Quantitative Control for Stoichiometric Protein Synthesis

Abstract

Bacterial protein synthesis rates have evolved to maintain preferred stoichiometries at striking precision, from the components of protein complexes to constituents of entire pathways. Setting relative protein production rates to be well within a factor of two requires concerted tuning of transcription, RNA turnover, and translation, allowing many potential regulatory strategies to achieve the preferred output. The last decade has seen a greatly expanded capacity for precise interrogation of each step of the central dogma genome-wide. Here, we summarize how these technologies have shaped the current understanding of diverse bacterial regulatory architectures underpinning stoichiometric protein synthesis. We focus on the emerging expanded view of bacterial operons, which encode diverse primary and secondary mRNA structures for tuning protein stoichiometry. Emphasis is placed on how quantitative tuning is achieved. We discuss the challenges and open questions in the application of quantitative, genome-wide methodologies to the problem of precise protein production.

Keywords: differential RNA stability; differential translation; expression stoichiometry; operon mRNA isoform; proportional synthesis.

Figure 1

Schematic representation of the atp operon from Bacillus subtilis. Control in the expression of genes occurs at the steps of differential transcription due to leaky intrinsic terminators, followed by mRNA processing that leads to differential mRNA stability (a minor processing site in atpB is omitted for clarity; see Figure 3). The genes transcribed in the diverse polycistronic mRNA isoforms are then translated at different rates. All control steps contribute to ATP synthase subunits being produced in proportion to their stoichiometry in the complex (ribosome profiling data from Reference 96).

Figure 2

End-enriched RNA-seq (Rend-seq) data (from 96) showing coverage trace for the asd operon in Bacillus subtilis, which includes four cotranscribed genes. Peaks in 5′-mapped (orange) 3′-mapped (blue) reads mark mRNA boundaries. Four promoters can be seen, as well as three intrinsic terminators. Transcript ends were confirmed not to arise from mRNA processing by orthogonal experiments (not shown). The internal promoters and terminators lead to a complete set of nine possible mRNA isoforms, highlighting the possible complexity of transcription architecture. The read coverage between peaks can be used to infer the abundance of each isoform.

Figure 3

End-enriched RNA-seq (Rend-seq) data (from Reference 96) showing coverage trace for the atp operon in Bacillus subtilis, truncated to include only the first five genes. Peaks in 5′-mapped (orange) and 3′-mapped (blue) reads mark mRNA boundaries. Two RNase Y cleavage sites (scissors), one promoter, and one intrinsic terminator are shown. mRNA processing sites validated through orthogonal experiments (not shown). Darker gray indicates higher abundance of transcript isoforms (as in Figure 2), and red, dashed isoforms are rapidly degraded and therefore undetectable.