A web application for automatic prediction of gene translation elongation efficiency

Sokolov, V. S.; Zuraev, Bulat S.; Lashin, Sergey A.; Matushkin, Yury G.

doi:10.1515/jib-2015-256

Cited by 6 publications

(6 citation statements)

References 16 publications

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“…In this article, we have analyzed elongation efficiency indices calculated by EloE (Elongation Efficiency) tool [ 7 ] (developed by Sokolov V.S, Novosibirsk, Russia). The executable file of the tool as well as the user’s manual, input and output data are deposited in the Supplementary files .…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, bioinformatic estimation of factors contributing to protein abundance, such as elongation efficiency, is an important step towards in silico prediction of protein abundance levels. Here we investigate the capability to predict protein abundance for phylogenetically diverse organisms by using the EloE (Elongation Efficiency) tool [ 7 , 8 , 9 , 10 ]. This tool calculates parameters that impact elongation efficiency of the translation stage: codon bias, number of secondary structures in mRNA, and energy of secondary structures in mRNA.…”

Section: Introductionmentioning

confidence: 99%

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Bioinformatic Assessment of Factors Affecting the Correlation between Protein Abundance and Elongation Efficiency in Prokaryotes

Korenskaia

Matushkin

Lashin

et al. 2022

IJMS

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Protein abundance is crucial for the majority of genetically regulated cell functions to act properly in prokaryotic organisms. Therefore, developing bioinformatic methods for assessing the efficiency of different stages of gene expression is of great importance for predicting the actual protein abundance. One of these steps is the evaluation of translation elongation efficiency based on mRNA sequence features, such as codon usage bias and mRNA secondary structure properties. In this study, we have evaluated correlation coefficients between experimentally measured protein abundance and predicted elongation efficiency characteristics for 26 prokaryotes, including non-model organisms, belonging to diverse taxonomic groups The algorithm for assessing elongation efficiency takes into account not only codon bias, but also number and energy of secondary structures in mRNA if those demonstrate an impact on predicted elongation efficiency of the ribosomal protein genes. The results show that, for a number of organisms, secondary structures are a better predictor of protein abundance than codon usage bias. The bioinformatic analysis has revealed several factors associated with the value of the correlation coefficient. The first factor is the elongation efficiency optimization type—the organisms whose genomes are optimized for codon usage only have significantly higher correlation coefficients. The second factor is taxonomical identity—bacteria that belong to the class Bacilli tend to have higher correlation coefficients among the analyzed set. The third is growth rate, which is shown to be higher for the organisms with higher correlation coefficients between protein abundance and predicted translation elongation efficiency. The obtained results can be useful for further improvement of methods for protein abundance prediction.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bioinformatic Assessment of Factors Affecting the Correlation between Protein Abundance and Elongation Efficiency in Prokaryotes

Korenskaia

Matushkin

Lashin

et al. 2022

IJMS

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“…The algorithm has been described in the previous studies [36,37,61] and represented in a detail in a recent article [38], we used the same version of EloE software, which is available in the supplementary materials of that study. Briefly, EloE calculates translation elongation efficiency indices (EEI) considering a number of factors in various combinations, namely, the impact of codon content, number of secondary structures, and energy of these structures in mRNA for all protein-coding genes of the studied organism [62]. Various combinations form the five types of translation elongation efficiency indices (see Table 1).…”

Section: Elongation Efficiency Calculationmentioning

confidence: 99%

Bioinformatic Analysis Reveals the Role of Translation Elongation Efficiency Optimisation in the Evolution of Ralstonia Genus

Korenskaia,

Matushkin,

Mustafin

et al. 2023

Biology

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Translation efficiency modulates gene expression in prokaryotes. The comparative analysis of translation elongation efficiency characteristics of Ralstonia genus bacteria genomes revealed that these characteristics diverge in accordance with the phylogeny of Ralstonia. The first branch of this genus is a group of bacteria commonly found in moist environments such as soil and water that includes the species R. mannitolilytica, R. insidiosa, and R. pickettii, which are also described as nosocomial infection pathogens. In contrast, the second branch is plant pathogenic bacteria consisting of R. solanacearum, R. pseudosolanacearum, and R. syzygii. We found that the soil Ralstonia have a significantly lower number and energy of potential secondary structures in mRNA and an increased role of codon usage bias in the optimization of highly expressed genes’ translation elongation efficiency, not only compared to phytopathogenic Ralstonia but also to Cupriavidus necator, which is closely related to the Ralstonia genus. The observed alterations in translation elongation efficiency of orthologous genes are also reflected in the difference of potentially highly expressed gene’ sets’ content among Ralstonia branches with different lifestyles. Analysis of translation elongation efficiency characteristics can be considered a promising approach for studying complex mechanisms that determine the evolution and adaptation of bacteria in various environments.

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“…The EloE (Elongation Efficiency) web application, in turn, can be useful in preliminary estimation of translation elongation efficiency for genes for which experimental data are not available yet. Its results can be used, for instance, in other programs modelling artificial genetic structures in genetically engineered experiments [5].…”

Section: Introductionmentioning

confidence: 99%

To the question of the digital platform “bioinformatics” creating and its system-forming solutions

Kratov

Zybarev

2020

Journal of Integrative Bioinformatics

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The article reports the main provisions of the concept and solutions for creating the digital platform in the field of bioinformatics and the formation of the thematically oriented and industrial digital ecosystems on its basis. The composition and structure of the digital platform are discussed: information repositories, data and knowledge bases, thematically oriented software repository, task-oriented services for various target groups of users. Within the framework of the platform, it is also planned to organize a system of high-quality access to specialized data centres and high-performance computing infrastructure. Particular attention is devoted to one of the components of such platform - the project office for bioresource collections management. The project office has registered such types of collections as animal collections: wild and laboratory animals, live breeding, museum zoological animal collections, farm animals; plant collections: herbarium funds of plants biological diversity, living collections of natural flora, agricultural plants. Collection types such as collections of human biomaterials, cell culture collections, microorganism collections are important for medical research.

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A web application for automatic prediction of gene translation elongation efficiency

Cited by 6 publications

References 16 publications

Bioinformatic Assessment of Factors Affecting the Correlation between Protein Abundance and Elongation Efficiency in Prokaryotes

Bioinformatic Assessment of Factors Affecting the Correlation between Protein Abundance and Elongation Efficiency in Prokaryotes

Bioinformatic Analysis Reveals the Role of Translation Elongation Efficiency Optimisation in the Evolution of Ralstonia Genus

To the question of the digital platform “bioinformatics” creating and its system-forming solutions

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