|Title||Codon use and mRNA structure analyses across kingdoms indicates selection on both mRNA stability and translatability|
|Author(s)||Westerhof, L.B.; Sterken, M.G.; Wilbers, R.H.P.; Luijben, Lucia; Raaij, D.R. van; Snoek, L.B.; Bakker, J.; Schots, A.|
|Event||The second conference of the International Society for Plant Molecular Farming, Ghent, 2016-05-25/2016-05-27|
Laboratory of Nematology
|Publication type||Abstract in scientific journal or proceedings|
|Abstract||Codon use and mRNA structure analyses across kingdoms indicates selection on both mRNA stability and translatability
Lotte B. Westerhof, Mark G. Sterken, Ruud H.P. Wilbers, Lucia Luijben, Debbie R. van Raaij, L. Basten Snoek, Jaap Bakker and Arjen Schots
To boost heterologous protein production the codon use of a gene of interest is often adapted to reflect the expression host’s codon use in highly expressed genes (optimal codons). However, the results obtained with this strategy are variable. A comparison between the overall codon use and the codon use in highly expressed genes of several plant species revealed that optimal codons are not always the codons of which the use is most increased with expression. Although the codon composition of highly expressed genes differs between monocots and dicots, often the same codons are linked strongest to expression (here after named expression codons). We used these conserved expression codons to optimise the codon composition of three genes, which enhanced protein yield significantly upon stable and transient expression in plants. Upon stable transformation both transcript levels and protein yield per transcript increased. Next, we analysed whether this expression-linked codon bias found in plants also extends to other kingdoms of life. Thereto, expression-linked codon use was investigated in Escherichia coli (Bacteria), Saccharomyces cerevisiae (Fungi), Caenorhabditis elegans (Animalia) and Mus musculus (Animalia) using more than 250 microarrays per species. We found that a common codon use bias exits over all species. In addition, computational analyses of various mRNA characteristics revealed a similar selection pressure across kingdoms that increases both stability and translatability. Combining gene expression data with available protein abundance data showed that an increased number of stem-loop transitions together with a reduction of stem size increases translation efficiency. An algorithm was developed that combines the use of optimal and expression codons to create an ideal mRNA structure for any given gene. This algorithm was again tested in plants and lead to a significant increase in protein production. The spin off company TripleT Biosciences combines this algorithm with all available knowledge on codon use and offers a codon optimization tool.