High Capacity cDNA Reverse Transcription kits. To confirm morphological species identification, gDNA or cDNA was used in broad-specificity barcoding PCRs, followed by Sanger sequencing and phylogenetic analysis (as detailed for mitochondrial diversity analysis below) to confirm species identification.

## Intra- and inter-population mitochondrial diversity

Mitochondrial diversity was assessed through Sanger sequencing of amplified PCR products from multiple assays targeting the cytochrome oxidase subunit 1 (CO1) gene (Bernasconi et al., 2000; Folmer et al., 1994; Kumar et al., 2007; Zittra et al., 2016) depending on the geographic region. Sub-sample testing was used to select a primer set (Kumar et al., 2007) producing a ~700 base pair (bp) product for screening all geographical populations. A primer combination to amplify the full length CO1 gene, binding at the 5' and 3' tRNA respectively, produced a ~1150bp sequence (Bernasconi et al., 2000; Shaikevich & Zakharov, 2010; Simon et al., 1994).

## Consensus sequence and alignment assembly

Sequencing analysis was carried out in MEGA11 (Tamura et al., 2021) as previously described (Walker et al., 2021). All

mitochondrial CO1 nucleotide sequences for *Cx. tritaeniorhynchus* available on GenBank (NCBI: txid7178, 992 sequences) were downloaded and aligned with the 69 CO1 sequences generated in this study. Three CO1 alignments were constructed; (A) all *Cx. tritaeniorhynchus* sequences with coverage of the fragment generated by the *Kumar et al.* primer set (Kumar et al., 2007) (253 sequences, 686 positions) including concomitant species obtained during field-collections, (B) all *Cx. tritaeniorhynchus* CO1 gene full length sequences, maximising the length (20 sequences, 1538 positions), and (C) all *Cx. tritaeniorhynchus* CO1 sequences currently available with sufficient fragment overlap, to balance the length of alignment but maximise number of reference sequences included (1007 sequences, 414 positions). The positions of the alignments and primer binding regions according to the *Cx. tritaeniorhynchus* complete mitochondrial genome reference sequence NC_028616 is shown in Figure 2.

## Phylogenetic tree construction and analysis

Each alignment was examined using the “Find-Best-Fit Maximum Likelihood substitution model” for phylogenetic analysis and tree construction as previously described (Jeffries et al., 2021). Models used were the General Time Reversible model (Nei & Kumar, 2000) (GTR) or the Tamura three-parameter model (Tamura, 1992) (T92). The tree with the highest log

<figure><img src="image_5.png" /><figcaption>**Figure 2. CO1 primer sets and sequence alignment positions.** Excerpt of nucleotide sequence from the complete mitochondrial reference genome of *Cx. tritaeniorhynchus* (NC_028616). Red, underlined text – primer binding sites o background – nucleotides comprising the full CO1 gene; Blue, underlined – Kumar *et al.* primer binding sites; Blue background – Position of alignment (a) of sequence set binding regions; Text in bold – Location of alignment (b) maximizing the length and with almost full CO1 gene coverage; Green text – Location of alignment (c) maxi included.</figcaption></figure>
likelihood is shown. The percentage of trees in which the associated taxa clustered together is shown next to the branches. Initial tree(s) for the heuristic search were obtained automatically by applying Neighbor-Joining and BioNJ algorithms to a matrix of pairwise distances estimated using the Maximum Composite Likelihood (MCL) approach, and then selecting the topology with superior log likelihood value. The trees are drawn to scale, with branch lengths measured in the number of substitutions per site. Codon positions included were 1st+2nd+3rd+Noncoding. All positions containing gaps and missing data were eliminated. The phylogeny test was by Bootstrap method with 1000 replications. Evolutionary analyses were conducted in MEGA11 (Tamura et al., 2021).

## Mitochondrial diversity and haplotype analyses

Mitochondrial diversity of populations was further assessed through mitochondrial diversity metrics, analysis of haplotypes, generation of haplotype networks, and pairwise comparison of genetic differentiation, including both study-generated and available reference COI sequences. *Cx. tritaeniorhynchus* COI alignments were analysed using DnaSP V6.12.03 (Rozas et al., 2017) to assess sequence polymorphisms and determine nucleotide and haplotype diversity. Haplotype networks were constructed within PopART (Leigh & Bryant, 2015) using the TCS inference method (Clement et al., 2000).

Intra- and inter-group variation was assessed at the individual, country and regional population levels using Arlequin V3.5.2.2 (Excoffier & Lischer, 2010), with analysis of molecular variance (AMOVA) (Excoffier et al., 1992) and visualisation of outputs in R V3.5.0 (R Core Team, 2018).

## Bacterial 16S rRNA gene amplicon sequencing

Microbiomes of selected specimens were analysed using barcoded high-throughput amplicon sequencing of the bacterial 16S rRNA gene. To enable analysis of the differences in microbiome between species (*Cx. tritaeniorhynchus* and concomitant species), physiological status (blood-fed or non-blood-fed) and geographic location (both intra- and inter-country) samples were selected from specific groups for comparison (Table 2). Mosquito specimens were surface sterilised prior to extraction, and negative controls comprising both DNA extraction and RNA extraction-Reverse Transcription blanks were included alongside the samples. Sequencing of each extract was undertaken using universal 16S rRNA V3-V4 region primers (FOR: 5'-CCTACGGGNGGCWGCAG-3', REV: 5'-GGACTACHVGGGTATCTAATCC-3') (Klindworth et al., 2013) in accordance with standard Illumina 16S rRNA metagenomic sequencing library protocols with the Nextera XT Index Kit v2 used to barcode samples for multiplexing. Sequencing was performed on an Illumina MiSeq, with the MiSeq v2

<table><caption>**Table 2.** Sampling groups and associated information for 16S microbiome analysis. Abbreviations: N = Number of samples in that group, NBFF = Non-blood-fed-female, BFF = Blood-fed-female, NA type = Nucleic Acid type, gDNA = genomic DNA, cDNA = complementary DNA (RNA extracts after reverse-transcription).</caption><thead><tr><td>Group</td><td>Species</td><td>Country</td><td>Collection Location</td><td>N</td><td>Status</td><td>Body part</td><td>NA type</td></tr></thead><tbody><tr><td>AA</td><td><i>Cx. tritaeniorhynchus</i></td><td>Bangladesh</td><td>Paba, Rajashahi</td><td>10</td><td>NBFF</td><td>Whole</td><td>gDNA</td></tr><tr><td>AB</td><td><i>Cx. tritaeniorhynchus</i></td><td>Bangladesh</td><td>Bagmara, Rajashahi</td><td>7</td><td>NBFF</td><td>Whole</td><td>gDNA</td></tr><tr><td>B</td><td><i>Cx. tritaeniorhynchus</i></td><td>Albania</td><td>Fier (Sop)</td><td>16</td><td>NBFF</td><td>Whole</td><td>gDNA</td></tr><tr><td>C</td><td><i>Cx. pipiens</i></td><td>Albania</td><td>Fier (Sop)</td><td>16</td><td>NBFF</td><td>Whole</td><td>gDNA</td></tr><tr><td>D</td><td><i>Oc. caspius</i></td><td>Albania</td><td>Fier (Sop)</td><td>16</td><td>NBFF</td><td>Whole</td><td>gDNA</td></tr><tr><td>E</td><td><i>Cx. tritaeniorhynchus</i></td><td>Albania</td><td>Fier (Sop)</td><td>15</td><td>NBFF</td><td>Abdomen</td><td>cDNA</td></tr><tr><td>F</td><td><i>Cx. tritaeniorhynchus</i></td><td>Albania</td><td>Fier (Sop)</td><td>12</td><td>BFF</td><td>Abdomen</td><td>cDNA</td></tr><tr><td>G</td><td><i>Cx. tritaeniorhynchus</i></td><td>Albania</td><td>Vlore</td><td>10</td><td>NBFF</td><td>Abdomen</td><td>cDNA</td></tr><tr><td>H</td><td><i>Cx. tritaeniorhynchus</i></td><td>Madagascar</td><td>Brickaville</td><td>10</td><td>NBFF</td><td>Whole</td><td>cDNA</td></tr><tr><td>I</td><td><i>Cx. tritaeniorhynchus</i></td><td>Madagascar</td><td>Farafangana</td><td>9</td><td>NBFF</td><td>Whole</td><td>cDNA</td></tr><tr><td>J</td><td><i>Cx. tritaeniorhynchus</i></td><td>Madagascar</td><td>Ihosy</td><td>10</td><td>NBFF</td><td>Whole</td><td>cDNA</td></tr><tr><td>K</td><td><i>Cx. tritaeniorhynchus</i></td><td>Madagascar</td><td>Maevatanana</td><td>9</td><td>NBFF</td><td>Whole</td><td>cDNA</td></tr><tr><td>L</td><td><i>Cx. tritaeniorhynchus</i></td><td>Madagascar</td><td>Miandrivazo</td><td>9</td><td>NBFF</td><td>Whole</td><td>cDNA</td></tr><tr><td>M</td><td><i>Cx. tritaeniorhynchus</i></td><td>Madagascar</td><td>Toamasina</td><td>10</td><td>NBFF</td><td>Whole</td><td>cDNA</td></tr><tr><td>N</td><td><i>Cx. tritaeniorhynchus</i></td><td>Madagascar</td><td>Tsaramandroso</td><td>12</td><td>NBFF</td><td>Abdomen</td><td>cDNA</td></tr><tr><td>O</td><td><i>Cx. tritaeniorhynchus</i></td><td>Madagascar</td><td>Tsaramandroso</td><td>15</td><td>BFF</td><td>Abdomen</td><td>cDNA</td></tr><tr><td>P</td><td><i>Cx. antennatus</i></td><td>Madagascar</td><td>Tsaramandroso</td><td>14</td><td>NBFF</td><td>Abdomen</td><td>cDNA</td></tr></tbody></table>
(500 cycle) reagent kit, with libraries sequenced as 250bp
paired-end reads (PE).

Data cleaning, quality control and filtering

Microbiome bioinformatics analyses were carried out on demul-
tiplexed reads using “Quantitative Insights Into Microbial
Ecology” (QIIME)2 Core (q2cli) 2020.2 distribution (Bolyen
et al., 2019). Demultiplexed reads were divided according
to extract type of gDNA (16S of all microbiota present)
or cDNA (actively expressed microbial 16S) (along with
their respective blank control samples) and analysed sepa-
rately in downstream analysis. Reads were imported into
QIIME2 and the V3-V4 primer and Nextera adapter sequences
were removed using the “q2-cutadapt” plugin (Martin,
2011). Quality plots were generated and visualised using the
“q2-demux summarize” command to assess and select
optimal quality filtering parameters including truncation length
for any adaptor sequence removal. Quality filtering, denois-
ing and chimera removal was carried out using the “Diversive
Amplicon Denoising Algorithm” (DADA) “q2-dada2” plugin
(Callahan et al., 2016) (“denoise-paired” command, gDNA:
“p-trunc-len-f 231, p-trunc-len-r 229”; cDNA: “p-trunc-len-f 233,
p-trunc-len-r 229”) to group Amplicon Sequence Variants
(ASVs) within the data. The feature-table artifacts generated
were filtered to exclude features present within the blank
controls (“q2-feature-table filter-samples”).

Taxonomic identification of features

Taxonomic assignment of ASVs was carried out using
the “q2-feature-classifier” plugin (Bokulich et al., 2018)
(“classify-sklearn” command (Pedregosa et al., 2011)) with
a pre-trained SILVA classifier (Naive Bayes classifier was
pre-trained on the 16S rRNA SILVA SSU v138 99% refer-
ence database (Quast et al., 2013), with the V3-V4 primers).
The taxonomy classifier generated was used to remove
mitochondrial and chloroplast ASVs from each feature table
(“q2-taxa filter-table” plugin) to remove host and background
non-relevant features. The samples were then filtered further
(“q2-feature-table filter-features”) to remove features with
frequencies below 100, and to only include the relevant
samples for each comparative analysis. The taxonomic
assignments were visualised using “q2-taxa barplot” to show
relative taxonomic abundance across all individual samples.

Alpha and beta diversity analysis

Within the qiime2 phylogeny plugin, the “q2-phylogeny align-
to-tree-mafft-fasttree” command was used, incorporating rep-
resentative sequence artifacts from each of the gDNA and
cDNA groups (rep-seqs output from DADA2) to produce rooted
phylogenetic trees for diversity analysis. For each com-
parison set, using the respective filtered feature tables,
alpha and beta diversity analysis was conducted through the
qiime2 diversity plugin, using “qiime diversity core-metrics-
phylogenetic” (Faith, 1992). The sampling depth was selected
from visualising feature tables (“q2-feature-table summarize”)
for each comparison, generating alpha rarefaction visualisa-
tions (“q2-diversity alpha-rarefaction”) with “-p-max-depth” just
over the median frequency per sample from the feature table,

and then by balancing the number of features, with the number
of samples from each group retained (Weiss et al., 2017). The
diversity core metrics results were then generated and visu-
alised using the relevant alpha or beta “group-significance”
commands (Anderson, 2001; Kruskal & Wallis, 1952). Pair-
wise PERMANOVA tests with 999 permutations were used
for comparisons between groups for the variable of inter-
est and a significance level of P value <0.01 was used as the
threshold. The metrics consulted for alpha (within-group)
diversity were the Shannon diversity Index, Faith’s phylogenetic
diversity and the Evenness. For beta (between-group) diver-
sity the metrics consulted were the Bray-Curtis, Unweighted-
Unifrac (pairwise) and Weighted-Unifrac.

Differential abundance testing - ANCOM

To test for the presence of any differentially abundant taxa
within each sample comparison group the analysis of com-
position of microbiomes (ANCOM) method was used within
the qiime2 composition plugin (Mandal et al., 2015). The
“q2-composition add-pseudocount” command was used, fol-
lowed by “q2-composition ancom” with the relevant variable
selected for each comparison, to investigate if any association
may be apparent. Results were visualised in volcano plots,
and assessed through the test statistic, W, to determine
significance.

Wolbachia PCR detection and multi-locus strain typing

Amplification of *Wolbachia*-specific 16S rRNA gene sequences was undertaken targeting the conserved *Wolbachia* 16S rRNA gene using W-Spec primers (438bp) (Werren & Windsor, 2000), in addition to a primer set designed for quantitiave PCR (target length: 102bp) (Gomes et al., 2017). *Wolbachia* MLST was undertaken to characterise *Wolbachia* strains using the sequences of five conserved genes (*gatB*, *coxA*, *hcpA*, *ftsZ* and *fbpA*) as molecular markers to genotype each strain (Baldo et al., 2006). In addition, an alternative primer set targeting a 271bp fragment of the *ftsZ* gene sequence in *Wolbachia* strains from Supergroups A and B was used on selected samples (de Oliveira et al., 2015). PCR reactions and Sanger sequencing of *Wolbachia* MLST PCR products were carried out as previously described (Jeffries et al., 2018a). Sequencing analysis was carried out in MEGA11 (Tamura et al., 2021), using methodology previously described, with consensus sequences used to perform nucleotide BLAST (NCBI) database queries, and for *Wolbachia* gene searches against the *Wolbachia* MLST database (http://pubmlst.org/wolbachia). Phylogenetic analysis of MLST gene locus sequences was performed as previously described for the mosquito *COI* gene.

Results

JEV vector competence of a Cx. tritaeniorhynchus Greek
population

After incubation for 14 days following an infectious blood-
meal, high levels of JEV (strain CNS138-11) were detected
in both the abdomen and head/thorax of all (28/28)
surviving females, indicating JEV was successfully acquired
and disseminated (Figure 3). The mean qPCR Ct value for
<figure><img src="image_6.png" /><figcaption>**Figure 3.** JEV vector competence experiment on European *Cx. tritaeniorhynchus* colonised from Greece. Scatter dot plot of quantitative PCR data. Horizontal bars represent mean JEV copies/µl per group. Boxed numbers show the number of JEV positive samples / total number of samples tested per group.</figcaption></figure>

abdomen and head/thorax was 23.58 and 24.19 respectively. Our results also indicate 25/28 (89%) saliva extracts had detectable virus, with a mean qPCR Ct value of 26.93.

## Mitochondrial diversity of *Cx. tritaeniorhynchus* populations

Sequences from a total of 69 *Cx. tritaeniorhynchus* specimens, originating from six countries, spread across four continents were generated in this study. Sequence coverage and length was used to generate three *COI* gene analyses: 1) maximising coverage and comparison of the partial *COI* gene fragment (primers from (Kumar et al., 2007)) and concomitant species sequences, 253 sequences and 686 nucleotides; (Figure 4A) 2) maximising the length for comparison of the full *COI* gene, 20 sequences and 1538 nucleotides; (Figure 4B) and 3) maximising the number of comparative sequences, with sufficient *COI* fragment overlap, 1007 sequences and 414 nucleotides which demonstrates complex phylogenetic relationships (Figure 5). The earliest common ancestors were sequences from India and China and Asian-only clades represent ~70% (673/1007) of sequences.

Sequences from Georgia obtained in this study group most closely to sequences from Turkey and Kuwait (Figure 5 - blue inset sub-tree). The next monophyletic group with more geographically diverse sequences included a group from Madagascar (Figure 5, purple inset sub-tree). Another clade, developing from a group of Indian sequences, included sequences from Turkey, Ghana, Bangladesh, Albania and Greece (Figure 5 - green inset sub-tree). Lineages with the greatest extent of genetic distance (using *Cx. sitiens* as an outgroup and Asian ancestral sequences from India and China) were from Australia (Figure 5 - yellow inset sub-tree), followed by Madagascar and Europe.

## Global mitochondrial diversity metrics

Genetic diversity metrics were generated from 21 countries and 6 regions (Table 3). When all sequences were compared individually across the 414 nucleotide positions in 1007 sequences, 139 variable sites (S) and 444 haplotypes (h) were identified. The overall haplotype diversity (Hd) was 0.97864, the average number of nucleotide differences (K) was 9.16425, and the nucleotide diversity per site (Pi) was 0.02214. The
<figure><img src="image_7.png" /><figcaption>**Figure 4.** *Cx. tritaeniorhynchus* partial and full CO1 maximum likelihood phylogenetic trees. (A) Partial CO1 include concomitant species using GTR model +G, parameter = 1.1140 and [+I], 61.54% sites. Tree log likelihood = -4937.50, 253 sequences, 686 positions. (B) Full CO1 gene. Model: T92 +G, parameter = 0.0500 and [+I], 57.20% sites. Tree log likelihood = -2829.05, 20 sequences, 1538 positions.</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>**Figure 5.** *Cx. tritaeniorhynchus CO1* phylogenetic tree with maximum reference sequences. Partial *CO1* gene, maximum reference sequences. Model: T92 (Tamura, 1992) +G, parameter = 0.3850 and [+I], 47.76% sites. Tree log likelihood = -3611.47. 1009 sequences, 414 positions. Two *Cx. sitiens* sequences included as an outgroup.</figcaption></figure>
<table><caption>**Table 3.** *Cx. tritaeniorhynchus* population genetic diversity metrics. Total number of sites: 414. n: Number of samples; S: Number of variable sites; h: Number of haplotypes; Hd: Haplotype diversity; K: Average number of nucleotide differences; Pi: Nucleotide diversity (per site); PiJC: Nucleotide diversity (Jukes-Cantor).</caption><thead><tr><th>Region</th><th>Country</th><th>n</th><th>S</th><th>H</th><th>Hd</th><th>K</th><th>Pi</th><th>PiJC</th></tr></thead><tbody><tr><td rowspan="15">Asia</td><td>All (n=11)</td><td>909</td><td>137</td><td>412</td><td>0.97487</td><td>9.12217</td><td>0.02203</td><td>0.02265</td></tr><tr><td>Bangladesh</td><td>10</td><td>13</td><td>9</td><td>0.97778</td><td>2.77778</td><td>0.00671</td><td>0.00675</td></tr><tr><td>China</td><td>608</td><td>116</td><td>290</td><td>0.96684</td><td>10.07545</td><td>0.02434</td><td>0.02509</td></tr><tr><td>Japan</td><td>33</td><td>40</td><td>30</td><td>0.99432</td><td>12.97159</td><td>0.03133</td><td>0.03226</td></tr><tr><td>Pakistan</td><td>80</td><td>30</td><td>31</td><td>0.84778</td><td>2.44399</td><td>0.0059</td><td>0.00594</td></tr><tr><td>Singapore</td><td>6</td><td>9</td><td>6</td><td>1</td><td>3.2</td><td>0.00773</td><td>0.00778</td></tr><tr><td>South Korea</td><td>3</td><td>22</td><td>3</td><td>1</td><td>14.66667</td><td>0.03543</td><td>0.03653</td></tr><tr><td>Sri Lanka</td><td>7</td><td>7</td><td>5</td><td>0.85714</td><td>2</td><td>0.00483</td><td>0.00486</td></tr><tr><td>Vietnam</td><td>1</td><td>N/A</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Thailand</td><td>1</td><td>N/A</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Timor-Leste</td><td>1</td><td>N/A</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Australia</td><td>Australia</td><td>19</td><td>6</td><td>4</td><td>0.73099</td><td>2.33918</td><td>0.00565</td><td>0.00569</td></tr><tr><td rowspan="3">Africa</td><td>All (n=2)</td><td>34</td><td>22</td><td>19</td><td>0.95544</td><td>3.39037</td><td>0.00819</td><td>0.00825</td></tr><tr><td>Madagascar</td><td>28</td><td>16</td><td>14</td><td>0.93651</td><td>2.86508</td><td>0.00692</td><td>0.00697</td></tr><tr><td>Ghana</td><td>6</td><td>6</td><td>5</td><td>0.93333</td><td>2.2</td><td>0.00531</td><td>0.00534</td></tr><tr><td rowspan="6">Middle East</td><td>All (n=3)</td><td>4</td><td>8</td><td>4</td><td>1</td><td>4.5</td><td>0.01087</td><td>0.01098</td></tr><tr><td>Kuwait</td><td>2</td><td>1</td><td>2</td><td>1</td><td>1</td><td>0.00242</td><td>0.00242</td></tr><tr><td>Saudi Arabia</td><td>1</td><td>N/A</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>UAE</td><td>1</td><td>N/A</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>All (n=2)</td><td>22</td><td>13</td><td>8</td><td>0.85714</td><td>3.28571</td><td>0.00794</td><td>0.008</td></tr><tr><td rowspan="3">Eurasia</td><td>Turkey</td><td>13</td><td>12</td><td>6</td><td>0.82051</td><td>3.35897</td><td>0.00811</td><td>0.00818</td></tr><tr><td>Georgia</td><td>9</td><td>2</td><td>3</td><td>0.55556</td><td>0.88889</td><td>0.00215</td><td>0.00215</td></tr><tr><td>All (n=2)</td><td>19</td><td>3</td><td>4</td><td>0.64327</td><td>0.76023</td><td>0.00184</td><td>0.00184</td></tr><tr><td rowspan="2">Europe</td><td>Albania</td><td>11</td><td>3</td><td>4</td><td>0.6</td><td>0.69091</td><td>0.00167</td><td>0.00167</td></tr><tr><td>Greece</td><td>8</td><td>1</td><td>2</td><td>0.53571</td><td>0.53571</td><td>0.00129</td><td>0.0013</td></tr><tr><td colspan="2"><strong>Sequence totals</strong></td><td><strong>1007</strong></td><td><strong>139</strong></td><td><strong>444</strong></td><td><strong>0.97864</strong></td><td><strong>9.16425</strong></td><td><strong>0.02214</strong></td><td><strong>N/A</strong></td></tr></tbody></table>

highest within-country nucleotide diversity per site was seen in South Korea (Pi = 0.03543) and lowest was in Greece (Pi = 0.00129). Asian sequences produced the highest nucleotide diversity per site (Pi = 0.02203), and European sequences had the lowest within-region diversity (Pi = 0.00184).

## Haplotype networks and pairwise comparison analysis

*COI* haplotype networks using full-length *COI* gene sequences (20 sequences, 1500 positions) (Figure 6A) suggested a linear pattern with sequences from Asia clustering separately to sequences from Eurasia, Europe and Africa (the latter being most divergent from the Asia haplogroup). Partial *COI* gene

sequences (1007 sequences, 414 positions) (Figure 6B) produced a more complex haplotype network with one group from South Asia and two groups from East Asia. Haplotypes found in Australia and Timor-Leste appear to be branching from the large South Asian cluster. The haplotypes from Georgia appeared to branch from haplotypes present in Turkey and the Kuwait, sitting between the two large South, and East Asian foundational haplogroups. In a separate cluster, haplotypes from Greece and Albania branched off from the main South Asian haplogroup, linked alongside some haplotypes present in Turkey and Ghana. The haplotype present in Saudi Arabia also originated from this branch, and the
<figure><img src="image_9.png" /><figcaption>**Figure 6.** CO1 haplotype networks for Cx. tritaeniorhynchus. (A) Full CO1 gene haplotype network for Cx. tritaeniorhynchus (maximising the length of sequences). (B) Global partial CO1 haplotype network for Cx. tritaeniorhynchus (maximising number of reference sequences). Haplotype networks were constructed using the TCS network method in PopArt (Leigh & Bryant, 2015) with nodes coloured according to country-of-origin.</figcaption></figure>
haplotypes present in Madagascar then extended and diverged further from the end of this branch. Pairwise comparison analysis heatmaps for differences in genetic diversity within and between populations (Figure 7) revealed sequences from Australia as having the greatest difference to other countries/regions, and sequences from East Asia having the greatest intra-group differences. The matrix of pairwise fixation index ($F_{ST}$) indicates high genetic differentiation between populations in different countries and regions, particularly for the Australian, as well as the African and European groups. The divergence time between populations is also relatively lower for these populations.

## Bacteria identified using microbiome analysis

We compared the composition and diversity of microbes present between collection locations or countries, physiological states (blood-fed or non-blood-fed), or between *Cx. tritaeniorhynchus* and concomitant mosquito species (Table 2). Species of potential relevance to mosquito biocontrol were detected including *Wolbachia*, *Asaia*, *Serratia*, *Pseudomonas* and *Apibacter* but presence and abundance levels were variable across individuals and populations. From 57 Madagascar samples, 34 had *Apibacter* (0.05–99.87% relative abundance), seven had *Pseudomonas* (1.0–29.92%), three had *Asaia* (1.30–34.06%) and one had *Serratia* (20.38%). Pathogenic bacteria were also detected including *Escherichia shigella*, *Vibrio cholerae* and species within the *Bartonella*, *Anaplasma*, *Rickettsia*, *Mycoplasma*, *Enterobacter*, *Helicobacter* and *Proividencia* genera. *Bartonella* was found in an Albania sample at a relative abundance of 27.45%. *Escherichia shigella* was found in two Albanian samples (5.81% and 0.34% relative abundance) with this second sample also containing *Vibrio cholerae* at 6.28%. In Madagascar, *Escherichia shigella* was identified in five specimens with abundance ranging from 0.41–30.00%, *Bartonella* in one specimen with 45.32% abundance and this specimen also had *Pseudomonas* at 8.63% abundance. *Anaplasma* was also found in Madagascar samples with relative abundance ranging from 5.02–73.71%. Division down to taxonomic level 7 showed these ASVs were identified as *Anaplasma marginale*, *Anaplasma platys* and the rest classified within the *Anaplasma* genus. *Mycoplasma* was also identified in seven individuals (0.33–21.61%) and *Escherichia shigella* in six individuals from Madagascar (0.03–1.91%).

## Microbiome diversity analysis

Concomitant species comparisons were possible for mosquitoes collected from Fier in Albania and Tsaramandroso in Madagascar. For Fier, gDNA samples from whole, non-blood-fed *Cx. tritaeniorhynchus* (n=16), *Cx. pipiens* (n=16) and *Oc. caspius* (n=16) specimens demonstrated variation in microbial composition. Alpha diversity within each species group showed no significant differences, however, beta diversity analysis showed clear differences between the species (Bray-Curtis p=0.001 and Weighted-Unifrac p=0.005). ANCOM identified *Wolbachia* as the only significant differentially abundant feature between the groups (W=265) due to high abundance in *Cx. pipiens*. From Tsaramandroso, cDNA extracted from abdomens of non-blood-fed female *Cx. tritaeniorhynchus* (n=12) and *Cx. antenatus* (n=14) demonstrated no significant difference in alpha or beta diversity and no significant differentially abundant taxa in ANCOM analysis. Comparisons were also made from

abdomens of non-blood-fed and blood-fed female specimens collected from Fier (non-blood-fed n=15, blood-fed n=12) and Tsaramandroso (non-blood-fed n=12, blood-fed n=15). For both countries, alpha- and beta-diversity and ANCOM highlighted no differences which were statistically significant.

## Microbiome variation of intra-country *Cx. tritaeniorhynchus* populations

For intra-country comparisons specimens from two sites 35km apart in Bangladesh were compared: Paba (n=10) and Bagmara (n=7). No statistically significant differences were found through alpha- or beta-diversity, or ANCOM analysis. Within Albania, cDNA from non-blood-fed female abdomens also collected 35 km apart from Fier (n=15) and Vlore (n=10) were compared. The differences between individuals within these groups were found to be significant (Faith's phylogenetic diversity metric, p=0.0087), as well as between the groups (Unweighted-Unifrac, p=0.016) and *Enterobacteriaceae* was found to be significantly differentially abundant (ANCOM, W=156), with a higher abundance in Vlore than in Fier. For Madagascar, the microbiome data was generated from cDNA extracted from whole non-blood-fed females from 6 sites; Brickaville (n=10), Farafangana (n=9), Ihosy (n=10), Maevatanana (n=9), Miandrivazo (n=10) and Toamasina (n=10). Alpha diversity did not highlight any significant difference between individuals within groups, but beta-diversity showed a difference between the locations (overall Weighted-Unifrac, p=0.003), with significance between Brickaville-Miandrivazo (p=0.012), Farafangana-Miandrivazo (p=0.012), Ihosy-Miandrivazo (p=0.001) and Maevatanana-Miandrivazo (p=0.004). ANCOM, however, found no significant differentially expressed taxa.

## Inter-country microbiome comparisons

Samples from Bangladesh and Albania (gDNA, whole-body, non-blood-fed) were compared and alpha-diversity demonstrated no significant difference between individuals within each group, whereas beta-diversity highlighted differences between each country, with Bray-Curtis (p=0.001) and Unweighted-Unifrac (p=0.001). ANCOM analysis showed there were several differentially abundant taxa between the groups from Bangladesh and Albania. The three taxa which were most statistically significant were two *Erwinia* species (W=235 and W=224) and *Asaia* (W=219), with their abundance in Albania much greater than in Bangladesh.

For comparisons between Albania and Madagascar, one comparison was made between non-blood-fed and the other between blood-fed *Cx. tritaeniorhynchus* from the two countries (cDNA, abdomen samples). For non-blood fed, none of the alpha- or beta-diversity indexes showed significant results but ANCOM highlighted *Anaerobacillus* as a significant differentially abundant taxa (W=260), with higher abundance in Madagascar than Albania. This genus was present in 9/12 samples from Tsaramandroso, Madagascar (relative abundance range of <1% to 6.08%), present in 4/10 samples from Vlore, Albania, (<1% to 1.99%) and in 0/15 samples from Fier (Sop), Albania. For the comparison between blood-fed females across the two countries, alpha-diversity showed no significant difference between the individuals in each group;
<figure><img src="image_10.png" /><figcaption>**Figure 7.** Global genetic diversity Country and Regional populations pairwise comparison heatmaps. *Cx. tritaeniorhynchus* partial CO1 maximum reference sequences alignment used for haplotype and pairwise analyses within Arlequin software and visualised in R. *F*<sub>ST</sub> = pairwise fixation index: 0=two populations genetically identical, 1=two populations are genetically different; maximum genetic diversity between two populations.</figcaption></figure>
from Fier (Sop), Albania (n=12) and Tsaramandroso, Madagascar (n=15). The Bray-Curtis beta-diversity metric showed a significant difference between the groups from each country (p=0.003) and ANCOM highlighted that reads classified in the *Bacillus* genus were significantly differentially abundant (W=266), with a relatively high abundance in samples from Madagascar, and absent from the blood-fed mosquitoes from Albania.

## Detection and phylogeny of *Wolbachia* bacteria strains

Taxonomic abundance analysis from microbiome analysis did show evidence for the presence of *Wolbachia* in *Cx. tritaeniorhynchus* samples from Bangladesh, Albania and Madagascar. One sample from Bagmara, Bangladesh exhibited a relative abundance of *Wolbachia* comprising 39.77% of the total microbial composition, and two further specimens from the same

location had 5.94% and 4.72% relative abundance. A blood-fed specimen collected in Fier (Sop), Albania, had a *Wolbachia* relative abundance of 22.50%. Three non-blood-fed samples from Albania, collected in Fier (Sop) and Vlore, also showed the presence of *Wolbachia* with relative abundances of 5.88%, 1.11% (Sop) and 1.32% (Vlore). Concomitant Albanian *Cx. pipiens* mosquitoes (a species known to be naturally infected with the wPip strain of *Wolbachia*) were shown to have variable *Wolbachia* relative abundances, ranging from 0–38.24%. Confirmation of *Wolbachia*-specific 16S rRNA amplification was possible for some samples from Albania and Bangladesh (Table 4). Further analysis using *Wolbachia* MLST showed a variable pattern of amplification and sequencing but partial MLST profiles were obtained for samples from Albania and Bangladesh (Table 5). Partial MLST allelic profiles and phylogenetic analysis (Figure 8) indicated that these

<table><caption>**Table 4.** *Wolbachia* positive *Cx. tritaeniorhynchus* samples. *Wolbachia* testing success through 16S microbiome analysis, *Wolbachia*-specific 16S qPCR, or *Wolbachia* MLST gene PCRs. + denotes successful amplification/detection, - denotes *Wolbachia* not detected through this method, *denotes successful sequencing. NBFF – Non-blood-fed female, BFF – Blood-fed female.</caption><thead><tr><th>Location (year)</th><th>Sample ID</th><th>16S V3-V4</th><th>16S qPCR</th><th>gatB</th><th>coxA</th><th>fpbA</th><th>ftsZ</th><th>hcpA</th></tr></thead><tbody><tr><td rowspan="4">Bagmara, Rajshahi, Bangladesh (2013)</td><td>Bang T6 109 1 (AB2) NBFF</td><td>+</td><td>+</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Bang T6 109 2 (AB3) NBFF</td><td>-</td><td>+</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Bang T6 109 3 (AB4) NBFF</td><td>+</td><td>+</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Bang T6 110 1 (AB5) NBFF</td><td>+</td><td>-</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="4">Manda, Naogaon, Bangladesh (2013)</td><td>Bang T6 196 2 BFF</td><td>-</td><td>+</td><td>+</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td>BG0 T6 194 1 NBFF</td><td></td><td>+</td><td></td><td>+</td><td>+</td><td></td><td></td></tr><tr><td>BG0 T6 194 1 NBFF</td><td></td><td>+</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>BG0 T6 194 3 BFF</td><td></td><td>+</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="3">Shengjin, Lezhe, Albania (2015)</td><td>AG0 T222 BFF1</td><td></td><td>+</td><td>-</td><td>+</td><td>+</td><td>+</td><td>+</td></tr><tr><td>AG0 T222 BFF2</td><td></td><td>+</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>AG0 T222 BFF3</td><td></td><td>+</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sop, Fier, Albania (2015)</td><td>AG0 T201BFF</td><td></td><td>+</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sop, Fier, Albania (2017)</td><td>ALB-17-SOP-CT-N12-WD (gDNA) BBF</td><td></td><td>+</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

<table><caption>**Table 5.** *Wolbachia* partial MLST gene allelic profiles for resident strains in *Cx. tritaeniorhynchus* populations. "CM" = Allele number of the closest allelic match, with the number of nucleotide differences in brackets. "EM" = Exact match on that locus to the allele number provided. "SG" = Super group to which isolates with that allele at that locus belong. *denotes where the query sequence was truncated, therefore the full locus wasn't available for comparison. "-" denotes where sequencing was attempted from PCR products but the sequence data quality wasn't sufficient for analysis. "NS" denotes where no clear PCR amplified product was obtained and therefore sequencing was not attempted.</caption><thead><tr><th>Country and sample ID</th><th>gatB</th><th>coxA</th><th>hcpA</th><th>ftsZ</th><th>fbpA</th></tr></thead><tbody><tr><td rowspan="2">Bangladesh - BG0 T6 196 2 F9</td><td rowspan="2">-</td><td rowspan="2">-</td><td>CM 12 (1)</td><td>-</td><td>EM 27</td></tr><tr><td>SG B</td><td>-</td><td>SG B</td></tr><tr><td rowspan="2">Albania - AG0 T222 BFF1 E9</td><td rowspan="2">NS</td><td rowspan="2">-</td><td>CM 280* (0)</td><td>EM 4</td><td></td></tr><tr><td>SG B</td><td>SG B</td><td></td></tr></tbody></table>
<figure><img src="image_11.png" /><figcaption>**Figure 8.** *Wolbachia* MLST gene phylogenetic trees. The T92 model (Tamura, 1992) was used for all. *Wolbachia* Supergroups A and B are highlighted in red and blue respectively. The sequences obtained from *Cx. tritaeniorhynchus* from Albania and Bangladesh are shown in orange and green respectively. (A) *fbpA* gene locus. Tree log likelihood = -1947.41 (+G, parameter = 0.2126). The analysis involved 113 nucleotide sequences and 429 positions. An *fbpA* sub-tree is also shown separately (yellow border) for more detailed visualisation of the *Wolbachia fbpA* sequences obtained from *Cx. tritaeniorhynchus*. (B) *hcpA* gene locus. Log likelihood = -1825.87. (+G, parameter = 0.3916). 111 nucleotide sequences and 444 positions. (C) Partial *ftsZ* locus. Log likelihood = -535.33 (+G, parameter = 0.2600). 113 nucleotide sequences and 189 positions.</figcaption></figure>
*Wolbachia* strains were different from one another but both placed within Supergroup B. Using the *Wolbachia* fbpA locus, the two strain do appear closely related (Figure 8).

Discussion

Despite the presence of *Cx. tritaeniorhynchus* first being reported in Albania in 1960 (Danielovi & Adhami, 1960), further published European occurrence reports were scarce until the 2000s when this species was recorded in Greece (*Lytra & Emmanuel*, 2014a, *Lytra & Emmanuel*, 2014b; *Patsoula et al.*, 2017; *Samanidou & Harbach*, 2003). Recent extensive entomological surveys carried out in Albania (including this study) have identified *Cx. tritaeniorhynchus* within multiple areas for the first time (Alves et al., 2014; Gugushvili, 2002; Lessard et al., 2021; *Samanidou & Harbach*, 2003), highlighting a trend towards expansion of the known geographical range. Entomological surveillance in Europe has also identified other invasive mosquito vector species such as *Aedes albopictus*, highlighting the risk of exotic vector species becoming established (Medlock et al., 2012). Concurrently, there has been an increase in outbreaks and circulation of mosquito-borne arboviruses such as WNV in Europe (Bakonyi et al., 2013; Calzolari, 2016; Engler et al., 2013). To our knowledge, this study is the first to assess JEV vector competence in a European population of *Cx. tritaeniorhynchus* and our results emphasise the possibility of future introductions and JEV epidemics outside of Asia. Previous detection of JEV RNA in mosquitoes and birds in Italy further reinforces this point (Platonov et al., 2012; Ravanini et al., 2012).

In our study, a lower number of saliva samples (compared to mosquito body parts) had detectable virus after the 14-day incubation which might be expected, as the excretion of virus in the saliva is the final process in the infection pathway, following after viral acquisition and dissemination. Caution must be taken in over-extrapolating these results given 1) we were unable to generate comparative vector competence data between geographically dispersed populations due to colonisation difficulties and 2) direct extrapolation of laboratory vector competence to wild populations is likely to be imprecise given the complexity of transmission dynamics in wild populations. Comparisons to previous studies are also problematic due to variation in infection and detection methods. For example, a study in Korea resulted in 33-67% JEV transmission (via capillary tube saliva collection, or onward infection of chickens) (Turell et al., 2006) and in India, using ELISA in whole bodies, variable infection rates were reported, from 0-48% (Philip Samuel et al., 2010). The relatively lower infection rates seen in the latter study may be, at least in part, a result of reduced sensitivity of ELISA for virus detection or differences in JEV infectious doses.

Our study should enable a more accurate taxonomic classification of *Cx. tritaeniorhynchus* – particularly important as hybridisation within species complexes (e.g. *Cx. pipiens*) can influence arbovirus transmission (Shaikevich et al., 2016). The mitochondrial *CO1* gene has been most frequently used

(Ashfaq et al., 2014; Karthika et al., 2018; Kumar et al., 2007; Li et al., 2020; Rajavel et al., 2015; Xie et al., 2021) allowing species discrimination and investigation of maternal inheritance patterns (Cywinska et al., 2006; Hebert et al., 2003; Karthika et al., 2018). Our genetic diversity metrics quantified the genetic distances and divergence within population groups, identifying 444 haplotypes and 139 variable sites, with a haplotype diversity of 0.97864 and a nucleotide diversity per site of 0.02214. To our knowledge this is the first published study examining such a geographically diverse mitochondrial dataset – previous studies have identified 28 (Karthika et al., 2018) and 303 (Xie et al., 2021) haplotypes, with the latter finding a Hd of 0.97 and Pi of 0.02434 which is comparable to our study. Analysis of regional population groups identified 412 haplotypes in Asia, four in Australia, 19 in Africa, four in the Middle East, eight in Eurasia and four in Europe. The only previous study for European *Cx. tritaeniorhynchus* found two haplotypes within the same population, collected in a single rice field in western Greece (*Lytra & Emmanuel*, 2014b). Our samples from the same location identified two haplotypes which were also present in Albania, and a further two haplotypes were found in Albania only.

The haplotype network and pairwise comparison analysis also indicated that (as expected) geographical location influences mitochondrial diversity. For example, there was a distinct grouping of 14 haplotypes in Madagascar, none of which were found in any other countries or regions. The greater genetic distances of some groups, such as Australia, Madagascar, and Europe, is logical but are genetic bottlenecks or selection pressures occurring during adaptation to new environments? Maternal lineages can provide insight into possible movement patterns and although *Cx. tritaeniorhynchus* are estimated to have an average flight distance of just under 70 metres, some studies have found that during long-distance wind-assisted dispersal, they can migrate 200–500 kilometres (Verdonschot & Besse-Lototskaya, 2014). As adults overwinter, this species may use a combination of long-distance migration and hibernation in situ, as strategies to survive unfavourable conditions in temperate regions (Min & Xue, 1996). The ability to disperse over such long distances and adapt to variable conditions is likely to provide more opportunities for range expansion and to increase gene exchange among different populations (Xie et al., 2021).

Our microbiome analysis revealed some bacteria such as *Asaia* that was present in all populations and differentially abundant in Albania when compared to Bangladesh. However, as *Asaia* can be environmentally acquired (Favia et al., 2007), it may depend on differing exposures in local habitats, rather than a country-wide distinction. In Albania, *Cx. pipiens* had a greater abundance of *Wolbachia* (ANCOM, W=265) but a lower abundance of *Asaia* than the other two species. Although not statistically significant and some individuals had both *Wolbachia* and *Asaia*, further studies should be undertaken to determine any antagonistic associations as seen in mosquito lab colonies (Hughes et al., 2014; Rossi et al., 2015).
Apibacter was detected in Madagascar samples (both at high prevalence and for some individuals high relative abundance) and in individuals from Bangladesh and Albania. Apibacter have been relatively recently isolated and classified in 2016 from various bee species (Kwong & Moran, 2016; Praet et al., 2016), as well as being reported in house flies (Park et al., 2019) and Cx. fusocephala from Thailand (Thongsripong et al., 2021). These bacteria are thought to be beneficial endosymbionts with characteristics of adaptation to the gut environment and a degree of host-specificity (Kwong et al., 2018). Apibacter may also confer a degree of protection against pathogens with a recent study finding an association between Apibacter in bees and decreased infection by a trypanosomatid gut parasite Crithidia bombi (Kwong et al., 2018; Mockler et al., 2018).

Several genera which contain pathogenic species including *Anaplasma*, *Rickettsia*, *Bartonella*, *Vibrio*, *Helicobacter*, *Proividencia*, *Mycoplasma* and *Escherichia* (Christou, 2011) were identified but it was not possible to classify the ASVs beyond genus level to determine whether they were pathogenic species. *Escherichia shigella* and *Vibrio cholerae* were identified and can cause dysentery and severe cholera respectively. These pathogenic bacteria may have been present in local aquatic environments and environmentally acquired. However, detection does not imply *Cx. tritaeniorhynchus* has the capacity for onward transmission, although it may theoretically be possible to mechanically disperse bacteria between water sources. *Anaplasma marginale* and *Anaplasma platys*, which can cause anaplasmosis in cattle and dogs respectively, are vector-borne pathogens, although they are mainly thought to be transmitted by ticks. A recent study in China found a wide range of *Rickettsiales*, including *Anaplasma* spp., in mosquito species, including *Cx. tritaeniorhynchus* (Guo et al., 2016). Phylogenetic analysis suggested a potential role for mosquitoes in vector-borne transmission of *Anaplasma marginale*, with other *Anaplasma* species suggested to be vertically transmitted (Guo et al., 2016). Finding these bacteria at relatively high abundance in blood-fed mosquitoes in our study, and not in the matched non-blood-fed mosquitoes may suggest these bacteria were present in the blood meals and not disseminated infections. Even without vectorial capacity, mechanical transmission during blood-feeding may be possible and the high abundance in blood-fed-females would suggest a relatively frequent exposure to *Anaplasma*, particularly *Anaplasma marginale*, from feeding on cattle. Bacteria from the *Bartonella* genus are also vector-borne, with ticks, fleas, lice and sandflies implicated as vectors (Billeter et al., 2008; Jacomo et al., 2002). *Bartonella* species can infect humans and animals causing bartonellosis. Although *Bartonella* was only identified in a few *Cx. tritaeniorhynchus* individuals from each country, when present it was highly abundant. *Bartonella* was found dominating the microbiome in 4/13 concomitant *Cx. antennatus* specimens in Madagascar despite none found in the matched group of *Cx. tritaeniorhynchus* from the same location.

Our microbiome analysis identified the presence of *Wolbachia* in populations with variable levels of relative abundance (0–40%) suggesting the likely presence of multiple strains at low prevalence spread across several continents. Phylogenetic analysis of the *Wolbachia* 16S and MLST gene loci confirms the strains from individuals in Albania and Bangladesh are placed within Supergroup B. Although the strains do differ from one another where comparison was possible on the *Wolbachia* *fbpA* locus, they appear to be closely related. Some previous studies have not identified *Wolbachia* in *Cx. tritaeniorhynchus* (Kittayapong et al., 2000; Nugapola et al., 2017; Ravikumar et al., 2010; Tsai et al., 2004), however, a study from Thailand (Wiwatanaratanabutr, 2013) and recently from Singapore (Ding et al., 2020), reported *Wolbachia* in small numbers of individual mosquitoes. *Cx. tritaeniorhynchus* is implicated as a vector of *Dirofilaria immitis*, a filarial nematode with an obligatory symbiotic relationship with *Wolbachia*, requiring its presence for survival. However, phylogenetic analysis carried out in our study indicates the *Wolbachia* strains are not likely to result from filarial infections given the placement within Supergroup B (Dyab et al., 2016). It remains to be determined whether these *Wolbachia* strains influence reproductive success through the cytoplasmic incompatibility phenotype, are vertically transmitted with high rates of maternal transmission, or impact vectorial capacity. Low infection rates may suggest they do not possess the beneficial phenotypic characteristics most useful for mosquito biocontrol and may not inhibit arboviruses as seen in some other studies on native strains (Tsai et al., 2006). However, low-level natural *Wolbachia* strains in *Cx. tritaeniorhynchus* populations are unlikely to be prohibitive to the development of *Wolbachia*-based biocontrol strategies, such as through transinfection of non-native strains. Further analysis of larger sample numbers from diverse geographical areas is needed including non-PCR based methods such as microscopy to visualise bacteria in mosquito tissues (Walker et al., 2021).

## Conclusions

Our study provides evidence that a European population of *Cx. tritaeniorhynchus* is a competent vector of JEV and shows that a high degree of mitochondrial and microbial diversity is present across geographically dispersed populations of this species. Future vector competence experiments should incorporate factors, such as temperature, to more closely mimic the current and potential future environmental niches inhabited by this vector. Establishing whether geographically diverse populations of *Cx. tritaeniorhynchus* are competent vectors for other medically important arboviruses such as WNV and RVFV is also a priority as exemplified by its involvement in the first incursion of RVFV outside of Africa. This study also provides evidence for the presence of diverse bacteria, including those considered candidates for biocontrol, and pathogenic bacteria. Further studies should be undertaken to determine if *Wolbachia* strains naturally reside within *Cx. tritaeniorhynchus* populations. Increased surveillance and novel control strategies for *Cx. tritaeniorhynchus* will be important with climate
change increasing the range of this invasive species which can
transmit multiple arboviruses of concern to public health.

## Data availability

### Extended data

Open Science Framework: Microbiome data associated with. Jeffries *et al*. Mitchondrial and microbial diversity of the invasive mosquito vector species Culex tritaeniorhynchus across its extensive inter-continental geographic range. https://doi.org/10.17605/OSF.IO/DJ7WA (Jeffries & Walker, 2023)

This project contains the raw 16S sequencing reads in FASTA format.

Data are available under the terms of the **Creative Commons Zero "No rights reserved" data waiver** (CC0 1.0 Public domain dedication).

## Acknowledgements

The authors would like to acknowledge and thank the following people for their assistance during this study: Eliot Hurn, Fara Raharimalala, Seth Irish and Laith Yakob.

## References

Akhter R, Hayes CG, Baqar S, et al.: West Nile virus in Pakistan. III. Comparative vector capability of *Culex tritaeniorhynchus* and eight other species of mosquitoes. *Trans R Soc Trop Med Hyg.* 1982; **76**(4): 449-453.

PubMed Abstract | Publisher Full Text

Alves J, DePina A, Diallo M, et al.: First report of *Culex (Culex) tritaeniorhynchus* Giles, 1901 (Diptera: Culicidae) in the Cape Verde Islands. *Zool Caboverdiana*. 2014; 5(1): 14–19.

Reference Source

Anderson MJ: A new method for non-parametric multivariate analysis of variance. *Austral Ecol.* 2001; **26**(1): 32–46.

Publisher Full Text

Ashfaq M, Hebert PDN, Mirza JH, et al.: Analyzing mosquito (Diptera: Culicidae) diversity in Pakistan by DNA barcoding. *PLoS One*. 2014; **9**(5): e97268.

PubMed Abstract | Publisher Full Text | Free Full Text

Bakonyi T, Ferenci Z, Erdélyi K, et al.: Explosive spread of a neuroinvasive lineage 2 West Nile virus in Central Europe, 2008/2009. *Vet Microbiol*. 2013; **165**(1-2): 61-70.

PubMed Abstract | Publisher Full Text

Baldo L, Hotopp JCD, Jolley KA, et al.: Multilocus sequence typing system for the endosymbiont *Wolbachia pipientis*. *Appl Environ Microbiol*. 2006; **72**(11): 7098-7110.

PubMed Abstract | Publisher Full Text | Free Full Text

Bernasconi MV, Valsangiacomo C, Piffaretti JC, et al.: Phylogenetic relationships among Muscoidea (Diptera: Calyptratae) based on mitochondrial DNA sequences. *Insect Mol Biol*. 2000; **9**(1): 67-74.

PubMed Abstract | Publisher Full Text

Billeter SA, Levy MG, Chomel BB, et al.: Vector transmission of *Bartonella* species with emphasis on the potential for tick transmission. *Med Vet Entomol*. 2008; **22**(1): 1–15.

PubMed Abstract | Publisher Full Text

Bokulich NA, Kaehler BD, Rideout JR, et al.: Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin. *Microbiome*. 2018; **6**(1): 90.

PubMed Abstract | Publisher Full Text | Free Full Text

Bolling BG, Weaver SC, Tesh RB, et al.: Insect-specific virus discovery: Significance for the arbovirus community. *Viruses*. 2015; **7**(9): 4911-4928.

PubMed Abstract | Publisher Full Text | Free Full Text

Bolyen E, Rideout JR, Dillon MR, et al.: Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. *Nat Biotechnol*. 2019; **37**(8): 852-857.

PubMed Abstract | Publisher Full Text | Free Full Text

Callahan BJ, McMurdie PJ, Rosen MJ, et al.: DADA2: High-resolution sample inference from Illumina amplicon data. *Nat Methods*. 2016; **13**(7): 581-583.

PubMed Abstract | Publisher Full Text | Free Full Text

Calzolari M: Mosquito-borne diseases in Europe: an emerging public health threat. *Reports Parasitol*. 2016; **5**: 1–12.

Publisher Full Text

Campbell G, Hills S, Fischer M, et al.: Estimated global incidence of Japanese encephalitis: a systematic review. *Bull World Health Organ*. 2011; **89**(10): 766-774, 774A-774E.

PubMed Abstract | Publisher Full Text | Free Full Text

Cansado-Utrilla C, Zhao SY, McCall PJ, et al.: The microbiome and mosquito vectorial capacity: rich potential for discovery and translation. *Microbiome*. 2021; 9(1): 111.

PubMed Abstract | Publisher Full Text | Free Full Text

Christou L: The global burden of bacterial and viral zoonotic infections. *Clin Microbiol Infect*. 2011; **17**(3): 326-330.

PubMed Abstract | Publisher Full Text | Free Full Text

Clement M, Posada D, Crandall KA: TCS: A computer program to estimate gene genealogies. *Mol Ecol*. 2000; **9**(10): 1657-1659.

PubMed Abstract | Publisher Full Text

Cywinska A, Hunter FF, Hebert PDN: Identifying Canadian mosquito species through DNA barcodes. *Med Vet Entomol*. 2006; **20**(4): 413-424.

PubMed Abstract | Publisher Full Text

Danielović V, Adhami J: Mosquitoes of Albania and their medical importance. *Ceskoslov Parasitol*. 1960; **7**: 41–47.

de Oliveira CD, Gonçalves DS, Baton LA, et al.: Broader prevalence of Wolbachia in insects including potential human disease vectors. *Bull Entomol Res*. 2015; **105**(3): 305-15.

PubMed Abstract | Publisher Full Text

Detinova TS: Age-Grouping Methods in Diptera of Medical Importance with Special Reference to Some Vectors of Malaria. In: *Monogr Ser World Health Organ* (Geneva: World Health Organisation), 1962; **47**: 13-191.

PubMed Abstract | Publisher Full Text

Ding H, Yeo H, Puniamoorthy N: *Wolbachia* infection in wild mosquitoes (Diptera: Culicidae): implications for transmission modes and host-endosymbiont associations in Singapore. *Parasit Vectors*. 2020; **13**(1): 612.

PubMed Abstract | Publisher Full Text | Free Full Text

Dyab AK, Galal LA, Mahmoud AE, et al.: Finding *wolbachia* in filarial larvae and culicidae mosquitoes in upper Egypt governorate. *Korean J Parasitol*. 2016; **54**(3): 265-272.

PubMed Abstract | Publisher Full Text | Free Full Text

Engler O, Savini G, Papa A, et al.: European surveillance for West Nile virus in mosquito populations. *Int J Environ Res Public Health*. 2013; **10**(10): 4869-4895.

PubMed Abstract | Publisher Full Text | Free Full Text

Erlanger TE, Weiss S, Keiser J, et al.: Past, Present, and Future of Japanese Encephalitis. *Emerg Infect Dis*. 2009; **15**(1): 1-7.

PubMed Abstract | Publisher Full Text | Free Full Text

Excoffier L, Sischer HEL: Arlequin suite ver 3.5: A new series of programs to perform population genetics analyses under Linux and Windows. *Mol Ecol Resour*. 2010; **10**(3): 564-567.

PubMed Abstract | Publisher Full Text

Excoffier L, Smouse PE, Quattro JM: Analysis of Molecular Variance Inferred From Metric Distances Among DNA Haplotypes: Application to Human Mitochondrial DNA Restriction Data. *Genetics*. 1992; **131**(2): 479-491.

PubMed Abstract | Publisher Full Text | Free Full Text

Faith DP: Conservation evaluation and phylogenetic diversity. *Biol Conserv*. 1992; **61**(1): 1-10.

Publisher Full Text

Favia G, Ricci I, Damiani C, et al.: Bacteria of the genus *Asaia* stably associate with *Anopheles stephensi*, an Asian malarial mosquito vector. *Proc Natl Acad Sci U S A*. 2007; **104**(21): 9047-9051.

PubMed Abstract | Publisher Full Text | Free Full Text

Folmer O, Black M, Hoeh W, et al.: DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. *Mol Mar Biol Biotechnol*. 1994; **3**(5): 294-299.

PubMed Abstract

Fontenille D: [Arbovirus transmission cycles in Madagascar]. *Arch Inst Pasteur Madagascar*. 1989; **55**(1): 1-317.

PubMed Abstract

Franz AWE, Kantor AM, Passarelli AL, et al.: Tissue barriers to arbovirus infection in mosquitoes. *Viruses*. 2015; **7**(7): 3741-3767.

PubMed Abstract | Publisher Full Text | Free Full Text
Gao X, Liu H, Li X, et al.: Changing Geographic Distribution of Japanese Encephalitis Virus Genotypes, 1935-2017. *Vector Borne Zoonotic Dis.* 2019; **19**(1): 35-44.

PubMed Abstract | Publisher Full Text

Gomes FM, Hixson BL, Tyner MWD, et al.: Effect of naturally occurring *Wolbachia* in *Anopheles gambiae* s.l. mosquitoes from Mali on *Plasmodium falciparum* malaria transmission. *Proc Natl Acad Sci U S A.* 2017; **114**(47): 12566-12571.

PubMed Abstract | Publisher Full Text | Free Full Text

Gugushvili G: Mosquitoes (Diptera: Culicidae) of Georgia. *Proc Inst Zool Tbilisi.* 2002; **21**: 235-237.

Günay F, Picard M, Robert V: MosKeyTool: An interactive identification key for mosquitoes of Euro-Mediterranean. 2017.

Reference Source

Guo WP, Tian JH, Lin XD, et al.: Extensive genetic diversity of Rickettsiales bacteria in multiple mosquito species. *Sci Rep.* 2016; **6**: 38770.

PubMed Abstract | Publisher Full Text | Free Full Text

Hayes CG, Baker RH, Baqar S, et al.: Genetic variation for West Nile virus susceptibility in *Culex tritaeniorhynchus*. *Am J Trop Med Hyg.* 1984; **33**(4): 715-724.

PubMed Abstract | Publisher Full Text

Hebert PDN, Ratnasingham S, de Waard JR: Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species. *Proc Biol Sci.* 2003; **270** Suppl 1(Suppl 1): S96-S99.

PubMed Abstract | Publisher Full Text | Free Full Text

Hughes GL, Dodson BL, Johnson RM, et al.: Native microbiome impedes vertical transmission of *Wolbachia* in *Anopheles* mosquitoes. *Proc Natl Acad Sci U S A.* 2014; **111**(34): 12498-1503.

PubMed Abstract | Publisher Full Text | Free Full Text

Jacomo V, Kelly PJ, Raoult D: Natural history of *Bartonella* infections (an exception to Koch's postulate). *Clin Diagn Lab Immunol.* 2002; **9**(1): 8-18.

PubMed Abstract | Publisher Full Text | Free Full Text

Jeffries CL, Cansado-Utrilla C, Beavogui AH, et al.: Evidence for natural hybridisation and novel *Wolbachia* strain superinfections in the *Anopheles gambiae* complex from Guinea. *R Soc Open Sci.* 2021; **8**(4): 202032.

PubMed Abstract | Publisher Full Text | Free Full Text

Jeffries CL, Lawrence GG, Golovko G, et al.: Novel *Wolbachia* strains in *Anopheles* malaria vectors from Sub-Saharan Africa [version 2; peer review: 3 approved]. *Wellcome Open Res.* 2018a; **3**: 113.

PubMed Abstract | Publisher Full Text | Free Full Text

Jeffries CL, Tantely LM, Raharimalala FN, et al.: Diverse novel resident *Wolbachia* strains in Culicine mosquitoes from Madagascar. *Sci Rep.* 2018b; **8**(1): 17456.

PubMed Abstract | Publisher Full Text | Free Full Text

Jeffries CL, Walker T: The Potential Use of *Wolbachia*-Based Mosquito Biocontrol Strategies for Japanese Encephalitis. *PLoS Negl Trop Dis.* 2015; **9**(6): e0003576.

PubMed Abstract | Publisher Full Text | Free Full Text

Jeffries CL, Walker T: Microbiome data associated with Jeffries *et al.* Mitchellondral and microbial diversity of the invasive mosquito vector species *Culex tritaeniorhynchus* across its extensive inter-continental geographic range. *Open Science framework [DATASET].* 2023. http://www.doi.org/10.17605/OSF.IO/DJ7WA

Jupatanakul N, Sim S, Dimopoulos G: The insect microbiome modulates vector competence for arboviruses. *Viruses.* 2014; **6**(11): 4294-4313.

PubMed Abstract | Publisher Full Text | Free Full Text

Jupp PG, Kemp A, Grobbelaar A, et al.: The 2000 epidemic of Rift Valley fever in Saudi Arabia: Mosquito vector studies. *Med Vet Entomol.* 2002; **16**(13): 245-252.

PubMed Abstract | Publisher Full Text

Karthika P, Vadivalagan C, Thirumurugan D, et al.: DNA barcoding of five Japanese encephalitis mosquito vectors (*Culex fuscosephala*, *Culex gelidus*, *Culex tritaeniorhynchus*, *Culex pseudovishnui* and *Culex vishnui*). *Acta Trop.* 2018; **183**: 84-91.

PubMed Abstract | Publisher Full Text

Kilpatrick AM, Fonseca DM, Ebel GD, et al.: Spatial and temporal variation in vector competence of *Culex pipiens* and *Cx. restuans* mosquitoes for West Nile virus. *Am J Trop Med Hyg.* 2010; **83**(3): 607-13.

PubMed Abstract | Publisher Full Text | Free Full Text

Kittayapong P, Baisley KJ, Baimai V, et al.: Distribution and diversity of *Wolbachia* infections in Southeast Asian mosquitoes (Diptera: Culicidae). *J Med Entomol.* 2000; **37**(3): 340-345.

PubMed Abstract | Publisher Full Text

Klindworth A, Pruesse E, Schweer T, et al.: Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. *Nucleic Acids Res.* 2013; **41**(1): e1.

PubMed Abstract | Publisher Full Text | Free Full Text

Kruskal WH, Wallis WA: Use of Ranks in One-Criterion Variance Analysis. *J Am Statist Assoc.* 1952; **47**(260): 583-621.

Publisher Full Text

Kumar NP, Rajavel AR, Natarajan R, et al.: DNA barcodes can distinguish species of Indian mosquitoes (Diptera: Culicidae). *J Med Entomol.* 2007; **44**(1): 1-7.

PubMed Abstract | Publisher Full Text

Kwong WK, Moran NA: *Apibacter adventoris* gen. nov., sp. nov., a member of the *phylum Bacteroidetes* isolated from honey bees. *Int J Syst Evol Microbiol.* 2016; **66**(3): 1323-1329.

PubMed Abstract | Publisher Full Text | Free Full Text

Kwong WK, Steele MI, Moran NA: Genome sequences of *Apibacter* spp., gut symbionts of Asian honey bees. *Genome Biol Evol.* 2018; **10**(4): 1174-1179.

PubMed Abstract | Publisher Full Text | Free Full Text

Leigh JW, Bryant D: POPART: Full-feature software for haplotype network construction. *Methods Ecol Evol.* 2015; **6**(9): 1110-1116.

Publisher Full Text

Lessard BD, Kurucz N, Rodriguez J, et al.: Detection of the Japanese encephalitis vector mosquito *Culex tritaeniorhynchus* in Australia using molecular diagnostics and morphology. *Parasit Vectors.* 2021; **14**(1): 411.

PubMed Abstract | Publisher Full Text | Free Full Text

Li S, Jiang F, Lu H, et al.: Mosquito Diversity and Population Genetic Structure of Six Mosquito Species From Hainan Island. *Front Genet.* 2020; **11**: 602863.

PubMed Abstract | Publisher Full Text | Free Full Text

Lord JS: Changes in rice and livestock production and the potential emergence of Japanese encephalitis in Africa. *Pathogens.* 2021; **10**(3): 294-303.

PubMed Abstract | Publisher Full Text | Free Full Text

Luo QC, Hao YJ, Meng F, et al.: The mitochondrial genomes of *Culex tritaeniorhynchus* and *Culex pipiens pallens* (Diptera: Culicidae) and comparison analysis with two other *Culex* species. *Parasit Vectors.* 2016; **9**(1): 406.

PubMed Abstract | Publisher Full Text | Free Full Text

Lytra IC, Emmanuelou NG: Presence of *Culex tritaeniorhynchus* (Diptera: Culicidae) in rice fields of Western Greece. *Hell Plant Prot J.* 2014a; **7**(1): 15-18.

Reference Source

Lytra I, Emmanuelou N: Study of *Culex tritaeniorhynchus* and species composition of mosquitoes in a rice field in Greece. *Acta Trop.* 2014b; **134**: 66-71.

PubMed Abstract | Publisher Full Text

Mandal S, Van Treuren W, White RA, et al.: Analysis of composition of microbiomes: a novel method for studying microbial composition. *Microb Ecol Health Dis.* 2015; **26**: 27663.

PubMed Abstract | Publisher Full Text | Free Full Text

Martin M: Cutadapt Removes Adapter Sequences from High-Throughput Sequencing Reads. *EMBnet J.* 2011; **17**(1): 10-12.

Publisher Full Text

Martinez-de la Puente J, Ruiz S, Soriguer R, et al.: Effect of blood meal digestion and DNA extraction protocol on the success of blood meal source determination in the malaria vector *Anopheles atroparvus*. *Malar J.* 2013; **12**: 109.

PubMed Abstract | Publisher Full Text | Free Full Text

Medlock JM, Hansford KM, Schaffner F, et al.: A Review of the Invasive Mosquitoes in Europe: Ecology, Public Health Risks, and Control Options. *Vector Borne Zoonotic Dis.* 2012; **12**: 435-447.

PubMed Abstract | Publisher Full Text | Free Full Text

Min JG, Xue M: Progress in studies on the overwintering of the mosquito *Culex tritaeniorhynchus*. *Southeast Asian J Trop Med Public Health.* 1996; **27**(4): 810-817.

PubMed Abstract

Minard G, Mavingui P, Moro CV: Diversity and function of bacterial microbiota in the mosquito holobiont. *Parasit Vectors.* 2013; **6**: 146.

PubMed Abstract | Publisher Full Text | Free Full Text

Mockler BK, Kwong WK, Moran NA, et al.: Microbiome structure influences infection by the parasite *Cithidia bombi* in bumble bees. *Appl Environ Microbiol.* 2018; **84**(7): e02335-17.

PubMed Abstract | Publisher Full Text | Free Full Text

Moreira LA, Iturbe-Ormaetxe I, Jeffery JA, et al.: A *Wolbachia* symbiont in *Aedes aegypti* limits infection with dengue, Chikungunya, and *Plasmodium*. *Cell.* 2009; **139**(7): 1268-78.

PubMed Abstract | Publisher Full Text

Nei M, Kumar S: Molecular Evolution and Phylogenetics. Oxford: Oxford University Press, 2000.

Reference Source

Nugapola NWNP, De Silva WAPP, Karunaratne SHP: Distribution and phylogeny of *Wolbachia* strains in wild mosquito populations in Sri Lanka. *Parasit Vectors.* 2017; **10**(1): 230.

PubMed Abstract | Publisher Full Text | Free Full Text

Orsborne J, Furuya-Kanamori L, Jeffries CL, et al.: Investigating the blood-host plasticity and dispersal of *Anopheles coluzzii* using a novel field-based methodology. *Parasit Vectors.* 2019; **12**(1): 143.

PubMed Abstract | Publisher Full Text | Free Full Text

Park R, Dzialo MC, Nsabimana D, et al.: *Apibacter muscae* sp. Nov., a novel bacterial species isolated from house flies. *Int J Syst Evol Microbiol.* 2019; **69**(11): 3586-3592.

PubMed Abstract | Publisher Full Text

Patsoula E, Beleri S, Vakali A, et al.: Records of *Aedes albopictus* (Skuse, 1894) (Diptera: Culicidae) and *Culex tritaeniorhynchus* (Diptera: Culicidae)
Expansion in Areas in Mainland Greece and Islands. *Vector Borne Zoonotic Dis.* 2017; **17**(3): 217-223.

PubMed Abstract | Publisher Full Text

Pedregosa F, Varoquaux G, Gramfort A, et al.: Scikit-learn: Machine Learning in Python. *J Mach Learn.* 2011; **12**: 2825-2830.

Reference Source

Philip Samuel P, Arunachalam N, Rajendran R, et al.: Temporal Variation in the Susceptibility of *Culex tritaeniorhynchus* (Diptera: Culicidae) to Japanese Encephalitis Virus in an Endemic Area of Tamil Nadu, South India. *Vector Borne Zoonotic Dis.* 2010; **10**(10): 1003-1008.

PubMed Abstract | Publisher Full Text

Platonov AE, Rossi G, Karan LS, et al.: Does the Japanese encephalitis virus (JEV) represent a threat for human health in Europe? Detection of JEV RNA sequences in birds collected in Italy. *Euro Surveill.* 2012; **17**(32): 20241.

PubMed Abstract | Publisher Full Text

Praet J, Aerts M, de Brandt E, et al.: *Apibacter mensalis* sp. Nov.: A rare member of the bumblebee gut microbiota. *Int J Syst Evol Microbiol.* 2016; **66**(4): 1645-1651.

PubMed Abstract | Publisher Full Text

Quast C, Pruesse E, Yilmaz P, et al.: The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. *Nucleic Acids Res.* 2013; **41**(Database issue): 590-596.

PubMed Abstract | Publisher Full Text | Free Full Text

R Core Team: R: A language and environment for statistical computing. 2018.

Reference Source

Rajavel AR, Pradeep Kumar N, Natarajan R, et al.: Morphological and molecular characterization of the ecological, biological and behavioural variants of the JE vector *Culex tritaeniorhynchus*: An assessment of its taxonomic status. *J Vector Borne Dis.* 2015; **52**(1): 40-51.

PubMed Abstract

Ravanini P, Huhtamo E, Ilaria V, et al.: Japanese encephalitis virus RNA detected in *culex pipiens* mosquitoes in Italy. *Euro Surveill.* 2012; **17**(28): 20221.

PubMed Abstract | Publisher Full Text

Ravikumar H, Ramachandraswamy N, Sampathkumar S, et al.: A preliminary survey for Wolbachia and bacteriophage WO infections in Indian mosquitoes (Diptera: Culicidae). *Trop Biomed.* 2010; **27**(3): 384-393.

PubMed Abstract

Reisen WK, Hayes CG, Azra K, et al.: West Nile virus in Pakistan. *II. Entomological studies at Changa Manga National Forest, Punjab Province*. *Trans R Soc Trop Med Hyg.* 1982; **76**(4): 437-448.

PubMed Abstract | Publisher Full Text

Reuben R, Tewari SC, Hiriyan J, et al.: Illustrated Keys to Species of *Culex* (*Culex*) Associated With Japanese Encephalitis in Southeast Asia (Diptera: Culicidae). *Mosq Syst.* 1994; **26**: 75-96.

Reference Source

Robert V, Günay F, Le Goff G, et al.: Distribution chart for Euro-Mediterranean mosquitoes (western Palaearctic region). *J Eur Mosq Control Assoc.* 2019; **37**.

Reference Source

Rossi P, Ricci I, Cappelli A, et al.: Mutual exclusion of *Asaia* and *Wolbachia* in the reproductive organs of mosquito vectors. *Parasit Vectors.* 2015; **8**: 278.

PubMed Abstract | Publisher Full Text | Free Full Text

Rozas J, Ferrer-Mata A, Sanchez-DelBarrio JC, et al.: DnaSP 6: DNA sequence polymorphism analysis of large data sets. *Mol Biol Evol.* 2017; **34**(12): 3299-3302.

PubMed Abstract | Publisher Full Text

Sakai RK, Baker RH: A method for detecting and measuring concealed variability in the mosquito, *Culex tritaeniorhynchus*. *Genetics.* 1972; **71**(2): 287-296.

PubMed Abstract | Publisher Full Text | Free Full Text

Samanidou A, Harbach RE: *Culex* (*Culex*) tritaniorhynchus Giles, a newly discovered potential vector of arboviruses in Greece. *J Eur Mosq Control Assoc.* 2003; **16**: 15-17.

Reference Source

Shaikevich EV, Vinogradova EB, Bouattour A, et al.: Genetic diversity of *Culex pipiens* mosquitoes in distinct populations from Europe: contribution of *Cx. quinquefasciatus* in Mediterranean populations. *Parasit Vectors.* 2016; **9**: 47.

PubMed Abstract | Publisher Full Text | Free Full Text

Shaikevich EV, Zakharov IA: Polymorphism of mitochondrial COI and nuclear ribosomal ITS2 in the *Culex pipiens* complex and in *Culex torrentium* (Diptera: Culicidae). *Comp Cytogenet.* 2010; **4**(2): 161-174.

Publisher Full Text

Simon-Loriere E, Faye O, Prot M, et al.: Autochthonous Japanese Encephalitis with Yellow Fever Coinfection in Africa. *N Engl J Med.* 2017; **376**(15): 1483-1485.

PubMed Abstract | Publisher Full Text

Simon C, Frati F, Beckenbach A, et al.: Evolution, Weighting, and Phylogenetic Utility of Mitochondrial Gene Sequences and a Compilation of Conserved Polymerase Chain Reaction Primers. *Ann Entomol Soc Am.* 1994; **87**(6): 651-701.

Publisher Full Text

Takahashi M: Variation in susceptibility among colony strains of *Culex tritaeniorhynchus* to Japanese encephalitis virus infection. *Jpn J Med Sci Biol.* 1980; **33**(6): 321-329.

PubMed Abstract | Publisher Full Text

Takken W, Verhulst NO: Host Preferences of Blood-Feeding Mosquitoes. *Annu Rev Entomol.* 2013; **58**: 433-453.

PubMed Abstract | Publisher Full Text

Tamura K: Estimation of the number of nucleotide substitutions when there are strong transition-transversion and G+C-content biases. *Mol Biol Evol.* 1992; **9**(4): 678-687.

PubMed Abstract | Publisher Full Text

Tamura K, Stecher G, Kumar S: MEGA11: Molecular Evolutionary Genetics Analysis Version 11. *Mol Biol Evol.* 2021; **38**(7): 3022-3027.

PubMed Abstract | Publisher Full Text | Free Full Text

Tantely ML, Le Goff G, Boyer S, et al.: An updated checklist of mosquito species (Diptera: Culicidae) from Madagascar. *Parasite*. 2016; **23**: 20.

PubMed Abstract | Publisher Full Text | Free Full Text

Thongripong P, Chandler JA, Kittayapong P, et al.: Metagenomic shotgun sequencing reveals host species as an important driver of virome composition in mosquitoes. *Sci Rep.* 2021; **11**(1): 8448.

Tsai KH, Huang CG, Wu WJ, et al.: Parallel Infection of Japanese Encephalitis Virus and *Wolbachia* within Cells of Mosquito Salivary Glands. *J Med Entomol.* 2006; **43**(4): 752-756.

PubMed Abstract | Publisher Full Text

Tsai KH, Lien JC, Huang CG, et al.: Molecular (Sub) grouping of endosymbiont *Wolbachia* infection among mosquitoes of Taiwan. *J Med Entomol.* 2004; **41**(4): 677-683.

PubMed Abstract | Publisher Full Text

Turell MJ, Mores CN, Dohm DJ, et al.: Laboratory transmission of Japanese encephalitis, West Nile, and Getah viruses by mosquitoes (Diptera: Culicidae) collected near Camp Greaves, Gyeonggi Province, Republic of Korea 2003. *J Med Entomol.* 2006; **43**(5): 1076-1081.

PubMed Abstract | Publisher Full Text

Verdonschot PFM, Besse-Lototskaya AA: Flight distance of mosquitoes (Culicidae): A metadata analysis to support the management of barrier zones around rewetted and newly constructed wetlands. *Limnologica*. 2014; **45**: 69-79.

Publisher Full Text

Walker T, Quek S, Jeffries CL, et al.: Stable high-density and maternally inherited *Wolbachia* infections in *Anopheles moucheti* and *Anopheles demeilloni* mosquitoes. *Curr Biol.* 2021; **31**(11): 2310-2320.e5.

PubMed Abstract | Publisher Full Text | Free Full Text

Weaver SC, Reisen WK: Present and future arboviral threats. *Antiviral Res.* 2010; **85**(2): 328-45.

PubMed Abstract | Publisher Full Text | Free Full Text

Weiss S, Xu ZZ, Peddada S, et al.: Normalization and microbial differential abundance strategies depend upon data characteristics. *Microbiome*. 2017; **5**(1): 27.

PubMed Abstract | Publisher Full Text | Free Full Text

Werren JH, Windsor DM: *Wolbachia* infection frequencies in insects: evidence of a global equilibrium? *Proc Biol Sci.* 2000; **267**(1450): 1277-1285.

PubMed Abstract | Publisher Full Text | Free Full Text

Wiwatanaratanabutr I: Geographic distribution of wolbachial infections in mosquitoes from Thailand. *J Invertebr Pathol.* 2013; **114**(3): 337-340.

PubMed Abstract | Publisher Full Text

Xie GL, Ma XR, Liu QY, et al.: Genetic structure of *Culex tritaeniorhynchus* (Diptera: Culicidae) based on COI DNA barcodes. *Mitochondrial DNA B Resour.* 2021; **6**(4): 1411-1415.

PubMed Abstract | Publisher Full Text | Free Full Text

Yang DK, Kweon CH, Kim BH, et al.: TaqMan reverse transcription polymerase chain reaction for the detection of Japanese encephalitis virus. *J Vet Sci.* 2004; **5**(4): 345-351.

PubMed Abstract | Publisher Full Text

Zittra C, Flechl E, Kothmayer M, et al.: Ecological characterization and molecular differentiation of *Culex pipiens* complex taxa and *Culex torrentium* in eastern Austria. *Parasit Vectors.* 2016; **9**: 197.

PubMed Abstract | Publisher Full Text | Free Full Text