Abstract
BackgroundCell-to-cell variation in gene expression strongly affects population behavior and is key to multiple biological processes. While codon usage is known to affect ensemble gene expression, how codon usage influences variation in gene expression between single cells is not well understood.ResultsHere, we used a Sort-seq based massively parallel strategy to quantify gene expression variation from a green fluorescent protein (GFP) library containing synonymous codons in Escherichia coli. We found that sequences containing codons with higher tRNA Adaptation Index (TAI) scores, and higher codon adaptation index (CAI) scores, have higher GFP variance. This trend is not observed for codons with high Normalized Translation Efficiency Index (nTE) scores nor from the free energy of folding of the mRNA secondary structure. GFP noise, or squared coefficient of variance (CV2), scales with mean protein abundance for low-abundant proteins but does not change at high mean protein abundance.ConclusionsOur results suggest that the main source of noise for high-abundance proteins is likely not originating at translation elongation. Additionally, the drastic change in mean protein abundance with small changes in protein noise seen from our library implies that codon optimization can be performed without concerning gene expression noise for biotechnology applications.
Highlights
Cell-to-cell variation in gene expression strongly affects population behavior and is key to multiple biological processes
Mean translational rate can be affected by multiple genetic elements, including the strength of ribosome binding sites, mRNA secondary structures, and codon usage, as well as growth-related factors such as charged tRNA concentrations and the copy number of free ribosomes [18]
Design of a Synthetic Gene Library with synonymous codons To systematically study the influence of codon usage in cell-to-cell protein variability, a green fluorescent protein (GFP) library was designed with the first 8 codons after the start codon (ATG) randomly mutated to synonymous codons, resulting in a library of 4096 GFP coding sequences
Summary
Cell-to-cell variation in gene expression strongly affects population behavior and is key to multiple biological processes. Mean translational rate can be affected by multiple genetic elements, including the strength of ribosome binding sites, mRNA secondary structures, and codon usage, as well as growth-related factors such as charged tRNA concentrations and the copy number of free ribosomes [18]. These genetic elements and growth-related factors may affect the variability of translational rate between single cells, which further influence variability of protein abundance. Despite significant knowledge on the effects of codon usage on mean gene expression, how and to what extent codon usage affects cell-to-cell variability in protein abundance is poorly understood. With codon optimization used as a popular method for enhancing and controlling expression [32], determining any additional consequences, such as on the variability, is important
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