Dataset Information

Translation in Prokaryotes.

ABSTRACT: This review summarizes our current understanding of translation in prokaryotes, focusing on the mechanistic and structural aspects of each phase of translation: initiation, elongation, termination, and ribosome recycling. The assembly of the initiation complex provides multiple checkpoints for messenger RNA (mRNA) and start-site selection. Correct codon-anticodon interaction during the decoding phase of elongation results in major conformational changes of the small ribosomal subunit and shapes the reaction pathway of guanosine triphosphate (GTP) hydrolysis. The ribosome orchestrates proton transfer during peptide bond formation, but requires the help of elongation factor P (EF-P) when two or more consecutive Pro residues are to be incorporated. Understanding the choreography of transfer RNA (tRNA) and mRNA movements during translocation helps to place the available structures of translocation intermediates onto the time axis of the reaction pathway. The nascent protein begins to fold cotranslationally, in the constrained space of the polypeptide exit tunnel of the ribosome. When a stop codon is reached at the end of the coding sequence, the ribosome, assisted by termination factors, hydrolyzes the ester bond of the peptidyl-tRNA, thereby releasing the nascent protein. Following termination, the ribosome is dissociated into subunits and recycled into another round of initiation. At each step of translation, the ribosome undergoes dynamic fluctuations between different conformation states. The aim of this article is to show the link between ribosome structure, dynamics, and function.

SUBMITTER: Rodnina MV

PROVIDER: S-EPMC6120702 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Translation in Prokaryotes.

Rodnina Marina V MV

Cold Spring Harbor perspectives in biology 20180904 9

This review summarizes our current understanding of translation in prokaryotes, focusing on the mechanistic and structural aspects of each phase of translation: initiation, elongation, termination, and ribosome recycling. The assembly of the initiation complex provides multiple checkpoints for messenger RNA (mRNA) and start-site selection. Correct codon-anticodon interaction during the decoding phase of elongation results in major conformational changes of the small ribosomal subunit and shapes ...[more]

PMID: 29661790

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Project description:BackgroundComputational prediction methods are currently used to identify genes in prokaryote genomes. However, identification of the correct translation initiation sites remains a difficult task. Accurate translation initiation sites (TISs) are important not only for the annotation of unknown proteins but also for the prediction of operons, promoters, and small non-coding RNA genes, as this typically makes use of the intergenic distance. A further problem is that most existing methods are optimized for Escherichia coli data sets; applying these methods to newly sequenced bacterial genomes may not result in an equivalent level of accuracy.ResultsBased on a biological representation of the translation process, we applied Bayesian statistics to create a score function for predicting translation initiation sites. In contrast to existing programs, our combination of methods uses supervised learning to optimally use the set of known translation initiation sites. We combined the Ribosome Binding Site (RBS) sequence, the distance between the translation initiation site and the RBS sequence, the base composition of the start codon, the nucleotide composition (A-rich sequences) following start codons, and the expected distribution of the protein length in a Bayesian scoring function. To further increase the prediction accuracy, we also took into account the operon orientation. The outcome of the procedure achieved a prediction accuracy of 93.2% in 858 E. coli genes from the EcoGene data set and 92.7% accuracy in a data set of 1243 Bacillus subtilis 'non-y' genes. We confirmed the performance in the GC-rich Gamma-Proteobacteria Herminiimonas arsenicoxydans, Pseudomonas aeruginosa, and Burkholderia pseudomallei K96243.ConclusionHon-yaku, being based on a careful choice of elements important in translation, improved the prediction accuracy in B. subtilis data sets and other bacteria except for E. coli. We believe that most remaining mispredictions are due to atypical ribosomal binding sequences used in specific translation control processes, or likely errors in the training data sets.

Dataset Information

Translation in Prokaryotes.

Publications

Translation in Prokaryotes.

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