Faculty Opinions recommendation of A unifying autocatalytic network-based framework for bacterial growth laws.

2021 ◽  
Author(s):  
Tsvi Tlusty
Keyword(s):  
Bacterial Growth ◽  
Growth Laws ◽  
Bacterial Growth Laws

scholarly journals A unifying autocatalytic network-based framework for bacterial growth laws

2021 ◽  
Vol 118 (33) ◽  
pp. e2107829118
Author(s):  
Anjan Roy ◽  
Dotan Goberman ◽  
Rami Pugatch
Keyword(s):  
Growth Rate ◽  
Rna Polymerase ◽  
Bacterial Growth ◽  
Temperature Perturbation ◽  
Protein Ratio ◽  
C Protein ◽  
Protein Subunits ◽  
The Core ◽  
Growth Laws ◽  
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 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.

On the Types of Bacterial Growth Laws

2015 ◽  
Vol 10 (1) ◽  
pp. 154-163
Author(s):  
В.А. Лихошвай ◽  
V.A. Likhoshvai
Keyword(s):  
Bacterial Growth ◽  
Universal Principle ◽  
Linear Type ◽  
Size Growth ◽  
Unlimited Growth ◽  
Growth Laws ◽  
Bacterial Cell Cycle ◽  
Living Organisms ◽  
Modern Form ◽  
Bacterial Growth Laws

Volume, mass and envelope surface area of a bacterium are significant parameters of cell development during one bacterial cell cycle. In our previous studies it was shown that during one division cycle cells can encounter the problem of unlimited size growth. Two fundamental types of bacterial growth laws, which were called “exponential” and “linear”, have been identified. Under certain conditions exponentially growing cells encounter the problem of unlimited growth, whereas lineally growing cells don’t. In this study the laws of bacterial size growth were shown to belong exclusively to the linear type. It was demonstrated that this phenomenon is a consequence of the universal principle of storage and transmission of genetic information essential to all living organisms. The bacterial growth laws of exponential type could exist only at the very early stages of cell evolution, when the genetic machinery had not evolved yet into its modern form.

scholarly journals Bacterial growth laws and their applications

2011 ◽  
Vol 22 (4) ◽  
pp. 559-565 ◽  
Author(s):  
Matthew Scott ◽  
Terence Hwa
Keyword(s):  
Bacterial Growth ◽  
Growth Laws ◽  
Bacterial Growth Laws

scholarly journals Cellular perception of growth rate and the mechanistic origin of bacterial growth laws

2021 ◽  
Author(s):  
Chenhao Wu ◽  
Rohan Balakrishnan ◽  
Matteo Mori ◽  
Gabriel Manzanarez ◽  
Zhongge Zhang ◽  
...  
Keyword(s):  
Growth Rate ◽  
Bacterial Growth ◽  
Ribosome Biogenesis ◽  
Broad Class ◽  
E Coli ◽  
Regulatory Circuit ◽  
Cellular Behaviors ◽  
Growth Laws ◽  
Growth Transitions ◽  
Bacterial Growth Laws

Cells organize many of their activities in accordance to how fast they grow. Yet it is not clear how they perceive their rate of growth, which involves thousands of reactions. Through quantitative studies of E. coli under exponential growth and during growth transitions, here we show that the alarmone ppGpp senses the rate of translational elongation by ribosomes, and together with its roles in controlling ribosome biogenesis and activity, closes a key regulatory circuit that enables the cell to perceive the rate of its own growth for a broad class of growth-limiting conditions. This perception provides the molecular basis for the emergence of simple relations among the cellular ribosome content, translational elongation rate, and the growth rate, as manifested by bacterial growth laws. The findings here provide a rare view of how cells manage to collapse the complex, high-dimensional dynamics of the underlying molecular processes to perceive and regulate emergent cellular behaviors, an example of dimension reduction performed by the cells themselves.

scholarly journals Bacterial growth laws reflect the evolutionary importance of energy efficiency

2014 ◽  
Vol 112 (2) ◽  
pp. 406-411 ◽  
Author(s):  
Arijit Maitra ◽  
Ken A. Dill
Keyword(s):  
Energy Efficiency ◽  
Bacterial Growth ◽  
Growth Conditions ◽  
High Energy ◽  
Fast Growth ◽  
Growth Speed ◽  
Energy Costs ◽  
Extensive Literature ◽  
E Coli ◽  
Growth Laws

We are interested in the balance of energy and protein synthesis in bacterial growth. How has evolution optimized this balance? We describe an analytical model that leverages extensive literature data on growth laws to infer the underlying fitness landscape and to draw inferences about what evolution has optimized inEscherichia coli. IsE. colioptimized for growth speed, energy efficiency, or some other property? Experimental data show that at its replication speed limit,E. coliproduces about four mass equivalents of nonribosomal proteins for every mass equivalent of ribosomes. This ratio can be explained if the cell’s fitness function is the the energy efficiency of cells under fast growth conditions, indicating a tradeoff between the high energy costs of ribosomes under fast growth and the high energy costs of turning over nonribosomal proteins under slow growth. This model gives insight into some of the complex nonlinear relationships between energy utilization and ribosomal and nonribosomal production as a function of cell growth conditions.

scholarly journals A bacterial growth law out of steady-state

2018 ◽  
Author(s):  
Yael Korem Kohanim ◽  
Dikla Levi ◽  
Ghil Jona ◽  
Anat Bren ◽  
Uri Alon
Keyword(s):  
Growth Rate ◽  
Steady State ◽  
Bacterial Growth ◽  
Experimental Tests ◽  
Spare Capacity ◽  
Allocation Model ◽  
Steady State Growth ◽  
Fluctuating Environments ◽  
Growth Laws ◽  
State Growth

SummaryBacterial growth depends on numerous reactions, and yet follows surprisingly simple laws that inspired biologists for decades. Growth laws until now primarily dealt with steady-state exponential growth in constant conditions. However, bacteria in nature often face fluctuating environments, with nutritional upshifts and downshifts. We therefore ask whether there are growth laws that apply to changing environments. We derive a law for strong upshifts using an optimal resource-allocation model that was previously calibrated at steady-state growth: the post-shift growth rate equals the geometrical mean of the pre-shift growth rate and the growth rate on saturating carbon. We test this using chemostat and robotic batch culture experiments, as well as previous data from several species, and find good agreement with the model predictions. The increase in growth rate after an upshift indicates that ribosomes have spare capacity. We demonstrate theoretically that spare ribosomal capacity has the cost of slow steady-state growth, but is beneficial in fluctuating environments because it prevents large overshoots in intracellular metabolites after an upshift and allows rapid response to change. We also provide predictions for downshifts for future experimental tests. Spare capacity appears in diverse biological systems, and the present study quantifies the optimal degree of spare capacity, which rises the slower the growth rate, and suggests that it can be precisely regulated.

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