The non-neutral, multi-level, phenotypic impact of synonymous mutations revealed through heterologous gene expression in human cells.
Differences in codon frequency between genomes, genes, or positions along a gene, modulate transcription and translation efficiency, leading to phenotypic and functional differences. Here, we present a multiscale analysis of the effects of synonymous codon recoding during heterologous gene expression in human cells, quantifying the phenotypic consequences of codon usage bias at different molecular and cellular levels, with an emphasis on translation elongation. Six synonymous versions of an antibiotic resistance gene were generated, fused to a fluorescent reporter, and independently expressed in HEK293 cells. Multiscale phenotype was analysed by means of: quantitative transcriptome and proteome assessment, as proxies for gene expression; cellular fluorescence, as a proxy for single-cell level expression; and real-time cell proliferation in absence or presence of antibiotic, as a proxy for the cell fitness. We show that differences in codon usage bias strongly impact the molecular and cellular phenotype: (i) they result in large differences in mRNA levels and in protein levels, leading to differences of over fifteen times in translation efficiency; (ii) they introduce unpredicted splicing events; (iii) they lead to reproducible phenotypic heterogeneity; and (iv) they lead to a trade-off between the benefit of antibiotic resistance and the burden of heterologous expression. In human cells in culture, codon usage bias modulates gene expression by modifying mRNA availability and suitability for translation, leading to differences in protein levels and eventually eliciting functional phenotypic changes. IMPORTANCESynonymous codons encode for the same amino acid, but they are not neutral regarding gene expression or protein synthesis. Bias between synonymous codons have evolved naturally and are also applied in biotechnology protein production. We have studied the multilevel impact of codon usage on a human cell system. We show that differences in codon usage lead to transcriptomic, proteomic and functional changes, modulating gene expression and cellular phenotype.