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A unifying autocatalytic network-based framework for bacterial growth laws

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 univer...

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Autores principales: Roy, Anjan, Goberman, Dotan, Pugatch, Rami
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379944/
https://www.ncbi.nlm.nih.gov/pubmed/34389683
http://dx.doi.org/10.1073/pnas.2107829118
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author Roy, Anjan
Goberman, Dotan
Pugatch, Rami
author_facet Roy, Anjan
Goberman, Dotan
Pugatch, Rami
author_sort Roy, Anjan
collection PubMed
description 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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spelling pubmed-83799442021-08-30 A unifying autocatalytic network-based framework for bacterial growth laws Roy, Anjan Goberman, Dotan Pugatch, Rami Proc Natl Acad Sci U S A Biological Sciences 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. National Academy of Sciences 2021-08-17 2021-08-13 /pmc/articles/PMC8379944/ /pubmed/34389683 http://dx.doi.org/10.1073/pnas.2107829118 Text en Copyright © 2021 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Roy, Anjan
Goberman, Dotan
Pugatch, Rami
A unifying autocatalytic network-based framework for bacterial growth laws
title A unifying autocatalytic network-based framework for bacterial growth laws
title_full A unifying autocatalytic network-based framework for bacterial growth laws
title_fullStr A unifying autocatalytic network-based framework for bacterial growth laws
title_full_unstemmed A unifying autocatalytic network-based framework for bacterial growth laws
title_short A unifying autocatalytic network-based framework for bacterial growth laws
title_sort unifying autocatalytic network-based framework for bacterial growth laws
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8379944/
https://www.ncbi.nlm.nih.gov/pubmed/34389683
http://dx.doi.org/10.1073/pnas.2107829118
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