Protein degradation sets the fraction of active ribosomes at vanishing growth

Calabrese, Ludovico; Grilli, Jacopo; Osella, Matteo; Kempes, Christopher P.; Lagomarsino, Marco Cosentino; Ciandrini, Luca

doi:10.1371/journal.pcbi.1010059

Cited by 23 publications

(39 citation statements)

References 58 publications

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“…As such, we were interested if our model for dynamic proteome allocation would successfully predict cell size and division control upon exit from stationary phase. Under such conditions, the effects of protein turnover on cell physiology become crucial [41]. From Eq.…”

Section: Resultsmentioning

confidence: 99%

Dynamic trade-offs between biomass accumulation and division determine bacterial cell size and proteome in fluctuating nutrient environments

Banerjee

Kratz

2022

Preprint

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Bacteria dynamically regulate cell size and growth rate to thrive in changing environments. While much work has been done to characterize bacterial growth physiology and cell size control during steady-state exponential growth, a quantitative understanding of how bacteria dynamically regulate cell size and growth in time-varying nutrient environments is lacking. Here we develop a dynamic coarse-grained proteome sector model which connects growth rate and division control to proteome allocation in time-varying environments in both exponential and stationary phase. In such environments, growth rate and size control is governed by trade-offs between prioritization of biomass accumulation or division, and results in the uncoupling of single-cell growth rate from population growth rate out of steady-state. Specifically, our model predicts that cells transiently prioritize ribosome production, and thus biomass accumulation, over production of division machinery during nutrient upshift, explaining experimentally observed size control behaviors. Strikingly, our model predicts the opposite behavior during downshift, namely that bacteria temporarily prioritize division over growth, despite needing to upregulate costly division machinery and increasing population size when nutrients are scarce. Importantly, when bacteria are subjected to pulsatile nutrient concentration, we find that cells exhibit a transient memory of the previous metabolic state due to the slow dynamics of proteome reallocation. This phenotypic memory allows for faster adaptation back to previously-seen environments when nutrient fluctuations are short-lived.

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Section: Resultsmentioning

confidence: 99%

Dynamic trade-offs between biomass accumulation and division determine bacterial cell size and proteome in fluctuating nutrient environments

Banerjee

Kratz

2022

Preprint

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“…For example, in fast growing bacteria quantitative descriptions of the cell cycle [63,64] and of the "laws" governing the global resource partitioning in the cell [43,65,66] have been proposed. These basic aspects of cell physiology greatly contribute to gene expression rates and their fluctuations by setting the cell volume, protein dilution, as well as the concentration of key enzymes [67].…”

Section: Discussionmentioning

confidence: 99%

Out-of-equilibrium gene expression fluctuations in presence of extrinsic noise

Biondo

Singh

Caselle

et al. 2023

Preprint

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Cell-to-cell variability in protein concentrations is strongly affected by extrinsic noise, especially for highly expressed genes. Extrinsic noise can be due to fluctuations of several possible cellular factors connected to cell physiology and to the level of key enzymes in the expression process. However, how to identify the predominant sources of extrinsic noise in a biological system is still an open question. This work considers a general stochastic model of gene expression with extrinsic noise represented as colored fluctuations of the different model rates, and focuses on the out-of-equilibrium expression dynamics. Combining analytical calculations with stochastic simulations, we fully characterize how extrinsic noise shapes the protein variability during gene activation or inactivation, depending on the prevailing source of extrinsic variability, on its intensity and timescale. In particular, we show that qualitatively different noise profiles can be identified depending on which are the fluctuating parameters. This indicates an experimentally accessible way to pinpoint the dominant sources of extrinsic noise using time-coarse experiments.

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“…The amount of ribosomes unused for growth, R U , which is required to maintain super-exponential growth, is an interesting prediction of our model that can be tested in future experiments. Non-zero R U could potentially result from ribosome degradation during the cell cycle [39] or ribosome allocation towards a proteome reserve [40], although the exact dynamics of these processes during cell cycle are not yet known. Our model also predicts that, in nutrient-rich growth environments, cells allocate proportionally more of their ribosomes to producing more ribosomes and length material rather than surface area maintenance and division proteins, suggesting that surface area and division proteins belong to the metabolic sector of the proteome [33,34].…”

Section: Discussionmentioning

confidence: 99%

Super-exponential growth and stochastic size dynamics in rod-like bacteria

Cylke

Banerjee

2022

Preprint

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Proliferating bacterial cells exhibit stochastic growth and shape dynamics but the regulation of noise in bacterial growth and morphogenesis remains poorly understood. A quantitative understanding of morphogenetic noise control, and how it changes under different growth conditions, would provide better insights into cell-to-cell variability and intergenerational fluctuations in cell physiology. Using multigenerational growth and shape data of single Escherichia coli and Caulobacter crescentus cells, we deduce the equations governing growth and shape dynamics of bacterial cells. Interestingly, we find that both E. coli and C. crescentus cells grow faster than an exponential within a cell cycle, irrespective of nutrient or temperature conditions. We propose a mechanistic model that explains the emergence of super-exponential growth from autocatalytic production of ribosomes, coupled to the rate of cell elongation and surface area synthesis. Using this new model and statistical inference on large datasets, we construct the Langevin equations governing cell size and shape dynamics of E. coli cells in different growth conditions. The single-cell level model predicts how noise in intragenerational and intergenerational processes regulate variability in cell morphology and generation times, revealing quantitative strategies for cellular resource allocation and morphogenetic noise control in different growth conditions.

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Protein degradation sets the fraction of active ribosomes at vanishing growth

Cited by 23 publications

References 58 publications

Dynamic trade-offs between biomass accumulation and division determine bacterial cell size and proteome in fluctuating nutrient environments

Dynamic trade-offs between biomass accumulation and division determine bacterial cell size and proteome in fluctuating nutrient environments

Out-of-equilibrium gene expression fluctuations in presence of extrinsic noise

Super-exponential growth and stochastic size dynamics in rod-like bacteria

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