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      Molecular Evidence of Wolbachia Species in Wild-Caught Aedes albopictus and Aedes aegypti Mosquitoes in Four States of Northeast India

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          Abstract

          Wolbachia, a Gram-negative intracellular bacterium, naturally infects many arthropods, including mosquito vectors responsible for the spread of arboviral diseases such as Zika, chikungunya, and dengue fever. Certain Wolbachia strains are involved in inhibiting arbovirus replication in mosquitoes, and this phenomenon is currently being studied to combat disease vectors. A study was conducted in four states in north-eastern India to investigate the presence of natural Wolbachia infection in wild-caught Aedes albopictus and Aedes aegypti mosquitoes, the established vectors of dengue. The detection of a Wolbachia infection was confirmed by nested PCR and sequencing in the two mosquito species Ae. aegypti and Ae. albopictus. Positivity rates observed in Ae. aegypti and Ae. albopictus pools were 38% (44 of 115) and 85% (41 of 48), respectively, and the difference was significant (chi-square = 28.3174, p = 0.00000010). Sequencing revealed that all detected Wolbachia strains belonged to supergroup B. Although Wolbachia infection in Ae. aegypti has been previously reported from India, no such reports are available from north-eastern India. Data on naturally occurring Wolbachia strains are essential for selecting the optimal strain for the development of Wolbachia-based control measures. This information will be helpful for the future application of Wolbachia-based vector control measures in this part of the country.

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          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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            MEGA11: Molecular Evolutionary Genetics Analysis Version 11

            The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor , and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net .
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              BioEdit: a user-friendly biological sequences alignment editor and analysis program for Windows 97/98/ NT

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                Author and article information

                Contributors
                Journal
                J Trop Med
                J Trop Med
                jtm
                Journal of Tropical Medicine
                Hindawi
                1687-9686
                1687-9694
                2023
                5 September 2023
                : 2023
                : 6678627
                Affiliations
                1ICMR-Regional Medical Research Centre North East Region, Dibrugarh, Assam 786010, India
                2Periyar University, Centre for PG & Research Studies, Dharmapuri 635205, India
                3ICMR-Vector Control Research Centre, Puducherry 605006, India
                Author notes

                Academic Editor: Rajib Chowdhury

                Author information
                https://orcid.org/0000-0003-0651-2739
                Article
                10.1155/2023/6678627
                10497363
                37706052
                1d0f9d08-04f1-4c9f-beb1-93230a1dcb2a
                Copyright © 2023 Sathishkumar Vinayagam et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 31 May 2023
                : 17 August 2023
                : 25 August 2023
                Funding
                Funded by: Indian Council of Medical Research
                Award ID: VIR/9/2017/ECD-1
                Categories
                Research Article

                Infectious disease & Microbiology
                Infectious disease & Microbiology

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