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      First molecular detection of Borrelia theileri subclinical infection in a cow from Brazil

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          Abstract

          Borrelia theileri is a relapsing fever group Borrelia that is transmitted to cattle by ticks of the genus Rhipicephalus. In this study, we describe the first molecular detection of B. theileri subclinical infection in a cow in Brazil. During the examination of stained blood smears of 10 cows from a farm with a recent history of fatal Trypanosoma vivax trypanosomiasis, spirochete-like structures were incidentally detected in one of the cows. The animal presented good body score, normal hematocrit and normal-colored ocular mucosa. Temperature, heart rate and respiratory rate were all normal. The animal was infested by ticks, which were morphologically identified as Rhipicephalus microplus. The diagnosis was confirmed by testing DNA extracted from a blood sample using a PCR targeting a ≈ 650 bp fragment of the flagellin B (flaB) gene of Borrelia spp. The partial flaB sequence obtained showed 99.83% similarity with B. theileri. Phylogenetically, the flaB partial sequence generated herein clustered with other B. theileri sequences, being separated from B. lonestari. This is the first molecular detection of B. theileri subclinical infection in a cow in Brazil. The possible implications of this finding are discussed.

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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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            MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods.

            Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.
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              A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood.

              The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximum- likelihood principle, which clearly satisfies these requirements. The core of this method is a simple hill-climbing algorithm that adjusts tree topology and branch lengths simultaneously. This algorithm starts from an initial tree built by a fast distance-based method and modifies this tree to improve its likelihood at each iteration. Due to this simultaneous adjustment of the topology and branch lengths, only a few iterations are sufficient to reach an optimum. We used extensive and realistic computer simulations to show that the topological accuracy of this new method is at least as high as that of the existing maximum-likelihood programs and much higher than the performance of distance-based and parsimony approaches. The reduction of computing time is dramatic in comparison with other maximum-likelihood packages, while the likelihood maximization ability tends to be higher. For example, only 12 min were required on a standard personal computer to analyze a data set consisting of 500 rbcL sequences with 1,428 base pairs from plant plastids, thus reaching a speed of the same order as some popular distance-based and parsimony algorithms. This new method is implemented in the PHYML program, which is freely available on our web page: http://www.lirmm.fr/w3ifa/MAAS/.
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                Author and article information

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                Journal
                Veterinary Research Communications
                Vet Res Commun
                Springer Science and Business Media LLC
                0165-7380
                1573-7446
                June 2023
                October 26 2022
                June 2023
                : 47
                : 2
                : 963-967
                Article
                10.1007/s11259-022-10020-x
                36287370
                2ba4d102-cabe-4e8c-88b7-692192df67df
                © 2023

                https://www.springernature.com/gp/researchers/text-and-data-mining

                https://www.springernature.com/gp/researchers/text-and-data-mining

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