遺伝子制御の教科書を書き直す:大事なのは全体像(Rewriting the Textbook on Gene Regulation: It’s the Big Picture That Counts)


カリフォルニア大学サンディエゴ校の研究者が、分子生物学のセントラルドグマを再考する UC San Diego researchers rethink the central dogma of molecular biology

2022-12-22 カリフォルニア大学サンディエゴ校(UCSD)



遺伝子制御の原理は、バクテリアのDNAとRNA、タンパク質を定量的に結びつけている Principles of gene regulation quantitatively connect DNA to RNA and proteins in bacteria

Rohan Balakrishnan,Matteo Mori,Igor Segota,Zhongge Zhang,Ruedi Aebersold,Christina Ludwig,Terence Hwa
Science  Published:9 Dec 2022
DOI: 10.1126/science.abk2066

Doing the math on the central dogma

Gene expression can in theory be modulated at the level of transcription or translation, but both of these processes have constraints that complicate prediction of their outputs. To obtain a better quantitative understanding of the control of gene expression in bacteria, Balakrishnan et al. measured promotor on-rates, messenger RNA abundance, and protein abundance for more than 1500 genes in the bacterium Escherichia coli under many different growth conditions. Protein abundance largely reflects gene promoter on-rates and transcription, but has to comply with general constraints that keep the protein concentration constant and limit the number of ribosomes—and thus translational capacity. The authors propose a balancing of transcription with translation through Rsd, a factor that controls the availability of RNA polymerase. Their results may be useful in the design of synthetic circuits in bacteria and the prediction of their behavior in various growth conditions. —LBR

Structured Abstract

The intracellular concentration of a protein depends on the rates of several processes, including transcription, translation, and the degradation and/or dilution of messenger RNAs (mRNAs) and proteins. These rates can be vastly different for different genes and across different growth conditions because of gene-specific regulation. At the systems level, protein concentrations are further affected by the availability of shared gene expression machineries—e.g., RNA polymerases and ribosomes—and are constrained by the approximately invariant cellular mass density. Even in one of the best-characterized model organisms, Escherichia coli, it is unclear how the gene-specific and systems-level effects work together toward setting the cellular proteome. This knowledge gap has not only hindered our efforts in building a predictive framework of gene expression but has also limited our abilities in guiding the rational design of gene circuits.

We undertook a quantitative, genome-scale study, combining experimental and theoretical approaches, to tease apart the contribution of the specific and global effects on cellular protein concentrations in exponentially growing E. coli cells across a variety of growth conditions. We complemented genome-scale proteomic and transcriptomic data with biochemical measurements of total absolute mRNA abundances and synthesis rates. We compared these measurements to gene dosage and the concentrations of ribosomes and RNA polymerases to quantitatively characterize the activity of the gene expression machinery across conditions. This comprehensive dataset allowed us to analyze, in quantitative detail, the interplay between the activity of gene expression machinery, the activity of individual promoters, and the resulting protein concentrations.

We compiled a comprehensive atlas of the determinants of gene expression across conditions—from the concentrations of genes, mRNAs, and proteins to the rates of transcriptional and translational initiation and mRNA degradation for thousands of genes. We were able to determine the on rate of each promoter, a quantity capturing the overall effect of transcriptional regulation that has been elusive through most existing gene expression studies. Unexpectedly, we found that for most genes, the cytosolic protein concentrations were primarily determined by the innate magnitude of their promoter on rates, which spanned more than three orders of magnitude. Changes in protein concentrations resulting from changes in growth conditions were typically much smaller—well within one order of magnitude—and were mostly exerted through changes in transcription initiation.

E. coli’s strategy to implement gene regulation can be summarized by two design principles. First, protein concentrations are predominantly set transcriptionally, with relatively invariant posttranscriptional characteristics (translation efficiencies and degradation rates) for most mRNAs and growth conditions. Second, the overall fluxes of transcription and translation are tightly coordinated: The average density of five ribosomes per kilobase is nearly invariant across mRNA species and across growth conditions, even though the mRNA and ribosome abundances can each vary substantially. We find this coordination to be implemented through the anti-sigma factor Rsd, which modulates the availability of RNA polymerases for transcription across different growth conditions. These two principles lead to a quantitative formulation of the central dogma of bacterial gene expression, connecting mRNA and protein concentrations to the regulatory activities of the corresponding promoters.

These quantitative relationships reveal the unexpectedly simple strategies used by E. coli to attain desired protein concentrations despite the complexity of global physiological constraints: Individual protein concentrations are primarily set by gene-specific transcriptional regulation, with global transcriptional regulation set to cancel the strong growth rate dependence of protein synthesis. These relations provide the basis for understanding the behavior of more complex genetic circuits in different conditions and for the inverse problem of deducing regulatory activities given the observed mRNA and protein levels.


Protein concentrations are set by a complex interplay between gene-specific regulatory processes and systemic factors, including cell volume and shared gene expression machineries. Elucidating this interplay is crucial for discerning and designing gene regulatory systems. We quantitatively characterized gene-specific and systemic factors that affect transcription and translation genome-wide for Escherichia coli across many conditions. The results revealed two design principles that make regulation of gene expression insulated from concentrations of shared machineries: RNA polymerase activity is fine-tuned to match translational output, and translational characteristics are similar across most messenger RNAs (mRNAs). Consequently, in bacteria, protein concentration is set primarily at the promoter level. A simple mathematical formula relates promoter activities and protein concentrations across growth conditions, enabling quantitative inference of gene regulation from omics data.