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      Mapping the tRNA modification landscape of Bartonella henselae Houston I and Bartonella quintana Toulouse

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          Abstract

          Transfer RNA (tRNA) modifications play a crucial role in maintaining translational fidelity and efficiency, and they may function as regulatory elements in stress response and virulence. Despite their pivotal roles, a comprehensive mapping of tRNA modifications and their associated synthesis genes is still limited, with a predominant focus on free-living bacteria. In this study, we employed a multidisciplinary approach, incorporating comparative genomics, mass spectrometry, and next-generation sequencing, to predict the set of tRNA modification genes responsible for tRNA maturation in two intracellular pathogens— Bartonella henselae Houston I and Bartonella quintana Toulouse, which are causative agents of cat-scratch disease and trench fever, respectively. This analysis presented challenges, particularly because of host RNA contamination, which served as a potential source of error. However, our approach predicted 26 genes responsible for synthesizing 23 distinct tRNA modifications in B. henselae and 22 genes associated with 23 modifications in B. quintana. Notably, akin to other intracellular and symbiotic bacteria, both Bartonella species have undergone substantial reductions in tRNA modification genes, mostly by simplifying the hypermodifications present at positions 34 and 37. Bartonella quintana exhibited the additional loss of four modifications and these were linked to examples of gene decay, providing snapshots of reductive evolution.

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          Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

          S Altschul (1997)
          The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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            Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation

            The Interactive Tree Of Life ( https://itol.embl.de ) is an online tool for the display, manipulation and annotation of phylogenetic and other trees. It is freely available and open to everyone. iTOL version 5 introduces a completely new tree display engine, together with numerous new features. For example, a new dataset type has been added (MEME motifs), while annotation options have been expanded for several existing ones. Node metadata display options have been extended and now also support non-numerical categorical values, as well as multiple values per node. Direct manual annotation is now available, providing a set of basic drawing and labeling tools, allowing users to draw shapes, labels and other features by hand directly onto the trees. Support for tree and dataset scales has been extended, providing fine control over line and label styles. Unrooted tree displays can now use the equal-daylight algorithm, proving a much greater display clarity. The user account system has been streamlined and expanded with new navigation options and currently handles >1 million trees from >70 000 individual users. Graphical Abstract iTOL: an online tool for the tree display and annotation.
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              Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration

              Data visualization is an essential component of genomic data analysis. However, the size and diversity of the data sets produced by today’s sequencing and array-based profiling methods present major challenges to visualization tools. The Integrative Genomics Viewer (IGV) is a high-performance viewer that efficiently handles large heterogeneous data sets, while providing a smooth and intuitive user experience at all levels of genome resolution. A key characteristic of IGV is its focus on the integrative nature of genomic studies, with support for both array-based and next-generation sequencing data, and the integration of clinical and phenotypic data. Although IGV is often used to view genomic data from public sources, its primary emphasis is to support researchers who wish to visualize and explore their own data sets or those from colleagues. To that end, IGV supports flexible loading of local and remote data sets, and is optimized to provide high-performance data visualization and exploration on standard desktop systems. IGV is freely available for download from http://www.broadinstitute.org/igv, under a GNU LGPL open-source license.
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                Author and article information

                Contributors
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                URI : https://loop.frontiersin.org/people/2320344/overviewRole: Role: Role: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/144095/overviewRole: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/16154/overviewRole: Role: Role: Role:
                URI : https://loop.frontiersin.org/people/198777/overviewRole: Role: Role: Role: Role: Role: Role: Role: Role: Role:
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                13 March 2024
                2024
                : 15
                : 1369018
                Affiliations
                [1] 1Department of Microbiology and Cell Science, University of Florida , Gainesville, FL, United States
                [2] 2Department of Biological Engineering, Massachusetts Institute of Technology , Cambridge, MA, United States
                [3] 3Singapore-MIT Alliance for Research and Technology , Singapore, Singapore
                [4] 4Université de Lorraine, UAR2008/US40 IBSLor, EpiRNA-Seq Core Facility and UMR7365 IMoPA, CNRS-Inserm, Biopôle UL , Nancy, France
                [5] 5Division of Biological Sciences, University of Montana , Missoula, MT, United States
                [6] 6Genetic Institute, University of Florida , Gainesville, FL, United States
                Author notes

                Edited by: Jiqiang Ling, University of Maryland, United States

                Reviewed by: Assaf Katz, University of Chile, Chile

                Jack A. Dunkle, University of Alabama, United States

                *Correspondence:Valérie de Crécy-Lagard, vcrecy@ 123456ufl.edu

                These authors have contributed equally to this work

                Article
                10.3389/fmicb.2024.1369018
                10965804
                38544857
                726760e4-818c-4a63-9e4c-2cbd4db850e7
                Copyright © 2024 Quaiyum, Sun, Marchand, Sun, Reed, Motorin, Dedon, Minnick and de Crécy-Lagard.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 11 January 2024
                : 26 February 2024
                Page count
                Figures: 5, Tables: 1, Equations: 0, References: 85, Pages: 13, Words: 8684
                Funding
                The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was funded by the National Institutes of Health (project numbers GM070641, ES026856, and ES024615) and the National Research Foundation of Singapore through the Singapore-MIT Alliance for Research and Technology Antimicrobial Resistance Interdisciplinary Research Group.
                Categories
                Microbiology
                Original Research
                Custom metadata
                Microbial Physiology and Metabolism

                Microbiology & Virology
                intracellular pathogens,trna modification,mass spectrometry,next-generation sequencing,bartonella

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