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      Codon Usage Domains over Bacterial Chromosomes

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          Abstract

          The geography of codon bias distributions over prokaryotic genomes and its impact upon chromosomal organization are analyzed. To this aim, we introduce a clustering method based on information theory, specifically designed to cluster genes according to their codon usage and apply it to the coding sequences of Escherichia coli and Bacillus subtilis. One of the clusters identified in each of the organisms is found to be related to expression levels, as expected, but other groups feature an over-representation of genes belonging to different functional groups, namely horizontally transferred genes, motility, and intermediary metabolism. Furthermore, we show that genes with a similar bias tend to be close to each other on the chromosome and organized in coherent domains, more extended than operons, demonstrating a role of translation in structuring bacterial chromosomes. It is argued that a sizeable contribution to this effect comes from the dynamical compartimentalization induced by the recycling of tRNAs, leading to gene expression rates dependent on their genomic and expression context.

          Synopsis

          Genomic sequencing projects are clearly showing that cellular components are not randomly encoded over bacterial chromosomes. Order arises for a variety of reasons. Bailly-Bechet and colleagues focused here on the role of translation in shaping bacterial chromosomes. Due to degeneracy of the genetic code, each amino acid can be encoded by multiple codons. Gene encoding is not random, though, and, depending on the genes, some codons are preferred to their synonyms. This is the so-called codon bias phenomenon. The authors analyzed the usage of synonymous codons for protein encoding and its geography over bacterial chromosomes. They found that genes sharing similar codon bias tend to be close to each other on the chromosome, in coherent patches more extended than transcriptional units. Their hypothesis is that those correlations in codon bias enable the cell to locally recycle tRNAs employed during translation, reducing stalling of the ribosomes due to rare tRNAs. This also entails a dependence of expression rates of a gene on its chromosomal context. Furthermore, their analysis made clear that genes involved in anabolic pathways, mainly active when the cell is starving, have a similar codon usage, and that they are encoded on the lagging strand of DNA. They hypothesize that this is due to relative translation efficiency of the lagging strand as compared with the leading one, illustrating the role of translation in creating structural evolutionary constraints.

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          Most cited references59

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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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            Long-range correlations in nucleotide sequences.

            DNA sequences have been analysed using models, such as an n-step Markov chain, that incorporate the possibility of short-range nucleotide correlations. We propose here a method for studying the stochastic properties of nucleotide sequences by constructing a 1:1 map of the nucleotide sequence onto a walk, which we term a 'DNA walk'. We then use the mapping to provide a quantitative measure of the correlation between nucleotides over long distances along the DNA chain. Thus we uncover in the nucleotide sequence a remarkably long-range power law correlation that implies a new scale-invariant property of DNA. We find such long-range correlations in intron-containing genes and in nontranscribed regulatory DNA sequences, but not in complementary DNA sequences or intron-less genes.
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              Co-variation of tRNA abundance and codon usage in Escherichia coli at different growth rates.

              We have used two-dimensional polyacrylamide gel electrophoresis to fractionate tRNAs from Escherichia coli. A sufficiently high degree of resolution was obtained for 44 out of 46 tRNA species in E. coli to be resolved into individual electrophoretic components. These isolated components were identified by hybridization to tRNA-specific oligonucleotide probes. Systematic measurements of the abundance of each individual tRNA isoacceptor in E. coli, grown at rates varying from 0.4 to 2.5 doublings per hour, were made with the aid of this electrophoretic protocol. We find that there is a biased distribution of the tRNA abundance at all growth rates, and that this can be roughly correlated with the values of codon frequencies in the mRNA pools calculated for bacteria growing at different rates. The tRNA species cognate to abundant codons increase in concentration as the growth rate increases but not as dramatically as might be anticipated. The levels of most of the tRNA isoacceptors cognate to less abundant codons remain unchanged with increasing growth rates. The result of these changes in tRNA abundance is that the relative increase in the amounts of major tRNA species in the bacteria growing at the fastest growth rates is more modest than previous estimates from this laboratory suggested. Furthermore, a systematic error in previous estimates of ribosomal RNA content of the bacteria has been detected. This will account for the quantitative discrepancies between the previous and the present data for tRNA abundance.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Comput Biol
                pcbi
                plcb
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, USA )
                1553-734X
                1553-7358
                April 2006
                21 April 2006
                : 2
                : 4
                : e37
                Affiliations
                [1 ] CNRS URA 2171, Institute Pasteur, Unité Génétique in silico, Paris, France
                [2 ] CNRS URA 2171, Institute Pasteur, Unité Génétique des Génomes Bactériens, Paris, France
                [3 ] Abdus Salam International Center Theoretical Physics, Trieste, Italy
                [4 ] Computing Laboratory, University of Kent, Canterbury, Kent, United Kingdom
                Max Planck Institute for Molecular Genetics, Germany
                Author notes
                * To whom correspondence should be addressed. E-mail: massimo@ 123456pasteur.fr
                Article
                05-PLCB-RA-0333R2 plcb-02-04-06
                10.1371/journal.pcbi.0020037
                1447655
                16683018
                c0f9edc9-06a0-4db9-93c3-4529a0d5bcdb
                Copyright: © 2006 Bailly-Bechet 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.
                History
                : 21 November 2005
                : 13 March 2006
                Page count
                Pages: 13
                Categories
                Research Article
                Bioinformatics - Computational Biology
                Microbiology
                Molecular Biology - Structural Biology
                Statistics
                Systems Biology
                Eubacteria
                Custom metadata
                Bailly-Bechet M, Danchin A, Iqbal M, Marsili M, Vergassola M (2006) Codon usage domains over bacterial chromosomes. PLoS Comput Biol 2(4): e37. DOI: 10.1371/journal.pcbi.0020037

                Quantitative & Systems biology
                Quantitative & Systems biology

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