Predictive design of mRNA translation initiation region to control prokaryotic translation efficiency.

Precise prediction of prokaryotic translation efficiency can provide valuable information for optimizing bacterial host for the production of biochemical compounds or recombinant proteins. However, dynamic changes in mRNA folding throughout translation make it difficult to assess translation efficiency. Here, we systematically determined the universal folding regions that significantly affect the efficiency of translation in Escherichia coli. By assessing the specific regions for mRNA folding, we could construct a predictive design method, UTR Designer, and demonstrate that proper codon optimization around the 5'-proximal coding sequence is necessary to achieve a broad range of expression levels. Finally, we applied our method to control the threshold value of input signals switching on a genetic circuit. This should increase our understanding of the processes underlying gene expression and provide an efficient design principle for optimizing various biological systems, thereby facilitating future efforts in metabolic engineering and synthetic biology.

[1]  J. Plotkin,et al.  Synonymous but not the same: the causes and consequences of codon bias , 2011, Nature Reviews Genetics.

[2]  Joachim Frank,et al.  The Cryo-EM Structure of a Translation Initiation Complex from Escherichia coli , 2005, Cell.

[3]  J. Keasling Manufacturing Molecules Through Metabolic Engineering , 2010, Science.

[4]  Sang Woo Seo,et al.  Quantitative correlation between mRNA secondary structure around the region downstream of the initiation codon and translational efficiency in Escherichia coli. , 2009, Biotechnology and bioengineering.

[5]  V. Ramakrishnan,et al.  Ribosome Structure and the Mechanism of Translation , 2002, Cell.

[6]  I. Boni,et al.  Protein S1 counteracts the inhibitory effect of the extended Shine-Dalgarno sequence on translation. , 2002, RNA.

[7]  Christopher A. Voigt,et al.  Automated Design of Synthetic Ribosome Binding Sites to Precisely Control Protein Expression , 2009, Nature Biotechnology.

[8]  P. Sharp,et al.  The codon Adaptation Index--a measure of directional synonymous codon usage bias, and its potential applications. , 1987, Nucleic acids research.

[9]  Pamela A Silver,et al.  Parts plus pipes: synthetic biology approaches to metabolic engineering. , 2012, Metabolic engineering.

[10]  Keith E. J. Tyo,et al.  Isoprenoid Pathway Optimization for Taxol Precursor Overproduction in Escherichia coli , 2010, Science.

[11]  Deepak Chandran,et al.  Computational tools for metabolic engineering. , 2012, Metabolic engineering.

[12]  L. Wernisch,et al.  Solving the riddle of codon usage preferences: a test for translational selection. , 2004, Nucleic acids research.

[13]  Thomas H Segall-Shapiro,et al.  Creation of a Bacterial Cell Controlled by a Chemically Synthesized Genome , 2010, Science.

[14]  A. Serganov,et al.  Structured mRNAs Regulate Translation Initiation by Binding to the Platform of the Ribosome , 2007, Cell.

[15]  S. Joseph,et al.  Unfolding of mRNA secondary structure by the bacterial translation initiation complex. , 2006, Molecular cell.

[16]  Brian F. Pfleger,et al.  Combinatorial engineering of intergenic regions in operons tunes expression of multiple genes , 2006, Nature Biotechnology.

[17]  Gregory Stephanopoulos,et al.  Reevaluating synthesis by biology. , 2010, Current opinion in microbiology.

[18]  Farren J. Isaacs,et al.  Precise Manipulation of Chromosomes in Vivo Enables Genome-Wide Codon Replacement , 2011, Science.

[19]  E. Marcotte,et al.  Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation , 2007, Nature Biotechnology.

[20]  G. Stephanopoulos,et al.  Tuning genetic control through promoter engineering. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[21]  David Tollervey,et al.  Coding-Sequence Determinants of Gene Expression in Escherichia coli , 2009, Science.

[22]  Jan van Duin,et al.  Translational standby sites: how ribosomes may deal with the rapid folding kinetics of mRNA. , 2003 .

[23]  P. R. Jensen,et al.  Artificial promoters for metabolic optimization. , 1998, Biotechnology and bioengineering.

[24]  Sriram Kosuri,et al.  Scalable gene synthesis by selective amplification of DNA pools from high-fidelity microchips , 2010, Nature Biotechnology.

[25]  Erik Winfree,et al.  Thermodynamic Analysis of Interacting Nucleic Acid Strands , 2007, SIAM Rev..

[26]  Sang Woo Seo,et al.  Synthetic regulatory tools for microbial engineering , 2012, Biotechnology and Bioprocess Engineering.

[27]  Sang Woo Seo,et al.  Design of 5'-untranslated region variants for tunable expression in Escherichia coli. , 2007, Biochemical and biophysical research communications.

[28]  D. Petranovic,et al.  Tunable promoters in systems biology. , 2005, Current opinion in biotechnology.

[29]  J. Keasling Synthetic biology and the development of tools for metabolic engineering. , 2012, Metabolic engineering.

[30]  G. Georgiou,et al.  Comprehensive engineering of Escherichia coli for enhanced expression of IgG antibodies. , 2011, Metabolic engineering.