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      Novel symbionts and potential human pathogens excavated from argasid tick microbiomes that are shaped by dual or single symbiosis

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          Abstract

          Research on vector-associated microbiomes has been expanding due to increasing emergence of vector-borne pathogens and awareness of the importance of symbionts in the vector physiology. However, little is known about microbiomes of argasid (or soft-bodied) ticks due to limited access to specimens. We collected four argasid species ( Argas japonicus, Carios vespertilionis, Ornithodoros capensis, and Ornithodoros sawaii) from the nests or burrows of their vertebrate hosts. One laboratory-reared argasid species ( Ornithodoros moubata) was also included. Attempts were then made to isolate and characterize potential symbionts/pathogens using arthropod cell lines. Microbial community structure was distinct for each tick species. Coxiella was detected as the predominant symbiont in four tick species where dual symbiosis between Coxiella and Rickettsia or Coxiella and Francisella was observed in C. vespertilionis and O. moubata, respectively. Of note, A. japonicus lacked Coxiella and instead had Occidentia massiliensis and Thiotrichales as alternative symbionts. Our study found strong correlation between tick species and life stage. We successfully isolated Oc. massiliensis and characterized potential pathogens of genera Ehrlichia and Borrelia. The results suggest that there is no consistent trend of microbiomes in relation to tick life stage that fit all tick species and that the final interpretation should be related to the balance between environmental bacterial exposure and endosymbiont ecology. Nevertheless, our findings provide insights on the ecology of tick microbiomes and basis for future investigations on the capacity of argasid ticks to carry novel pathogens with public health importance.

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          MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

          We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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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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              DADA2: High resolution sample inference from Illumina amplicon data

              We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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                Author and article information

                Contributors
                Journal
                Comput Struct Biotechnol J
                Comput Struct Biotechnol J
                Computational and Structural Biotechnology Journal
                Research Network of Computational and Structural Biotechnology
                2001-0370
                19 April 2022
                2022
                19 April 2022
                : 20
                : 1979-1992
                Affiliations
                [a ]Laboratory of Parasitology, Department of Disease Control, Faculty of Veterinary Medicine, Hokkaido University, Sapporo, Hokkaido 060-0818, Japan
                [b ]Department of Animal Medicine, Faculty of Veterinary Medicine, South Valley University, Qena 83523, Egypt
                [c ]Division of Bioinformatics, Research Center for Zoonosis Control, Hokkaido University, Sapporo, Hokkaido 001-0020, Japan
                [d ]Laboratory of Wildlife Biology and Medicine, Department of Environmental Veterinary Sciences, Faculty of Veterinary Medicine, Hokkaido University, Sapporo, Hokkaido 060-0818, Japan
                [e ]Department of Veterinary Pathobiology, Faculty of Veterinary Medicine, Lilongwe University of Agriculture and Natural Resources, P.O. Box 219, Lilongwe, Malawi
                [f ]Division of International Research Promotion, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Hokkaido 001-0020, Japan
                [g ]Department of Hygiene and Zoonoses, Faculty of Veterinary Medicine, Mansoura University, Mansoura 35516, Egypt
                [h ]Laboratory of Systemic Infection, Department of Bacteriology-I National Institute of Infectious Diseases Toyama 1-23-1, Shinjuku-ku, Tokyo 162-8640 Japan
                [i ]Laboratory of Epidemiology, Department of Veterinary Medicine, Joint Faculty of Veterinary Medicine, Yamaguchi University, 1677-1 Yoshida, Yamaguchi 753-8515, Japan
                [j ]Division of Risk Analysis and Management, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Hokkaido 001-0020, Japan
                [k ]Faculty of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki 305-8572, Japan
                [l ]Department of Bacteriology-I, National Institute of Infectious Diseases, Toyama 1-23-1, Shinjuku-ku, Tokyo 162-8640, Japan
                [m ]One Health Research Center, Hokkaido University, Sapporo, Hokkaido 001-0020, Japan
                [n ]International Collaboration Unit, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Hokkaido 001-0020, Japan
                Author notes
                [* ]Corresponding author at: Laboratory of Parasitology, Department of Disease Control, Faculty of Veterinary Medicine, Hokkaido University, Sapporo, Hokkaido 060-0818, Japan. ryo.nakao@ 123456vetmed.hokudai.ac.jp
                Article
                S2001-0370(22)00137-4
                10.1016/j.csbj.2022.04.020
                9062450
                35521555
                26fa7c4a-f9c9-4ed7-ac3c-6c798479abd9
                © 2022 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 19 February 2022
                : 15 April 2022
                : 15 April 2022
                Categories
                Research Article

                argasid ticks,dual symbiosis,infection,pathogens,vector-borne diseases

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