Proceedings of the National Academy of Sciences · 2024 · 18 citations · 54 references
Life SciencesBiochemistryMolecular BiologyGene ExpressionProtein TranslationTranscriptionProtein SynthesisRibosome BiogenesisRna Polymerase RegulationTranslation In EukaryotesTranslation In ProkaryotesTranslation RegulationCellular GrowthCellular Growth MechanismsCellular Resource AllocationGrowth Rate TraitsMrna Synthesis DynamicsRibosome Biogenesis In YeastTranslation Kinetics
Experimental observations tracing back to the 1960s imply that ribosome quantities play a prominent role in determining a cell’s growth. Nevertheless, in biologically relevant scenarios, growth can also be influenced by the levels of mRNA and RNA polymerase. Here, we construct a quantitative model of biosynthesis providing testable scenarios for these situations. The model explores a theoretically motivated regime where RNA polymerases compete for genes and ribosomes for transcripts and gives general expressions relating growth rate, mRNA concentrations, ribosome, and RNA polymerase levels. On general grounds, the model predicts how the fraction of ribosomes in the proteome depends on total mRNA concentration and inspects an underexplored regime in which the trade-off between transcript levels and ribosome abundances sets the cellular growth rate. In particular, we show that the model predicts and clarifies three important experimental observations, in budding yeast and Escherichia coli bacteria: i) that the growth-rate cost of unneeded protein expression can be affected by mRNA levels, ii) that resource optimization leads to decreasing trends in mRNA levels at slow growth, and iii) that ribosome allocation may increase, stay constant, or decrease, in response to transcription-inhibiting antibiotics. Since the data indicate that a regime of joint limitation may apply in physiological conditions and not only to perturbations, we speculate that this regime is likely self-imposed.
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Interdependence of Cell Growth and Gene Expression: Origins and Consequences
Matthew P. Scott, Carl W. Gunderson, Eduard M. Mateescu et al. · Science · 2010 · 1.6K citations
Optimality and evolutionary tuning of the expression level of a protein
Growth Rate-Dependent Global Effects on Gene Expression in Bacteria
Stefan Klumpp, Zhongge Zhang, Terence Hwa · Cell · 2009 · 755 citations · Full text