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  • Title: Anatomy of Escherichia coli ribosome binding sites.
    Author: Shultzaberger RK, Bucheimer RE, Rudd KE, Schneider TD.
    Journal: J Mol Biol; 2001 Oct 12; 313(1):215-28. PubMed ID: 11601857.
    Abstract:
    During translational initiation in prokaryotes, the 3' end of the 16S rRNA binds to a region just upstream of the initiation codon. The relationship between this Shine-Dalgarno (SD) region and the binding of ribosomes to translation start-points has been well studied, but a unified mathematical connection between the SD, the initiation codon and the spacing between them has been lacking. Using information theory, we constructed a model that treats these three components uniformly by assigning to the SD and the initiation region (IR) conservations in bits of information, and by assigning to the spacing an uncertainty, also in bits. To build the model, we first aligned the SD region by maximizing the information content there. The ease of this process confirmed the existence of the SD pattern within a set of 4122 reviewed and revised Escherichia coli gene starts. This large data set allowed us to show graphically, by sequence logos, that the spacing between the SD and the initiation region affects both the SD site conservation and its pattern. We used the aligned SD, the spacing, and the initiation region to model ribosome binding and to identify gene starts that do not conform to the ribosome binding site model. A total of 569 experimentally proven starts are more conserved (have higher information content) than the full set of revised starts, which probably reflects an experimental bias against the detection of gene products that have inefficient ribosome binding sites. Models were refined cyclically by removing non-conforming weak sites. After this procedure, models derived from either the original or the revised gene start annotation were similar. Therefore, this information theory-based technique provides a method for easily constructing biologically sensible ribosome binding site models. Such models should be useful for refining gene-start predictions of any sequenced bacterial genome.
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