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      Novel Rickettsia genotypes in ticks in French Guiana, South America

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          Abstract

          Rickettsia are obligate intracellular bacteria often associated with ticks and best known for causing human diseases (rickettsiosis), including typhus fever and sporadic cases of serious infection. In this study, we conducted a large survey of ticks in French Guiana to understand the overall diversity of Rickettsia in this remote area largely covered by dense rainforests. Out of 819 individuals (22 tick species in six genera), 252 (30.8%) samples were positive for Rickettsia infection. Multilocus typing and phylogenetic analysis identified 19 Rickettsia genotypes, but none was 100% identical to already known Rickettsia species or strains. Among these 19 genotypes, we identified two validated Rickettsia species, Rickettsia amblyommatis (spotted fever group) and Rickettsia bellii (bellii group), and characterized a novel and divergent Rickettsia phylogenetic group, the guiana group. While some tick hosts of these Rickettsia genotypes are among the most common ticks to bite humans in French Guiana, their potential pathogenicity remains entirely unknown. However, we found a strong association between Rickettsia genotypes and their host tick species, suggesting that most of these Rickettsia genotypes may be nonpathogenic forms maintained through transovarial transmission.

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          Most cited references 48

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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            Cutadapt removes adapter sequences from high-throughput sequencing reads

             Marcel Martin (2011)
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              Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis.

               J Castresana (2000)
              The use of some multiple-sequence alignments in phylogenetic analysis, particularly those that are not very well conserved, requires the elimination of poorly aligned positions and divergent regions, since they may not be homologous or may have been saturated by multiple substitutions. A computerized method that eliminates such positions and at the same time tries to minimize the loss of informative sites is presented here. The method is based on the selection of blocks of positions that fulfill a simple set of requirements with respect to the number of contiguous conserved positions, lack of gaps, and high conservation of flanking positions, making the final alignment more suitable for phylogenetic analysis. To illustrate the efficiency of this method, alignments of 10 mitochondrial proteins from several completely sequenced mitochondrial genomes belonging to diverse eukaryotes were used as examples. The percentages of removed positions were higher in the most divergent alignments. After removing divergent segments, the amino acid composition of the different sequences was more uniform, and pairwise distances became much smaller. Phylogenetic trees show that topologies can be different after removing conserved blocks, particularly when there are several poorly resolved nodes. Strong support was found for the grouping of animals and fungi but not for the position of more basal eukaryotes. The use of a computerized method such as the one presented here reduces to a certain extent the necessity of manually editing multiple alignments, makes the automation of phylogenetic analysis of large data sets feasible, and facilitates the reproduction of the final alignment by other researchers.
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                Author and article information

                Contributors
                olivier.duron@ird.fr
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                13 February 2020
                13 February 2020
                2020
                : 10
                Affiliations
                GRID grid.433120.7, Laboratoire Maladies Infectieuses et Vecteurs: Ecologie, Génétique, Evolution et Contrôle (MIVEGEC), , Centre National de la Recherche Scientifique (CNRS) - Institut pour la Recherche et le Développement (IRD) - Université de Montpellier (UM), ; 911 Avenue Agropolis, F-34394 Montpellier, France
                Article
                59488
                10.1038/s41598-020-59488-0
                7018960
                32054909
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                Funding
                Funded by: Laboratoire d'excellence CEBA (Centre d'Etude de la Biodiversité Amazonienne)
                Funded by: Laboratoire d'excellence CEBA (Centre d'Etude de la Biodiversité Amazonienne)
                Funded by: Laboratoire d'excellence CEBA (Centre d'Etude de la Biodiversité Amazonienne)
                Funded by: Laboratoire d'excellence CEBA (Centre d'Etude de la Biodiversité Amazonienne)
                Categories
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                © The Author(s) 2020

                Uncategorized

                bacterial infection, infectious-disease epidemiology

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