Summary Gene expression noise (heterogeneity) leads to phenotypic diversity among isogenic individual cells. Our current understanding of gene expression noise is mostly limited to transcription, as separating translational noise from transcriptional noise has been challenging. It also remains unclear how translational heterogeneity originates. Using a transcription-normalized reporter system, we discovered that stop codon readthrough is heterogeneous among single cells, and individual cells with higher UGA readthrough grow faster from stationary phase. Our work also revealed that individual cells with lower protein synthesis levels exhibited higher UGA readthrough, which was confirmed with ribosome-targeting antibiotics (e.g., chloramphenicol). Further experiments and mathematical modeling suggest that varied competition between ternary complexes and release factors perturbs the UGA readthrough level. Our results indicate that fluctuations in the concentrations of translational components lead to UGA readthrough heterogeneity among single cells, which enhances phenotypic diversity of the genetically-identical population and facilitates its adaptation to changing environments.

Gene expression has been considered a highly accurate process, and deviation from such fidelity has been shown previously to be detrimental for the cell. More recently, increasing evidence has supported the notion that the accuracy of gene expression is indeed flexibly variable. The levels of errors during gene expression differ from condition to condition and even from cell to cell within genetically identical populations grown under the same conditions. The different levels of errors resulting from inaccurate gene expression are now known to play key roles in regulating microbial stress responses and host interactions. This minireview summarizes the recent development in understanding the level, regulation, and physiological impact of errors during gene expression.