ArticleProceedings of the National Academy of Sciences of the United States of America2021
A unifying autocatalytic network-based framework for bacterial growth laws.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 44 citations in OpenAlex.
- Coarse-grained resource allocation modeling for decoding and rewiring microbial metabolism.Trends in microbiology · 2026Review
- Evolutionary constraints on RNA polymerase gene positioning in the genome of fast-growing bacteria.Nucleic acids research · 2026Article
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- How DoesACS synthetic biology · 2024Article
- How total mRNA influences cell growth.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- A coarse-grained bacterial cell model for resource-aware analysis and design of synthetic gene circuits.Nature communications · 2024Article
- Optimal control of ribosome population for gene expression under periodic nutrient intake.Journal of the Royal Society, Interface · 2024Article
- The modular biochemical reaction network structure of cellular translation.NPJ systems biology and applications · 2023Article
- Assessment of Stoichiometric Autocatalysis across Element Groups.Journal of the American Chemical Society · 2023Article
- Self-reproduction and doubling time limits of different cellular subsystems.NPJ systems biology and applications · 2023Article
- Speed variations of bacterial replisomes.eLife · 2022Article
- The correlation between cell and nucleus size is explained by an eukaryotic cell growth model.PLoS computational biology · 2022Article
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recently discovered simple quantitative relations, known as bacterial growth laws, hint at the existence of simple underlying principles at the heart of bacterial growth. In this work, we provide a unifying picture of how these known relations, as well as relations that we derive, stem from a universal autocatalytic network common to all bacteria, facilitating balanced exponential growth of individual cells. We show that the core of the cellular autocatalytic network is the transcription-translation machinery-in itself an autocatalytic network comprising several coupled autocatalytic cycles, including the ribosome, RNA polymerase, and transfer RNA (tRNA) charging cycles. We derive two types of growth laws per autocatalytic cycle, one relating growth rate to the relative fraction of the catalyst and its catalysis rate and the other relating growth rate to all the time scales in the cycle. The structure of the autocatalytic network generates numerous regimes in state space, determined by the limiting components, while the number of growth laws can be much smaller. We also derive a growth law that accounts for the RNA polymerase autocatalytic cycle, which we use to explain how growth rate depends on the inducible expression of the rpoB and rpoC genes, which code for the RpoB and C protein subunits of RNA polymerase, and how the concentration of rifampicin, which targets RNA polymerase, affects growth rate without changing the RNA-to-protein ratio. We derive growth laws for tRNA synthesis and charging and predict how growth rate depends on temperature, perturbation to ribosome assembly, and membrane synthesis.
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