Inflating bacterial cells by increased protein synthesis

Basan, Markus; Zhu, Manlu; Dai, Xiongfeng; Warren, Mya; Sévin, Daniel C.; Wang, Yi‐Ping; Hwa, Terence

doi:10.15252/msb.20156178

Cited by 192 publications

(323 citation statements)

References 34 publications

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“…Strikingly, cells with high fluorescence were also significantly larger and had lower SA/V values than those that were not fluorescent. Similar results have also recently been observed by others (Basan et al, 2015). In addition to chloramphenicol treatment, this provides another example of a situation where α slowed down but did not lead to an increase in SA/V because the associated decrease in β must have been even larger and dominated the final effect on SA/V, further supporting the model that it is the balance between these two rates – rather than their absolute values – that determines SA/V.…”

Section: Resultssupporting

confidence: 93%

Relative Rates of Surface and Volume Synthesis Set Bacterial Cell Size

Harris

Theriot

2016

Cell

220

413

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Summary Many studies have focused on the mechanisms underlying length and width determination in rod-shaped bacteria. Here, we focus instead on cell surface area to volume ratio (SA/V), and demonstrate that SA/V homeostasis underlies size determination. We propose a model whereby the instantaneous rates of surface and volume synthesis both scale with volume. This model predicts that these relative rates dictate SA/V and that cells approach a new steady-state SA/V exponentially, with a decay constant equal to the volume growth rate. To test this, we exposed diverse bacterial species to sublethal concentrations of a cell wall biosynthesis inhibitor and observed dose-dependent decreases in SA/V. Furthermore, this decrease was exponential and had the expected decay constant. The model also quantitatively describes SA/V alterations induced by other chemical, nutritional, and genetic perturbations. We additionally present evidence for a surface material accumulation threshold underlying division, sensitizing cell length to changes in SA/V requirements.

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Section: Resultssupporting

confidence: 93%

Relative Rates of Surface and Volume Synthesis Set Bacterial Cell Size

Harris

Theriot

2016

Cell

220

413

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“…In the simplest scenario, one may assume that the dry density of cells (denoted below as "density") is strongly regulated, and therefore the cell volume is approximately proportional to the total protein mass, i.e., V ∝ M = j p j , which is a reasonable approximation for bacteria [27]. We assume each protein has the same mass and set the cell density as 1 to simplify the following formulas.…”

Section: Constant Cell Density Modelmentioning

confidence: 99%

“…We consider the scenario wherein the cell volume is proportional to the total mass of proteins, based on the fact that cellular dry mass density is well regulated [27]. We show that this model produces mRNA and protein concentrations fluctuating around a constant value throughout the cell cycle with bounded fluctuations.…”

mentioning

confidence: 99%

Homeostasis of protein and mRNA concentrations in growing cells

Lin

Amir

2018

Preprint

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Many experiments show that the concentrations of protein and mRNA fluctuate but on average are constant in growing cells, independent of the genome copy number. However, models of stochastic gene expression often assume constant gene expression rates that are proportional to the gene copy numbers, which are therefore incompatible with experiments. Here, we construct a minimal gene expression model to fill this gap. We show that (1) because the ribosomes translate all proteins, the concentrations of proteins are regulated in an exponentially growing cell volume; (2) the competition between genes for the RNA polymerases makes the gene expression rate independent of the genome number; (3) the fluctuations in ribosome level and cell density can generate a global extrinsic noise in protein concentrations; (4) correlations between mRNA and protein levels can be quantified.Despite the noisy nature of gene expression [1][2][3][4][5][6], various aspects of single cell dynamics, such as volume growth, are effectively deterministic. Recent single-cell measurements show that the growth of cell volumes is often exponential. These include bacteria [7][8][9][10], budding yeast [10][11][12][13][14] and mammalian cells [10,15]. Moreover, the mRNA and protein numbers are on average proportional to the cell volume throughout the cell cycle [16][17][18][19][20]. Therefore, the homeostasis of mRNA concentration and protein concentration is maintained in an exponentially growing cell volume. The exponential growths of mRNA and protein number indicate dynamical transcription and translation rates proportional to the cell volume, and also independent of the genome copy number. However, current gene expression models often assume a fixed cell volume with constant transcription and translation rates [1,5,[21][22][23], which are proportional to the gene copy number. Therefore, fixed cell volume models fail to reveal how cells keep constant mRNA and protein concentrations as the cell volume grows and the genome is replicated.The homeostasis of protein and mRNA concentrations imply that there must be a regulatory mechanism in place to prevent the accumulation of noise over time and to maintain a bounded distribution of concentrations. The goal of this work is to identify such a mechanism by developing a genome-wide coarse-grained model taking into account explicitly cell volume growth. We will consider an idealized cell in which genes are constitutively expressed for simplicity. The ubiquity of homeostasis suggests that the global machineries of gene expression, RNA polymerases (RNAPs) and ribosomes, should play a central role within the model. Indeed, as we will show later, the exponential growth of cell volume, protein and mRNA number originates from the auto-catalytic nature of ribosomes, the limiting factor in the translational process [24][25][26]. The bounded distributions of concentrations are a result of the fact that ribosomes make all proteins. The independence of the mRNA concentration of the genome copy number is a natural resul...

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“…In particular, the cell density was found to be roughly constant across several distinct conditions, including inhibition of protein synthesis, and only slightly larger in the case of protein over-expression [43,44]. The fact that cell density is mini-…”

Section: Discussionmentioning

confidence: 99%

A yield-cost tradeoff governs Escherichia coli's decision between fermentation and respiration in carbon-limited growth

Mori

Marinari

Martino

2017

Preprint

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Many microbial systems are known to actively reshape their proteomes in response to changes in growth conditions induced e.g. by nutritional stress or antibiotics. Part of the re-allocation accounts for the fact that, as the growth rate is limited by targeting specific metabolic activities, cells simply respond by fine-tuning their proteome to invest more resources into the limiting activity (i.e. by synthesizing more proteins devoted to it). However, this is often accompanied by an overall re-organization of metabolism, aimed at improving the growth yield under limitation by re-wiring resource through different pathways. While both effects impact proteome composition, the latter underlies a more complex systemic response to stress. By focusing on E. coli's 'acetate switch', we use mathematical modeling and a re-analysis of empirical data to show that the transition from a predominantly fermentative to a predominantly respirative metabolism in carbon-limited growth results from the trade-off between maximizing the growth yield and minimizing its costs in terms of required the proteome share. In particular, E. coli's metabolic phenotypes appear to be Pareto-optimal for these objective functions over a broad range of dilutions.The physiology of cell growth can nowadays be experimentally probed in exponentially growing bacteria both at bulk (see e.g. the bacterial growth laws detailed in [1][2][3]) and at single cell resolution [4][5][6][7]. Refining the picture developed since the 1950s [8,9], recent studies have shown that changes in growth conditions are accompanied by a massive re-organization of the cellular proteome, whereby resources are re-distributed among protein classes (e.g. transporters, metabolic enzymes, ribosome-affiliated proteins, etc.) so as to achieve optimal growth performance [10]. This in turn underlies significant modifications in cellular energetics to cope with the increasing metabolic burden of fast growth [11][12][13].E. coli's 'acetate switch' is a major manifestation of the existence of a complex interplay between metabolism and gene expression. Slowly growing E. coli cells tend to operate close to the theoretical limit of maximum biomass yield [14,15]. Fast-growing cells, instead, typically show lower yields, together with the excretion of carbon equivalents such as acetate [13]. One can argue that, in the latter regime, cells optimize enzyme usage, i.e. they minimize the protein costs associated to growth, while at slow growth they try to use nutrients as efficiently as possible [13]. As one crosses over from one regime to the other, E. coli's growth physiology appears to be determined to a significant extent by the trade-off between growth and its biosynthetic costs. Interestingly, a similar overflow scenario appears in other cell types in proliferating regimes (see e.g. the Crabtree effect in yeast [16,17] or the Warburg effect in cancer cells [18][19][20]).Several phenomenological models have tackled the issue of how metabolism and gene expression coordinate to optimize growth in ...

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Inflating bacterial cells by increased protein synthesis

Cited by 192 publications

References 34 publications

Relative Rates of Surface and Volume Synthesis Set Bacterial Cell Size

Relative Rates of Surface and Volume Synthesis Set Bacterial Cell Size

Homeostasis of protein and mRNA concentrations in growing cells

A yield-cost tradeoff governs Escherichia coli's decision between fermentation and respiration in carbon-limited growth

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