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The assessment of transcriptome-wide ribosome binding to mRNAs is useful for studying the dynamic regulation of protein synthesis. Two methods frequently applied in eukaryotic cells that operate at different levels of resolution are polysome profiling, which reveals the distribution of ribosome loads across the transcriptome, and ribosome footprinting (also termed ribosome profiling or Ribo-Seq), which when combined with appropriate data on mRNA expression can reveal ribosome densities on individual transcripts. In this study we develop methods for relating the information content of these two methods to one another, by reconstructing theoretical polysome profiles from ribosome footprinting data. Our results validate both approaches as experimental tools. Although we show that both methods can yield highly consistent data, some published ribosome footprinting datasets give rise to reconstructed polysome profiles with non-physiological features. We trace these aberrant features to inconsistencies in RNA and Ribo-Seq data when compared to datasets yielding physiological polysome profiles, thereby demonstrating that modelled polysomes are useful for assessing global dataset properties such as its quality in a simple, visual approach. Aside from using polysome profile reconstructions on published datasets, we propose that this also provides a useful tool for validating new ribosome footprinting datasets in early stages of analyses., (© The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research.)

mRNA translation is a key process determining growth, proliferation and duration of a Chinese hamster ovary (CHO) cell culture and influences recombinant protein synthesis rate. During bioprocessing, CHO cells can experience stresses leading to reprogramming of translation and decreased global protein synthesis. Here we apply polysome profiling to determine reprogramming and translational capabilities in host and recombinant monoclonal antibody-producing (mAb) CHO cell lines during batch culture. Recombinant cell lines with the fastest cell specific growth rates were those with the highest global translational efficiency. However, total ribosomal capacity, determined from polysome profiles, did not relate to the fastest growing or highest producing mAb cell line, suggesting it is the ability to utilise available machinery that determines protein synthetic capacity. Cell lines with higher cell specific productivities tended to have elevated recombinant heavy chain transcript copy numbers, localised to the translationally active heavy polysomes. The highest titre cell line was that which sustained recombinant protein synthesis and maintained high recombinant transcript copy numbers in polysomes. Investigation of specific endogenous transcripts revealed a number that maintained or reprogrammed into heavy polysomes, identifying targets for potential cell engineering or those with 5' untranslated regions that might be utilised to enhance recombinant transcript translation., (© 2017 The Authors. Biotechnology Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Translational control is central to the gene expression pathway and was the focus of the 2013 annual Translation UK meeting held at the University of Kent. The meeting brought together scientists at all career stages to present and discuss research in the mRNA translation field, with an emphasis on the presentations on the research of early career scientists. The diverse nature of this field was represented by the broad range of papers presented at the meeting. The complexity of mRNA translation and its control is emphasized by the interdisciplinary research approaches required to address this area with speakers highlighting emerging systems biology techniques and their application to understanding mRNA translation and the network of pathways controlling it.