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      Genome Stability of Lyme Disease Spirochetes: Comparative Genomics of Borrelia burgdorferi Plasmids

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          Abstract

          Lyme disease is the most common tick-borne human illness in North America. In order to understand the molecular pathogenesis, natural diversity, population structure and epizootic spread of the North American Lyme agent, Borrelia burgdorferi sensu stricto, a much better understanding of the natural diversity of its genome will be required. Towards this end we present a comparative analysis of the nucleotide sequences of the numerous plasmids of B. burgdorferi isolates B31, N40, JD1 and 297. These strains were chosen because they include the three most commonly studied laboratory strains, and because they represent different major genetic lineages and so are informative regarding the genetic diversity and evolution of this organism. A unique feature of Borrelia genomes is that they carry a large number of linear and circular plasmids, and this work shows that strains N40, JD1, 297 and B31 carry related but non-identical sets of 16, 20, 19 and 21 plasmids, respectively, that comprise 33–40% of their genomes. We deduce that there are at least 28 plasmid compatibility types among the four strains. The B. burgdorferi ∼900 Kbp linear chromosomes are evolutionarily exceptionally stable, except for a short ≤20 Kbp plasmid-like section at the right end. A few of the plasmids, including the linear lp54 and circular cp26, are also very stable. We show here that the other plasmids, especially the linear ones, are considerably more variable. Nearly all of the linear plasmids have undergone one or more substantial inter-plasmid rearrangements since their last common ancestor. In spite of these rearrangements and differences in plasmid contents, the overall gene complement of the different isolates has remained relatively constant.

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          Most cited references 230

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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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            CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice.

            The sensitivity of the commonly used progressive multiple sequence alignment method has been greatly improved for the alignment of divergent protein sequences. Firstly, individual weights are assigned to each sequence in a partial alignment in order to down-weight near-duplicate sequences and up-weight the most divergent ones. Secondly, amino acid substitution matrices are varied at different alignment stages according to the divergence of the sequences to be aligned. Thirdly, residue-specific gap penalties and locally reduced gap penalties in hydrophilic regions encourage new gaps in potential loop regions rather than regular secondary structure. Fourthly, positions in early alignments where gaps have been opened receive locally reduced gap penalties to encourage the opening up of new gaps at these positions. These modifications are incorporated into a new program, CLUSTAL W which is freely available.
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              Tandem repeats finder: a program to analyze DNA sequences.

               G. Benson (1999)
              A tandem repeat in DNA is two or more contiguous, approximate copies of a pattern of nucleotides. Tandem repeats have been shown to cause human disease, may play a variety of regulatory and evolutionary roles and are important laboratory and analytic tools. Extensive knowledge about pattern size, copy number, mutational history, etc. for tandem repeats has been limited by the inability to easily detect them in genomic sequence data. In this paper, we present a new algorithm for finding tandem repeats which works without the need to specify either the pattern or pattern size. We model tandem repeats by percent identity and frequency of indels between adjacent pattern copies and use statistically based recognition criteria. We demonstrate the algorithm's speed and its ability to detect tandem repeats that have undergone extensive mutational change by analyzing four sequences: the human frataxin gene, the human beta T cellreceptor locus sequence and two yeast chromosomes. These sequences range in size from 3 kb up to 700 kb. A World Wide Web server interface atc3.biomath.mssm.edu/trf.html has been established for automated use of the program.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                14 March 2012
                : 7
                : 3
                Affiliations
                [1 ]Department of Pathology, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
                [2 ]Department of Medicine and Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, United States of America
                [3 ]Department of Biological Sciences, Hunter College of the City University of New York, New York City, New York, United States of America
                [4 ]Department of Medicine, Health Science Center, Stony Brook University, Stony Brook, New York, United States of America
                [5 ]Department of Medicine, New Jersey Medical School, Newark, New Jersey, United States of America
                [6 ]J. Craig Venter Institute, Rockville, Maryland, United States of America
                [7 ]Biology Department, Brookhaven National Laboratory, Upton, New York, United States of America
                University of Kentucky College of Medicine, United States of America
                Author notes

                Conceived and designed the experiments: SRC WMH WGQ BJL JJD SES CMF. Performed the experiments: EFM EBG MV DR JKA LCV SF JFW GID HMK JES RAH SRC. Analyzed the data: SRC EBG MV LCV SF WGQ EFM. Contributed reagents/materials/analysis tools: SRC BJL WGQ EFM CMF. Wrote the paper: SRC.

                [¤a]

                Current address: Virginia, United States of America

                [¤b]

                Current address: Center for Genomic Sciences, United States Army Medical Research Institute of Infectious Diseases, Ft. Detrick, Maryland, United States of America

                [¤c]

                Current address: Bethesda, Maryland, United States of America

                Article
                PONE-D-11-25819
                10.1371/journal.pone.0033280
                3303823
                22432010
                Casjens et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                Page count
                Pages: 24
                Categories
                Research Article
                Biology
                Evolutionary Biology
                Genetics
                Molecular Genetics
                Genomics
                Microbiology
                Bacteriology
                Medicine
                Infectious Diseases
                Bacterial Diseases

                Uncategorized

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