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      Complete Genome Sequence of Citrobacter freundii Myophage Moon

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          Abstract

          Citrobacter freundii and other Gram-negative opportunistic pathogens necessitate concern from the public health sector. Bacteriophages that kill such pathogens may be useful in the control and containment of these infections. Here, we describe the genome of a newly isolated T4-like myophage of C. freundii, Moon, and present its features.

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          GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions.

          J Besemer (2001)
          Improving the accuracy of prediction of gene starts is one of a few remaining open problems in computer prediction of prokaryotic genes. Its difficulty is caused by the absence of relatively strong sequence patterns identifying true translation initiation sites. In the current paper we show that the accuracy of gene start prediction can be improved by combining models of protein-coding and non-coding regions and models of regulatory sites near gene start within an iterative Hidden Markov model based algorithm. The new gene prediction method, called GeneMarkS, utilizes a non-supervised training procedure and can be used for a newly sequenced prokaryotic genome with no prior knowledge of any protein or rRNA genes. The GeneMarkS implementation uses an improved version of the gene finding program GeneMark.hmm, heuristic Markov models of coding and non-coding regions and the Gibbs sampling multiple alignment program. GeneMarkS predicted precisely 83.2% of the translation starts of GenBank annotated Bacillus subtilis genes and 94.4% of translation starts in an experimentally validated set of Escherichia coli genes. We have also observed that GeneMarkS detects prokaryotic genes, in terms of identifying open reading frames containing real genes, with an accuracy matching the level of the best currently used gene detection methods. Accurate translation start prediction, in addition to the refinement of protein sequence N-terminal data, provides the benefit of precise positioning of the sequence region situated upstream to a gene start. Therefore, sequence motifs related to transcription and translation regulatory sites can be revealed and analyzed with higher precision. These motifs were shown to possess a significant variability, the functional and evolutionary connections of which are discussed.
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            Bacteriophage T4 genome.

            Eric Miller, Elizabeth M. Kutter, Gisela Mosig … (2003)
            Phage T4 has provided countless contributions to the paradigms of genetics and biochemistry. Its complete genome sequence of 168,903 bp encodes about 300 gene products. T4 biology and its genomic sequence provide the best-understood model for modern functional genomics and proteomics. Variations on gene expression, including overlapping genes, internal translation initiation, spliced genes, translational bypassing, and RNA processing, alert us to the caveats of purely computational methods. The T4 transcriptional pattern reflects its dependence on the host RNA polymerase and the use of phage-encoded proteins that sequentially modify RNA polymerase; transcriptional activator proteins, a phage sigma factor, anti-sigma, and sigma decoy proteins also act to specify early, middle, and late promoter recognition. Posttranscriptional controls by T4 provide excellent systems for the study of RNA-dependent processes, particularly at the structural level. The redundancy of DNA replication and recombination systems of T4 reveals how phage and other genomes are stably replicated and repaired in different environments, providing insight into genome evolution and adaptations to new hosts and growth environments. Moreover, genomic sequence analysis has provided new insights into tail fiber variation, lysis, gene duplications, and membrane localization of proteins, while high-resolution structural determination of the "cell-puncturing device," combined with the three-dimensional image reconstruction of the baseplate, has revealed the mechanism of penetration during infection. Despite these advances, nearly 130 potential T4 genes remain uncharacterized. Current phage-sequencing initiatives are now revealing the similarities and differences among members of the T4 family, including those that infect bacteria other than Escherichia coli. T4 functional genomics will aid in the interpretation of these newly sequenced T4-related genomes and in broadening our understanding of the complex evolution and ecology of phages-the most abundant and among the most ancient biological entities on Earth.
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              Optimal alignments in linear space.

              Nicholas E. Myers, Stewart L W Miller (1988)
              Space, not time, is often the limiting factor when computing optimal sequence alignments, and a number of recent papers in the biology literature have proposed space-saving strategies. However, a 1975 computer science paper by Hirschberg presented a method that is superior to the new proposals, both in theory and in practice. The goal of this paper is to give Hirschberg's idea the visibility it deserves by developing a linear-space version of Gotoh's algorithm, which accommodates affine gap penalties. A portable C-software package implementing this algorithm is available on the BIONET free of charge.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Genome Announc
                Journal ID (iso-abbrev): Genome Announc
                Journal ID (hwp): ga
                Journal ID (pmc): ga
                Journal ID (publisher-id): GA
                Title: Genome Announcements
                Publisher: American Society for Microbiology (1752 N St., N.W., Washington, DC )
                ISSN (Electronic): 2169-8287
                Publication date (Electronic): 29 January 2015
                Publication date Collection: Jan-Feb 2015
                Volume: 3
                Issue: 1
                Electronic Location Identifier: e01427-14
                Affiliations
                [1]Center for Phage Technology, Texas A&M University, College Station, Texas, USA
                Author notes
                Address correspondence to Gabriel F. Kuty Everett, gabbyeverett@ 123456tamu.edu .
                Article
                Publisher ID: genomeA01427-14
                DOI: 10.1128/genomeA.01427-14
                PMC ID: 4319498
                PubMed ID: 25635027
                SO-VID: 7bf7aaf5-9fe7-4449-a301-e06d8924dc07
                Copyright © Copyright © 2015 Edwards et al.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported license.

                History
                Date received : 1 December 2014
                Date accepted : 18 December 2014
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 13, Pages: 2, Words: 1148
                Categories
                Subject: Viruses
                Custom metadata
                cover-date January/February 2015
                access-type free

                ScienceOpen disciplines: Genetics
                Data availability:
                ScienceOpen disciplines: Genetics

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