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      Molecular signature of hypersaline adaptation: insights from genome and proteome composition of halophilic prokaryotes

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          Abstract

          A comparative genomic and proteomic study of halophilic and non-halophilic prokaryotes identifies specific genomic and proteomic features typical of halophilic species that are independent from genomic GC-content and taxonomic position.

          Abstract

          Background

          Halophilic prokaryotes are adapted to thrive in extreme conditions of salinity. Identification and analysis of distinct macromolecular characteristics of halophiles provide insight into the factors responsible for their adaptation to high-salt environments. The current report presents an extensive and systematic comparative analysis of genome and proteome composition of halophilic and non-halophilic microorganisms, with a view to identify such macromolecular signatures of haloadaptation.

          Results

          Comparative analysis of the genomes and proteomes of halophiles and non-halophiles reveals some common trends in halophiles that transcend the boundary of phylogenetic relationship and the genomic GC-content of the species. At the protein level, halophilic species are characterized by low hydrophobicity, over-representation of acidic residues, especially Asp, under-representation of Cys, lower propensities for helix formation and higher propensities for coil structure. At the DNA level, the dinucleotide abundance profiles of halophilic genomes bear some common characteristics, which are quite distinct from those of non-halophiles, and hence may be regarded as specific genomic signatures for salt-adaptation. The synonymous codon usage in halophiles also exhibits similar patterns regardless of their long-term evolutionary history.

          Conclusion

          The generality of molecular signatures for environmental adaptation of extreme salt-loving organisms, demonstrated in the present study, advocates the convergent evolution of halophilic species towards specific genome and amino acid composition, irrespective of their varying GC-bias and widely disparate taxonomic positions. The adapted features of halophiles seem to be related to physical principles governing DNA and protein stability, in response to the extreme environmental conditions under which they thrive.

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          Most cited references47

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          The codon Adaptation Index--a measure of directional synonymous codon usage bias, and its potential applications.

          P. Sharp, W Li (1987)
          A simple, effective measure of synonymous codon usage bias, the Codon Adaptation Index, is detailed. The index uses a reference set of highly expressed genes from a species to assess the relative merits of each codon, and a score for a gene is calculated from the frequency of use of all codons in that gene. The index assesses the extent to which selection has been effective in moulding the pattern of codon usage. In that respect it is useful for predicting the level of expression of a gene, for assessing the adaptation of viral genes to their hosts, and for making comparisons of codon usage in different organisms. The index may also give an approximate indication of the likely success of heterologous gene expression.
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            MOLMOL: a program for display and analysis of macromolecular structures.

            MOLMOL is a molecular graphics program for display, analysis, and manipulation of three-dimensional structures of biological macromolecules, with special emphasis on nuclear magnetic resonance (NMR) solution structures of proteins and nucleic acids. MOLMOL has a graphical user interface with menus, dialog boxes, and on-line help. The display possibilities include conventional presentation, as well as novel schematic drawings, with the option of combining different presentations in one view of a molecule. Covalent molecular structures can be modified by addition or removal of individual atoms and bonds, and three-dimensional structures can be manipulated by interactive rotation about individual bonds. Special efforts were made to allow for appropriate display and analysis of the sets of typically 20-40 conformers that are conventionally used to represent the result of an NMR structure determination, using functions for superimposing sets of conformers, calculation of root mean square distance (RMSD) values, identification of hydrogen bonds, checking and displaying violations of NMR constraints, and identification and listing of short distances between pairs of hydrogen atoms.
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              Dinucleotide relative abundance extremes: a genomic signature.

              Early biochemical experiments established that the set of dinucleotide odds ratios or 'general design' is a remarkably stable property of the DNA of an organism, which is essentially the same in protein-coding DNA, bulk genomic DNA, and in different renaturation rate and density gradient fractions of genomic DNA in many organisms. Analysis of currently available genomic sequence data has extended these earlier results, showing that the general designs of disjoint samples of a genome are substantially more similar to each other than to those of sequences from other organisms and that closely related organisms have similar general designs. From this perspective, the set of dinucleotide odds ratio (relative abundance) values constitute a signature of each DNA genome, which can discriminate between sequences from different organisms. Dinucleotide-odds ratio values appear to reflect not only the chemistry of dinucleotide stacking energies and base-step conformational preferences, but also the species-specific properties of DNA modification, replication and repair mechanisms.
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                Author and article information

                Journal
                Genome Biol
                Genome Biology
                BioMed Central
                1465-6906
                1465-6914
                2008
                9 April 2008
                : 9
                : 4
                : R70
                Affiliations
                [1 ]Bioinformatics Center, Indian Institute of Chemical Biology, 4, Raja SC Mullick Road, Kolkata - 700 032, India
                [2 ]Department of Biology, The Pennsylvania State University, Mueller Lab, University Park, PA 16802, USA
                [3 ]Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, PA 16802, USA
                [4 ]Structural Biology and Bioinformatics Division, Indian Institute of Chemical Biology, 4, Raja SC Mullick Road, Kolkata - 700 032, India
                Article
                gb-2008-9-4-r70
                10.1186/gb-2008-9-4-r70
                2643941
                18397532
                de9d3e47-66d5-497a-83b7-61787df15aa9
                Copyright © 2008 Paul et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 13 March 2008
                : 1 April 2008
                : 9 April 2008
                Categories
                Research

                Genetics
                Genetics

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